Targeting MicroRNAs for Modulation of the...

87
UNIVERSIDADE DE LISBOA FACULDADE DE FARMÁCIA Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation Master Thesis Dissertation Gisela Silva Gordino Master in Biopharmaceutical Sciences - FFUL Supervisor Dra. Julie C. Ribot Molecular Medicine Institute 2016

Transcript of Targeting MicroRNAs for Modulation of the...

Page 1: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

UNIVERSIDADE DE LISBOA

FACULDADE DE FARMÁCIA

Targeting MicroRNAs for Modulation of the Anti-Tumor

Human γδ T Cell Differentiation

Master Thesis Dissertation

Gisela Silva Gordino

Master in Biopharmaceutical Sciences - FFUL

Supervisor

Dra. Julie C. Ribot

Molecular Medicine Institute

2016

Page 2: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 2

UNIVERSIDADE DE LISBOA

FACULDADE DE FARMÁCIA

Targeting MicroRNAs for Modulation of the Anti-Tumor

Human γδ T Cell Differentiation

Master Thesis Dissertation

Gisela Silva Gordino

Master in Biopharmaceutical Sciences - FFUL

Supervisor

Dra. Julie C. Ribot

Molecular Medicine Institute

2016

Page 3: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 3

Abstract

Recent developments in the immunology field have validated immunotherapy as being

capable of extending cancer patients survival, highlighting its role as a promising anti-tumor

treatment. However, a wider and more successful application of adoptive cell therapy requires

a better understanding of the molecular determinants, in effector lymphocytes, of functional

differentiation, recognition and elimination of tumor cells.

γδ T cells have been proposed as the first line of immune defense, acting in response to a

variety of stress-inducible or pathogen-associated metabolites. Their activation includes a

potent cytolytic and inflammatory activity against a wide range of malignant cells as one of

its most important features. Although clinical trials have aimed at modulating their activity,

they were only able to achieve objective responses in the range of 10-33%. Therefore, it has

become evident that understanding the mechanisms involved in regulating γδ T cell activation

and functional differentiation is critical for their manipulation in clinical settings.

Importantly, data from the host laboratory has recently shown that the anti-tumor effector

properties of γδ T cells were selectively acquired upon stimulation with interleukin (IL)-2, but

not with IL-7. The effects caused by IL-2 depended on the Mitogen-Activated Protein

Kinase/Extracellular Signal-Related Kinase (MAPK/ERK) signaling and induced de novo

expression of the transcription factors (TFs) T-bet and eomesodermin, as well as the cytolytic

enzyme perforin. Based on this background, this project proposes to explore an additional

layer in the regulation of γδ T cell differentiation, by characterizing the post-transcriptional

mechanisms mediated by microRNAs (miRs).

In mammals, more than 700 miRs have already been identified and shown to regulate many

developmental and differentiation processes. For instance, with regard to the immune system,

overexpressing miR-491 decreases the interferon (IFN)-γ production in cluster of

differentiation (CD)8+ T cells, miR-583 inhibits natural killer (NK) cells differentiation

process, and miR-181a expression regulates activation of memory T helper (Th)17 cells

through modulation of ERK phosphorylation. This notwithstanding, no miRs have yet been

implicated in human γδ T cell differentiation into anti-tumor effectors.

By performing a ribonucleic acid-sequencing (RNA-seq) analysis, we have been able to

identify a discrete repertoire of miRs possibly implied in regulating γδ T cell type 1 functional

differentiation. Selected miRs candidates have been validated by reverse transcriptase-

polymerase chain reaction (RT-PCR): miR-135b, 10a and 20b were upregulated in mature γδ

T cells while; miR-181a and 196b were downregulated in mature γδ T cells.

We next manipulated the expression of these miRs following two different gain-of-function

strategies (electroporation with mimics and retroviral transduction). We observed that miR-

181a and 196b overexpression decreases γδ T cell differentiation into type 1 effectors, while

enhancing their proliferation. On the other hand, our preliminary results indicate that miR-

135b, 10a and 20b impair γδ T cell proliferation without affecting their anti-tumor functions.

If confirmed, these findings could have major implications for the manipulation of γδ T cells

in cancer immunotherapy.

Keywords: Anti-tumor; Differentiation; γδ T cells; Immunotherapy; microRNA.

Page 4: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 4

Resumo

Desenvolvimentos recentes na área da imunologia validaram a imunoterapia como sendo

capaz de aumentar a sobrevivência de pacientes com cancro, evidenciando o seu papel

promissor no tratamento desta doença. No entanto, uma aplicação mais abrangente e bem-

sucedida da terapia celular adoptiva requer um conhecimento profundo dos determinantes

moleculares, em linfócitos T efectores, de diferenciação funcional, reconhecimento e

eliminação de células tumorais.

Os linfócitos T γδ têm sido propostos como a primeira linha de defesa imunológica, em

resposta a uma variedade de metabolitos induzidos pelo stress ou associados a organismos

patogénicos. A activação destas células inclui uma actividade citolítica e inflamatória potente,

contra uma vasta gama de células malignas, como uma das suas características principais.

Embora os ensaios clínicos tenham tentado modular a actividade destes linfócitos, estes só

alcançaram respostas objectivas na ordem dos 10-33%. Tornou-se assim evidente que a

compreensão dos mecanismos envolvidos na regulação da activação e da diferenciação

funcional dos linfócitos T γδ é crítica para a sua manipulação em contextos clínicos.

De forma importante, resultados obtidos pelo laboratório de acolhimento demonstraram que

as propriedades anti-tumor efectoras dos linfócitos T γδ eram adquiridas, selectivamente,

mediante estimulação com IL-2, mas não quando estimulados com IL-7. Os efeitos mediados

por IL-2 eram dependentes da via de sinalização de MAPK/ERK e induziam a expressão de

novo dos factores de transcrição T-bet e eomesodermina, assim como da enzima citolítica

perforina. Com base nestes dados, este projecto propõe explorar um outro nível de regulação

na diferenciação de linfócitos T γδ, caracterizando os mecanismos pós-transcrição mediados

por miRs.

Em mamíferos, mais de 700 miRs foram já identificados e demonstrados como sendo capazes

de regular vários processos de desenvolvimento e diferenciação. Em relação ao sistema

imunitário, os padrões de expressão destas pequenas espécies de RNA variam consoante o

tipo de linfócitos e também de acordo com o estadio de desenvolvimento. Curiosamente,

alguns estudos demonstraram que esses perfis de expressão são únicos em cada etapa do

desenvolvimento das células T tímicas. De acordo com esta informação, a remoção dos miRs

maduros na fase inicial do desenvolvimento de timócitos resultou num bloqueio do seu

desenvolvimento e na consequente redução de linfócitos T αβ periféricos assim como reduziu

a pool de células iNKT. Adicionalmente, vários miRs têm sido também correlacionados com

a desregulação das capacidades efectoras de diversos tipos de linfócitos. Alguns exemplos

incluem: a sobreexpressão do miR-491 em linfócitos T CD8+ que demonstrou ser capaz de

diminuir a produção de IFN-γ; a expressão do miR-583 foi correlacionada com a inibição da

diferenciação de células NK e; a expressão do miR-181a demonstrou regular a activação de

linfócitos de memória Th17 ao modular a fosforilação da ERK. Apesar disso, não surgiram

ainda miRs implicados na diferenciação de linfócitos T γδ humanos em efectores anti-

tumorais.

Neste trabalho fomos capazes de identificar um repertório discreto de miRs possivelmente

implicados na regulação da diferenciação funcional do tipo 1 em linfócitos T γδ. Para tal,

recorremos à análise dos dados obtidos em ensaios de sequenciação de RNA em linfócitos T

Page 5: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 5

γδ imaturos versus maduros, isolados a partir de amostras de timo humano. Utilizando a

metodologia de RT-PCR validámos esses dados, reduzindo a lista inicial de treze para cinco

potenciais candidatos: miR-135b, 10a e 20b que se encontravam sobreexpressos em linfócitos

T γδ maduros e; miR-181a e 196b que tinham expressão reduzida em linfócitos T γδ maduros.

Surpreendentemente, quando analisada a presença destes miRs por RT-PCR em linfócitos T

γδ isolados da periferia (i.e. amostras de sangue de dadores saudáveis), o padrão de expressão

para os cinco candidatos era mais semelhante à sua expressão em timócitos γδ recém-isolados

– ou seja, imaturos – do que à expressão observada em timócitos γδ em cultura com IL-2 – ou

seja, maduros/diferenciados. Tais resultados parecem sugerir que o padrão de expressão

destes miRs candidatos poderá estar associado a um processo transiente, capaz de restaurar os

seus níveis basais assim que as células se encontrem completamente diferenciadas e entrem

num processo de repouso. De acordo com esta hipótese, quando os linfócitos T γδ periféricos

foram colocados em cultura com as citosinas IL-7 ou IL-2 – que atribui às células um estado

imaturo ou maduro, respectivamente – o estímulo induzido pelas citosinas demonstrou ser

capaz de romper com o estado de repouso das células, conforme comprovado pela alteração

nos padrões de expressão destes miRs. Mais ainda, em linfócitos T γδ periféricos cultivados

com IL-7, os miRs-135b, 10a e 20b aparentaram ter um comportamento diferente do

observado em timócitos γδ em cultura também com IL-7, visto que a sua expressão surge

aumentada nestas amostras periféricas.

Importantemente, estas experiências demonstraram também que as subpopulações Vδ1 and

Vδ2 isoladas a partir do sangue de controlos saudáveis obtiveram valores semelhantes para a

expressão dos miRs. Estes resultados estão então de acordo com o facto de se terem registado

padrões semelhantes na expressão dos miRs candidatos, quando comparados os resultados

entre as amostras de linfócitos T γδ recém-isoladas a partir do timo com as amostras recém-

isoladas a partir de sangue humano.

De seguida procedeu-se à manipulação da expressão destes miRs utilizando duas estratégias

de ganho-de-função diferentes: electroporação com mimetizadores ou transdução retroviral.

Ao sobreexpressar os miRs candidatos, usando o sistema Neon, fomos capazes de observar

que nos linfócitos T γδ periféricos em cultura com IL-7+IL-2 a proliferação aparenta estar

comprometida nas amostras que sobreexpressaram os miRs-135b, 10a e 20b, sobretudo

quando delimitados à subpopulação Vδ2. Tal resultado é consistente com os dados obtidos

durante as experiências de RT-PCR, que sugerem um papel para estes três miRs na regulação

das respostas funcionais em linfócitos T γδ que já se encontrem completamente diferenciados.

De forma importante, apesar de só se ter conseguido explorar a manipulação destes linfócitos

numa amostra de timo, quando utilizando o sistema Neon, os resultados obtidos foram

também indicativos de um papel na regulação do desenvolvimento e diferenciação de

linfócitos T γδ por parte dos miRs-181a e 196b, visto que estes foram capazes de reduzir a

expressão de TNF-α em cerca de 10% dentro da subpopulação Vδ1, ao mesmo tempo que

parecem induzir a sua proliferação.

De acordo com estes dados, a transdução retroviral do miR-181a em linfócitos T γδ

periféricos demonstrou ser capaz de aumentar a proliferação destas células enquanto, ao

mesmo tempo, diminuiu a expressão de IFN-γ e TNF-α. No que concerne os resultados do

processo de diferenciação, embora tenham ocorrido pequenas diferenças nas duas

Page 6: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 6

subpopulações, tais alterações na subpopulação Vδ2 foram demasiado reduzidas para serem

consideradas. Pelo contrário, a expressão de IFN-γ e TNF-α em células Vδ1+ foi

significativamente comprometida pela presença do miR-181a, reduzindo a produção destas

citosinas em cerca de 12%. Interessa salientar que esta não é a primeira vez que a

sobreexpressão do miR-181a é correlacionada com a redução da produção de IFN-γ e TNF-α,

visto que tal foi já observado recentemente em linfócitos humanos CD4+ ou na linha celular

HEK293K, respectivamente.

Estes resultados, em conjunto com outros relatórios semelhantes, sustentam um papel

regulatório do miR-181a na diferenciação funcional de células T, que deve ser aprofundado

no que diz respeito aos linfócitos T γδ.

No seu conjunto, estas experiências de ganho-de-função permitiram-nos observar que a

sobreexpressão dos miRs-181a e 196b diminui a diferenciação dos linfócitos T γδ em

efectores do tipo 1, ao mesmo tempo que aumenta a sua proliferação. Por outro lado, estes

resultados preliminares indicam que o miR-135b, 10a e 20b comprometem a proliferação

destes linfócitos sem afectar as suas propriedades anti-tumorais. Interessantemente, em ambas

as experiências de ganho-de-função, as células Vδ1+ surgiram com sendo a subpopulação que

registou as alterações mais significativas. Deste modo, seria importante sobreexpressar estes

miRs em mais amostras de timo, uma vez que os timócitos γδ são enriquecidos em células

Vδ1. Se validados, estes resultados poderão ter grandes implicações na manipulação dos

linfócitos T γδ para a imunoterapia em cancro.

Como seguimento lógico deste projecto, pretende-se identificar as redes de mRNAs

controladas pelos nossos miRs candidatos, recorrendo a uma combinação de ferramentas

bioinformáticas e bioquímicas. Esta visão integrada dos efeitos de um determinado miR no

transcriptoma humano será fundamental para compreender o seu papel na diferenciação

funcional dos linfócitos T γδ.

Adicionalmente, pretende-se tentar definir um perfil patogénico para estes miRs na

diferenciação funcional dos linfócitos T γδ, tendo como base amostras de pacientes com

cancro. Interessantemente, a presença e as capacidades efectoras dos linfócitos T γδ

periféricos foram anteriormente relatadas como estando comprometidas em amostras de

pacientes com melanoma, glioblastoma e cancro do estômago. Como tal, cremos ser possível

observar uma expressão anormal dos miRs envolvidos no processo de diferenciação funcional

dos linfócitos T γδ em amostras obtidas a partir de sangue periférico deste género de

pacientes. Para verificar essa hipótese, contamos com a parceria estabelecida com o

Departamento de Oncologia do Hospital de Santa Maria, através do Dr. Luís Costa, que nos

permitirá ter acesso a amostras de sangue obtidas a partir de um grupo definido de pacientes,

aquando a altura do diagnóstico.

Palavras-Chave: Anti-tumor; Diferenciação, Linfócitos T γδ; Imunoterapia; microRNAs.

Page 7: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 7

Acknowledgements

I wish to take this opportunity to thank to everyone who has been involved in this journey,

which allowed me to grow, not only professionally but also personally.

To begin, I would like to thank Professor Dr. Bruno Silva-Santos for giving me the

opportunity to integrate this already large “family”, known as the BSS lab. Thanks for always

believing in me and in this project, and to always try to push me further. Your constructive

criticism not only allowed me to grow scientifically, but thanks to you I have always tried to

improve my work every step of the way.

I also wish to give thanks to all of my colleagues in the BSS lab, who made me feel welcomed

since the first day, but in particular to those who have also endowed me with some of their

skills. In special, I want to thank Nina for the enormous sympathy and the amazing help she

gave me by teaching me how to work with the Neon system, and also with the retrovirus. I

could always come to you with a million questions that you always answered with kindness

and a smile on your face. Thank you for that! To Tiago, my main “retrovirus teacher”, who

taught me almost everything I know about culturing bacteria and producing virus. Thank you

for the many hours you have spent unveiling the mysteries of this “small world” to me and for

making these experiments look more “user friendly”. To Anita, thanks for always trying to

help me with my microRNA doubts and for teaching me how to do the sequencing step. To

Natacha, thanks for teaching me how to do an RT-PCR with those amazing 384 well plates,

and for helping me to do it three times!

There are other several colleagues, who have somehow made my life in the lab easier, and to

whom I wish to thank: to Karine for always trying to help when I was having some doubts in

my experiments and for listening to my first oral presentation when I was so nervous; to

Sérgio, for showing me where (and how) to pick up the thymus and blood samples, and for

processing the thymus for me sometimes, when I was too busy; to André, Biagio, Cláudia,

Paula and Pedro, for their selfless help, their sympathy and their kind word during rough

times; to Helena, our more recent teammate, in whom I have found an unexpected friend,

thank you for that special hug when I needed the most; and to Sofia, your constant help is

priceless, you have literally saved the final step of my retrovirus experiment, so if I have

results to show here it is thanks to you!

I also wish to give thanks to some of my friends and family. To my dad and my grandparents,

for supporting me in this step of my education, for never judging and for taking care of me the

best you knew and you were able to. Thank you for your enormous heart!

To my closest friends Rita and Andreia, for listening and for giving me support, and for never

complaining about me not having the time to visit you, even if just to drink a coffee. Thank

you for being there for me, always!

Finally, there are two special persons to whom I owe and to whom I want to thank the most.

To Julie: my mentor, my teacher and my friend. You have always trusted in me and in my

skills from the beginning and you always believed I would thrive not only in the lab, but also

in other many aspects of my life. Thank you for being my role model: an excellent

hardworking scientist and also an excellent person, as I have only met few during my whole

Page 8: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 8

life. I could not have asked for a better supervisor. In you I could always find a word of

encouragement, a sparkle of optimism and a solution for every problem. Even when I saw no

light at the end of the tunnel, you did, and you always made me believe that we were able to

pull this through, as we did! So thank you for this marvelous journey, for teaching me, for

letting me try to do things my own way, for having my back every time and for making me go

beyond my limits, but most of all thank you for choosing me.

To my boyfriend: I could write a whole page just to thank you and still there would be a lot

more to say! Thanks for being there for me every step of the way, for helping picking me up

when I was down, for believing in me and for listening to me talking about my work, even

when I had the same conversation over and over again, hopping that you were able to provide

me with the answers. Thank you for waking up earlier than you had to just so you could make

me company in those hard days when I had to deal with my “ghosts”, I would never forget

that in a million years! Thank you for the sleepy breakfasts, the long conversations at late

(and earlier) hours, and for your unselfish and unconditional love. You always said that

everything was going to be just fine, and you were right, it really did!

I cannot finish without thanking to my guardian angel, my mom, who raised me to be the

women I am today, and to whom I turn to in my darkest hours. I know you are always looking

out for me and that somehow you had always given the strength to achieve my goals.

Wherever you are, I hope I am making you proud.

Page 9: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 9

Table of Contents

Abstract ................................................................................................................................................... 3

Resumo .................................................................................................................................................... 4

Acknowledgements ................................................................................................................................. 7

List of Figures ....................................................................................................................................... 11

List of Abbreviations ............................................................................................................................. 13

1. Introduction ....................................................................................................................................... 17

1.1 γδ T Cells as Key-Players in Immunity ....................................................................................... 17

1.1.1 Adaptive vs Innate Immune System ..................................................................................... 17

1.1.2 γδ T Cell Development and Differentiation ......................................................................... 18

1.1.3 γδ T Cell Target Recognition and Response ........................................................................ 21

1.2 Cancer and γδ T Cells .................................................................................................................. 23

1.2.1 The Immune System and Cancer .......................................................................................... 23

1.2.2 γδ T Cells in Cancer ............................................................................................................. 24

1.3 MiR Role in Gene Regulation ..................................................................................................... 27

1.3.1 MiR Biogenesis and Maturation ........................................................................................... 27

1.3.2 MiR Silencing Mechanisms ................................................................................................. 28

1.3.3 MiR-Mediated Regulation of T Cell Biology ...................................................................... 29

2. Aims of the Thesis ............................................................................................................................. 33

3. Materials and Methods ...................................................................................................................... 35

3.1 Ethics ........................................................................................................................................... 35

3.2 Lymphocyte Preparations ............................................................................................................ 35

3.3 Cell Culture ................................................................................................................................. 35

3.4. Quantitative RT-PCR ................................................................................................................. 36

3.5 γδ T cell Transfection using Neon System for Mimics Delivery ................................................ 36

3.6 MiR-Overexpressing Recombinant Retrovirus Production ......................................................... 37

3.7 γδ T cell Transduction with the Retroviral Constructs ................................................................ 38

3.8 FACS Analysis ............................................................................................................................ 39

3.9 Statistical Analysis ...................................................................................................................... 40

4. Results ............................................................................................................................................... 42

4.1 MiR Signature Associated with γδ T Cell Type 1 Differentiation .............................................. 42

4.2 RT-PCR Validation of the miR Candidates ................................................................................ 43

4.2.1 RT-PCR in γδ Thymocytes Validates Top Five miR Candidates ........................................ 43

Page 10: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 10

4.2.2 MiR Candidates Expression Profile in Peripheral γδ T Cells is more Similar to Freshly-

isolated than to IL-2 Cultured γδ Thymocytes .............................................................................. 44

4.2.3 Comparison of miR Candidates Expression on Vδ1 vs Vδ2 Subpopulations Shows No

Significant Differences in their Expression Levels ....................................................................... 46

4.3 Setup of the Conditions for an Efficient miR Transfection using the Neon System ................... 47

4.4 Analysis of the Impact of Mimics Delivery on γδ T Cell Differentiation and Proliferation ....... 50

4.4.1 Peripheral Vδ2 γδ T Cells Transfected with miR-135b, 10a and 20b Mimics tend to

Proliferate Less when Cultured with IL-7 plus IL-2 ..................................................................... 51

4.4.2 Peripheral γδ T Cells Transfected with the miR Mimics show No Significant Differences in

IFN-γ and TNF-α Production ........................................................................................................ 52

4.4.3 MiR-181a and miR-196b Overexpression Decreases TNF-α Production in Vδ1

Electroporated γδ Thymocytes ...................................................................................................... 53

4.5 Overexpression of Candidate miRs using Retroviral Constructs ................................................ 54

4.5.1 MiR Overexpression was Not Efficient for All of the miR Constructs ................................ 54

4.5.2 MiR-181a Overexpression in Peripheral γδ T Cells Increases Cell Proliferation ................ 55

4.5.3 MiR-181a Overexpression in Peripheral γδ T Cells Increases Vδ1 T Cell Activation and

Programmed Cell Death ................................................................................................................ 56

4.5.4 Overexpression of miR-181a in Peripheral γδ T Cells did not Influence their

Effector/Memory Phenotype ......................................................................................................... 58

4.5.5 Overexpression of miR-181a in Peripheral γδ T Cells Reduces IFN-γ and TNF-α Production

in the Vδ1 Subpopulation .............................................................................................................. 60

5. Discussion ......................................................................................................................................... 63

6. Future Plans ....................................................................................................................................... 72

7. Bibliography ...................................................................................................................................... 74

Page 11: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 11

List of Figures

Figure 1 - γδ T cell recognition and response. ...................................................................................... 22

Figure 2 – Inferred leukocyte frequencies and prognostic associations in 25 human cancers. ............. 24

Figure 3 – Anti-tumor functions of γδ T cells. ...................................................................................... 26

Figure 4 – The “linear” canonical pathway of miR processing. ............................................................ 29

Figure 5 – Schematic representation of the procedure to develop a retroviral construct with the DNA

of interest. .............................................................................................................................................. 38

Figure 6 – Schematic representation of the transfection process. ......................................................... 39

Figure 7 – FACS gating strategy. .......................................................................................................... 40

Figure 8 – Human γδ thymocytes are devoid of IFN-γ production and cytotoxic functions but IL-2

signal differentiates them into cytotoxic type 1 effector T cells. .......................................................... 42

Figure 9 – MiR signature associated with γδ T cell type 1 differentiation. ........................................... 43

Figure 10 - RT-PCR in γδ thymocytes validates top five miR candidates. ........................................... 44

Figure 11 - MiR candidates expression profile in peripheral γδ T cells is more similar to freshly-

isolated than to IL-2 cultured γδ thymocytes. ....................................................................................... 45

Figure 12 – MiR-135b, 10a and 20b expression is upregulated in IL-7 or IL-2 cultured peripheral γδ T

cells indicating a rupture in their resting status. .................................................................................... 46

Figure 13 - Comparison of miR candidates expression on Vδ1 vs Vδ2 subpopulations shows no

significant differences in their expression levels. .................................................................................. 47

Figure 14 – Transfection of the siRNACD45 using the Neon system proves to be efficient on silencing

CD45 in γδ T cells. ................................................................................................................................ 48

Figure 15 – Transfection of the siRNACD45 using the Neon system does not compromise γδ T cell

survival. ................................................................................................................................................. 49

Figure 16 – Neon protocol timeline for mimics delivery. ..................................................................... 50

Figure 17 – Mimics delivery to PBMC-isolated γδ T cells using the Neon system occurred efficiently.

............................................................................................................................................................... 50

Figure 18 – Peripheral Vδ2 γδ T cells transfected with miR-135b, 10a and 20b mimics tend to

proliferate less when cultured with IL-7 plus IL-2. ............................................................................... 51

Figure 19 – Peripheral γδ T cells transfected with the miR mimics show no significant differences in

IFN-γ and TNF-α production. ............................................................................................................... 52

Figure 20 – MiR-181a and miR-196b overexpression decreases TNF-α production in Vδ1

electroporated γδ thymocytes. ............................................................................................................... 53

Figure 21 –MiR overexpression was not efficient for all of the miR constructs: 3T3 cells. ................. 54

Figure 22 – MiR overexpression was not efficient for all of the miR constructs: γδ T cells. ............... 55

Figure 23 – MiR-181a overexpression in peripheral γδ T cells increases cell proliferation. ................ 56

Figure 24 – MiR-181a overexpression in peripheral γδ T cells increases Vδ1 T cell activation. ......... 57

Page 12: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 12

Figure 25 – MiR-181a overexpression in peripheral γδ T cells increases Vδ1 T cell programmed cell

death. ..................................................................................................................................................... 58

Figure 26 – Overexpression of miR-181a in peripheral γδ T cells did not influence their

effector/memory phenotype. ................................................................................................................. 59

Figure 27 – Overexpression of miR-181a in peripheral γδ T cells reduces IFN-γ and TNF-α production

in the Vδ1 subpopulation....................................................................................................................... 60

Figure 28 – Summary of the results obtained upon overexpression of miR-181a in peripheral γδ T

cells........................................................................................................................................................ 61

Page 13: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 13

List of Abbreviations

Ab: antibody

ADCC: Ab-dependent cell cytotoxicity

Ag: antigen

AGO: Argonaute

AICD: activation-induced cell death

APC: antigen-presenting cells

ATPase: F1-Adenylpyrophosphatase

B: bone marrow-derived

BFA: brefeldin

BTN: butyrophilin family

C. elegans: Caenorhabditis elegans

CD: cluster of differentiation

cDNA: complementary deoxyribonucleic acid

CLL: chronic lymphocytic leukemia

CM: central memory

CMV: cytomegalovirus

D: diversity

DC: dendritic cell

DETC: dendritic epidermal γδ T cells

DGCR8: DiGeorge syndrome critical region 8

DN: double-negative

DOT: delta one T

DP: double-positive

EA-1: early activation antigen

EM: effector memory

ERK: extracellular signal-related kinase

Exp5: exportin-5

FACS: fluorescence-activated cell sorting

FISH: fluorescent in situ hybridization

γδ NKT cells: NK1.1+ γδ cells

γδ17 cells: IL-17A-producing γδ cells

Page 14: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 14

GFP: green fluorescent protein

GLUT1: glucose transporter 1

HEK293T TAT: human embryonic kidney 293 cells with large T antigen and a transcription

transactivator

HITS-CLIP: high-throughput sequencing of RNA isolated by cross-linking

immunoprecipitation

HIV: human immunodeficiency virus

HMBPP: (E)-4-hydroxy-3-methyl-but-2-enylpyrophosphate

IFN-γ: interferon-γ

Ig: immunoglobulin

IL: interleukin

iNKT: invariant natural killer T

IPP: isopentenyl pyrophosphate

J: junctional

LNA: locked nucleic acid

mAb: monoclonal Ab

MACS: magnetic cell sorting

MAPK: mitogen-activated protein kinase

MDSCs: myeloid derived suppressor cells

MFI: mean-fluorescence intensity

MHC: major histocompatibility complex

MICA: MHC Class-I chain-related A

MICB: MHC Class-I chain-related B

miR: microRNA

mRNA: messenger RNA

NEAA: minimum essential amino acids

NKG2D: natural killer group 2 member D

NK: natural killer

NKR: NK cell receptor

NKT: natural killer T

P-Ag: phosphoantigen

PAMP: pathogen-associated molecular patterns

Page 15: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 15

PBL: peripheral blood lymphocyte

PBMC: peripheral blood monocyte cells

PCR: polymerase chain reaction

Pen/Strep: penicillin and streptomycin

pMIG-PGW: MSCV-IRES-GFP-PGW plasmid

pre-miR: precursor miR

pri-miR: primary miR

PRKC: protein kinase C epsilon

PRR: pattern recognition receptor

qPCR: quantitative PCR

RISC: RNA-induced silencing complex

RNA: ribonucleic acid

RNase: ribonuclease

RNA-seq: RNA sequencing

RT: reverse transcriptase

siRNA: small interfering RNA

SNORD44: small nucleolar RNA C/D Box 44

SP: single-positive

T: thymic-derived

T-ALL: T cell acute lymphoblastic leukemia

TAL: tumor-associated leukocytes

TCR: T-cell receptor

TF: transcription factor

Th: T helper

TIL: tumor infiltrating lymphocytes

TLR: toll-like receptor

TME: tumor microenvironment

TNF-α: tumor necrosis factor α

UTR: untranslated region

V: variable

Page 16: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 16

Introduction

Page 17: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 17

1. Introduction

1.1 γδ T Cells as Key-Players in Immunity

1.1.1 Adaptive vs Innate Immune System

Defense against microbial assaults is an essential necessity for all living organisms.

Consequently, all life forms have evolved strategies that are designed to limit the invasion of

the host by microorganisms (Schenten and Medzhitov, 2011). Immunity, as it is known, refers

to the global ability of the host to resist the predation of microbes that would otherwise

destroy it. It has many facets, but the greatest dichotomy separates adaptive immunity –

usually known as “acquired immunity” – from innate immunity – also termed as “natural

immunity” or “innate resistance” (Hoebe et al., 2004).

Traditionally, innate immunity is assumed to be rapid, “non-specific”, and identical

qualitatively and quantitatively each time the same pathogen is encountered. Many of the

innate immune cells are considered to be short-lived, making “memory” a moot concept. On

the other hand, adaptive immunity features are considered to include the generation of long-

lived, antigen (Ag)-specific cells after initial exposure to an Ag or pathogen. Thus, these cells

respond faster and more robustly to subsequent encounters with the same Ag or pathogen,

which consists the basis of vaccination (Clem, 2011; Lanier and Sun, 2009).

The adaptive immunity is usually attributed to two classes of specialized cells: thymic-derived

(T) lymphocytes and bone marrow-derived (B) lymphocytes, which further differentiate into

plasma cells in order to secrete antibodies (Ab) (Lanier and Sun, 2009; Medzhitov and

Janeway, 2000).

Deletion of self-reactive T and B cell clones during lymphocyte development forms the basis

for the discrimination between self and non-self by the adaptive immune system (Schenten

and Medzhitov, 2011). Lymphocytes able to overcome this clonal deletion will display a

single kind of structurally unique receptor, creating a very large and diverse repertoire of

antigen receptors in the entire lymphocyte population, in a process called clonal selection,

thus increasing the probability of an individual lymphocyte to encounter an Ag that binds to

its receptor. Upon infection these lymphocytes are activated and start to proliferate, by a

process known as clonal expansion, a mechanism which is essential for the generation of an

efficient immune response (Medzhitov and Janeway, 2000; Mogensen et al., 2009).

Adaptive immunity comprises many of the same effector mechanisms that are used in the

innate immune system, but is able to target them with greater precision. However, it takes

three to five days for sufficient numbers of clones to be produced and to differentiate into

effector cells, creating a time gap that would allow for most pathogens to damage the host. In

contrast, the effector mechanisms of innate immunity are activated immediately after

infection and rapidly control infecting pathogen replication. For this reason, containing the

infection until the lymphocytes can begin to deal with it is considered the main function of the

innate immunity (Janeway et al., 2001; Medzhitov and Janeway, 2000).

Granulocytes, monocytes, macrophages, dendritic cells (DCs), and NK cells have been

delegated to the innate immune system, which also comprises epithelial cell barriers, proteins

Page 18: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 18

of the complement system and anti-microbial peptides, and also other soluble factors (Hoebe

et al., 2004; Lanier and Sun, 2009).

The innate immune response relies on recognition of evolutionarily conserved structures on

pathogens, termed pathogen-associated molecular patterns (PAMPs), through a limited

number of germ line-encoded pattern recognition receptors (PRRs), of which the family of

Toll-like receptors (TLRs) is the most well-known (Akira et al., 2006; Medzhitov and

Janeway, 2000; Mogensen, 2009). In specific cases, PRRs also recognize host factors as

“danger” signals, as for instance when they are present in aberrant locations or abnormal

molecular complexes as a consequence of inflammation, infection or in other types of cellular

stress (Beg, 2002; Mogensen, 2009).

PAMPs are characterized by being invariant among entire classes of pathogens, essential for

pathogen survival, and distinguishable from “self” (Janeway, 1989). Detection of PAMPs by

PRRs leads to the induction of inflammatory responses and innate host defenses. PRR-

induced signal transduction pathways ultimately result in the activation of gene expression

and synthesis of a broad range of molecules, which include: cytokines, chemokines, cell

adhesion molecules, and immunoreceptors (Akira et al., 2006; Iwasaki and Medzhitov, 2015;

Mogensen, 2009). In addition, the sensing of microbes by PRRs expressed on antigen-

presenting cells (APCs), particularly DCs, will lead to the activation of adaptive immune

responses (Iwasaki and Medzhitov, 2015).

It is now universally recognized that innate instruction of adaptive immunity is a critical step

that controls the activation, types, and duration of the adaptive immune response. Innate

instruction occurs initially during the interaction between APCs and T cells. While this

interaction is critical for the generation of an adaptive immune response, it is clear that innate

control of the adaptive immunity is a process that occurs at multiple stages throughout the

immune response and involves all cell types contributing to a particular response (Hoebe et

al., 2004; Schenten and Medzhitov, 2011). Importantly, the distinctions between innate and

adaptive immunity have recently become blurred: certain subsets of B and T cells, such as B1

cells, γδ T cells, and invariant natural killer T (iNKT) cells, are often referred to as innate-like

lymphocytes (Murphy et al., 2008); while some innate immune cells, as for instance the NK

cells, seem not to fit the conventions, by showing features normally attributed exclusively to

cells of the adaptive immune system (Lanier and Sun, 2009; O’Leary et al., 2006; Sun et al.,

2009). In this project we will be focusing our attention to the less well-known subset of T

lymphocytes, which seems to comprise features from both the adaptive and the innate

immune system: the γδ T cells.

1.1.2 γδ T Cell Development and Differentiation

T lymphocytes develop from a common lymphoid progenitor in the bone marrow that also

gives rise to B lymphocytes, but those progeny destined to give rise to T cells leave the bone

marrow and migrate to the thymus (Janeway et al., 2001). T cell differentiation in the thymus

can be divided into discrete stages based on CD4 and CD8 expression: CD4 and CD8 double-

negative (DN) early thymic progenitors; more differentiated CD4 and CD8 double-positive

Page 19: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 19

(DP) thymocytes and; differentiated CD4 or CD8 single-positive (SP) thymocytes. The DN

stage is heterogeneous and can be subdivided into four distinct subsets in mice, based on the

expression of CD44 and CD25 (Germain, 2002). In humans, three distinct DN stages can be

recognized: a CD34+CD38

-CD1a

- stage that represents the most immature thymic subset and

the consecutive CD34+CD38

+CD1a

- and CD34

+CD38

+CD1a

+ stages, with CD1a expression

correlating with T lineage commitment (Dik et al., 2005; Joachims et al., 2006).

T-cell development has to accommodate the production of two distinct lineages of T cells

with different types of T-cell receptor (TCR): αβ and γδ (Janeway et al., 2001). Although

most T cells express αβ TCR and either of the TCR-associated molecules CD4 or CD8 on

their surface, a small minority (1–10%) demonstrates a γδ TCR, predominantly CD4–CD8

(i.e. DN) phenotype, an observation that can be explained by the fact that γδ TCR directly

binds to an Ag superstructure in an manner that is independent of the Major

Histocompatibility Complex (MHC)/peptide complexes (Deniger et al., 2014; Girardi, 2006;

Kabelitz et al., 2014; Lafont et al., 2014). Expression of a γδ TCR heterodimer at the surface

of a T cell in the thymus inhibits recombination of βTCR-chain locus during the CD4–CD8

stage, leading to commitment of the T cell to the γδ lineage (Deniger et al., 2014; Xiong and

Raulet, 2007). When exiting the thymus, this DN status is typically maintained probably

because co-receptors are dispensable for functional γδ TCR binding to Ags (Hayday, 2009;

Prinz et al., 2013). Importantly, commitment to the γδ T cell lineage has consistently been

shown to be dependent on the Notch signaling pathway, with the Notch-activators NOTCH1

and NOTCH3 genes instructing the earliest human intrathymic precursors to adopt a γδ T-cell

fate (Ciofani et al., 2006; García-Peydró et al., 2003; Van de Walle et al., 2013).

γδ T cells are defined by the expression of γ and δ heterodimer of TCR chains (γTCR/δTCR)

(Deniger et al., 2014; Xiang et al., 2014). For these two TCR loci, recombination of variable

(V), diversity (D, for δ chain), and junctional (J) region sequence elements generates a TCR

diversity, similar to the generation of B-cell Ab diversity via recombination of heavy and light

chains (Girardi, 2006).

The human γδ TCR complex is composed by the γδ TCR itself and various CD3 chains

following the stoichiometry: TCRγδCD32γδζ2 (Siegers et al., 2007). The assembly of a γδ

TCR complex in thymic progenitors has immediate consequences for γδ T-cell development

as the “strong” signals stemming from this kind of TCR – when compared to the “weaker”

signals from the pre-TCR – drive γδ/αβ common precursors into the γδ lineage (Haks et al.,

2005; Hayes et al., 2005; Zarin et al., 2015).

Functional responses by γδ T cells can be stratified by the V region of the TCRδ chain, also

usually termed as Vδ (Deniger et al., 2014; Kabelitz et al., 2014). In humans, γδ T cells are

limited to a small repertoire of V gene segments when undergoing chain rearrangement in

comparison with those available for Vα, Vβ, Immunoglobulin (Ig) light or Ig heavy chain

rearrangements. Three main Vδ gene segments – Vδ1, Vδ2 and Vδ3 – are most frequently

used in the rearrangement of this chain, although there are five less used Vδ segments that

have both a Vδ and a Vα designation, due to the location of the δ locus within the α locus on

the 14th

human chromosome (Adams et al., 2015; Boneville et al., 2010; Thedrez et al.,

2007). Seven functional Vγ gene segments - Vγ2, Vγ3, Vγ4, Vγ5, Vγ8, Vγ9 and Vγ11 -

Page 20: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 20

located within the γ locus on chromosome 7 in humans are used for rearrangement of the γ

chain, but several Vγ pseudogenes who are also found in this locus are not used in

productively arranged γδ TCRs (Adams et al., 2015). This restricted repertoire of Vδ and Vγ

gene segments available for rearrangement has led to speculate that these TCRs recognized

only conserved self-proteins of low variability. However, even though there are much more V

elements that may be used for α and β gene rearrangements, γδ TCRs have a greater potential

diversity than αβ T cells because of their ability to incorporate multiple tandem copies of their

D elements (Adams et al., 2015; Elliott et al., 1988; Girardi, 2006).

Productive recombination and pairing of matching the γ and δ chains facilitates the transition

of a “γδ quality control checkpoint”, selecting γδ T-cell precursors for their competence to

transduce signals via their TCR (Livak et al., 1995; Passoni et al., 1997; Prinz et al., 2006;

Prinz et al., 2013). In mice, naïve γδ T cells – as defined by a CD44lo

CD27+CD62L

+

phenotype – can leave the thymus at this point and populate secondary lymphoid organs and

blood (Prinz et al., 2013; Turchinovich and Pennington, 2011). However, γδ T cells that do

not exit the thymus at this stage can undergo further intrathymic differentiation before they

are exported to the periphery. This differentiation process will result in the development of

multiple murine γδ T-cell subsets, starting with the dendritic epidermal γδ cells (DETCs),

followed by the IL-17A-producing γδ cells (γδ17 cells), and ultimately the NK1.1+ γδ cells

(γδ NKT cells) (Azuara et al., 1997; Haas et al., 2009; Prinz et al., 2013; Vicari et al., 1996;

Zarin et al., 2015). Also, γδ T cells can be further differentiated into IFN-γ producers

(Schmolka et al., 2013; Shibata et al., 2012; Shibata et al., 2014; Zarin et al., 2015).

Mouse and human γδ T cells share many developmental and functional properties (Bonneville

et al., 2010; Vantourout and Hayday, 2013), such as the fact that γδ T cells are highly

effective at killing tumor cells and providing IFN-γ-mediated protective responses against

cancer. Moreover, the main determinants of tumor cell recognition — namely the γδ TCR and

NK cell receptors (NKRs), such as the natural killer group 2 member D (NKG2D) — are

shared by both species (Correia et al., 2013; Silva-Santos et al., 2015).

However, in contrast to what has been observed in mice, where functional properties of γδ T

cells can be acquired during their development in the thymus by a process known as

“developmental pre-programming” (Ribot et al., 2009), human γδ thymocytes are immature

(Ribot et al., 2014). In fact, their Th1/cytotoxic functions are selectively acquired only upon

ex vivo stimulation with IL-2 or IL-15 – but not when using IL-4 or IL-7 – through a process

dependent on the MAPK/ERK signaling (Ribot et al., 2014). This stimulus induced the de

novo expression of the TFs T-bet and eomesodermin, as well as the cytolytic enzyme perforin,

required for the cytotoxic type 1 program (Ribot et al., 2014).

In humans, γδ T cells can usually be found in the human mucosa, tongue, vagina, intestine,

lung, liver, and skin and can comprise up to 50% of the T cell population in intestinal

epithelial lymphocytes. Interestingly, in adult thymus, Vγ3, Vγ4 and Vγ1 rearrangements are

suppressed by the programmed rearrangement process, favoring production of Vγ2+ and other

adult-type γδ T cells. This indicates that a maturation process might confer these cells with

their specific homing properties which enables them to exit the thymus and home to

secondary lymphoid organs (Xiong and Raulet, 2007).

Page 21: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 21

Additionally, circulating γδ T cells can be found in the blood and lymphoid organs and

represent up to 0,5–16% (on average: 4%) of all CD3+ cells found in adult peripheral blood

(Carding and Egan, 2002; Deniger et al., 2014; Lafont et al., 2014). Specifically, the Vδ2

isotype is expressed by 50–95% of γδ T cells from human peripheral blood, whereas TCRs

including the Vδ1 and/or Vδ3 isotypes are predominantly found in γδ T cells from tissues

(skin, intestine, thymus) (Bonneville et al., 2010; Deniger et al., 2014; Lafont et al., 2014,

Ribot et al., 2014).

1.1.3 γδ T Cell Target Recognition and Response

Usually considered innate-like T cells (deBarros et al., 2011; Lafont et al., 2014), γδ T cells

possess a combination of innate and adaptive immune cell qualities. In fact, they can

rearrange TCR genes to produce J diversity and develop a memory phenotype, which is a

feature of the adaptive immune system, but they can also use a restricted TCR as a pattern

recognition receptor, which is a feature of the innate immune system (Girardi, 2006).

Some of their main features include being involved in the stress response to injured epithelia

and in tissue homeostasis by limiting the dissemination of malignant or infected cells and by

regulating the nature of the subsequent adaptive immune response. Additionally, γδ T cells

have potent MHC-unrestricted cytotoxicity, a high potential for cytokine release and a broad-

spectrum recognition of cancer cells (Hannani et al., 2012). Furthermore, ligands that interact

with γδ TCRs can be MHC molecules, MHC-like molecules or MHC-unrelated molecules

(figure 1), and receptor recognition varies accordingly with the γδ T cell subtype (Bonneville

et al., 2010; Hayday, 2009).

Most of the known human γδ T cell ligands are specific for the Vδ1 or the Vδ2 isotype

(Deniger et al., 2014). Vδ1+ γδ T cells are capable of recognizing several members of the

MHC superfamily family, all of which deemed MHC-like ligands, including members of the

CD1 family presenting lipids (Adams et al., 2015; Bonneville et al., 2010; Cardigan and

Egan, 2002). For instance, both Vγ1Vδ1 and Vγ2Vδ1 recognize the non-polymorphic MHC

molecule CD1c; Vγ5Vδ1 is a receptor for a galactosylceramide-CD1d complexes commonly

described in the activation of natural killer T (NKT) cells (Deniger et al., 2014; Spada et al.,

2000) and; recently CD1d has been shown to be a ligand for at least a subset of both Vδ1+ and

Vδ3+ γδ T cells (Adams et al., 2015). Moreover, Vδ1

+ cells have specificity for MHC Class-I

chain-related A and B (MICA and MICB, respectively), molecules that participate in evasion

of immune surveillance following viral infection and are usually present on tumor cells in

response to cellular stress (Bonneville et al., 2010; Gomes et al., 2010; Spada et al., 2010; Xu

et al., 2011).

Vδ2+ γδ T cells have preferred pairing with Vγ9, originating Vγ9Vδ2 cells, and this is the

most extensively studied sub-group of human γδ T cells. Several of its ligands have already

been identified, which include: the phosphoantigen (P-Ag) isopentenyl pyrophosphate (IPP)

and its isomer (E)-4-hydroxy-3-methyl-but-2-enylpyrophosphate (HMBPP) (Alexander et al.,

2008); members of the butyrophilin family (BTN), such as BTN3A1 (Harly et al., 2012); the

F1-Adenylpyrophosphatase (ATPase) (Scotet et al., 2005); the apolipoprotein A-I (Scotet et

Page 22: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 22

al., 2005) and; Mycobacterium tuberculosis and Mycobacterium leprae (Constant et al., 1994;

Lafont et al., 2001).

In contrast to the Vδ2 subpopulation, much less is known about the Vδ1 subset and even less

is known about the cells expressing the remainder Vγ chains. However, similarly to the

observed in Vγ9Vδ2 T cells, there is indirect evidence of a Vγ3 role in immunity against

cytomegalovirus (CMV) (Déchanet et al., 1999; Vermijlen et al., 2010) and human

immunodeficiency virus (HIV) (Wesch et al., 1998).

Figure 1 - γδ T cell recognition and response. For γδ T cells to be suitable for stress surveillance they recognize a spectrum

of molecules signifying dysregulation. These molecules may be self-encoded TCR and NKG2D ligands (T10 and T22, P-

Ags, MICA, etc.), or non-self-encoded, e.g., common products of multiple pathogens (HMBPP), unique products of very

common pathogens (e.g., putative CMV or Herpes ligands), or TLR ligands. The cells can then deploy several types of

function appropriate to different types of stress, directed against non-self or self-targets. The responses are negatively

regulated via inhibitory receptors for MHC-I, UPA, and probably other ligands. [Hayday, 2009]

Besides activation through the TCR- ligand mechanisms, γδ T cells can also be indirectly

activated by pro-inflammatory cytokines released by TLR-induced DCs and NK cells

(Bonneville et al., 2010; Hannani et al., 2012; Hao et al., 2010). Human γδ T cells can also

recognize and be activated by Ab-opsonized cells or microorganisms through binding of

IgGs, which mediates Ab-dependent cell cytotoxicity (ADCC) (Chen and Freedman, 2008;

Seidel et al., 2014).

Upon activation, these cells become capable of producing inflammatory cytokines,

chemokines, directly lyse infected or malignant cells, and establish a memory response to

attack pathogens upon re-exposure (Deniger et al., 2014; Hayday, 2009; Wesch et al., 2014),

as described below.

Page 23: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 23

1.2 Cancer and γδ T Cells

1.2.1 The Immune System and Cancer

Bearing several differences when compared to normal cells, cancer cells have two unique

main characteristics: uncontrolled growth and metastasis (Zhou, 2014). Additionally, recent

studies have shown that cancer cells have eight hallmarks, which include sustained

proliferative signaling, evading growth suppressors, cell death resistance, replicative

immortality, angiogenesis induction, metastasis and invasion activity, energy metabolism

reprogramming, and evading immune destruction (Hanahan and Weinberg, 2011; Zhou,

2014). Currently, cancer can be treated by using several methodologies, which include

surgery (Recht and Houlihan, 1995), radiotherapy (Bijker et al., 2006), chemotherapy (Goffin

et al., 2010), biological therapy (Manganoni et al., 2000), hormone therapy (Prezioso et al.,

2004), and targeted therapies (Urruticoechea et al., 2010; Vanneman and Dranoff, 2012).

However, since an occurrence of 20-30 million new cases of cancer is predicted to occur all

over the world by 2030 and, of those, it is expected that 13-17 million people will die from

the disease, no cancer therapy presently available seems to be entirely satisfactory

(Katikireddi and Setty, 2013; Siegel et al., 2012). Thus, cancer treatment remains a

challenging issue for both scientists and clinicians.

Recent developments in immunology, as for instance the successes of sipuleucel‑T and

ipilimumab in Phase III clinical trials, have validated the principle that immunotherapy can

also extend cancer patient survival, stressing out this type of therapy as a new anti-tumor

promising candidate (Vanneman and Dranoff, 2012; Zhou, 2014). Interestingly, research

published over the past decade in tumor immunology has validated the concept of cancer

immune surveillance which predicts that the immune system can recognize precursors of

cancer and, in most cases, destroy these precursors before they become clinically apparent

(Dunn et al., 2002; Galon et al., 2013; Hamaï et al., 2010). In fact, several studies have

identified specific patterns of immune activation associated with patient survival, proving that

the immune system can recognize and eliminate aberrant cancer cells arising within the

human body (Zhou, 2014). Additionally, twenty two types of leukocytes have been recently

associated with twenty five different types of cancer, whose presence or absence can indicate

a favorable or an adverse prognostic depending on the tumor type (figure 2) (Gentles et al.,

2015), with a special emphasis for the favorable outcome attributed to γδ T cell presence.

Thus, it has become clear that the immune system not only protects the host against tumor

development but also sculpts the immunogenic phenotype of a developing tumor and can

favor the emergence of resistant tumor cell variants (Galon et al., 2013; Hamaï et al., 2010;

Zhou, 2014).

In cancer patients, the immune system is apparently not proficient in eliminating cancer cells,

suggesting a suppression of its anti-tumor function. Indeed, it has been shown that several

factors may contribute to this immunosuppression such as a low frequency of high-avidity

anti-tumor T cells or the presence of CD4+CD25

+ regulatory T cells (Dugué et al., 2013; Frey

and Monu, 2006; Zhou, 2014). Therefore, using immunological methods capable of removing

this anti-tumor immunosuppression and/or able to increase the anti-tumor immunity can be

very useful for cancer treatment (Zhou, 2014).

Page 24: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 24

Figure 2 – Inferred leukocyte frequencies and prognostic associations in 25 human cancers. A) Global prognostic

associations for 22 leukocyte types across 25 cancers (n = 5,782 tumors; left) and 14 solid non-brain tumors (n = 3,238

tumors; right), ranked by unweighted meta-z score, with a false discovery rate (FDR) threshold of 25% indicated for each

plot. B) Concordance and differences in tumor-associated leukocytes (TAL) prognostic associations between breast cancers

and lung adenocarcinoma. Resting and activated subsets in are indicated by “–” and “+”, respectively. Red and blue bars in

indicate adverse and favorable prognostic associations, respectively. [Adapted from Gentles et al., 2015]

It is by now well established that the immune context of the tumor microenvironment (TME)

can influence cancer progression and outcome. Within the TME, several sub-populations of

effector cells can participate in cancer cell control and removal. All subsets of immune cells

can be found within tumors, but their presence differs accordingly with the tumor type and

stage of the disease and also between individuals (Hanahan and Weinberg, 2011; Lafont et

al., 2014).

In jawed vertebrates, B cells, αβ T cells and γδ T cells use genetically recombined receptors to

survey the environment and mediate the host defenses against disease. Among these

populations, the best studied T cell lineage is the one expressing αβ TCRs: within this group

the T cells often described as ‘‘conventional’’ are the most fully understood; less well

understood are the αβ T cell specialized populations that recognize non-peptide presenting

MHC molecules, who are often present at high frequencies in particular tissues or organs

(Adams et al., 2015; Deniger et al., 2014). Even more enigmatic are cells that express a γδ

TCR since this cell lineage remains the most poorly understood in terms of Ag recognition

and also to what concerns differentiation into effector cell subsets (Adams et al., 2015;

Hayday, 2009; Ribot et al., 2014). Albeit this fact, γδ T cells are already being targeted for

cancer immunotherapy due to multiple promising preclinical studies (Gomes et al., 2010; Liu

et al., 2008; Silva-Santos et al., 2015).

1.2.2 γδ T Cells in Cancer

γδ T cells have been proposed as the first line of immune defense that responds to a variety of

stress-inducible or pathogen-associated proteins or metabolites (Hayday, 2009). However,

A B

Page 25: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 25

contrary to mouse γδ thymocytes, human γδ thymocytes are functionally immature, but

nonetheless are highly poised to become type 1 cytotoxic effector cells. In fact, exogenous IL

‑2 or IL‑15 signals alone, in the absence of TCR stimulation, can upregulate type 1 TFs and

endow γδ thymocytes with IFN-γ-producing and tumor-killing functions (Ribot et al., 2014;

Silva-Santos et al., 2015).

Therefore, it is not surprising that γδ T cells actively contribute to the immune response

against many tumors, which include lymphoma, myeloma, melanoma, breast, colon, lung,

ovary, and prostate cancer (Bouet-Toussaint et al., 2008; Cordova et al., 2012; Dieli et al.,

2007; Kang et al., 2009; Lafont et al., 2014; Meraviglia et al., 2010). Of note, when expanded

in vitro in the presence of IL‑2, γδ T cells isolated from patients with melanoma,

glioblastoma, neuroblastoma or renal, breast, lung, ovarian, colon, pancreatic or blood cancers

efficiently killed tumor cell lines and/or primary cancer samples (Lo Presti et al., 2014; Silva-

Santos et al., 2015). This anti-tumor role can be accomplished directly through their cytotoxic

activity against tumors (Lafont et al., 2014). Moreover, γδ T cells can indirectly regulate the

biological functions of other cells, such as DCs, NK cells, NKT cells, CD4+CD8

+ T cells and

IFN-γ-producing CD8+ T cells by producing the pro-inflammatory cytokines IFN-γ and tumor

necrosis factor (TNF)-α, by Ag presenting or by producing signaling agents, such as IL-17,

IL-10 and IL-4 (figure 3) (Bonneville et al., 2010; Hao et al., 2010; Lafont et al., 2014; Rei et

al., 2015; Thedrez et al., 2007).

Owing to these potent effector functions, γδ T cells are currently attractive mediators for

immunotherapy, namely against cancer. However, clinical trials completed to date have

shown objective responses of only 10-33% (Gomes et al., 2010). This lack of response to

treatment could be explained by a deficient expansion and/or functions of effector γδ T cells.

Of note, Vδ1+ T cell lines have generally outperformed their Vδ2

+ counterparts (Correia et al.,

2011; Lo Presti et al., 2014) which makes it somewhat paradoxical that almost all of the

clinical applications of γδ T cells have thus far concentrated on Vγ9Vδ2+ T cells (Silva-

Santos et al., 2015).

Research on γδ T cell activation molecular mechanisms has demonstrated that TCR co-

stimulation plays a central role in this process, thus creating a possibility for positive (in case

of infection or cancer) or negative (in chronic inflammation or autoimmunity) modulation of

γδ T cell responses in the clinic (Ribot and Silva-Santos, 2013). Namely, CD27 expression

endows Vγ9Vδ2 peripheral blood lymphocytes (PBLs) with enhanced proliferative capacity,

expanding the γδ T cell group capable of producing IFN-γ, which clearly could be useful for

cancer immunotherapy (deBarros et al., 2011).

Earlier this year, recent advances in γδ T cell-based immunotherapy gave rise to the first

clinical application based on the Vδ1 subpopulation reported thus far: Delta One T (DOT)

cells, described as highly reproducible cells for selective, large scale expansion and

differentiation of cytotoxic Vδ1+ T cells, have showed a high potential in pre-clinical models

of chronic lymphocytic leukemia (CLL). Importantly, development of these cells did not

require any genetic manipulation and was able to specifically targeted leukemic, but not

healthy cells, in vitro. Their application prevented wide-scale tumor dissemination to

peripheral organs in vivo, without any signs of healthy tissue damage, providing proof-of-

Page 26: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 26

principle for clinical application of DOT cells in adoptive immunotherapy of CLL (Almeida

et al., 2016).

Figure 3 – Anti-tumor functions of γδ T cells. A) γδ T cells can recognize tumor cells through interaction with (i) TCR

ligands, such as P-Ags, F1-ATPase, BTN3A1, EPCR,…, and (ii) innate receptor ligands, such as ULBP, MICA/B, and

nectin-like 5. Following sensing of tumor antigens or stress signals, γδ T cells are activated and can kill tumor cells through

cytotoxic mechanisms that rely on the perforin/granzyme pathway, the death receptor pathway in response to TRAIL or Fas-

L expression, and ADCC in the presence of tumor-specific antibodies. B) γδ T cell activation leads to TNF-α and IFN-γ

production and CD40-L expression that promote DC maturation and T cell differentiation into Th1 cells. IL-17-producing γδ

Th17 cells favor Th17 effector cell development. Th1 and Th17 effector T cells display anti-tumor functions to control tumor

development. C) Through a trogocytosis mechanism, activated γδ T cells can capture and express CD1d molecules and then

promote iNKT cell activation. Activated γδ T cells can also display antigen-presenting cell functions (MHCI and II, CD40,

CD83, and CD86 expression) and activate both naïve and effector T cells with cytotoxic activity against tumor cells. D)

Activated γδ T cells can provide a co-stimulatory signal to NK cells through CD137L expression to promote their anti-tumor

activity. E) In the presence of specific signals, activated γδ T cells can display a Tfh profile (i.e., IL-4, IL-10, and CXCL13

production and CD40-L expression) to help B cell antibody production. Although not yet demonstrated, production of

antibodies against specific tumor antigens could be involved in the humoral anti-tumor response. [Lafont et al., 2014]

Page 27: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 27

However, some reports have emerged that suggest a pro-tumor role of γδ T cells in cancer.

Despite the well-established concept of γδ T cells as potent anti-tumor tumor infiltrating

lymphocytes (TIL), a study in 2007 on human breast cancer surprisingly revealed a potential

pro-tumor function of these cells (Peng et al., 2007; Rei et al., 2015), with the γδ TILs being

the most significant predictor of relapse and poor survival in these cancer patients (Ma et al.,

2012; Silva-Santos et al., 2015). Moreover, recent reports have revealed an unexpected series

of pro-tumor functions of γδ T cells in mouse models and human patients (Rei et al., 2014,

Rei et al., 2015). In particular, IL-17-producing (Vδ1+) γδ T cells have been reported, for the

first time in human, to promote the chronic inflammation associated with colorectal cancer,

through recruitment of myeloid derived suppressor cells (MDSCs) (Wu et al., 2014).

Additionally, γδ T cells have been shown to promote cancer progression by enhancing

angiogenesis (Wakita et al., 2010). Once more, the common mediator for all of these

functions appears to be the cytokine IL-17, whose pathogenic effects seem to be able to

override the anti-tumor immune response orchestrated by IFN-γ production (Rei et al., 2015).

Given this apparent dual role of γδ T cells in the context of cancer, depending on their

cytokine profile, it becomes fundamental to understand the molecular mechanisms associated

with the regulation of their functional differentiation.

1.3 MiR Role in Gene Regulation

1.3.1 MiR Biogenesis and Maturation

MiRs are evolutionarily conserved, short (20–23-nucleotide), single-stranded, non-coding

RNAs that regulate target genes at the post-transcriptional level by antisense binding to their

target 3’-untranslated regions (UTRs) (Sheppard et al., 2014; Winter et al., 2009; Zhou et al.,

2011), which results in translational repression and/or degradation of the targeted transcript

(Carthew and Sontheimer, 2009). MiRs were first discovered in Caenorhabditis elegans (C.

elegans) in 1993 (Lee et al., 1993; Zhou et al., 2011), and are estimated to regulate about 90%

of human protein-coding genes, which clearly indicates the powerful role of miRs in

regulating human genes (Friedman et al., 2008; Mogilyansky and Rigoutsos, 2013). In

mammalian cells, more than 700 miRs have been already identified and shown to regulate

many developmental and differentiation processes (Friedman et al., 2008).

Most of the human miRs reside in intergenic regions and use their own gene promoter for

expression (Lau et al., 2001; Lee et al., 2004; Zhou et al., 2011). The remainders are located

mostly in the introns of coding genes and are generally transcribed coincidentally with their

host genes (Saini et al., 2007).

MiR genes are very similar to protein coding genes since the majority of them are transcribed

by RNA Polymerase II, resulting in primary miR (pri-miR) transcripts that are then capped

and polyadenylated (Cai et al., 2004; Lee et al., 2004). Moreover, miR promoters are

regulated by the same epigenetic marks as those used in protein coding genes (Barski et al.,

2009). In the nucleus, the double-stranded RNA hairpin structure in a pri-miR transcript is

processed by a type III ribonuclease (RNase III) known as Drosha and a non-catalytic protein

Page 28: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 28

named DiGeorge syndrome critical region 8 (DGCR8). By forming a complex with the RNase

III enzyme, DGCR8 orients the catalytic domain of Drosha that releases hairpins from pri-

miRs, resulting into 60–80 nucleotide stem-loop structures, called precursor miRs (pre-miRs)

(Gregory et al., 2006; Zhou et al., 2011). However, not all miRs are processed in this way. A

special subset, known as mirtrons are not cleaved by Drosha, as the spliced intron already

corresponds to a specific processed miR precursor (Okamura et al., 2007).

After being formed, pre-miRs fold into small helical structures, allowing for their recognition

by Exportin-5 (Exp5). Then, Exp5 in complex with Ran-GTP exports the pre-miR from the

nucleus to the cytoplasm, where a second type III RNase, Dicer, cleaves the pre-miR into 18–

24 base pair duplexes, generating mature miRs (Winter et al., 2009). These mature species

contain a guide strand, which targets specific messenger RNAs (mRNAs) through the seed

sequence, and an antisense strand, also known as passenger strand or miR* strand (Meijer et

al., 2014). During miR maturation in the cytoplasm, the Argonaute protein (AGO) – a critical

component of RNA-induced silencing complexes (RISC) – is thought to stabilize the guide

strand, which is crucial for miR function (Kai and Pasquinelli, 2010; Zhou et al., 2011).

1.3.2 MiR Silencing Mechanisms

In order to elicit their silencing mechanisms, mature miRs are incorporated into the RISC by

loading their guide strand into the AGO protein. This protein normally uses the seed sequence

of the 5’ terminus – which is the thermodynamically less-stable end of the miR duplex – to

recognize complementary mRNA transcripts and then proceed with their degradation or

translational silencing (figure 4) (Bartel, 2004; Hutvágner and Zamore, 2002; Podshivalova

and Salomon, 2013; Winter et al., 2009).

There are four AGO proteins in human cells (AGO1-AGO4). AGO2 possesses catalytic

activity and can cleave bound mRNAs. The function of AGO1 is less well-defined but it can

affect miR-mediated inhibition of translation, splicing, and transcription (Matsui et al., 2015).

Although all AGO proteins have the ability to interact with small RNAs, it has been shown

that passenger strand cleavage and RNA chaperone activities that are intrinsic to both AGO1

and AGO2 are sufficient to load these small RNAs into the RISC complex (Wang et al., 2009;

Wang et al., 2012), highlighting the importance of these two proteins in the miR silencing

mechanisms.

Assembly of the miR into RISC is regulated by thermodynamic properties but it can also be

subject to additional regulation as the ratio miR:miR* varies dramatically depending on the

miR duplex properties, on the tissue where they are being processed and on the

developmental stages (Ro et al., 2007). Importantly, although direct cleavage of the targeted

mRNA will cause a reduction of the mRNA levels, inhibition of protein translation will not

affect the mRNA levels of the targeted protein (Zhou et al., 2011).

Page 29: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 29

Figure 4 – The “linear” canonical pathway of miR processing. Canonical maturation includes production of the pri-miR

by RNA polymerase II (or III) and cleavage of the pri-miR by the Drosha–DGCR8 complex in the nucleus. The resulting pre-

miR, is exported by Exp5–Ran-GTP. Once in the cytoplasm, Dicer cleaves the pre-miR hairpin to its mature length. The

functional (guide) strand of the mature miR is loaded together with AGO proteins into the RISC, where it guides RISC to

silence target mRNAs, whereas the passenger strand (black) is degraded [Winter et al., 2009]

1.3.3 MiR-Mediated Regulation of T Cell Biology

MiR expression patterns vary among lymphocyte subsets and stages of development,

indicating that these small RNAs may contribute to lymphocyte identity or functional state

(Jeker and Bluestone, 2013). By instance, miR expression profiles at each thymic T cell

developmental stage have been shown to be unique, with some miRs undergoing expression

changes up to three orders of magnitude during maturation (Kirigin et al., 2012).

Accordingly, removal of all mature miRs at early stages of thymocyte development via Dicer

or Drosha knockouts has resulted in developmental blockage and consequent reduction of the

peripheral mature αβ T and iNKT cell pool (Cobb et al., 2005; Podshivalova and Salomon,

2013; Seo et al., 2010; Zhou et al., 2011).

Furthermore, it has been shown that expression of miR-181 promotes NK cell development,

through the suppression of NLK – a Notch inhibitor – providing an important link between

miRs and this signaling pathway (Cichocki et al., 2011). In agreement with this, deletion of

miR-181a-1/b-1 inhibited the development of Notch1 oncogene-induced T cell acute

lymphoblastic leukemia (T-ALL). Importantly, Notch oncogenes use normal thymic

progenitor cell genetic programs for tumor transformation. However, comparative analyses of

miR-181a-1/b-1 function in normal thymocyte and tumor development demonstrated that

Page 30: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 30

these miRs could be specifically targeted to inhibit tumor development with little toxicity to

normal development (Fragoso et al., 2012).

MiRs have also been implicated in T cell survival and proliferation. For instance,

overexpression of miR-491 in CD8+ and CD4

+ T cells inhibited cell proliferation and

promoted apoptosis. This inhibition was probably achieved by targeting the pro-survival

protein Bcl-xL, the CDK4 and the TF-1 proteins, involved in cell proliferation (Yu et al.,

2016). Also, in tumor-reactive CD8+ T cells, miR-29b and miR-198 overexpression reduced

anti-apoptotic and proliferation-associated gene products by down-modulating JAK3 and

MCL-1, leading to immune dysfunction (Gigante et al., 2016).

Several other miRs have also been shown to impact on T cell functional differentiation. As an

example, overexpressing miR-491 decreased the IFN-γ production in CD8+ T cells (Yu et al.,

2016). Analogously, miR-146a expression in these cells was correlated with a memory

phenotype (Sheppard et al., 2014). Furthermore, this miR controlled Th1-cell differentiation

of human CD4+ T lymphocytes by targeting protein kinase C epsilon (PRKC) (Möhnle et al.,

2015). Similarly, when overexpressed, miR-20a inhibited TCR-mediated signaling and

cytokine production in human naïve CD4+ T cells (Reddycherla et al., 2015), while miR-583

impaired NK cells differentiation process (Yun et al., 2014). Moreover, miR-181a expression

was shown to regulate the activation of human memory Th17 cells through modulation of

ERK phosphorylation (Mele et al., 2015), highlighting once more the importance of this miR

in regulating T cell biology.

In mice, CD8+ T cells failed to undergo robust expansion and differentiation into short-lived

terminal effector cells in response to primary infection with Listeria monocytogenes or

Vaccinia virus in the absence of miR-150 (Smith et al., 2015). Importantly, this miR has been

identified as a positive regulator of IL-10 cytokine secretion in Th1 cells (King et al., 2016)

and is also able to regulate the Notch signaling by reducing NOTCH3 levels in T-cell lines

(Ghisi et al., 2011).

MiR functions have also been implied in regulating oncogenesis, some of them by impairing

and others by enhancing T cell functions. For instance, miR-152 overexpression enhanced NK

cytolysis against hepatoma cells, while miR-155 overexpression increased CD8+ T-cell anti-

tumor activity by enhancing responsiveness to homeostatic γc cytokines (Bian et al., 2015; Ji

et al., 2015). In contrast, miR-23a expression worked as a strong functional repressor of the

TF BLIMP-1, impairing T lymphocyte cytotoxicity and effector differentiation. Blockage of

miR-23a in CD8+ cytotoxic T lymphocytes prevented tumor-dependent immunosuppression

by restoring these cells functional properties (Lin et al., 2014). Consistently, overexpressing

the miR-23a cluster (which includes miR-23a, 27a, and 24) reduced IFN-γ levels and Ag-

specific cytotoxicity in human CD8+ T cells (Chandran et al., 2014).

Interestingly, some miRs have also been implied in regulating the T cell metabolism. For

instance, downregulation of miR-150 in human activated CD4+

T cells increased the SCL2A1

gene expression. The latter encodes for the glucose transporter 1 (GLUT1) protein, which has

great importance in the cellular metabolism (King et al., 2016). Additionally, in cases of

ovarian cancer a glucose restriction was shown to be imposed on T cells, thus dampening

their functions by maintaining high levels of miR-101 and miR-26a. Such restriction

Page 31: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 31

constrained the methyltransferase EZH2 expression, which is an important epigenetic

modifier (Zhao et al., 2016). Importantly, EZH2 was able to activate the Notch pathway by

suppressing Notch repressors. Consequently, this suppression stimulated T cell polyfunctional

cytokine expression and promoted their survival via Bcl-2 signaling (Zhao et al., 2016).

Altogether these results establish an important link between cellular metabolism,

differentiation and proliferation processes in T cells, mediated by miRs expression.

This notwithstanding, no miRs have yet been shown to be implicated in the differentiation of

human γδ T cells. Assessing the functional roles of these RNA species that regulate the

differentiation of anti-tumor γδ T cells could open avenues for the manipulation of these cells

in cancer immunotherapy.

Page 32: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 32

Aims of the Thesis

Page 33: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 33

2. Aims of the Thesis

Recent data from the host laboratory have reported that the anti-tumor effector properties of

γδ T cells were selectively acquired upon stimulation with IL-2 or IL-15, but not IL-7 (Ribot

et al., 2014). The effects of IL-2/IL-15 depended on MAPK/ERK signaling and induced the

de novo expression of the TFs T-bet and eomesodermin, as well as the cytolytic enzyme

perforin, required for the cytotoxic type 1 program. With this project, we propose to explore

an additional layer in the regulation of γδ T cell differentiation, by characterizing the post-

transcriptional mechanisms mediated by miRs.

The study of gene expression regulation has been largely dominated by transcriptional

mechanisms. However, the recent identification of small non-coding miRs has dramatically

modified our perception of biological processes. MiRs exert a strong inhibitory function on

the expression of mRNAs, either promoting their degradation, or preventing their translation.

Since this key post-transcriptional process controls the expression of most mammalian genes

(Berezikov et al., 2011), it becomes particularly interesting to analyze its role in cellular

differentiation processes.

Building on these considerations, we proposed to investigate the miR-dependent mechanisms

controlling the functional differentiation of human γδ T cells. In particular, we were interested

in identifying novel targets to be considered for the manipulation of γδ T cells in cancer

immunotherapy.

Thus, our work plan consisted of two main goals:

1) Characterize the miR repertoire associated with γδ T cell functional differentiation by

RNA-seq. The bioinformatic analysis of these results allowed us to identify discrete

repertoires of miRs associated with functional differentiation in human γδ T cells. We then

screened and validated, by RT-PCR, candidate miRs carefully selected from the library

obtained by the RNA-seq assay.

2) Characterize the role of selected miRs by performing gain-of-function experiments.

For this, we developed two different gain-of-function approaches: electroporation with miR

mimics using the Neon system or retroviral transduction of miR vectors on γδ T cells isolated

from healthy donors peripheral blood monocyte cells (PBMCs) or thymic biopsies.

This project constitutes the first comprehensive study of the miR-based post-transcriptional

events that control human γδ T cell functional differentiation. The recent molecular biology

tools associated with miR analyses and manipulation will serve the purpose of understanding

this process and identifying novel molecular targets valuable for the design of new clinical

protocols for cancer immunotherapy.

Page 34: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 34

Materials and Methods

Page 35: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 35

3. Materials and Methods

3.1 Ethics

Thymic specimens were routinely obtained during pediatric corrective cardiac surgery thanks

to an ongoing collaboration with Hospital de Santa Cruz (Carnaxide) and Dr. Ana E. Sousa

(IMM). Peripheral blood γδ T cells from healthy volunteers were obtained through the

Instituto Português do Sangue (Lisboa).

3.2 Lymphocyte Preparations

Thymic samples (from newborn to eight-year-old children) were processed by tissue

dispersion and Histopaque-1077 (Sigma-Aldrich) density gradient. PBMCs were collected

from anonymous healthy volunteers, diluted with 1 volume of PBS (Invitrogen Life

Technologies), and separated on a Histopaque-1077 density gradient.

γδ T cells were isolated (to >90% purity) through magnetic cell sorting (MACS) by positive

selection for the RT-PCR and Neon experiments or by negative selection for the retrovirus

experiments (both from Miltenyi Biotec). Alternatively, Vδ1 and Vδ2 T cells were

electronically sorted on a fluorescence-activated cell sorting (FACS) Aria cell sorter (BD

Biosciences).

3.3 Cell Culture

MACS isolated γδ T cells were cultured at a density of 5*105 cells/ml in round bottom 96-

well plates with RPMI 1640 and 2 mM L-glutamine supplemented with 10% FBS, 1% of

sodium pyruvate, 1% of HEPES, 1% of minimum essential amino acids (NEAA) , and 1% of

penicillin and streptomycin (Pen/Strep) (all from Invitrogen Life Technologies). Indicated

cytokines were added when mentioned (all from PreproTech, 10ng/ml).

Alternatively, for retroviral transduction experiments, γδ T cells were cultured at a 2*106

cell/ml density, in flat bottom 48-well plates in a DMEM medium (Invitrogen Life

Technologies) supplemented with 15% FBS, 1% of HEPES, 1% NEAA, and 1% of Pen/Strep.

Indicated cytokines were added when mentioned (all from PreproTech, 10ng/ml).

The human embryonic kidney 293 cells with large T antigen and a transcription transactivator

(HEK293T TAT) cell line (ATCC® CRL-11268™) and the NIH/3T3 cells (ATCC® CRL-

1658™) were grown in T 175 flasks in DMEM supplemented with 10% FBS, 1% of HEPES,

1% of NEAA, and 1% of Pen/Strep, during four to five days. After reaching the required cell

number for the experiment, the HEK293T TAT cell line was cultured in 10cm tissue culture

plates (Sigma-Aldrich TPP®) at a density of 5*10

5 cells/ml, whilst the NIH/3T3 cells were

cultured in flat bottom 6-well plates (Corning Incorporated) at a density of 7*104 cells/ml.

All incubations were performed at 37°C in a 5% CO2 environment.

Page 36: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 36

3.4. Quantitative RT-PCR

For miR expression analysis total RNA was extracted from MACS isolated γδ T cells by

using the miRNeasy Mini Kit (Qiagen) according to the manufacturer’s protocol. RNA

concentration and purity were determined using Qubit® RNA HS (High Sensitivity) Assay

Kit (Thermo Fisher Scientific). For complementary deoxyribonucleic acid (cDNA) synthesis

and qPCR amplification the miRCURY locked nucleic acid (LNA)TM

Universal RT miR PCR

protocol (Exiqon, 2014) was performed. Total RNA was reverse-transcribed into cDNA using

the T100® Thermal Cycler (BioRad) and all quantitative PCRs (qPCRs) were performed in

MicroAmp® Optical 384-Well Reaction Plate (Applied Biosystems) using the RT-PCR

ViiA7TM

system (Applied Biosystems). LNATM

PCR primer sets (Exiqon) were used on the

cDNA previously obtained and relative quantification of specific miRs to small nucleolar

RNA C/D Box 44 (SNORD44) reference was carried out using SYBR on ABI ViiA7TM

cycler

(Applied Biosystems). Data was analyzed using ViiA7TM

software v1.2.1.

3.5 γδ T cell Transfection using Neon System for Mimics Delivery

When indicated, MACS isolated γδ T cells were activated with anti-CD3 (HIT3a) and anti-

CD28 (CD28.2) (both from eBioscience) and cultured in round bottom 96-well plates with the

indicated cytokines. Then, they were transfected by the Neon electroporation transfection

system (Invitrogen) with an optimized version of the manufacturers recommended protocol

(Invitrogen, 2010). Briefly, the small interfering-RNA (siRNA)CD45 or the selected

miRCURY LNA™ miR Mimics (both from Exiqon) were transfected using indicated

concentrations. After testing different parameters with the siRNACD45, which was used only

for the setup, the settings were optimized at 1600V with three 10 ms pulses, using 25.000 γδ

T cells per transfection. As a negative control a miR mimic that has the same unique design

with two LNA™-enhanced passenger strands as the miRCURY LNA™ miR Mimics, and

whose guide strands have no homology to any known miR or mRNA sequences in mouse, rat

or human was used. The target sequence for each miR mimic was the following:

- hsa-miR-135b-5p: UAUGGCUUUUCAUUCCUAUGUGA

- hsa-miR-10a-5p: UACCCUGUAGAUCCGAAUUUGUG

- hsa-miR-20b-5p: CAAAGUGCUCAUAGUGCAGGUAG

- hsa-miR-181a-2-3p: ACCACUGACCGUUGACUGUACC

- hsa-miR-196b-5p: UAGGUAGUUUCCUGUUGUUGGG

- cel-miR-39-3p (negative control): UCACCGGGUGUAAAUCAGCUUG

Page 37: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 37

3.6 MiR-Overexpressing Recombinant Retrovirus Production

The native precursor stem-loop of the miRs candidates was cloned into the retroviral vector

MSCV-IRES-GFP-PGW (pMIG-PGW) using genomic DNA as a template and the following

primers (table 1):

Table 1 - Gene-specific primer design with 15bp extensions homologous to vector ends (in green for the forward primer, or

red for the reverse primer) for cloning of each one of the miR candidates into the pMig-PGW plasmid.

Primer Design for pMIG-PGW cloning Fwr_pMIG-PGW_miR-135b: CGCCGGAATTAGATCGAAGCCACCCCTCCTCATAC

Rev_pMIG-PGW_miR-135b: TAACCTCGAGAGATCACCGACTCAGAAAGCTCAGC

Fwr_pMIG-PGW_miR-10a: CGCCGGAATTAGATCAGGTTCTCGTCCCTTTGCG

Rev_pMIG-PGW_miR-10a: TAACCTCGAGAGATCTGCCTTCTTCGCACACTGA

Fwr_pMIG-PGW_miR-20b: CGCCGGAATTAGATCTGCAGTTAGTGAAGCAGCTTAGA

Rev_pMIG-PGW_miR-20b: TAACCTCGAGAGATCCCCGACAACAGCAAAACAGAT

Fwr_pMIG-PGW_miR-181a: CGCCGGAATTAGATCTCCTAGTATATAGCAGATCCCCAAT

Rev_pMIG-PGW_miR-181a: TAACCTCGAGAGATCGACTGCTCCTTACCTTGTTGAA

Fwr_pMIG-PGW_miR-196b: CGCCGGAATTAGATCTCCTCTCTCCCTGCCTTTCC

Rev_pMIG-PGW_miR-196b: TAACCTCGAGAGATCGGGACTGGTGTGTGTGTGT

After having the PCR product in which our miR-loop of interest was already amplified, the

Protocol I: In-Fusion Cloning Procedure w/Spin-Column Purification (Clontech, 2012) was

used to purify the PCR fragments (figure 5). For the first transformation process the StellarTM

Competent Cells were used according to the manufacturer’s protocol PT5055-2 (Clontech,

2011).

The plasmid pMIG-PGW either empty (pMIG-PGW-Empty) or containing the miR candidate

stem-loop fragment (pMIG-PGW-miR-X) was extracted from the bacteria using the GeneJET

Plasmid Miniprep Kit (Thermo Fisher Scientific). To confirm the presence of the miR insert

on the plasmid a DNA digestion using proper restriction enzymes was performed by

following the protocol for Fast Digestion of DNA (Thermo Fisher Scientific, 2012).

Besides the confirmation made by analyzing the samples fragment lengths in an agarose gel,

the presence of the miR candidates in each plasmid was accomplished by sending the samples

to sequence (STAB VIDA). Validation of the results was performed by analyzing the

sequences, expected and obtained, with the SnapGene® Viewer Software, Version 3.1.4.

After confirming each miR stem-loop presence and its integrity in the pMIG-PGW vector a

second transformation step was performed using a more stable strain of bacteria: this

transformation procedure followed the protocol One ShotTM Stbl3TM Chemically

Competent E. coli (Thermo Fisher Scientific, 2015). After a new plasmid purification and

another DNA digestion to confirm the presence of the clones, the viral supernatant was

produced by transfecting the plasmids pMIG-PGW (either empty or with miR-X), pCMV-

VSV-G and pCL-Eco with the Opti-MEM® (Life Technologies) and the X-tremeGENE9

DNA Transfection Reagent (Roche) into the HEK293T TAT cells cultured in 10cm culture

plates, as previously described (x-TremeGene, 2013). The efficiency of the viral particles was

tested by transducing 100.000 NIH/3T3 cells per well, in a Nunc™ 6-well plate, with 8μg/ml

of polybrene during a 60 min centrifugation at 37ºC, 2200 rpm. The cells rested in the

incubator at 37º C for 72h, washed with FACS buffer (1500 rpm 5 min), and resuspended in

Page 38: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 38

FACS buffer for FACS acquisition. As readout the percentage of green fluorescent protein

(GFP)+ cells was measured to assess the transduction efficiency.

Figure 5 – Schematic representation of the procedure to develop a retroviral construct with the DNA of interest.

[Adapted from Clontech, 2012]

3.7 γδ T cell Transduction with the Retroviral Constructs

For viral transduction of the γδ T cells, the latter were cultured in 48-well plate as previously

described. The cells were activated overnight with plate-bound monoclonal Abs (mAbs) anti-

CD3 (1μg/ml; HIT3a; eBiosciences) and anti-CD28 (1μg/ml; CD28.2; eBiosciences) in

presence of IL-7 or IL-7+IL-2 (10 ng/m PeproTech). 5*105 γδ T cells per well were

transduced with pMIG-PGW-miR-20b, pMIG-PGW-miR-181a or pMIG-PGW-Empty vector

using 160μl of concentrated viral supernatant per well (figure 6). The transduction was

performed with the addition of 100uL of polybrene (8μg/ml) followed by a 45 min

centrifugation at 37ºC, 2200 rpm. After 48h the transduced γδ T cells were restimulated and

stained with mAbs for FACS analysis of their functional properties, as explained in the next

section.

Page 39: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 39

Figure 6 – Schematic representation of the transfection process. Three different plasmids are required in order to produce

the virus - pMIG-PGW, pCMV-VSV-G and pCL-Eco. Virus production occurs in the HEK293T TAT cells; viral particles

are tested in the 3T3 cells for the GFP presence. Only then are the γδ T cells infected with the virus.

3.8 FACS Analysis

To assess γδ T cell proliferation, cytokine secretion and phenotypic features γδ T cells were

restimulated with PMA (50 ng/ml, Sigma-Aldrich; P-8139) and Ionomycin (1 μg/ml, Sigma-

Aldrich; I-0634) for 3h-4h at 37°C, with the addition of Brefeldin A (BFA) (10 μg/ml, Sigma-

Aldrich; B-7651). Cells were then transferred into 96-well V bottom plates (Nunc® Thermo

Fisher Scientific) and washed once in FACS buffer (1x PBS plus 2% FBS) supplemented with

BFA for 5 min, 1500 rpm at room temperature. For surface staining, cells were resuspended

in 50μl FACS buffer supplemented with BFA containing the indicated antibodies and

incubated for 30 min at 4ºC. Cells were then washed with FACS buffer supplemented with

BFA, resuspended in 150uL Fixation/Permeabilization buffer (eBiosciences) supplemented

with BFA and left to incubate for 30 min at 4ºC. Alternatively, to ensure the maintenance of

GFP expression, retrovirally transduced γδ T cells were fixed with 4% Paraformaldehyde

(Sigma-Aldrich) (Grupillo et al., 2011). Cells were then washed in Permeabilization buffer

(eBiosciences) and resuspended in Fc block (eBiosciences) for 10 min at 4ºC. For

intracellular cell staining the cells were incubated for 30 min at 4°C in 50μl of

Page 40: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 40

Permeabilization buffer containing the indicated antibodies. Cells were washed twice, first in

Permeabilization buffer and then in FACS buffer, and resuspended in 200μl of FACS buffer

for FACS analysis (figure 7).

For the Neon experiments, cells were labeled with the following fluorescent mAbs: anti–Vδ1-

FITC (TS8.2) (Thermo Fisher Scientific); anti–Vδ2-PerCP (B6), anti–TNF-α-PE-Cy7

(MAb11), anti–IFN-γ-PE (4S.B3), anti-Ki67-BV421 (Ki-67) (all from BioLegend);

LiveDead-APC-Cy7 (Life Technologies); and anti-CD45-PerCP for the Neon setup (2D1)

(eBiosciences). For the retroviral experiments cells were labelled with the following

fluorescent mAbs: anti-Vδ1-PE (REA173) (Miltenyibiotec); anti-Annexin V-APC (VAA-33),

anti–CD27-PE-Cy7 (LG.7F9), anti- IFN-γ-APC (4S.B3) (all from eBiosciences); anti-CD69-

BV421 (FN50), anti-CD45RA-PB (HI100), anti-Ki67-PB (Ki-67), anti–TNF-α-PE-Cy7

(MAb11) and anti-Vδ2-PerCP (B6) (all from Biolegend).

All incubations were performed in the dark. FACS acquisition was performed on FACS

Fortessa (BD Biosciences) cell analyzer.

All the data were analyzed using FlowJo v.9.8.1 software.

Figure 7 – FACS gating strategy. LiveDead negative cells were identified after selection of Live Cells (from previously

MACS isolated γδ T cells) and doublets exclusion. The Vδ1 and Vδ2 subpopulations were then identified within the

LiveDead negative subset.

3.9 Statistical Analysis

Differences between populations were assessed using the Student t test and are indicated in

the figures when significant. *p < 0,05; **p < 0,005; ***p < 0,001.

SS

C-A

FSC-A

FS

C-W

FSC-A LiveDead

1

0 103

104

105

0

103

104

105

160613 gd BC21 mimics IL7+IL2_miR C elegans.fcs…live´

<PerCP-A>: Vd2

<F

ITC

-A>

: V

d1

40.1

19.8

Vδ2

Page 41: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 41

Results

Page 42: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 42

4. Results

4.1 MiR Signature Associated with γδ T Cell Type 1 Differentiation

As illustrated below (figure 8), human γδ thymocytes are functionally immature and

differentiate into IFN-γ+ TNF-α

+ type 1 effector T cells upon IL-2 (but not IL-7) stimulation

(Ribot et al., 2014).

Figure 8 – Human γδ thymocytes are devoid of IFN-γ production and cytotoxic functions but IL-2 signal differentiates

them into cytotoxic type 1 effector T cells. MACS-purified γδ thymocytes either freshly isolated or cultured for 7 days in

the presence of the indicated cytokines, stained for IFN-γ and TNF-α following 4h of stimulation with PMA and ionomycin.

[Adapted from Ribot et al., 2014]

The effects caused by IL-2 depended on the MAPK/ERK signaling and induced de novo

expression of the TFs T-bet and eomesodermin, as well as the cytolytic enzyme perforin

(Ribot et al., 2014).

MiR discovery has brought another degree of complexity to γδ T cell regulation and clearly

needs to be considered when deciphering the molecular mechanisms that govern γδ T cell

differentiation. Thus, we decided to analyze by RNA-seq the miRs signature associated with

IL-2 (mature) versus IL-7 (immature) signaling in human γδ thymocytes. The unbiased

analysis of these results provided for the identification of discrete repertoires of miRs

associated with regulation of the transcriptional signatures for γδ T cell functional

differentiation.

We first proposed to select from this library 20 of the most abundant (in term of copy

numbers) and top differentially (all above 1.5 log fold-change) expressed miRs. These criteria

allowed us to build a heatmap highlighting the top candidate miRs for further screening

(figure 9). Whereas some miRs, such as miR-642a/10a/34c/20b/221 display a higher level of

expression within functional γδ T cells, others, namely miR-181a/196b/150/574/135a are

instead downregulated in those samples in comparison with immature γδ T cell controls.

Fresh

IL-7 IL-2

TNF-α

IFN

Page 43: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 43

Figure 9 – MiR signature associated with γδ T cell type 1 differentiation. Heatmap representation of feature expression,

limiting to the top miRs differentially expressed (log Fold Change > 1.5) in γδ thymocytes cultured with IL-7 versus IL-2.

Differentially expressed features were identified with discovery rate = 0.001. The heatmap was generated with the Genesis

software package. Two independent biological samples are shown for each condition (n=2).

4.2 RT-PCR Validation of the miR Candidates

4.2.1 RT-PCR in γδ Thymocytes Validates Top Five miR Candidates

As a first step for the selection of the most promising candidates, the most abundant and more

differentially expressed miRs – highlighted in red in figure 9 – were identified. The

expression of these miR candidates (thirteen in total) was measured by RT-PCR in other

samples of γδ thymocytes, cultured with IL-7 vs IL-2. The analysis of those results allowed

for the validation of part of the miR repertoire previously characterized by RNA-seq. This

initial phase has enabled to set the top five priority miRs that were to be used as a foundation

to drive this investigation (figure 10).

#1 #2 #1 #2

Page 44: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 44

Figure 10 - RT-PCR in γδ thymocytes validates top five miR candidates. Downregulated (A) versus upregulated (B)

miRs in differentiated γδ thymocytes, as identified by RNA-seq. miR expression was normalized to the average obtained

from freshly isolated γδ thymocyte samples. 5-8 independent thymi are depicted. The average results are represented by the

bold dash. γδ thymocytes cultured for 10-14 days with the indicated cytokines. Data obtained from 3 independent RT-PCR

experiments. *p < 0.05, **p < 0.005, ***p < 0.001.

4.2.2 MiR Candidates Expression Profile in Peripheral γδ T Cells is more Similar to

Freshly-isolated than to IL-2 Cultured γδ Thymocytes

Previous results from the lab have shown that γδ thymocytes are immature ex vivo but can

acquire a type 1 differentiation profile when cultured with IL-2 (Ribot et al., 2014). On the

other hand, given each individual history of infections, circulating γδ T cells are mostly

functionally mature cells, producing IFN-γ and TNF-α ex vivo (DeBarros et al., 2011).

Thus, to confirm that the selected miRs are involved in IL-2-induced differentiation of γδ T

cells, we assessed the expression of our miR candidates in γδ T cells freshly isolated from the

periphery. We were expecting to mimic the results obtained with IL-2 differentiated γδ

thymocytes. This was partially true with regard to the expression of miR-181a and 196b.

However, we observed that the expression of miR-135b, 10a and 20b displayed by peripheral

A

B

1,00E-06

1,00E-05

1,00E-04

1,00E-03

1,00E-02

1,00E-01

1,00E+00

Thy IL-7 Thy IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-181a

* 1,00E-05

1,00E-04

1,00E-03

1,00E-02

1,00E-01

1,00E+00

Thy IL-7 Thy IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-196b

*

0

10

20

30

40

50

Thy IL-7 Thy IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-135b

***

0

5

10

15

20

25

30

Thy IL-7 Thy IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-10a

*

0

0,5

1

1,5

2

2,5

3

Thy IL-7 Thy IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-20b

**

Page 45: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 45

γδ T cells was more similar to what we had observed in freshly isolated (immature) γδ

thymocytes than to the observed in IL-2 cultured γδ thymocytes (figure 11).

Figure 11 - MiR candidates expression profile in peripheral γδ T cells is more similar to freshly-isolated than to IL-2

cultured γδ thymocytes. Downregulated (A) versus upregulated (B) miRs in differentiated γδ thymocytes, as identified by

RNA-seq. miR expression was normalized to the average obtained from freshly isolated γδ thymocyte samples. 5-8

independent thymi (T) and 6-12 independent buffy-coats (B). The average results are represented by the bold dash. γδ

thymocytes either freshly isolated or cultured for 10-14 days with IL-2; γδ T cells from buffy-coats freshly isolated. Data

obtained from 3 independent RT-PCR experiments. *p < 0.05, ***p < 0.001.

Given these results, we hypothesized that these candidates expression pattern could be a

transient process capable of restoring the basal levels once the terminally differentiated cells

return to a resting state. Thus, in order to break this resting status, we next analyzed the

expression of the miR candidates in peripheral γδ T cells isolated from buffy-coats, either

fresh or when using similar culture conditions (figure 12).

In agreement with this, the results show that when peripheral γδ T cells are stimulated with

IL-7, and even more with IL-2, miR-135b, 10a and 20b expression is upregulated, indicating a

probable role of those miRs in both the proliferation and differentiation processes.

A

B

1,00E-06

1,00E-05

1,00E-04

1,00E-03

1,00E-02

1,00E-01

1,00E+00

Fresh (T) IL-2 (T) Fresh (B)

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-181a

***

***

1,00E-05

1,00E-04

1,00E-03

1,00E-02

1,00E-01

1,00E+00

Fresh (T) IL-2 (T) Fresh (B)

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-196b

***

***

0

10

20

30

40

50

Fresh (T) IL-2 (T) Fresh (B)

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-135b

***

*

0

5

10

15

20

25

30

Fresh (T) IL-2 (T) Fresh (B)

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-10a

***

0

0,5

1

1,5

2

2,5

3

Fresh (T) IL-2 (T) Fresh (B)

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-20b

***

***

Page 46: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 46

Figure 12 – MiR-135b, 10a and 20b expression is upregulated in IL-7 or IL-2 cultured peripheral γδ T cells indicating

a rupture in their resting status. Downregulated (A) versus upregulated (B) miRs in differentiated γδ thymocytes, as

identified by RNA-seq. miR expression was normalized to the average obtained from freshly isolated γδ T cell samples. 6-12

independent buffy-coats are depicted. The average results are represented by the bold dash. γδ T cells from buffy-coats were

either freshly isolated or cultured for 6-8 days with the indicated cytokines. Data obtained from 3 independent RT-PCR

experiments. *p < 0.05, **p < 0.005, ***p < 0.001.

4.2.3 Comparison of miR Candidates Expression on Vδ1 vs Vδ2 Subpopulations

Shows No Significant Differences in their Expression Levels

Human γδ T cells comprise two major subsets: Vδ1+ cells (5–30% of γδ PBLs, but more

abundant in tissues) and Vδ2+ cells (60–95% of γδ PBLs), both strongly biased toward

cytotoxic type 1 functions (Behr et al., 2009; Gomes et al., 2010; Ribot et al., 2014).

Interestingly, previous results from the lab have reported that those two subpopulations

followed similar rules of differentiation (Ribot et al., 2014).

We thus wondered whether the miRs profile associated with functional differentiation was

also shared between those two subsets. For this, we sorted Vδ1 and Vδ2 cells from healthy

donors PBMCs and compared their expression for the selected miR candidates.

A

B

0,01

0,1

1

BC Fresh BC IL-7 BC IL-2fo

ld-c

han

ge in

miR

exp

ress

ion

miR-181a

***

***

0,01

0,1

1

BC Fresh BC IL-7 BC IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-196b

***

**

0

1

2

3

4

5

BC Fresh BC IL-7 BC IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-135b

** **

0

1

2

3

4

5

6

7

8

BC Fresh BC IL-7 BC IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-10a

***

**

0

10

20

30

40

50

BC Fresh BC IL-7 BC IL-2

fold

-ch

ange

in m

iR e

xpre

ssio

n

miR-20b

*** ***

Page 47: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 47

We observed no significant differences in the miRs expression between the two isotypes

(figure 13), in agreement with the similar miRs expression profile observed in peripheral and

thymic γδ T cells (figures 10 and 12).

Figure 13 - Comparison of miR candidates expression on Vδ1 vs Vδ2 subpopulations shows no significant differences

in their expression levels. Downregulated (A) versus upregulated (B) miRs in differentiated γδ thymocytes, as identified by

RNA-seq. 6 independent buffy-coats are depicted. The average results are represented by the bold dash. Data obtained from 3

independent RT-PCR experiments.

4.3 Setup of the Conditions for an Efficient miR Transfection using the Neon

System

To further validate the potential role of the selected miR candidates in human γδ T cell

differentiation, we conducted a set of experiments to test their impact on γδ T cell functions.

To do so, we adopted a gain-of-function strategy, by delivering designed mimics to cultured

γδ T cells using the Neon transfection system.

We first needed to optimize the electroporation settings by using a siRNA – as previously

shown on CD4+ cells (Simpson et al., 2014) – which in our case was the siRNACD45, seen

that CD45 is usually expressed in activated γδ T cells (Braakman et al., 1991). Several

A

B

0,1

1

10

100

Vδ1 Vδ2

Ab

solu

te V

alu

es

miR-181a

1

10

100

1000

Vδ1 Vδ2

Ab

solu

te V

alu

es

miR-196b

0,01

0,1

1

Vδ1 Vδ2

Ab

solu

te V

alu

es

miR-135b

0,01

0,1

1

Vδ1 Vδ2

Ab

solu

te V

alu

es

miR-10a

0,01

0,1

1

Vδ1 Vδ2 A

bso

lute

Val

ue

s miR-20b

Page 48: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 48

parameters were tested in this experiment, namely: cytokine stimulation (IL-7 vs IL-2);

activation status (anti-CD3/CD28 platebound cultures); cell number per transfection;

electroporation voltage and; analysis timepoints. Based on the manufacturer’s manual

(Invitrogen, 2010), a mimic concentration of 200nM has been chosen for electroporation of

the γδ T cells with the top five miR candidates mimics.

As readout of the electroporation efficiency, we measured the CD45 mean-fluorescence

intensity (MFI) (figure 14). We also checked that the chosen electroporation conditions were

not compromising γδ T cell survival by measuring the percentage of live cells with a

LiveDead staining (figure 15).

Figure 14 – Transfection of the siRNACD45 using the Neon system proves to be efficient on silencing CD45 in γδ T

cells. Neon setup readout for anti-CD45 staining on 25.000 γδ thymocytes, electroporated with 1600V: A) γδ from thymus;

B) γδ from PMBC. The following parameters were tested: cytokine stimulation with either IL-7 or IL-2; anti-CD3/CD28

platebound cell activation (Act) or without activation (NA) and electroporation voltage with either 1500V (data not shown)

or 1600V. Time until readout: 120hours for thymus and 48hours for the PBMCs samples after the last electroporation. The

siRNACD45 concentration used was 500nM.

A

B

IL-7 IL-2

% o

f M

ax

CD45

Not Activated

0

3000

6000

9000

12000

15000

MFI

CD

45

(Th

ymu

s)

IL-7 IL-2 IL-7 IL-2

NA ACT

IL-7 IL-2

Activated

% o

f M

ax

CD45 0

3000

6000

9000

12000

MFI

CD

45

(P

BM

C)

IL-7 IL-2 IL-7 IL-2

NA ACT

siRNACD45

Control

Page 49: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 49

Figure 15 – Transfection of the siRNACD45 using the Neon system does not compromise γδ T cell survival. Neon setup

readout for LiveDead staining on 25.000 γδ thymocytes, electroporated with 1600V: A) γδ from thymus; B) γδ from PMBC.

The following parameters were tested: cytokine stimulation with either IL-7 or IL-2; anti-CD3/CD28 platebound cell

activation (Act) or without activation (NA) and electroporation voltage with either 1500V (data not shown) or 1600V. Time

until readout: 96h after the last electroporation. The siRNACD45 concentration used was 500nM.

Based on these results, we described the following conditions for electroporation of γδ T cells

using the Neon system: 25.000 γδ T cells per transfection at 1600V with three pulses of 10ms

each.

Interestingly, although the silencing on γδ thymocytes worked without of TCR stimulation,

for the peripheral γδ T cells anti-CD3/CD28 platebound activation appeared to be crucial for

the transfection efficiency. The time between the last electroporation and the functional

readout by FACS was also determined to be different: 48 hours for γδ T cells from PBMCs

versus 120hours for γδ thymocytes. Additionally, cell fitness was improved in the presence of

IL-7 but not with IL-2, so after the setup the cell-culture medium used had IL-7 only, or IL-

7+IL-2.

Based on these set-up experiments, a protocol timeline was established (figure 16). Since ex

vivo isolated γδ thymocytes are immature, we needed an extended timeline when compared to

the already differentiated peripheral γδ T cells. Thus, the protocol for the transfection in γδ

thymocytes comprises four electroporations with the Neon system, while peripheral γδ T cells

will undergo only two electroporation steps.

A B

0

10

20

30

40

50

60

70

80

90

100

% L

ive

Ce

lls (

Thym

us)

IL-7 IL-2 IL-7 IL-2

NA ACT

0

10

20

30

40

50

60

70

80

90

100

% L

ive

Ce

lls (

PB

MC

)

IL-7 IL-2 IL-7 IL-2

NA ACT

siRNACD45

Control

Page 50: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 50

Figure 16 – Neon protocol timeline for mimics delivery. Schematic representation of the timeline stablished for the Neon

experiment using mimics in γδ T cells isolated either from thymus or from PBMC. Three parameters were established as

readouts by using antibodies to perform cell staining: A) Cell proliferation (Ki67); B) Functional differentiation (IFN-γ vs

TNF-α); C) Phenotypical features (CD27 vs CD45RA); and D) Vδ1 and Vδ2 subpopulations.

4.4 Analysis of the Impact of Mimics Delivery on γδ T Cell Differentiation and

Proliferation

To verify the efficiency of the mimics delivery using the Neon system, we measured by RT-

PCR the expression of corresponding miR in electroporated peripheral γδ T cells. As

expected, we observed an upregulation of miR-181a, 196b, 135b and 10a expression when

cells have been electroporated with the corresponding mimics (figure 17). Data for the miR-

20b mimic is not available (N/A) because there were not enough cells to perform the

transfection for all the miR candidates.

Figure 17 – Mimics delivery to PBMC-isolated γδ T cells using the Neon system occurred efficiently. RT-PCR

experiment performed on γδ T cells which have been electroporated with the Neon system for miR mimics delivery, using

the previously stablished protocol timeline. Control value was calculated by normalizing the expression of unrelated miRs to

the expression of miR C. elegans. miR-20b data not available (N/A). The samples were frozen 48hours after the last

electroporation. Cells were cultured with IL-7+IL-2 at a 1/1000 ratio.

N/A

Page 51: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 51

4.4.1 Peripheral Vδ2 γδ T Cells Transfected with miR-135b, 10a and 20b Mimics tend

to Proliferate Less when Cultured with IL-7 plus IL-2

Based on the timeline previously established (figure 16), cell proliferation in response to IL-7

plus IL-2 stimulation has been assessed by staining electroporated peripheral Vδ1+ versus

Vδ2+ γδ T cells with anti-Ki67 (figure 18).

Although the Vδ1 subpopulation did not show any clear differences, it appears that the Vδ2

subpopulation tends to proliferate less upon electroporation of γδ T cells with the miRs-135b,

10a and 20b mimics. However, such results would benefit of having more samples to support

this apparent pattern.

Figure 18 – Peripheral Vδ2 γδ T cells transfected with miR-135b, 10a and 20b mimics tend to proliferate less when

cultured with IL-7 plus IL-2. Proliferation results for the transfection with the top five candidate miR mimics on PBMC-

isolated γδ T cells using the Neon system. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by

FACS analysis. Five independent buffy-coats are depicted (n=5) using dots with different colors for each sample. The

average results are represented by the bold dash. Cells were cultured with IL-7+IL-2 at a 1/1000 ratio.

A

B

0

10

20

30

40

50

60

70

80

90

100

% K

i67

+ C

ells

/ V

δ1

Ki67

Control miR-135b

0

10

20

30

40

50

60

70

80

90

100

% K

i67

+ C

ells

/ V

δ2

Control miR-135b

Ki67

Page 52: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 52

4.4.2 Peripheral γδ T Cells Transfected with the miR Mimics show No Significant

Differences in IFN-γ and TNF-α Production

We next analyzed the differentiation status of peripheral γδ T cells upon mimics transfection.

Electronically gated Vδ1 and Vδ2 subsets have been analyzed by FACS for their IFN-γ and

TNF-α expression. The absence of differences among the tested conditions impaired us to

draw any particular conclusions at this point (figure 19).

Figure 19 – Peripheral γδ T cells transfected with the miR mimics show no significant differences in IFN-γ and TNF-α

production. IFN-γ and TNF-α expression results for the transfection with the top five candidate miR mimics on PBMC-

isolated γδ T cells using the Neon system. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by

FACS analysis. Five independent buffy-coats are depicted (n=5) using dots with different colors for each sample. The

average results are represented by the bold dash. Cells were cultured with IL-7+IL-2 at a 1/1000 ratio.

A

B

0

5

10

15

20

25

30

35

% IF

N-γ

+ T

NF-α

+ C

ells

/ V

δ1

TNF-α

IFN

Control miR-135b

0

5

10

15

20

25

30

35

40

45

% IF

N-γ

+ T

NF-α

+ C

ells

/ V

δ2

TNF-α

IFN

Control miR-135b

Page 53: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 53

4.4.3 MiR-181a and miR-196b Overexpression Decreases TNF-α Production in Vδ1

Electroporated γδ Thymocytes

Since γδ T cells at earlier stages of development have more plasticity than their mature

counterparts (Bonneville et al., 2010; Caccamo et al., 2013), we anticipated that thymic γδ T

cells would be more prone to be manipulated. Thus, we have isolated γδ thymocytes from

thymic samples extracted during pediatric corrective cardiac surgery and we have

electroporated those γδ thymocytes with the mimics of interest, based on the timeline

previously established (figure 16).

Interestingly, γδ thymocytes electroporation with miR-181a and 196b mimics seems to reduce

TNF-α production in the Vδ1 subset from 50,2% to 39,8% and 33,9%, respectively, a

decrease that is not verified for the other tested mimics. A similar behavior is observed for

miR-196b in the Vδ2 subpopulation, with the TNF-α production decreasing from 67,5% to

58,1%. Interestingly, this reduction in TNF-α production is accompanied by a discrete

increase in cell proliferation on both the Vδ1 and the Vδ2 samples from this miR, as attested

by the Ki67 staining. Such increase, although smaller, was also registered in the other mimics

transfected samples (figure 20). However, more samples would allow us to verify such a

pattern in γδ thymocytes proliferation, upon overexpression of these miR candidates.

Figure 20 – MiR-181a and miR-196b overexpression decreases TNF-α production in Vδ1 electroporated γδ

thymocytes. TNF-α and Ki67 expression for the transfection with the top five candidate miR mimics, plus the control, using

the Neon system on thymus-isolated γδ T cells. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically

gated by FACS analysis. One sample is depicted. Mimics concentration: 50nM. Cells were cultured with IL-7+IL-2 at a

1/1000 ratio.

Control miR-181a miR-196b miR-135b miR-10a miR-20b

TN

F-α

Ki67

A

B

Control miR-181a miR-196b miR-135b miR-10a miR-20b

TN

F-α

Ki67

Page 54: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 54

4.5 Overexpression of Candidate miRs using Retroviral Constructs

4.5.1 MiR Overexpression was Not Efficient for All of the miR Constructs

In the past decade several tools have been developed to deliver genes into human cells.

Among them, genetically engineered retroviruses are currently the most popular tool for gene

delivery (Hu and Pathak, 2000; Liu and Berkhout, 2011). Thus, we also decided to use this

methodology as an alternative to our gain-of-function experiments.

The retroviral vectors encoding the precursor stem-loops for our top five miR candidates were

produced in the mammalian adherent cell line, HEK293T TAT and tested in the 3T3 cell line,

in order to verify the transduction efficiency. This was assessed through the measurement of

the GFP reporter in each sample (figure 21). Furthermore with this transduction test we

evaluated the produced viral titers.

FACS analysis shows that the transduction was efficiently achieved for the empty, the miR-

181a and the miR-20b vectors. However, we failed to detect any GFP expression in cells

transduced with the remaining miR vectors, thus restricting the list of miR candidates

available to be used in γδ T cells.

Figure 21 –MiR overexpression was not efficient for all of the miR constructs: 3T3 cells. Viral particle production in the

3T3 cell lineage using the top five miR candidates constructs, plus the empty vector, was assessed by measuring the GFP

expression levels: cells efficiently transduced verify higher percentage levels of GFP – empty, miR-181a and miR-20b –

while untransduced cells have lower or no GFP production at all, similar to the control cells profile (represented in grey).

Cells obtained from the 1st harvest, using a 5uL titer.

GFP

% o

f M

FI

Empty miR-181a miR-196b

84,9 61,7 0,9

miR-135b miR-10a miR-20b

0,53 0,75 14,1

Page 55: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 55

We then infected primary peripheral γδ T cells with the viral particles produced by the

HEK293T TAT cell line. We observed that the transduction was efficient for the empty and

the miR-181a vector, while the miR-20b infected cells expressed a non-significant amount of

GFP (figure 22). Based on these results, we decided to focus our analysis on the impact of

miR-181a overexpression.

Figure 22 – MiR overexpression was not efficient for all of the miR constructs: γδ T cells. Viral particle production in

the PBMCs-isolated γδ T cells using either the empty, the miR-181a or the miR-20b vector was assessed by measuring the

GFP expression levels: cells efficiently transduced verify higher levels of GFP – empty and miR-181a – while untransduced

cells – namely miR-20b – have lower or no GFP production at all, similar to the control cells profile (represented in grey).

Cells were cultured with IL-7 or IL-7+IL-2 at a 1/1000 ratio.

4.5.2 MiR-181a Overexpression in Peripheral γδ T Cells Increases Cell Proliferation

Several parameters have been assessed on peripheral γδ T cells following miR-181a retroviral

transduction, and compared to the results obtained from the samples transduced with the

empty vector.

We first analyzed cell proliferation of retrovirally transduced γδ T cells based on their Ki67

expression (figure 23).

The results show that both the Vδ1 and the Vδ2 subsets proliferate more when transduced

with the miR-181a vector. However, GFP+ (i.e. transduced) Vδ1

+ T cells displayed a higher

cell proliferation (15%-20% increase). Of note, GFP-

(i.e. untransduced) cells registered no

significant changes when comparing the empty vector with the miR-181a cell samples, and

could be used as an internal negative control, as expected.

GFP

% o

f M

FI

Empty miR-181a miR-20b

70,3 38,3 3,31

Page 56: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 56

Figure 23 – MiR-181a overexpression in peripheral γδ T cells increases cell proliferation. Proliferation has been

assessed by measuring Ki67 expression in GFP+ cells after transducing peripheral γδ T cells with either the empty vector or

with the miR-181a vector. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by FACS analysis.

Three independent buffy-coats are depicted (n=3) using dots with different colors for each sample. The average results are

represented by the bold dash. The left panels represent the IL-7 cultured γδ T cells. Cells were cultured with IL-7 or IL-7+IL-

2 at a 1/1000 ratio. *p < 0.05.

4.5.3 MiR-181a Overexpression in Peripheral γδ T Cells Increases Vδ1 T Cell

Activation and Programmed Cell Death

We next analyzed the activation status of γδ T cells upon miR-181a overexpression, thus we

performed a CD69 staining on peripheral γδ T cells transduced with the miR181a vs empty

vector (figure 24). CD69, also known as early activation antigen (EA-1), is a phosphorylated

cell surface protein transiently expressed early following T-cell activation by

phytohemagglutinin and activators of protein kinase C (Rutella et al., 2009).

Gate

d G

FP

+V

δ1

+ T

cel

ls

Ki67

Empty miR-181a

18,2 41,6

A

B

0

10

20

30

40

50

% K

i67

+ C

ells

0

10

20

30

40

50

60

% K

i67

+ C

ells

*

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Gate

d G

FP

+V

δ2

+ T

cel

ls

Ki67

5,78 10,4

Empty miR-181a

0

2

4

6

8

10

12

14

% K

i67

+ C

ells

0

5

10

15

20

25

30

% K

i67

+ C

ells

GFP+ GFP- GFP+ GFP-

IL-7 IL-7+IL-2

Page 57: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 57

We showed that γδ T cell activation is increased in samples overexpressing miR-181a, when

compared with the control samples, especially when gated on the Vδ1 subpopulation. Of note,

such alteration in cell activation between miR-181a and the control sample (i.e. empty vector)

seems to be higher when cells are cultured with IL-7, than when they are cultured with IL-

7+IL-2.

Figure 24 – MiR-181a overexpression in peripheral γδ T cells increases Vδ1 T cell activation. Activation has been

assessed by measuring CD69 expression in GFP+ cells after transducing peripheral γδ T cells with either the empty vector or

with the miR-181a vector. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by FACS analysis.

Three independent buffy-coats are depicted (n=3) using dots with different colors for each sample. The average results are

represented by the bold dash. The left panels represent the IL-7 cultured γδ T cells. Cells were cultured with IL-7 or IL-7+IL-

2 at a 1/1000 ratio. *p < 0.05.

A parameter intrinsically linked with cell activation is the programmed cell death, also known

as apoptosis. Thus, we stained peripheral γδ T cells with the apoptotic marker Annexin V to

analyze potential changes in the electronically gated Vδ1 and Vδ2 subpopulations. Although

not significant, our results show a higher percentage of Annexin V+ cells in the γδ T cells

overexpressing miR-181a than in the control cells. Importantly, this was true in all individual

transduced samples (figure 25).

A

B

Gate

d G

FP

+V

δ1

+ T

cel

ls

CD69

Empty miR-181a

20,9 35,7

0

10

20

30

40

% C

D6

9+

Ce

lls

*

0

10

20

30

40

50

60

% C

D6

9+

Ce

lls

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Gate

d G

FP

+V

δ2

+ T

cel

ls

54,1 65,4

Empty miR-181a

CD69

0102030405060708090

100

% C

D6

9+

Ce

lls

0102030405060708090

100

% C

D6

9+

Ce

lls

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Page 58: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 58

Figure 25 – MiR-181a overexpression in peripheral γδ T cells increases Vδ1 T cell programmed cell death. Apoptosis

has been assessed by measuring Annexin V expression in GFP+ cells after transducing peripheral γδ T cells with either the

empty vector or with the miR-181a vector. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by

FACS analysis. Three independent buffy-coats are depicted (n=3) using dots with different colors for each sample. The

average results are represented by the bold dash. The left panels represent the IL-7 cultured γδ T cells. Cells were cultured

with IL-7 or IL-7+IL-2 at a 1/1000 ratio.

4.5.4 Overexpression of miR-181a in Peripheral γδ T Cells did not Influence their

Effector/Memory Phenotype

It is commonly accepted that the expression of CD27 and CD45RA can help the

discrimination between effector/memory T cell subsets (Dieli et al., 2003). Thus, based on

these surface markers, we assessed whether miR-181a (over)expression could impact on

peripheral γδ T cells effector/memory phenotype (figure 26).

A

B

Gate

d G

FP

+V

δ1

+ T

cel

ls

Annexin V

20,9 35,7

Empty miR-181a

05

101520253035404550

% A

nn

exi

n V

+ C

ells

0

5

10

15

20

25

30

35

% A

nn

exi

n V

+ C

ells

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

0

10

20

30

40

50

60

70

80

% A

nn

exi

n V

+ C

ells

0

10

20

30

40

50

60

% A

nn

exi

n V

+ C

ells

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

56,4 71,4

Empty miR-181a

Annexin V

Gate

d G

FP

+V

δ2

+ T

cel

ls

Page 59: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 59

Figure 26 – Overexpression of miR-181a in peripheral γδ T cells did not influence their effector/memory phenotype.

Phenotypic features have been assessed through a CD27 vs CD45RA staining on GFP+ cells after transducing peripheral γδ T

cells with either the empty vector or with the miR-181a vector. Only the central memory (CM) population is represented in

the graphics. A) Vδ1 subpopulation; B) Vδ2 subpopulation. Populations electronically gated by FACS analysis. Three

independent buffy-coats are depicted (n=3) using dots with different colors for each sample. The average results are

represented by the bold dash. The left panels represent the IL-7 cultured γδ T cells. EM= Effector Memory. Cells were

cultured with IL-7 or IL-7+IL-2 at a 1/1000 ratio.

A detailed analysis of the results for each one of the four phenotypic populations (data not

shown) did not allow us to highlight any significant changes between the transduced miR-

181a and the control samples, as illustrated above when focusing on the CD27+CD45

- (CM)

population (figure 26). This led us to the conclusion that miR-181a overexpression did not

cause particular alterations in peripheral γδ T cell phenotype based on those effector/memory

markers.

A

B

CM

M

Naïve

EM

M

Effector

M

Gate

d G

FP

+V

δ2

+ T

cel

ls

Empty miR-181a

CD45RA

CD

27

0

10

20

30

40

50

60

70

80

90

% C

M C

ells

0

10

20

30

40

50

60

70

80%

CM

Ce

lls

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Gate

d G

FP

+V

δ1

+ T

cel

ls

CD45RA

CD

27

Empty miR-181a

0

2

4

6

8

10

12

14

% C

M C

ells

02468

101214161820

% C

M C

ells

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Page 60: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 60

4.5.5 Overexpression of miR-181a in Peripheral γδ T Cells Reduces IFN-γ and TNF-α

Production in the Vδ1 Subpopulation

We have finally analyzed the differentiation status of the Vδ1 and the Vδ2 subpopulations

upon miR-181a overexpression, by evaluating their IFN-γ and TNF-α expression.

Interestingly, we observed that overexpressing miR-181a on peripheral γδ T cells caused

alterations in both the IFN-γ and the TNF-α expression (figure 27). This was particularly

significant in the Vδ1+ subset and in the absence of IL-2.

Importantly, this is not the first time that miR-181a overexpression has been correlated with a

reduction in IFN-γ and TNF-α production, as it has been observed recently in human CD4+ T

lymphocytes or in the HEK293K cell line, respectively (Gao et al., 2016; Sang et al., 2015).

Figure 27 – Overexpression of miR-181a in peripheral γδ T cells reduces IFN-γ and TNF-α production in the Vδ1

subpopulation. Differentiation status was assessed by analyzing IFN-γ and TNF-α expression in GFP+ cells after transducing

peripheral γδ T cells with either the empty vector or with the miR-181a vector. A) Vδ1 subpopulation; B) Vδ2 subpopulation.

Populations electronically gated by FACS analysis. Three independent buffy-coats are depicted (n=3) using dots with

different colors for each sample. The average results are represented by the bold dash. The left panels represent the IL-7

cultured γδ T cells. Cells were cultured with IL-7 or IL-7+IL-2 at a 1/1000 ratio. *p < 0.05.

A

B

Gate

d G

FP

+V

δ1

+ T

cel

ls

TNF-α

IFN

Empty miR-181a

0

10

20

30

40

50

60

70

% IF

N-γ

+ TN

F-α

+ C

ells

*

0

10

20

30

40

50

60

% IF

N-γ

+ T

NF-α

+ C

ells

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Gate

d G

FP

+V

δ2

+ T

cel

ls

Empty miR-181a

TNF-α

IFN

0

20

40

60

80

100

120

% IF

N-γ

+ TN

F-α

+ C

ells

0

20

40

60

80

100

120

% IF

N-γ

+ TN

F-α

+ C

ells

IL-7 IL-7+IL-2

GFP+ GFP- GFP+ GFP-

Page 61: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 61

We finally sum up our data related to miR-181a transduction of peripheral γδ T cells (figure

28). We have gathered the different parameters assessed in the Vδ1 and Vδ2 subpopulations

and normalized those results with the data obtained for the control.

Importantly, although both the Vδ1 and the Vδ2 subpopulations have registered changes in

the γδ T cell features, it is worth noticing that the main changes following miR-181a

overexpression were verified in the Vδ1 subset, rather than in the Vδ2 subset.

Figure 28 – Summary of the results obtained upon overexpression of miR-181a in peripheral γδ T cells. A) Vδ1

subpopulation; B) Vδ2 subpopulation. Populations electronically gated by FACS analysis. Data obtained from the average

results of three independent buffy-coats and normalized to the average results obtained for the control samples (i.e. empty

vector data). The empty vector is represented by the grey bar; miR-181a vector represented by the black bar. Cells were

cultured with IL-7 or IL-7+IL-2 at a 1/1000 ratio. *p < 0.05.

Gate

d G

FP

+V

δ1

+ T

cel

ls

0

0,5

1

1,5

2

2,5

3

fold

-ch

ange

/ e

mp

ty (

1) *

* *

*

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

fold

-ch

ange

/ e

mp

ty (

1)

*

*

IL-7 IL-7+IL-2

A

B

Gate

d G

FP

+V

δ2

+ T

cel

ls

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

1,8

2

fold

-ch

ange

/ e

mp

ty (

2)

*

*

0

0,5

1

1,5

2

2,5

3

fold

-ch

ange

/ e

mp

ty (

2) *

IL-7 IL-7+IL-2

Page 62: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 62

Discussion

Page 63: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 63

5. Discussion

It has been shown that miR expression patterns vary among lymphocyte subsets and stages of

development, which may contribute to their identity or functional state (Jeker and Bluestone,

2013). By instance, miR expression profiles among each thymic T cell developmental stage

have been shown to be unique, with some miRs undergoing expression changes up to three

orders of magnitude during maturation (Kirigin et al., 2012). Accordingly, removal of all

mature miRs at early stages of thymocyte development via Dicer or Drosha knockouts has

resulted in developmental blockage and consequent reduction of the peripheral mature αβ T

and iNKT cell pool (Cobb et al., 2005; Podshivalova and Salomon, 2013; Seo et al., 2010;

Zhou et al., 2011).

Recently, several reports have demonstrated that various miRs, namely miR-181/583 and

miR-146a/150, are respectively expressed in human NK and CD8 T cell subsets and regulate

several aspects of their development and function (Cichocki et al., 2011; Ghisi et al., 2011;

Sheppard et al., 2014; Yun et al., 2014). Furthermore, miR-146a has been linked to the

control of the Th1-type differentiation in human CD4+ T cells by targeting the protein PRKCε

(Möhnle et al., 2015), whereas miR-20a overexpression has been proved to inhibit their TCR-

mediated signaling (Reddycherla et al., 2015).

Owing to their potent effector functions, γδ T cells have been proposed as the first line of

immune defense that responds to a variety of stress-inducible or pathogen-associated proteins

or metabolites (Hayday, 2009). Upon activation, these cells become capable of producing

inflammatory cytokines and directly lyse infected or malignant cells (Deniger et al., 2014;

Wesch et al., 2014). Namely, γδ T cells actively contribute to the anti-tumor immune response

in many tumors, including lymphoma, myeloma, melanoma, breast, colon, lung, ovary, and

prostate cancer (Bouet-Toussaint et al., 2008; Cordova et al., 2012; Dieli et al., 2007; Kang et

al., 2009; Lafont et al., 2014; Meraviglia et al., 2010). However, to date, no miRs have yet

been shown to be implicated in the differentiation of these cells into anti-tumor effectors.

With this idea in mind, we set ourselves to assess the functional roles of individual miR

possibly involved in the regulation of γδ T cell functions. To do so, we identified putative

candidates by RNA-seq, a powerful sequence-based methodology that allows for an in-depth

analysis of transcriptional signatures that define cell functions in physiologic or disease states

(Porichis et al., 2015; Szeto et al., 2014). A group of five candidate miRs were then validated

by RT-PCR. A 50-100 fold downregulation of the expression of miR-181a and 196b and a 2-

40 fold upregulation of the expression of miR-135b, 10a and 20b was confirmed to be

associated with type 1 γδ T cell functional differentiation (figure 10). Importantly, miR-181a

expression has been recently reported to be involved in human CD4+ T lymphocytes

functional regulation by directly targeting IFN-γ production (Sang et al., 2015), thus

supporting an analogous correlation for the reduced expression of miR-181a in our

differentiated γδ T cells.

Given each individual history of infections, circulating γδ T cells are mostly functionally

mature cells, producing IFN-γ and TNF-α, and displaying a dominant effector/memory

phenotype (Ribot et al., 2014). We were thus expecting to phenocopy the results obtained

with IL-2 differentiated γδ thymocytes on freshly isolated peripheral γδ T cells. Whereas this

Page 64: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 64

was partially true regarding the expression of miR-181a and 196b, we observed that the

expression of miR-135b, 10a and 20b displayed by peripheral γδ T cells was rather similar to

what we detected in freshly isolated (immature) γδ thymocytes (figure 11). Thus, we

postulated that these candidates expression pattern associated with functional differentiation is

a transient process that can restore basal levels once the terminally differentiated cells return

to a resting state.

To test this hypothesis, we next compared the expression of our miRs candidates by

peripheral γδ T cells before and after being stimulated with IL-7 and IL-2, in order to break

this resting status. Given the already established relationship between IL-7/IL-2 and γδ T cell

proliferation (Ribeiro et al., 2015), we could also envisage that the changes in miRs

expression displayed by cultured γδ T cells to be also related to this process. Indeed, miR-

135b, 10a and 20b have previously been reported to impact on the proliferation of lymphoma

cells, lung cancer cells and breast cancer cells, respectively (Matsuyama et al., 2011; Yu et

al., 2015; Zhou et al., 2014).

Knowing that the thymus and the blood are populated by different γδ T cell subsets (Vδ1+ and

Vδ2+, respectively) (Behr et al., 2009; Gomes et al., 2010), that follow the same rules of

functional differentiation upon IL-2 signaling (Ribot et al., 2014), we next wondered whether

our miR candidates expression profile would also follow the same miR expression pattern. As

anticipated, Vδ1 and Vδ2 PBMCs-sorted subpopulations displayed similar miR expression

levels (figure 13).

Having selected our top five miR candidates, we manipulated their expression in order to

potentially impact on γδ T cell effector functions. To this aim, we set two different strategies

for the gain-of-function experiments: 1) we overexpressed the miR candidates in γδ T cells by

mimics transfection using the Neon system and; 2) we transduced γδ T cells with retroviral

constructs overexpressing the selected miRs.

For the first gain-of-function methodology, we first optimized the parameters allowing for an

efficient mimics delivery into the γδ T cells. For this, we chose to work with siRNACD45, as

it is well-established that CD45 – a transmembrane tyrosine phosphatase found in all

leukocytes – is essential for the activation of T cells via the TCR (Altin and Sloan, 1997;

Janeway et al., 2001). Thus, we expected that an efficient transfection of this siRNA into our

γδ T cells would register a silencing effect on CD45, reasoned by a decrease on its MFI when

compared with the control samples. We also wanted to find a reasonable compromise between

the selected conditions and the γδ T cell survival rate that allowed us to electroporate these

lymphocytes without the risk of ending up without enough cells for the functional readout.

Such compromise was achieved by electroporating the γδ T cells with a voltage of 1600V,

during three 10ms pulses and using 25.000 cells per transfection.

Interestingly, whereas TCR activation seemed dispensable to achieve efficient silencing on γδ

thymocytes, it was crucial for peripheral γδ T cells, as previously reported in primary T cell

cultures (Jacobs et al., 2008; Rao et al., 2005; Tomkowicz et al., 2015). Once a naïve cell is

fully activated, the T cell activation threshold necessary to activate new gene transcription is

lowered in order to push the cell to proliferate and differentiate (Grossman et al., 2004; Mak

et al., 2014). Thus, we can expect that ex vivo isolated γδ thymocytes are constitutively TCR-

activated, whereas the peripheral mature γδ T cells are most probably in a resting state.

Page 65: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 65

Interestingly, cell fitness was improved in the presence of IL-7 but not when cells were

cultured with IL-2 only. Such result is consistent with the fact that IL-7 has been shown to be

involved in the survival of human γδ T cells (Michel et al., 2012).

The mimics concentration that has been previously described varies a lot depending on the

nature of the electroporated cells and the experimentalists: for instance primary CD4+ T cells

can be transfected with a concentration that ranges between 75uM and 500nM (Palin et al.,

2013; Simpson et al. 2014); whereas lymphoblastoid cells and the BJAB cell line only require

15nM and 50pM of mimics, respectively (Kalabus et al., 2012; Manzano et al., 2013). Based

on these reports we started performing our experiments in γδ T cells using two different

mimics concentration: 500nM and 50nM. However, if the former concentration seemed to be

too toxic for our cells, the latter concentration showed no significant differences in almost all

of the miR mimics samples (data no shown). Thus, based on this knowledge and also based

on the manufacturer’s manual recommendations, we chose to use a concentration of 200nM

of mimics to electroporate γδ T cells. To verify if the transfection process was occurring

efficiently we assessed by RT-PCR the expression of the top five miRs in electroporated

PBMC-isolated γδ T cells. As control, we normalized the expression of unrelated miRs to the

expression of the recommended miR-39-3p specific to C. elegans. As expected, we observed

a 2-15 fold increase of the miR-181a, 196b, 135b and 10a expression (figure 17). However,

due to a lack of cells, we were not able to assess the potential increase of miR-20b expression.

Of note, this assay has been performed only once and needs to be reproduced. Ideally, for

each electroporation experiment, one should perform also an RT-PCR validation, in order to

draw definitive conclusions about the efficiency of the transfection process. Such analysis

was unfortunately not possible, since the amount of isolated γδ T cells did not provide us with

enough material. Nevertheless, our preliminary data indicates that this electroporation method

is efficient and confirms previous literature reporting up to five-fold increase expression of

the targeted miR (Cheng et al., 2015; Simpson et al., 2014).

Additionally, although the RT-PCR is a simple and commonly used method to measure the

level of a miR, it does not distinguish between miRs in functional or non-functional pools

(Thomson et al., 2013). Consequently, although we can measure the efficiency of the mimics

delivery with this transfection system by RT-PCR, we cannot know the amount of mimics

being loaded into the RISC complex. As an alternative, we could use the fluorescent in situ

hybridization (FISH), a methodology that uses fluorescent probes to detect specific nucleic

acid sequences at the single cell level. This technique can be multiplexed and combined with

fluorescent Ab protein staining (Porichis et al., 2015), which could be an advantage given that

we are using FACS to assess the γδ T cells functional properties. Thus combining miR

detection and functional read out would be less expensive and time consuming.

Taking advantage of the optimized protocol for mimics transfection, we first investigated the

impact of our selected miRs on γδ T cell proliferation. For this, we stained electroporated γδ T

cells for Ki67, a nuclear antigen present in all phases of the cell growth cycle but is absent in

resting cells (Bryant et al., 2006). Interestingly, we observed that the Vδ2+ subset

proliferation was specifically affected upon electroporation with miR-135b, 10a and 20b but

not with miR-181a and 196b. This experiment would deserve to be reproduced with more

samples since, so far, due to an important individual variation, it was not statistically

Page 66: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 66

significant. However, this result is supported by our previous RT-PCR data, reporting an

increase of miR-135b, 10a and 20b in proliferating peripheral γδ T cells (figure 12).

We next analyzed the type 1 differentiation status of peripheral γδ T cells upon mimics

transfection by assessing the expression of IFN-γ and TNF-α. However, no significant

differences were observed. This could be explained by the following hypothesis: 1) although

the transfection occurred efficiently – as supposed by the results obtained in RT-PCR

experiment using the Neon transfected cells – the increase in miRs expression is not sufficient

to detect potential changes in the functional readout or; 2) the mimics transfection was not

efficient in all the PBMCs-isolated γδ T cell samples, which would explain at least part of the

heterogeneity observed in the results. Also, as discussed above, peripheral γδ T cells are

probably less easy to manipulate because they are already differentiated ex vivo, contrary to

immature γδ thymocytes that allow for the control of their differentiation program.

Consistent with this idea, we could indeed partially impair γδ T cell differentiation into TNF-

α producers when overexpressing miR-181a and 196b in γδ thymocytes, especially in the Vδ1

subpopulation. At the same time, electroporation of the γδ thymocytes with the miR mimics

seemed to modulate their proliferation, a result which was true not only for miR-181a and

miR-196b, but also for the other three miR candidates.

Analogously, overexpression of miR-181a in Hela cells suppressed the protein level of TNF-

α, while using an antagonist had the reverse effect, indicating that miR-181a can target TNF-α

and regulate its endogenous expression in human cells (Li et al., 2013). Importantly, although

miR-196b expression has been shown to increase cell proliferation and survival, and also

partially block differentiation of normal bone marrow hematopoietic progenitor cells in mice

(Popovic et al., 2009), this is the first time that this miR is implied in regulating TNF-α

production in humans. However, these results need to be confirmed with more thymic

samples.

As a footnote for the use of mimics in this experiment, although transient transfection of

chemically synthesized miRs is being widely used to study the functional properties of

endogenous miRs, it is still unclear whether transfected miR mimics behave similarly to

endogenous miRs. Importantly, Jin and colleagues have shown that transient electroporation

with miR mimics into HeLa cells led to the accumulation of high molecular weight RNA

species and that the use of high miR mimics concentrations induced non-specific alterations

in gene expression. In contrast, expression of the same miRs through lentiviral infection or

plasmid transfection of HeLa cells did not registered such anomalies (Jin et al., 2015), thus

emerging as a more reliable tool.

Based on this knowledge, we have decided to resort to an alternative gain-of-function

strategy, by overexpressing the miRs of interest using retrovirus. Most of the retroviral

technology used is based on the molony murine leukemia virus, which has a simple genome

with the gag, pol, and env genes encoding for the major structural proteins and essential

enzymes, flanked by long terminal repeats (Hu and Pathak, 2000; Pagès and Bru, 2004). Once

inside the cell, the inserted RNA is copied by the enzyme reverse transcriptase into double-

stranded DNA, which then becomes integrated into the host chromosome, allowing for the

long-term expression of the inserted gene (Liu and Berkhout, 2011). Importantly, using the

Page 67: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 67

original stem-loop of our miR contributes to a more physiological result avoiding false

positive results introduced by supra-physiological increase in miR levels generally achieved

after transient transfection (Thomson et al., 2011). Thus, we designed retroviral constructs

based on the original stem-loop of our top five miRs and cloned them into the plasmid pMIG-

PGW. Using two other plasmids – pCMV-VSV-G and pCL-Eco – the viral particles were

produced in the mammalian adherent cell line, HEK293T TAT.

Although we had assembled viral constructs for all our top five miR candidates – plus the

empty vector – we failed to produce high viral titers for miR-135b, 10a and 196b. To discard

the possibility of an error while transducing the 3T3 samples, we have also analyzed the

plates for the HEK293T TAT transduced cells using fluorescence microscopy. This allowed

us to see that, although in all plates a green fluorescence was emitted, the density of viral

particles was much higher for the empty, miR-20b and miR-181a vectors than for the other

three samples, in which the green fluorescent particles were only seen sparsely (data not

shown). Similarly, although we had successfully produced viral particles for this miR in the

HEK293T TAT cell line, we failed to transduce miR-20b in peripheral γδ T cells, This result

could be due to the fact that primary cells are usually more difficult to transduce than the cell

lines, probably because the latter are usually actively dividing, a feature due to their

immortalization which is not present in primary cells, but that is crucial for the transduction

efficiency.

The production of the retroviral constructs is a crucial step for an effective transduction and

several factors, such as the construction of the vector backbone and the transgene to be

transferred, can influence the viral vector production (Liu and Berkhout, 2011; Wightman et

al., 1991). In general, a bigger vector size leads to a lower efficiency of the viral transduction

(Hu and Pathak, 2000). However, this does not seem to be the problem in our case since the

viral vector sizes used varied between 6,806 Kb and 7,540 Kb. Another limiting factor for the

transduction efficiency is that the expression of the transgene in question can be toxic for the

host cells or can significantly reduce vector production (Hu and Pathak, 2000), meaning that

miR expression can impair the viral vector production by itself or that, in some cases, the

expression of the GFP can be compromised. This could explain why we were not able to

produce viral vectors for miR-135b, 10a, 20b and 196b. Moreover, the HEK293T TAT cell

line produces extracellular matrix proteins enriched with proteoglycans, and these

macromolecules are known to act as inhibitors during cell transduction, which might

eventually have reduced significantly the transduction efficiency (Le Doux et al., 1996; Le

Doux et al., 1998). A solution for this problem could be to use a suspension cell line to

produce our virus, as for instance the Jurkat cell line (Eaton et al., 2002). Additionally, the

TAT protein present in our cell line is essential in transcription and replication of viral genes

and has been proved to upregulate and downregulate several genes not only implicated in the

infection process but also implicated in cell proliferation and fitness (Park et al., 2007; Lee

and Park, 2009). Thus, we may envisage that miR-135b, 10a or 196b could be involved in the

regulation of one or more of those genes and that such a regulatory role could have impaired

the production of the viral particles in the HEK293T TAT cell line.

As a footnote, a more reliable assay to draw definite conclusions about the efficiency of the

virus production for our miR constructs would be to analyze the transduced cells by RT-PCR

Page 68: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 68

regarding these miRs expression, to assess if each specific miR had indeed an enhanced

expression or not. Unfortunately, due to material limitations, such analysis has not possible

for this experiment.

Similarly to the gain-of-function experiments using the Neon system, we have next analyzed

γδ T cell main features upon miR-181a overexpression by retroviral transduction.

Interestingly, we observed an increase in proliferation within miR-181a transduced (i.e.

GFP+) Vδ1 and Vδ2 subsets, when compared to the respective control samples (i.e. cell

transduced with the empty vector). As an additional internal control, we also verify that the

proliferation of untransduced cells (i.e. GFP-) within the same sample remained unaffected.

However, GFP+ Vδ1 T cells was the subpopulation that showed a higher increment in cell

proliferation, by increasing its Ki67 expression in 15% and 20% on average, when cultured

with IL-7 or with IL-7+IL-2, respectively.

Accordingly, miR-181a has already been implied in regulating cell proliferation. By instance,

human myeloid leukemia cell proliferation has been enhanced upon overexpression of miR-

181a due to a suppression effect elicited by this miR in the cell cycle inhibitor p27 (Wang et

al., 2009). Additionally, ectopic expression of miR-181a in HEK293T cells was shown to

significantly enhance cell proliferation by activating AKT, thus conferring cell resistance to

doxorubicin, a chemotherapeutic agent (Yan et al., 2015).

Consistently, in a NOTCH-induced T-ALL model, antagomir inhibition of miR-181a

expression in the human T-ALL cell line DND41 decreased cell proliferation and increased

apoptosis, through the downregulation of Notch targets (Fragoso et al., 2012). Notch

signaling plays a pivotal role in cell fate decision and lineage commitment of lymphocytes

(Gogoi et al., 2014), with major contributions for γδ T cell development (Ciofani et al., 2006;

García-Peydró et al., 2003; Van de Walle et al., 2013). Importantly, Notch signaling has also

been shown to control T cell proliferation as well as Th1/Th2 differentiation in the periphery

(Tanikagi et al., 2004). Furthermore, inhibition of Notch signaling by a γ-secretase inhibitor

was proved to decrease not only γδ T cell proliferation, but also to reduce CD69 and CD25

(IL-2R) expression, as well as impairing the CD107a expression, which is a degranulation

marker associated with cell cytotoxic potential (Gogoi et al., 2014).

In agreement with this, we observed an increase of peripheral γδ T cell activation upon miR-

181a overexpression. However, such alteration was more striking in the Vδ1 subpopulation

than in the Vδ2 counterpart, which might be explained by the fact that the Vδ2+ cells were

already much more activated (between 79-92% of the cells on average) than the Vδ1+

cells

(between 32-39% of the cells on average), probably not leaving much room for an increase in

their activation. Importantly, transduced cells verified higher activation levels than the

untransduced cells, consistent with the fact that the activation step in retrovirus-mediated gene

transfer plays a crucial role in the transduction efficiency when using retroviral vectors

(Costello et al., 2000).

We also observed that miR-181a overexpression induced an increase in cell apoptosis, as

measured by Annexin V staining, in agreement with previous reports showing that activated

CD69+ T cells were proven to engage apoptosis (Jiao et al., 2008; Meier et al., 2002; Rutella

et al., 2009). These results also highlight the fact that the phenomenon of activation-induced

Page 69: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 69

cell death (AICD) in T lymphocytes is regulated at every stage of their existence, playing a

crucial role in maintaining the T cell homeostasis during periods of intense cell activation by

balancing the life vs apoptosis switch (Green et al., 2003).

Regarding their phenotype based on the CD27 and CD45RA markers, the vast majority of γδ

thymocytes have previously showed an immature and naïve profile, contrary to the dominant

effector/memory phenotype of γδ PBLs. Importantly, peripheral γδ T cells were mainly

CD27-CD45

+, illustrating their dominant CM phenotype (50%), followed by an EM

phenotype (30%), an effector phenotype (15%) and finally a naïve phenotype (5%) (Dieli et

al., 2003; Qin et al., 2012; Ribot et al., 2014) Accordingly, in our results, the Vδ2 subset –

which constitutes the main subpopulation of circulating γδ T cells – registered a predominant

CM phenotype (between 50-80% of the cells) in both IL-7 and IL-7+IL-2 cultured γδ T cells.

However, it was interesting to observe that we have consistently registered a higher

percentage of naïve T cells in the Vδ1 subset – on average 40-80% were naïve cells – which

contrasted with the reduced pool of naïve T cells observed in the Vδ2 subset (on average 10-

30%). Such results are in agreement with the literature (deBarros et al., 2011; Qin et al.,

2012; Ribot et al., 2009). Also, this higher naïve phenotype in Vδ1+ cells is in agreement with

the previous observations that the Vδ1 subpopulation seems to be more prone to be

manipulated than the Vδ2 counterpart (Correia et al., 2011; Silva-Santos et al., 2015).

Albeit this fact, no significant alterations have been detected between the samples transduced

with the miR-181a vector and the samples transduced with the empty vector. Thus, it seems

that this miR does not have a significant impact in modulating γδ T cell phenotypic features,

which could be due to a lack of plasticity in these already mature cells. Importantly, plasticity

has been demonstrated to play a crucial role in the γδ T cell differentiation program: at earlier

stages, during γδ thymocyte development, these cells initially maintain a flexible lineage

differentiation, while at later stages they may become irreversibly committed to one lineage

(Bonneville et al., 2010; Caccamo et al., 2013).

Accordingly, it has been shown that with age the human cell pool of naïve T cell shrinks and

that old naïve T cells exhibit proliferation and effector-differentiation defects (Allman and

Miller, 2005; Linton and Dorshkind, 2004; Wertheimer et al., 2014). This could explain the

difficulties in modulating the phenotype of these already fully differentiated cells.

Furthermore, a specific memory subset of CD8+ T cells, called “memory T cells with a naive

phenotype”, has recently been discovered and proved to emerge with ageing. These cells

seemed to work as substitutes of the naïve cells, as they were the cell subset responding to the

presence of new infections (Pulko et al., 2016). Thus, we could envisage that a similar

behavior might be adopted in our γδ T cells, which would explain the fact of having many

more effector and memory T cells, than naïve T cells.

Last but not least, we have assessed if peripheral γδ T cells suffered alterations in their

functional differentiation upon miR-181a retroviral transduction. We observed a significant

reduction of IFN-γ and TNF-α expression within the Vδ1 subset differentiation when cells

were cultured with IL-7 or with IL-7+IL-2.

Consistently with our results, miR-181a overexpression has been previously correlated with a

reduction in IFN-γ production in human CD4+ T lymphocytes (Sang et al., 2015). Conversely,

Page 70: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 70

downregulation of the miR-181 family paralleled the upregulation of IFN-γ secreted by

activated human CD4+ lymphocytes (Fayyad-Kazan et al., 2014). Moreover, miR-181a

overexpression in Hela cells suppressed TNF-α expression, while a miR-181a antagonist had

the reverse effect (Li et al., 2013). Finally, miR-181a mimic transfection of HEK293T cells

inhibited their TNF-α expression by directly binding to its 3’-UTR section (Gao et al., 2016),

in a way similar to the observed during the IFN-γ inhibition (Fayyad-Kazan et al., 2014).

These results, together with other similar reports, support for a regulatory role of miR-181a in

cell functional differentiation and also in inflammatory processes.

Lastly, it is important to stress out that most of the changes induced by these gain-of-function

experiments – in retroviral vector transduction as well as in mimics transfection – happened

substantially in the Vδ1 subpopulation rather than in Vδ2 subpopulation, in agreement with

the fact that thymic (i.e. immature and Vδ1 enriched) γδ T cells have more plasticity, and thus

are more prone to be manipulated. Also, these results are consistent with previous reports

showing that Vδ1+ T cells generally outperform their Vδ2

+ counterparts regarding the

manipulation of their functional properties (Correia et al., 2011; Silva-Santos et al., 2015).

This information is highly relevant and should be considered when addressing further

experiments concerning the regulation of γδ T cell functional differentiation.

Page 71: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 71

Future Plans

Page 72: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 72

6. Future Plans

In this work, we have been able to manipulate miRs expression on peripheral and thymic γδ T

cells by overexpressing candidates potentially involved in the regulation of γδ T cell

functional differentiation. Reproducing the presented results using more samples would be

crucial to support our conclusions. Given that our work results have demonstrated that the

retroviral approach seems to be a more reliable tool for the gain-of-function experiments, it

would be logical that the future thymic and PBMCs-isolated γδ T cells would be manipulated

using the retroviral methodology to overexpress these miR candidates.

As a logical follow-up of this project, we plan to identify the mRNA networks controlled by

our candidate miRs using a combination of bioinformatics and biochemical assays, and

couple the effects of miR and mRNA manipulation on γδ T cell differentiation. To achieve

that, we intend to resource to three different methodologies: high-throughput sequencing of

RNA isolated by cross-linking immunoprecipitation (HITS-CLIP); in silico analysis that

predict miR targets based on the seed sequence and; luciferase assays to verify if the predicted

mRNAs are indeed direct targets of these candidate miRs. This holistic view of the

transcriptome-wide effects of a given miR will be critical to understand its role in γδ T cell

differentiation.

Finally, we aim at defining a miR pathogenic signature of γδ T cell differentiation in cancer

patient samples. Interestingly, a reduced number and impaired pro-inflammatory cytokine

production in circulating γδ T cells from patients with melanoma (Argentati et al., 2003),

glioblastoma (Bryant et al., 2009) and gastric cancer (Kuroda et al., 2012) has been reported.

We thus hypothesize that our candidate miRs will be abnormally expressed in peripheral γδ T

cells isolated from those patients in comparison with healthy donors. By assessing the

expression of these miRs in circulating γδ T cells from these patients, we expect to validate

their potential as immunotherapy targets. Peripheral blood will be collected from a defined

cohort of patients at the time of diagnostic, to avoid any experimental artefacts that could be

introduced by anti-tumor treatment. For this, we already have established a connection with

the Oncology Department of the Hospital de Santa Maria, directed by Dr. Luís Costa.

Page 73: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 73

Bibliography

Page 74: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 74

7. Bibliography

Adams EJ, Gu S, Luoma AM. 2015. Human gamma delta T cells: Evolution and ligand

recognition. Cell Immunol, 296(1): 31–40. doi: 10.1016/j.cellimm.2015.04.008.

Akira S, Uematsu S, Takeuchi O. 2006. Pathogen Recognition and Innate Immunity. Cell,

124(4), 783–801. doi: 10.1016/j.cell.2006.02.015.

Alexander AA, Maniar A, Cummings JS, Hebbeler AM, Schulze DH, Gastman BR, Pauza

CD, Strome SE, Chapoval AI. 2008. Isopentenyl pyrophosphate activated CD56+ γδ T

lymphocytes display potent anti-tumor activity towards human squamous cell carcinoma, Clin

Cancer Res, 14(13): 4232–40. doi: 10.1158/1078-0432.CCR-07-4912.

Allman D, Miller JP. 2005. B cell development and receptor diversity during aging. Curr

Opin Immunol, 17(5): 463–7. doi: 10.1016/j.coi.2005.07.002.

Almeida AR, Correia DV, Fernandes-Platzgummer A, da Silva CL, Gomes da Silva M, Anjos

DR, Silva-Santos B. 2016. Delta One T cells for immunotherapy of chronic lymphocytic

leukemia: clinical-grade expansion, differentiation and in vivo proof-of-concept. Clin Cancer

Res, 22(17): 1-28. doi: 10.1158/1078-0432.CCR-16-0597.

Altin JG, Sloan EK. 1997. The role of CD45 and CD45-associated molecules in T cell

activation. Immunol Cell Biol, 75(5): 430–45. doi: 10.1038/icb.1997.68.

Argentati K, Re F, Serresi S, Tucci MG, Bartozzi B, Bernardini G, Provinciali M. 2003.

Reduced number and impaired function of circulating gamma delta T cells in patients with

cutaneous primary melanoma. J Invest Dermatol, 120(5): 829–34. doi: 10.1046/j.1523-

1747.2003.12141.x.

Azuara V, Levraud JP, Lembezat MP, Pereira P. 1997. A novel subset of adult γδ thymocytes

that secretes a distinct pattern of cytokines and expresses a very restricted T cell receptor

repertoire. Eur J Immunol, 27(2): 544–53. doi: 10.1002/eji.1830270228.

Barski A, Jothi R, Cuddapah S, Cui K, Roh TY, Schones DE, Zhao K. 2009. Chromatin

poises miRNA-and protein-coding genes for expression. Genome Res, 19(10): 1742–51. doi:

10.1101/gr.090951.109.

Bartel DP. 2004. MicroRNAs: Genomics, Biogenesis, Mechanism, and Function. Cell,

116(2): 281–297. doi: 10.1016/S0092-8674(04)00045-5.

Beg AA. 2002. Endogenous ligands of Toll-like receptors: Implications for regulating

inflammatory and immune responses. Trends Immunol, 23(11): 509–12. doi: 10.1016/S1471-

4906(02)02317-7.

Behr C, Capone M, Couzi L, Taupin JL, Dechanet-Merville J. 2009. Vδ2neg

γδ T Cells, a

Multi-Reactive Tissue Subset: from Innate to Adaptive Altered-Self Surveillance. Open

Immunol J, 2(2): 106–18. doi: 10.2174/1874226200902020106.

Berezikov E. 2011. Evolution of microRNA diversity and regulation in animals. Nat Rev

Genet, 12(12): 846–60. doi: 10.1038/nrg3079.

Bian X, Si Y, Zhang M, Wei R, Yang X, Ren H, Zheng G, Wang C, Zhang Y. 2016. Down-

expression of miR-152 lead to impaired anti-tumor effect of NK via upregulation of HLA-G.

Tumor Biol, 37(3): 3749–56. doi: 10.1007/s13277-015-3669-7.

Bijker N, Meijnen P, Peterse JL, Bogaerts J, Van Hoorebeeck I, Julien JP, Gennaro M,

Rouanet P, Avril A, Fentiman IS, et al. 2006. Breast-Conserving Treatment With or Without

Radiotherapy in Ductal Carcinoma-In-Situ: Ten-Year Results of European Organisation for

Page 75: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 75

Research and Treatment of Cancer Randomized Phase III Trial 10853-A Study by the

EORTC Breast Cancer Cooperative Group and EORTC Radiotherapy Group. J Clin Onc,

24(21): 3381–7. doi: 10.1200/JCO.2006.06.1366.

Bonneville M, O’Brien RL, Born WK. 2010. Gamma-delta T cell effector functions: a blend

of innate programming and acquired plasticity. Nat Rev Immunol, 10(7): 467–78. doi:

10.1038/nri2781.

Bouet-Toussaint F, Cabillic F, Toutirais O, Le Gallo M, Thomas de la Pintière C, Daniel P,

Genetet N, Meunier B, Dupont-Bierre E, Boudjema K, et al. 2008. Vγ9Vδ2 T cell-mediated

recognition of human solid tumors. Potential for immunotherapy of hepatocellular and

colorectal carcinomas. Cancer Immunol Immunother, 57(4): 531–9. doi: 10.1007/s00262-007-

0391-3.

Braakman E, Sturm E, Vijverberg K, van Krimpen BA, Gratama JW, Bolhuis RL. 1991.

Expression of CD45 isoforms by fresh and activated human gamma delta T lymphocytes and

natural killer cells. Int Immunol, 3(7): 691-7.

Bryant RJ, Banks PM, O’Malley DP. 2006. Ki67 staining pattern as a diagnostic tool in the

evaluation of lymphoproliferative disorders. Histopathology, 48(5): 505–15. doi:

10.1111/j.1365-2559.2006.02378.x.

Bryant NL, Suarez-Cuervo C, Gillespie GY, Markert JM, Nabors LB, Meleth S, Lopez RD,

Lamb LS Jr. 2009. Characterization and immunotherapeutic potential of gamma-delta T-cells

in patients with glioblastoma. Neuro Oncol, 11(4): 357–67. doi: 10.1215/15228517-2008-111.

Caccamo N, Todaro M, Sireci G, Meraviglia S, Stassi G, Dieli F. 2013. Mechanisms

underlying lineage commitment and plasticity of human γδ T cells. Cell Mol Immunol, 10(1):

30–4. doi: 10.1038/cmi.2012.42.

Cai X, Hagedorn CH, Cullen BR. 2004. Human microRNAs are processed from capped,

polyadenylated transcripts that can also function as mRNAs. RNA, 10(12): 1957–66. doi:

10.1261/rna.7135204.

Carding SR, Egan PJ. 2002. Gamma-delta T cells: functional plasticity and heterogeneity. Nat

Rev Immunol, 2(5): 336–45. doi: 10.1038/nri797.

Carthew RW, Sontheimer EJ. 2009. Origins and Mechanisms of miRNAs and siRNAs. Cell,

136(4): 642–55. doi: 10.1016/j.cell.2009.01.035.

Chandran PA, Keller A, Weinmann L, Seida AA, Braun M, Andreev K, Fischer B, Horn E,

Schwinn S, Junker M, et al. 2014. The TGF-β-inducible miR-23a cluster attenuates IFN-γ

levels and antigen-specific cytotoxicity in human CD8+ T cells. J Leukoc Biol, 96(4): 633–45.

doi: 10.1189/jlb.3A0114-025R.

Chen Z, Freedman MS. 2008. CD16+ gammadelta T cells mediate antibody dependent cellular

cytotoxicity: potential mechanism in the pathogenesis of multiple sclerosis. Clin Immunol,

128(2): 219-27. doi: 10.1016/j.clim.2008.03.513.

Cheng YQ, Ren JP, Zhao, J, Wang JM, Zhou Y, Li GY, Moorman JP, Yao ZQ. 2015.

MicroRNA-155 regulates interferon-γ production in natural killer cells via Tim-3 signalling in

chronic hepatitis C virus infection. Immunology, 145(4), 485–97. doi: 10.1111/imm.12463.

Cichocki F, Felices M, McCullar V, Presnell SR, Al-Attar A, Lutz CT, Miller JS. 2011.

Cutting edge: microRNA-181 promotes human NK cell development by regulating Notch

signaling. J Immunol, 187(12): 6171–5. doi: 10.4049/jimmunol.1100835.

Ciofani M, Knowles GC, Wiest DL, von Boehmer H, Zúñiga-Pflücker JC. 2006. Stage-

Page 76: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 76

specific and differential notch dependency at the alphabeta and gammadelta T lineage

bifurcation. Immunity, 25(1): 105–16. doi: 10.1016/j.immuni.2006.05.010.

Clem AS. 2011. Fundamentals of vaccine immunology. J Glob Infect Dis, 3(1): 73–8. doi:

10.4103/0974-777X.77299.

Clontech. 2011. StellarTM

Competent Cells Protocol PT5055-2, 6880(0): 2.

Clontech. 2012. In-Fusion® HD Cloning Kit User Manual. In-Fusion Cloning, 1(11614): 1–

15. Retrieved from www.clontech.com/xxclt_ibcGetAttachment.jsp?cItemId=17497

Cobb BS, Nesterova TB, Thompson E, Hertweck A, O'Connor E, Godwin J, Wilson CB,

Brockdorff N, Fisher AG, Smale ST, et al. 2005. T cell lineage choice and differentiation in

the absence of the RNase III enzyme Dicer. J Exp Med, 201(9): 1367–73. doi:

10.1084/jem.20050572.

Constant P, Davodeau F, Peyrat MA, Poquet Y, Puzo G, Bonneville M, Fournié JJ. 1994.

Stimulation of human gamma delta T cells by nonpeptidic mycobacterial ligands. Science,

264(5156): 267–70.

Cordova A, Toia F, La Mendola C, Orlando V, Meraviglia S, Rinaldi G, Todaro M, Cicero G,

Zichichi L, Donni PL, et al. 2012. Characterization of Human γδ T Lymphocytes Infiltrating

Primary Malignant Melanomas. PLoS ONE, 7(11): 1–9. doi: 10.1371/journal.pone.0049878.

Correia DV, Fogli M, Hudspeth K, da Silva MG, Mavilio D, Silva-Santos B. 2011.

Differentiation of human peripheral blood Vd1+ T cells expressing the natural cytotoxicity

receptor NKp30 for recognition of lymphoid leukemia cells. Blood, 118(4), 992–1001. doi:

10.1182/blood-2011-02-339135.

Correia DV, Lopes A, Silva-Santos B. 2013. Tumor cell recognition by γδ T lymphocytes: T-

cell receptor vs. NK-cell receptors. Oncoimmunology, 2(1): e22892. doi: 10.4161/onci.22892.

Costello E, Munoz M, Buetti E, Meylan PR, Diggelmann H, Thali M. 2000. Gene transfer

into stimulated and unstimulated T lymphocytes by HIV-1-derived lentiviral vectors. Gene

Ther, 7(7), 596–604. doi: 10.1038/sj.gt.3301135.

DeBarros A, Chaves-Ferreira M, d'Orey F, Ribot JC, Silva-Santos B. 2011. CD70-CD27

interactions provide survival and proliferative signals that regulate T cell receptor-driven

activation of human γδ peripheral blood lymphocytes. Eur J Immunol, 41(1): 195–201. doi:

10.1002/eji.201040905.

Déchanet J, Merville P, Lim A, Retière C, Pitard V, Lafarge X, Michelson S, Méric C, Hallet

MM, Kourilsky P, et al. 1999. Implication of gammadelta T cells in the human immune

response to cytomegalovirus. J Clin Invest, 103(10): 1437–49. doi: 10.1172/JCI5409.

Deniger DC, Moyes JS, Cooper LJN. 2014. Clinical Applications of Gamma Delta T Cells

with Multivalent Immunity. Front Immunol, 5(12): 1–10. doi: 10.3389/fimmu.2014.00636.

Dieli F, Poccia F, Lipp M, Sireci G, Caccamo N, Di Sano C, Salerno A. 2003. Differentiation

of effector/memory Vdelta2 T cells and migratory routes in lymph nodes or inflammatory

sites. J Exp Med, 198(3): 391–7. doi: 10.1084/jem.20030235.

Dieli F, Vermijlen D, Fulfaro F, Caccamo N, Meraviglia S, Cicero G, Roberts A, Buccheri S,

D'Asaro M, Gebbia N, et al. 2007. Targeting human gamma-delta T cells with zoledronate

and interleukin-2 for immunotherapy of hormone-refractory prostate cancer. Cancer Res,

67(15): 7450–7. doi: 10.1158/0008-5472.CAN-07-0199.

Dik WA, Pike-Overzet K, Weerkamp F, de Ridder D, de Haas EF, Baert MR, van der Spek P,

Koster EE, Reinders MJ, van Dongen JJ, et al. 2005. New insights on human T cell

Page 77: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 77

development by quantitative T cell receptor gene rearrangement studies and gene expression

profiling. J Exp Med, 201(11): 1715–23. doi: 10.1084/jem.20042524.

Dugué PA, Rebolj M, Garred P, Lynge E. 2013. Immunosuppression and risk of cervical

cancer. Expert Rev Anticancer Ther, 13(1): 29–42. doi: 10.1586/era.12.159.

Dunn GP, Bruce AT, Ikeda H, Old LJ, Schreiber RD. 2002. Cancer immunoediting: from

immunosurveillance to tumor escape. Nat Immunol, 3(11): 991–8. doi: 10.1038/ni1102-991.

Eaton D, Gilham DE, O'Neill A, Hawkins RE. 2002. Retroviral transduction of human

peripheral blood lymphocytes with Bcl-X(L) promotes in vitro lymphocyte survival in pro-

apoptotic conditions. Gene Ther, 9(8): 527-35. doi: 10.1038/sj/gt/3301685.

Elliott JF, Rock EP, Patten PA, Davis MM, Chien YH. 1988. The adult T-cell receptor 5-

chain is diverse and distinct from that of fetal thymocytes. Nature, 331(6157): 627–31. doi:

10.1038/331627a0.

Exiqon. 2014. miRCURY LNATM

microRNA Mimics, Instruction Manual v1.0 (April), 1–14.

Fayyad-Kazan H, Hamade E, Rouas R, Najar M, Fayyad-Kazan M, El Zein N, ElDirani R,

Hussein N, Fakhry M, Al-Akoum C, et al. 2014. Downregulation of microRNA-24 and -181

parallels the upregulation of IFN-γ secreted by activated human CD4 lymphocytes. Hum

Immunol, 75(7): 677–85. doi: 10.1016/j.humimm.2014.01.007.

Fragoso R, Mao T, Wang S, Schaffert S, Gong X, Yue S, Luong R, Min H, Yashiro-Ohtani Y,

Davis M, et al. 2012. Modulating the Strength and Threshold of NOTCH Oncogenic Signals

by mir-181a-1/b-1. PLoS Genet, 8(8): e1002855. doi: 10.1371/journal.pgen.1002855.

Frey AB, Monu N. 2006. Effector-phase tolerance: another mechanism of how cancer escapes

antitumor immune response. J Leukoc Biol, 79(4): 652–62. doi: 10.1189/jlb.1105628.

Friedman RC, Farh KKH, Burge CB, Bartel DP. 2009. Most mammalian mRNAs are

conserved targets of microRNAs. Genome Res 2009; 19(1): 92–105. doi:

10.1101/gr.082701.108.

Galon J, Angell H, Bedognetti D, Marincola F. 2013. The Continuum of Cancer

Immunosurveillance: Prognostic, Predictive, and Mechanistic Signatures. Immunity, 39(1):

11–26. doi: 10.1016/j.immuni.2013.07.008.

Gao L, Wang G, Liu W, Kinser H, Franco HL, Mendelson CR. 2016. Reciprocal Feedback

between miR-181a and E2/ERα in Myometrium Enhances Inflammation Leading to Labor. J

Clin Endocrinol Metab, Jul(26): jc.2016-2078. doi: 10.1210/jc.2016-2078.

García-Peydró M, de Yébenes VG, Toribio ML. 2003. Sustained Notch1 signaling instructs

the earliest human intrathymic precursors to adopt a gammadelta T-cell fate in fetal thymus

organ culture. Blood, 102(7): 2444–51. doi: 10.1182/blood-2002-10-3261.

Gentles AJ, Newman AM, Liu CL, Bratman SV, Feng W, Kim D, Nair VS, Xu Y, Khuong A,

Hoang CD, et al. 2015. The prognostic landscape of genes and infiltrating immune cells

across human cancers. Nat Med, 21(8): 938-45. doi: 10.1038/nm.3909.

Germain RN. 2002. T-cell development and the CD4-CD8 lineage decision. Nat Rev

Immunol, 2(5): 309-22. doi: 10.1038/nri798.

Ghisi M, Corradin A, Basso K, Frasson C, Serafin V, Mukherjee S, Mussolin L, Ruggero K,

Bonanno L, Guffanti A, et al. 2011. Modulation of microRNA expression in human T-cell

development : targeting of NOTCH3 by miR-150. Blood, 117(26): 7053–62. doi:

10.1182/blood-2010-12-326629.

Page 78: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 78

Gigante M, Pontrelli P, Herr W, Gigante M, D'Avenia M, Zaza G, Cavalcanti E, Accetturo M,

Lucarelli G, Carrieri G, et al. 2016. miR-29b and miR-198 overexpression in CD8+ T cells of

renal cell carcinoma patients down-modulates JAK3 and MCL-1 leading to immune

dysfunction. J Transl Med, 14(1): 84. doi: 10.1186/s12967-016-0841-9.

Girardi M. 2006. Immunosurveillance and immunoregulation by gammadelta T cells. J Invest

Dermatol, 126(1): 25–31. doi: 10.1038/sj.jid.5700003.

Goffin J, Lacchetti C, Ellis PM, Ung YC, Evans WK. 2010. First-Line Systemic

Chemotherapy in the Treatment of Advanced Non-small Cell Lung Cancer: A Systematic

Review. J Thorac Oncol, 5(2): 260-74. doi: 10.1097/JTO.0b013e3181c6f035.

Gogoi D, Dar AA, Chiplunkar SV. 2014. Involvement of Notch in activation and effector

functions of γδ T cells. J Immunol, 192(5), 2054–62. doi: 10.4049/jimmunol.1300369.

Gomes AQ, Martins DS, Silva-Santos B. 2010. Targeting γδ T lymphocytes for cancer

immunotherapy: From novel mechanistic insight to clinical application. Cancer Res, 70(24):

10024–27. doi: 10.1158/0008-5472.CAN-10-3236.

Green DR, Droin N, Pinkoski M. 2003. Activation-induced cell death in T cells. Immunol

Rev, 193: 70-81.

Gregory RI, Chendrimada TP, Shiekhattar R. 2006. MicroRNA biogenesis: isolation and

characterization of the microprocessor complex. Methods Mol Biol, 342: 33–47. doi:

10.1385/1-59745-123-1:33.

Grossman Z, Min B, Meier-Schellersheim M, Paul WE. 2004. Concomitant regulation of T-

cell activation and homeostasis. Nat Rev Immunol, 4(5): 387–95. doi: 10.1038/nri1355.

Haas JD, González FH, Schmitz S, Chennupati V, Föhse L, Kremmer E, Förster R, Prinz I.

2009. CCR6 and NK1.1 distinguish between IL-17A and IFN-γ-producing γδ effector T cells.

Eur J Immunol, 39(12): 3488–97. doi: 10.1002/eji.200939922.

Haks MC, Lefebvre JM, Lauritsen JP, Carleton M, Rhodes M, Miyazaki T, Kappes DJ, Wiest

DL. 2005. Attenuation of gammadelta TCR signaling efficiently diverts thymocytes to the

alphabeta lineage. Immunity, 22(5): 595–606. doi: 10.1016/j.immuni.2005.04.003.

Hamaï A, Benlalam H, Meslin F, Hasmim M, Carré T, Akalay I, Janji B, Berchem G, Noman

MZ, Chouaib S. 2010. Immune surveillance of human cancer: If the cytotoxic T-lymphocytes

play the music, does the tumoral system call the tune? Tissue Antigens, 75(1): 1–8. doi:

10.1111/j.1399-0039.2009.01401.x.

Hanahan D, Weinberg RA. 2011. Hallmarks of cancer: the next generation. Cell, 144(5): 646-

74. doi: 10.1016/j.cell.2011.02.013.

Hannani D, Ma Y, Yamazaki T, Déchanet-Merville J, Kroemer G, Zitvogel L. 2012.

Harnessing γδ T cells in anticancer immunotherapy. Trends Immunol, 33(5): 199–206. doi:

10.1016/j.it.2012.01.006.

Hao J, Wu X, Xia S, Li Z, Wen T, Zhao N, Wu Z, Wang P, Zhao L, Yin Z. 2010. Current

progress in γδ T-cell biology. Cell Mol Immunol, 7(6): 409–413. doi: 10.1038/cmi.2010.50.

Harly C, Guillaume Y, Nedellec S, Peigné CM, Mönkkönen H, Mönkkönen J, Li J, Kuball J,

Adams EJ, Netzer S, et al. 2012. Key implication of CD277/butyrophilin-3 (BTN3A) in

cellular stress sensing by a major human γδ T-cell subset. Blood, 120(11): 2269–79. doi:

10.1182/blood-2012-05-430470.

Hayday AC. 2009. γδ T Cells and the Lymphoid Stress-Surveillance Response. Immunity,

31(2): 184–196. doi: 10.1016/j.immuni.2009.08.006.

Page 79: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 79

Hayes SM, Li L, Love PE. 2005. TCR signal strength influences αβ/γδ lineage fate. Immunity,

22(5): 583–93. doi: 10.1016/j.immuni.2005.03.014.

Hoebe K, Janssen E, Beutler B. 2004. The interface between innate and adaptive immunity,

Nat Immunol, 5(10): 971–74.

Hu WS, Pathak VK. 2000. Design of retroviral vectors and helper cells for gene therapy.

Pharmacol Rev, 52(4): 493–511.

Hutvágner G, Zamore PD. 2002. A microRNA in a multiple-turnover RNAi enzyme complex.

Science, 297(5589): 2056–60. doi: 10.1126/science.1073827.

Invitrogen. 2010. Neon TM

Transfection System. Optimization, MAN0001557: Rev A.0.

Iwasaki A, Medzhitov R. 2015. Control of adaptive immunity by the innate immune system.

Nat Immunol, 16(4): 343–53. doi: 10.1038/ni.3123.

Jacobs SR, Herman CE, Maciver NJ, Wofford JA, Wieman HL, Hammen JJ, Rathmell JC.

2008. Glucose uptake is limiting in T cell activation and requires CD28-mediated Akt-

dependent and independent pathways. J Immunol, 180(7): 4476-86.

Janeway CA Jr. 1989. Approaching the asymptote? Evolution and revolution in immunology.

Cold Spring Harb Symp Quant Biol, 54(1): 1–13. doi: 10.1101/SQB.1989.054.01.003.

Janeway CA Jr, Travers P, Walport M, et al. 2001. Immunobiology: The Immune System in

Health and Disease. 5th

edition, New York: Garland Science. Available from:

http://www.ncbi.nlm.nih.gov/books/NBK27090/.

Jeker LT, Bluestone JA. 2013. MicroRNA regulation of T-cell differentiation and function.

Immunol Rev, 253(1): 65–81. doi: 10.1111/imr.12061.

Ji Y, Wrzesinski C, Yu Z, Hu J, Gautam S, Hawk NV, Telford WG, Palmer DC, Franco Z,

Sukumar M, et al. 2015. miR-155 augments CD8+ T-cell antitumor activity in lymphoreplete

hosts by enhancing responsiveness to homeostatic γc cytokines. Proc Natl Acad Sci U S A,

112(2): 476–81. doi: 10.1073/pnas.1422916112.

Jiao Y, Fu J, Xing S, Fu B, Zhang Z, Shi M, Wang X, Zhang J, Jin L, Kang F, et al. 2009.

The decrease of regulatory T cells correlates with excessive activation and apoptosis of CD8+

T cells in HIV-1-infected typical progressors, but not in long-term non-progressors.

Immunology, 128(1 Suppl): 366–75. doi: 10.1111/j.1365-2567.2008.02978.x.

Jin HY, Gonzalez-Martin A, Miletic AV, Lai M, Knight S, Sabouri-Ghomi M, Head SR,

Macauley MS, Rickert RC, Xiao C2. 2015. Transfection of microRNA mimics should be used

with caution. Front Genet, 6(340): 1–23. doi: 10.3389/fgene.2015.00340.

Joachims ML, Chain JL, Hooker SW, Knott-Craig CJ, Thompson LF. 2006. Human alpha

beta and gamma delta thymocyte development: TCR gene rearrangements, intracellular TCR

beta expression, and gamma delta developmental potential--differences between men and

mice. J Immunol, 176(3): 1543–52.

Kabelitz D, Kalyan S, Oberg HH, Wesch D. 2013. Human Vδ2 versus non-Vδ2 γδ T cells in

antitumor immunity. Oncoimmunology, 2(3): e23304. doi: 10.4161/onci.23304.

Kai ZS, Pasquinelli AE. 2010. MicroRNA assassins: factors that regulate the disappearance of

miRNAs. Nat Struct Mol Biol, 17(1): 5–10. doi: 10.1038/nsmb.1762.

Kalabus JL, Cheng Q, Blanco JG. 2012. MicroRNAs Differentially Regulate Carbonyl

Reductase 1 (CBR1) Gene Expression Dependent on the Allele Status of the Common

Polymorphic Variant rs9024. PLoS ONE, 7(11): e48622. doi: 10.1371/journal.pone.0048622.

Page 80: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 80

Kang N, Zhou J, Zhang T, Wang L, Lu F, Cui Y, Cui L, He W. 2009. Adoptive

immunotherapy of lung cancer with immobilized anti-TCRγδ antibody-expanded human γδ T

Cells in peripheral blood. Cancer Biol Ther, 8(16): 1540–9. doi: 10.4161/cbt.8.16.8950.

Katikireddi RS, Setty SNRS. 2013. The incidence of common cancers in south indian region

– A hospital based cross sectional study. Int J Cur Res Rev, 5(23): 37–43.

King BC, Esguerra JL, Golec E, Eliasson L, Kemper C, Blom AM. 2016. CD46 Activation

Regulates miR-150-Mediated Control of GLUT1 Expression and Cytokine Secretion in

Human CD4+ T Cells. J Immunol, 196(4): 1636–45. doi: 10.4049/jimmunol.1500516.

Kirigin FF, Lindstedt K, Sellars M, Ciofani M, Low SL, Jones L, Bell F, Pauli F, Bonneau R,

Myers RM, et al. 2012. Dynamic microRNA gene transcription and processing during T cell

development. J Immunol, 188(7): 3257–67. doi: 10.4049/jimmunol.1103175.

Kuroda H, Saito H, Ikeguchi M. 2012. Decreased number and reduced NKG2D expression of

Vδ1 γδ T cells are involved in the impaired function of Vδ1 γδ T cells in the tissue of gastric

cancer. Gastric Cancer, 15(4): 433–9. doi: 10.1007/s10120-011-0138-x.

Lafont V, Sanchez F, Laprevotte E, Michaud HA, Gros L, Eliaou JF, Bonnefoy N. 2014.

Plasticity of γδ T Cells: Impact on the Anti-Tumor Response. Front Immunol, 5(622): 1–13.

doi: 10.3389/fimmu.2014.00622.

Lanier LL, Sun JC. 2009. Do the terms innate and adaptive immunity create conceptual

barriers? Nat Rev Immunol, 9(5): 302-3. doi: 10.1038/nri2547.

Lau NC, Lim LP, Weinstein EG, Bartel DP. 2001. An abundant class of tiny RNAs with

probable regulatory roles in Caenorhabditis elegans. Science, 294(5543): 858–62. doi:

10.1126/science.1065062.

Le Doux JM, Morgan JR, Snow RG, Yarmush ML. 1996. Proteoglycans secreted by

packaging cell lines inhibit retrovirus infection. J Virol, 70(9): 6468-73.

Le Doux JM, Morgan JR, Yarmush ML. 1998. Removal of proteoglycans increases efficiency

of retroviral gene transfer. Biotechnol Bioeng, 58(1): 23-34.

Lee MJ, Park JH. 2009. Pathway analysis in HEK 293T cells overexpressing HIV-1 tat and

nucleocapsid. J Microbiol Biotechnol, 19(10): 1103–8. doi: 10.4014/jmb.0903.03005.

Lee RC, Feinbaum RL, Ambros V. 1993. The C. elegans heterochronic gene lin-4 encodes

small RNAs with antisense complementarity to lin-14. Cell, 75(5): 843–54. doi:

10.1016/0092-8674(93)90529-Y.

Lee Y, Kim M, Han J, Yeom KH, Lee S, Baek SH, Kim VN. 2004. MicroRNA genes are

transcribed by RNA polymerase II. EMBO J, 23(20): 4051–60. doi:

10.1038/sj.emboj.7600385.

Li H, Chen X, Guan L, Qi Q, Shu G, Jiang Q, Yuan L, Xi Q, Zhang Y. 2013. MiRNA-181a

regulates adipogenesis by targeting tumor necrosis factor-α (TNF-α) in the porcine model.

PLoS ONE, 8(10): e71568. doi: 10.1371/journal.pone.0071568.

Lin R, Chen L, Chen G, Hu C, Jiang S, Sevilla J, Wan Y, Sampson JH, Zhu B, Li QJ. 2014.

Targeting miR-23a in CD8+ cytotoxic T lymphocytes prevents tumor-dependent

immunosuppression. J Clin Invest, 124(12): 5352–67. doi: 10.1172/JCI76561.

Linton PJ, Dorshkind K. 2004. Age-related changes in lymphocyte development and function.

Nat Immunol, 5(2): 133–9. doi: 10.1038/ni1033.

Liu YP, Berkhout B. 2011. MiRNA cassettes in viral vectors: Problems and solutions.

Page 81: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 81

Biochim Biophys Acta, 1809(11–12): 732–45. doi: 10.1016/j.bbagrm.2011.05.014.

Liu Z, Eltoum IE, Guo B, Beck BH, Cloud GA, Lopez RD. 2008. Protective

immunosurveillance and therapeutic antitumor activity of gammadelta T cells demonstrated in

a mouse model of prostate cancer. J Immunol, 180(9): 6044–53. doi: 10.1038/nrurol.2011.63.

Livak F, Petrie HT, Crispe IN, Schatz DG. 1995. In-frame TCR delta gene rearrangements

play a critical role in the alpha beta/gamma delta T cell lineage decision. Immunity, 2(6): 617–

27. doi: 1074-7613(95)90006-3.

Lo Presti E, Dieli F, Meraviglia S. 2014. Tumor-infiltrating γδ T lymphocytes: Pathogenic

role, clinical significance, and differential programing in the tumor microenvironment. Front

Immunol, 5(Nov): 607. doi: 10.3389/fimmu.2014.00607.

Ma C, Zhang Q, Ye J, Wang F, Zhang Y, Wevers E, Schwartz T, Hunborg P, Varvares MA,

Hoft DF, et al. 2012. Tumor-infiltrating γδ T lymphocytes predict clinical outcome in human

breast cancer. J Immunol, 189(10): 5029-36. doi: 10.4049/jimmunol.1201892.

Mak TW, Saunders ME, Jett BD. 2014. Primer to the Immune Response. 2nd

edition,

California: APCell Press. Available from:

https://books.google.pt/books?id=d4l81P7ODcIC&printsec.

Manganoni AM, Zane C, Pavoni L, Farisoglio C, Sereni E, Calzavara-Pinton P. 2011.

Cutaneous melanoma in patients in treatment with biological therapy: Review of the literature

and case report. Dermatol Online J, 17(8): 12.

Manzano M, Shamulailatpam P, Raja AN, Gottwein E. 2013. Kaposi’s sarcoma-associated

herpesvirus encodes a mimic of cellular miR-23. J Virol, 87(21): 11821–30. doi:

10.1128/JVI.01692-13.

Matsui M, Li L, Janowski BA, Corey DR. 2015. Reduced Expression of Argonaute 1,

Argonaute 2, and TRBP Changes Levels and Intracellular Distribution of RNAi Factors. Sci

Rep, 5(August): 12855. doi: 10.1038/srep12855.

Matsuyama H, Suzuki HI, Nishimori H, Noguchi M, Yao T, Komatsu N, Mano H, Sugimoto

K, Miyazono K. 2011. miR-135b mediates NPM-ALK – driven oncogenicity and renders IL-

17 – producing immunophenotype to anaplastic large cell lymphoma. Blood, 118(26), 6881–

92. doi: 10.1182/blood-2011-05-354654.

Medzhitov R, Janeway C Jr. 2000. Innate immunity. N Engl J Med, 343(5): 338-44.

Meier P, Dayer E, Blanc E, Wauters JP. 2002. Early T cell activation correlates with

expression of apoptosis markers in patients with end-stage renal disease. J Am Soc Nephrol,

13(1): 204–12.

Meijer HA, Smith EM, Bushell M. 2014. Regulation of miRNA strand selection: follow the

leader? Biochem Soc Trans, 42(4): 1135–40. doi: 10.1042/BST20140142.

Mele F, Basso C, Leoni C, Aschenbrenner D, Becattini S, Latorre D, Lanzavecchia A,

Sallusto F, Monticelli S. 2015. ERK phosphorylation and miR-181a expression modulate

activation of human memory TH17 cells. Nat Commun, 6: 6431. doi: 10.1038/ncomms7431.

Meraviglia S, Eberl M, Vermijlen D, Todaro M, Buccheri S, Cicero G, La Mendola C,

Guggino G, D'Asaro M, Orlando V, et al. 2010. In vivo manipulation of Vγ9Vδ2 T cells with

zoledronate and low-dose interleukin-2 for immunotherapy of advanced breast cancer

patients. Clin Exp Immunol, 161(2): 290–7. doi: 10.1111/j.1365-2249.2010.04167.x.

Michel ML, Pang DJ, Haque SF, Potocnik AJ, Pennington DJ, Hayday AC. 2012. Interleukin

7 (IL-7) selectively promotes mouse and human IL-17-producing γδ cells. Proc Natl Acad Sci

Page 82: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 82

U S A, 109(43): 17549-54. doi: 10.1073/pnas.1204327109.

Mogensen TH. 2009. Pathogen recognition and inflammatory signaling in innate immune

defenses. Clin Microbiol Rev, 22(2): 240–73. doi: 10.1128/CMR.00046-08.

Mogilyansky E, Rigoutsos I. 2013. The miR-17/92 cluster: a comprehensive update on its

genomics, genetics, functions and increasingly important and numerous roles in health and

disease. Cell Death Differ, 20(12): 1603–14. doi: 10.1038/cdd.2013.125.

Möhnle P, Schütz SV, van der Heide V, Hübner M, Luchting B, Sedlbauer J, Limbeck E,

Hinske LC, Briegel J, Kreth S. (2015). MicroRNA-146a controls Th1-cell differentiation of

human CD4+ T lymphocytes by targeting PRKCε. Eur J Immunol, 45(1): 260–72. doi:

10.1002/eji.201444667.

Murphy KP, Janeway C, Travers P, Walport M, Mowat A, Weaver C. 2012. Janeway's

immunobiology. 8th

edition, New York,: Garland Science.

O’Leary JG, Goodarzi M, Drayton DL, von Andrian UH. 2006. T cell- and B cell-

independent adaptive immunity mediated by natural killer cells. Nat Immunol, 7(5): 507–16.

doi: 10.1038/ni1332.

Okamura K, Hagen JW, Duan H, Tyler DM, Lai EC. 2009. The mirtron pathway generates

microRNA-class regulatory RNAs in Drosophila. Cell, 130(1), 89–100. doi:

10.1016/j.cell.2007.06.028.

Pagès JC, Bru T. 2004. Toolbox for retrovirologists. J Gene Med, 6(1): S67-82.

Palin AC, Ramachandran V, Acharya S, Lewis DB. 2013. Human neonatal naive CD4+ T

cells have enhanced activation-dependent signaling regulated by the microRNA miR-181a. J

Immunol, 190(6): 2682–91. doi: 10.4049/jimmunol.1202534.

Park SE, Lee MJ, Yang MH, Ahn KY, Jang SI, Suh YJ, Myung H, You JC, Park JH. 2007.

Expression profiles and pathway analysis in HEK 293 T cells overexpressing HIV-1 Tat and

nucleocapsid using cDNA microarray. J Microbiol Biotechnol, 17(1): 154–61.

Passoni L, Hoffman ES, Kim S, Crompton T, Pao W, Dong MQ, Owen MJ, Hayday AC.

1997. Intrathymic delta selection events in gammadelta cell development. Immunity, 7(1): 83–

95. doi: S1074-7613(00)80512-9.

Peng G, Wang HY, Peng W, Kiniwa Y, Seo KH, Wang RF. 2007. Tumor-infiltrating

gammadelta T cells suppress T and dendritic cell function via mechanisms controlled by a

unique toll-like receptor signaling pathway. Immunity, 27(2): 334–48. doi:

10.1016/j.immuni.2007.05.020.

Podshivalova K, Salomon DR. 2013. microRNA regulation of T lymphocyte immunity:

modulation of molecular networks responsible for T cell activation, differentiation and

development. Crit Rev Immunol, 33(5): 435-476.

Popovic R, Riesbeck LE, Velu CS, Chaubey A, Zhang J, Achille NJ, Erfurth FE, Eaton K, Lu

J, Grimes HL, et al. 2009. Regulation of mir-196b by MLL and its overexpression by MLL

fusions contributes to immortalization. Blood, 113(14): 3314–22. doi: 10.1182/blood-2008-

04-154310.

Porichis F, Hart MG, Griesbeck M, Everett HL, Hassan M, Baxter AE, Lindqvist M, Miller

SM, Soghoian DZ, Kavanagh DG, et al. 2015. High-throughput detection of miRNAs and

gene-specific mRNA at the single-cell level by flow cytometry. Nat Commun, 5(Dec): 5641.

doi: 10.1038/ncomms6641.

Prezioso D, Piccirillo G, Galasso R, Altieri V, Mirone V, Lotti T. 2004. Gynecomastia due to

Page 83: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 83

hormone therapy for advanced prostate cancer: a report of ten surgically treated cases and a

review of treatment options. Tumori, 90(4): 410-5.

Prinz I, Sansoni A, Kissenpfennig A, Ardouin L, Malissen M, Malissen B. 2006.

Visualization of the earliest steps of gammadelta T cell development in the adult thymus. Nat

Immunol, 7(9): 995–1003. doi: 10.1038/ni1371.

Prinz I, Silva-Santos B, Pennington DJ. 2013. Functional development of γδ T cells. Eur J

Immunol, 43(8): 1988–94. doi: 10.1002/eji.201343759.

Pulko V, Davies JS, Martinez C, Lanteri MC, Busch MP, Diamond MS, Knox K, Bush EC,

Sims PA, Sinari S, et al. 2016. Human memory T cells with a naive phenotype accumulate

with aging and respond to persistent viruses. Nat Immunol, 17(8): 966-75. doi:

10.1038/ni.3483.

Qin G, Liu Y, Zheng J, Xiang Z, Ng IH, Malik Peiris JS, Lau YL, Tu W. 2012. Phenotypic

and functional characterization of human gammadelta T-cell subsets in response to influenza

A viruses. J Infect Dis, 205(11): 1646–53. doi: 10.1093/infdis/jis253.

Rao PE, Petrone AL, Ponath PD. 2005. Differentiation and expansion of T cells with

regulatory function from human peripheral lymphocytes by stimulation in the presence of

TGF-{beta}. J Immunol, 174(3): 1446–55. doi: 10.4049/jimmunol.174.3.1446.

Recht A, Houlihan MJ. 1995. Conservative surgery without radiotherapy in the treatment of

patients with early-stage invasive breast cancer. A review. Ann Surg, 222(1): 9–18.

Reddycherla AV, Meinert I, Reinhold A, Reinhold D, Schraven B, Simeoni L. 2015. MiR-20a

inhibits TCR-Mediated signaling and cytokine production in human naïve CD4+ T cells. PLoS

ONE, 10(4): e0125311. doi: 10.1371/journal.pone.0125311.

Rei M, Gonçalves-Sousa N, Lança T, Thompson RG, Mensurado S, Balkwill FR, Kulbe H,

Pennington DJ, Silva-Santos B. 2014. Murine CD27(-)

Vγ6(+)

γδ T cells producing IL-17A

promote ovarian cancer growth via mobilization of protumor small peritoneal macrophages.

Proc Natl Acad Sci U S A, 111(34): E3562-70. doi: 10.1073/pnas.1403424111.

Rei M, Pennington DJ, Silva-Santos B. 2015. The Emerging Protumor Role of T

Lymphocytes: Implications for Cancer Immunotherapy. Cancer Res, 75(5): 798–802. doi:

10.1158/0008-5472.CAN-14-3228.

Ribeiro ST, Ribot JC, Silva-Santos B. 2015. Five Layers of Receptor Signaling in γδ T-Cell

Differentiation and Activation. Front Immunol, 6(Jan): 15. doi: 10.3389/fimmu.2015.00015.

Ribot JC, deBarros A, Pang DJ, Neves JF, Peperzak V, Roberts SJ, Girardi M, Borst J,

Hayday AC, Pennington DJ, et al. 2009. CD27 is a thymic determinant of the balance

between interferon-gamma and interleukin 17-producing gammadelta T cell subsets. Nat

Immunol, 10(4): 427–36. doi:10.1038/ni.1717.

Ribot JC, Silva-Santos B. 2013. Differentiation and activation of γδ T Lymphocytes: Focus

on CD27 and CD28 costimulatory receptors. Adv Exp Med Biol, 785: 95-105. doi:

10.1007/978-1-4614-6217-0_11.

Ribot JC, Ribeiro ST, Correia DV, Sousa AE, Silva-Santos B. 2014. Human γδ Thymocytes

Are Functionally Immature and Differentiate into Cytotoxic Type 1 Effector T Cells upon IL-

2/IL-15 Signaling. J Immunol, 192(5): 2237–43. doi: 10.4049/jimmunol.1303119.

Ro S, Park C, Young D, Sanders KM, Yan W. 2007. Tissue-dependent paired expression of

miRNAs. Nucleic Acids Res, 35(17): 5944–53. doi: 10.1093/nar/gkm641.

Rutella S, Rumi C, Lucia MB, Barberi T, Puggioni PL, Lai M, Romano A, Cauda R, Leone

Page 84: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 84

G. 1999. Induction of CD69 antigen on normal CD4+ and CD8

+ lymphocyte subsets and its

relationship with the phenotype of responding T-cells. Cytometry, 38(3): 95–101. doi:

10.1002/(SICI)1097-0320(19990615)38:33.0.CO;2-L.

Saini HK, Griffiths-Jones S, Enright AJ. 2007. Genomic analysis of human microRNA

transcripts. Proc Natl Acad Sci U S A, 104(45): 17719–24. doi: 10.1073/pnas.0703890104.

Sang W, Zhang C, Zhang D, Wang Y, Sun C, Niu M, Sun X, Zhou C, Zeng L, Pan B, et al.

2015. MicroRNA-181a, a potential diagnosis marker, alleviates acute graft versus host disease

by regulating IFN-γ production. Am J Hematol, 90(11): 998–1007. doi: 10.1002/ajh.24136.

Schenten D, Medzhitov R. 2011. The control of adaptive immune responses by the innate

immune system. Adv Immunol, 109: 87-124. doi: 10.1016/B978-0-12-387664-5.00003-0.

Schmolka N, Serre K, Grosso AR, Rei M, Pennington DJ, Gomes AQ, Silva-Santos B. 2013.

Epigenetic and transcriptional signatures of stable versus plastic differentiation of

proinflammatory γδ T cell subsets. Nat Immunol, 14(10): 1093–100. doi: 10.1038/ni.2702.

Scotet E, Martinez LO, Grant E, Barbaras R, Jenö P, Guiraud M, Monsarrat B, Saulquin X,

Maillet S, Estève JP, et al. 2005. Tumor recognition following Vγ9Vδ2 T cell receptor

interactions with a surface F1-ATPase-related structure and apolipoprotein A-I. Immunity,

22(1): 71–80. doi: 10.1016/j.immuni.2004.11.012.

Seidel UJ, Vogt F, Grosse-Hovest L, Jung G, Handgretinger R, Lang P. 2014. γδ T Cell-

Mediated Antibody-Dependent Cellular Cytotoxicity with CD19 Antibodies Assessed by an

Impedance-Based Label-Free Real-Time Cytotoxicity Assay. Front Immunol, 5: 618. doi:

10.3389/fimmu.2014.00618.

Seo KH, Zhou L, Meng D, Xu J, Dong Z, Mi QS. 2010. Loss of microRNAs in thymus

perturbs invariant NKT cell development and function. Cell Mol Immunol, 7(6): 447–53. doi:

10.1038/cmi.2010.49.

Sheppard HM, Verdon D, Brooks AE, Feisst V, Ho YY, Lorenz N, Fan V, Birch NP,

Didsbury A, Dunbar PR. 2014. MicroRNA regulation in human CD8+ T cell subsets –

cytokine exposure alone drives miR-146a expression. J Transl Med, 12(1): 292. doi:

10.1186/s12967-014-0292-0.

Shibata K. 2012. Close link between development and function of gamma-delta T cells.

Microbiol Immunol, 56(4): 217–27. doi: 10.1111/j.1348-0421.2012.00435.x.

Shibata K, Yamada H, Nakamura M, Hatano S, Katsuragi Y, Kominami R, Yoshikai Y. 2014.

IFN-γ-Producing and IL-17-Producing γδ T Cells Differentiate at Distinct Developmental

Stages in Murine Fetal Thymus. J Immunol, 192(5): 2210–8. doi: 10.4049/jimmunol.1302145.

Siegel R, Naishadham D, Jemal A. 2012. Cancer Statistics. CA Cancer J Clin, 62(1): 10–29.

doi: 10.3322/caac.20138.

Siegers GM, Swamy M, Fernández-Malavé E, Minguet S, Rathmann S, Guardo AC, Pérez-

Flores V, Regueiro JR, Alarcón B, Fisch P, et al. 2007. Different composition of the human

and the mouse gammadelta T cell receptor explains different phenotypes of CD3gamma and

CD3delta immunodeficiencies. J Exp Med, 204(11): 2537–44. doi: 10.1084/jem.20070782.

Silva-Santos B, Serre K, Norell H. 2015. γδ T cells in cancer. Nat Rev Immunol, 15(11): 683–

91. doi: 10.1038/nri3904.

Simpson LJ, Patel S, Bhakta NR, Choy DF, Brightbill HD, Ren X, Wang Y, Pua HH,

Baumjohann D, Montoya MM, et al. 2014. A microRNA upregulated in asthma airway T

cells promotes TH2 cytokine production. Nat Immunol, 15(12): 1162–70. doi:

Page 85: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 85

10.1038/ni.3026.

Smith NL, Wissink EM, Grimson A, Rudd BD. 2015. miR-150 Regulates Differentiation and

Cytolytic Effector Function in CD8+ T cells. Sci Rep, 5: 16399. doi: 10.1038/srep16399.

Spada FM, Grant EP, Peters PJ, Sugita M, Melián A, Leslie DS, Lee HK, van Donselaar E,

Hanson DA, Krensky AM, et al. 2000. Self-recognition of CD1 by gamma/delta T cells:

implications for innate immunity. J Exp Med, 191(6): 937–48.

Sun JC, Beilke JN, Lanier LL. 2009. Adaptive Immune Features of Natural Killer Cells.

Nature, 457(7229): 557–61. doi: 10.1038/nature07665.

Szeto CY, Lin CH, Choi SC, Yip TT, Ngan RK, Tsao GS, Li Lung M. 2014. Integrated

mRNA and microRNA transcriptome sequencing characterizes sequence variants and mRNA-

microRNA regulatory network in nasopharyngeal carcinoma model systems. FEBS Open Bio,

4: 128–40. doi: 10.1016/j.fob.2014.01.004.

Tanigaki K, Tsuji M, Yamamoto N, Han H, Tsukada J, Inoue H, Kubo M, Honjo T. 2004.

Regulation of alphabeta/gammadelta T cell lineage commitment and peripheral T cell

responses by Notch/RBP-J signaling. Immunity, 20(5): 611–22. doi: 10.1016/S1074-

7613(04)00109-8.

Thedrez A, Sabourin C, Gertner J, Devilder MC, Allain-Maillet S, Fournié JJ, Scotet E,

Bonneville M. 2007. Self/non-self discrimination by human γδ T cells: Simple solutions for a

complex issue? Immunol Rev, 215(1): 123–35. doi: 10.1111/j.1600-065X.2006.00468.x.

Thermo Fisher Scientific. 2012. Fast Digestion of DNA Protocol. Retrieved from

http://2014.igem.org/wiki/images/6/68/Digestion_Protocol.pdf.

Thermo Fisher Scientific. 2015. One Shot® TOP10 Chemically Competent E. coli, 3: 6–9.

Product Information Sheet, MAN0001497: Rev A.0. Retrieved from

https://www.thermofisher.com/order/catalog/product/C404010.

Thomson DW, Bracken CP, Goodall GJ. 2011. Experimental strategies for microRNA target

identification. Nucleic Acids Res, 39(16): 6845–53. doi: 10.1093/nar/gkr330.

Thomson DW, Bracken CP, Szubert JM, Goodall GJ. 2013. On Measuring miRNAs after

Transient Transfection of Mimics or Antisense Inhibitors. PLoS ONE, 8(1): e55214. doi:

10.1371/journal.pone.0055214.

Tomkowicz B, Walsh E, Cotty A, Verona R, Sabins N, Kaplan F, Santulli-Marotto S, Chin

CN, Mooney J, Lingham RB, et al. 2015. TIM-3 suppresses anti-CD3/CD28-induced TCR

activation and IL-2 expression through the NFAT signaling pathway. PLoS ONE, 10(10):

e0140694. doi: 10.1371/journal.pone.0140694.

Turchinovich G, Pennington DJ. 2011. T cell receptor signalling in γδ cell development:

Strength isn’t everything. Trends Immunol, 32(12): 567–73. doi: 10.1016/j.it.2011.09.005.

Urruticoechea A, Alemany R, Balart J, Villanueva A, Viñals F, Capellá G. 2010. Recent

advances in cancer therapy: an overview. Curr Pharm Des, 16(1): 3-10. doi:

10.2174/138161210789941847.

Van de Walle I, Waegemans E, De Medts J, De Smet G, De Smedt M, Snauwaert S,

Vandekerckhove B, Kerre T, Leclercq G, Plum J, et al. 2013. Specific Notch receptor-ligand

interactions control human TCR-αβ/γδ development by inducing differential Notch signal

strength. J Exp Med, 210(4): 683–97. doi: 10.1084/jem.20121798.

Vanneman M, Dranoff G. 2012. Combining immunotherapy and targeted therapies in cancer

treatment. Nat Rev Cancer, 12(4): 237–51. doi:10.1038/nrc3237.

Page 86: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 86

Vantourout P, Hayday A. 2013. Six-of-the-best: unique contributions of γδ T cells to

immunology. Nat Rev Immunol, 13(2): 88–100. doi: 10.1038/nri3384.

Vermijlen D, Brouwer M, Donner C, Liesnard C, Tackoen M, Van Rysselberge M, Twité N,

Goldman M, Marchant A, Willems F. 2010. Human cytomegalovirus elicits fetal gammadelta

T cell responses in utero. J Exp Med, 207(4): 807–21. doi: 10.1084/jem.20090348.

Vicari AP, Mocci S, Openshaw P, O'Garra A, Zlotnik A. 1996. Mouse gamma delta

TCR+NK1.1

+ thymocytes specifically produce interleukin-4, are major histocompatibility

complex class I independent, and are developmentally related to alpha beta TCR+NK1.1

+

thymocytes. Eur J Immunol, 26(7): 1424–9. doi: 10.1002/eji.1830260704.

Wakita D, Sumida K, Iwakura Y, Nishikawa H, Ohkuri T, Chamoto K, Kitamura H,

Nishimura H. 2010. Tumor-infiltrating IL‑17‑producing γδ T cells support the progression of

tumor by promoting angiogenesis. Eur J Immunol, 40(7): 1927–37. doi:

10.1002/eji.200940157.

Wang B, Li S, Qi HH, Chowdhury D, Shi Y, Novina CD. 2009. Distinct passenger strand and

mRNA cleavage activities of human Argonaute proteins. Nat Struct Mol Biol, 16(12): 1259–

66. doi: 10.1038/nsmb.1712.

Wang D, Zhang Z, O'Loughlin E, Lee T, Houel S, O'Carroll D, Tarakhovsky A, Ahn NG, Yi

R. 2012. Quantitative functions of argonaute proteins in mammalian development. Genes

Dev, 26(7): 693–704. doi: 10.1101/gad.182758.111.

Wertheimer AM, Bennett MS, Park B, Uhrlaub JL, Martinez C, Pulko V, Currier NL,

Nikolich-Žugich D, Kaye J, Nikolich-Žugich J. 2014. Aging and cytomegalovirus (CMV)

infection differentially and jointly affect distinct circulating T cell subsets in humans. J

Immunol, 192(5): 2143-55. doi: 10.4049/jimmunol.1301721.

Wesch D, Hinz T, Kabelitz D. 1998. Analysis of the TCR Vgamma repertoire in healthy

donors and HIV-1-infected individuals. Int Immunol, 10(8): 1067–75. doi:

10.1093/intimm/10.8.1067.

Wightman B, Bürglin TR, Gatto J, Arasu P, Ruvkun G. 1991. Negative regulatory sequences

in the lin-14 3′-untranslated region are necessary to generate a temporal switch during

Caenorhabditis elegans development. Genes Dev, 5(10): 1813–24. doi:

10.1101/gad.5.10.1813.

Winter J, Jung S, Keller S, Gregory RI, Diederichs S. 2009. Many roads to maturity:

microRNA biogenesis pathways and their regulation. Nat Cell Biol, 11(3): 228–34. doi:

10.1038/ncb0309-228.

Wu P, Wu D, Ni C, Ye J, Chen W, Hu G, Wang Z, Wang C, Zhang Z, Xia W, et al. 2014.

γδT17 cells promote the accumulation and expansion of myeloid-derived suppressor cells in

human colorectal cancer. Immunity, 40(5), 785–800. doi: 10.1016/j.immuni.2014.03.013.

X-tremeGENE Protocols. 2013. Easy DNA Transfection, Roche: 1-28.

Xiang Z, Liu Y, Zheng J, Liu M, Lv A, Gao Y, Hu H, Lam KT, Chan GC, Yang Y, et al.

2014. Targeted Activation of Human Vγ9Vδ2-T Cells Controls Epstein-Barr Virus-Induced B

Cell Lymphoproliferative Disease. Cancer Cell, 26(4): 565–76. doi:

10.1016/j.ccr.2014.07.026.

Xiong N, Raulet DH. 2007. Development and selection of gamma-delta T cells. Immunol Rev,

215: 15–31. doi: 10.1111/j.1600-065X.2006.00478.x.

Xu B, Pizarro JC, Holmes MA, McBeth C, Groh V, Spies T, Strong RK. 2011. Crystal

Page 87: Targeting MicroRNAs for Modulation of the Anti-Tumorrepositorio.ul.pt/bitstream/10451/27946/1/TM_Gisela... · 2017. 6. 3. · FFULisboa Targeting MicroRNAs for Modulation of the Anti-Tumor

FFULisboa

Targeting MicroRNAs for Modulation of the Anti-Tumor Human γδ T Cell Differentiation 87

structure of a gamma-delta T-cell receptor specific for the human MHC class I homolog

MICA. Proc Natl Acad Sci U S A, 108(6): 2414–9. doi: 10.1073/pnas.1015433108.

Yan ZX, Zheng Z, Xue W, Zhao MZ, Fei XC, Wu LL, Huang LM, Leboeuf C, Janin A,

Wang L, et al. 2015. MicroRNA181a Is overexpressed in t-cell leukemia/lymphoma and

related to chemoresistance. Biomed Res Int, 2015: 197241. doi: 10.1155/2015/197241.

Yu T, Liu L, Li J, Yan M, Lin H, Liu Y, Chu D, Tu H, Gu A, Yao M. 2015. MiRNA-10a is

upregulated in NSCLC and may promote cancer by targeting PTEN. Oncotarget, 6(30):

30239–50. doi: 10.18632/oncotarget.4972.

Yu T, Zuo QF, Gong L, Wang LN, Zou QM, Xiao B. 2016. MicroRNA-491 regulates the

proliferation and apoptosis of CD8(+)

T cells. Sci Reps, 6(Aug): 30923. doi:

10.1038/srep30923.

Yun S, Lee SU, Kim JM, Lee HJ, Song HY, Kim YK, Jung H, Park YJ, Yoon SR, Oh SR, et

al. 2014. Integrated mRNA-microRNA profiling of human NK cell differentiation identifies

MiR-583 as a negative regulator of IL2Rγ expression. PLoS ONE, 9(10): e108913. doi:

10.1371/journal.pone.0108913.

Zarin P, Chen EL, In TS, Anderson MK, Zúñiga-Pflücker JC. 2015. Gamma delta T-cell

differentiation and effector function programming, TCR signal strength, when and how

much? Cell Immunol, 296(1): 70–5. doi: 10.1016/j.cellimm.2015.03.007.

Zhao E, Maj T, Kryczek I, Li W, Wu K, Zhao L, Wei S, Crespo J, Wan S, Vatan L, et al.

2016. Cancer mediates effector T cell dysfunction by targeting microRNAs and EZH2 via

glycolysis restriction. Nat Immunol, 17(1): 95-103. doi: 10.1038/ni.3313.

Zhou J. 2014. Advances and Prospects in Cancer Immunotherapy. New J Sci, 2014: 1–13. doi:

10.1155/2014/745808.

Zhou L, Park JJ, Zheng Q, Dong Z, Mi Q. 2011. MicroRNAs are key regulators controlling

iNKT and regulatory T-cell development and function. Cell Mol Immunol, 8(5): 380–7. doi:

10.1038/cmi.2011.27.

Zhou W, Shi G, Zhang Q, Wu Q, Li B, Zhang Z. 2014. MicroRNA-20b promotes cell growth

of breast cancer cells partly via targeting phosphatase and tensin homologue (PTEN). Cell

Biosci, 4(1): 62. doi: 10.1186/2045-3701-4-62.