Laboratory Medicine Program

“Next-Gen” Pathology: Integrating New Technologies

Sylvia L. Asa, MD, PhD

Pathologist-in-Chief Medical Director

Laboratory Medicine Program University Health Network

Laboratory Medicine Program

What Is Pathology?

• Pathology, from the greek πάθος, pathos, “feeling, suffering” and λογία, logia “study of”

• the study and diagnosis of disease through examination of organs, tissues, bodily fluids, and whole bodies

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The Origins of Pathology

• The Autopsy • Dates back to ancient Egypt and Greece • The tool of the Physician-Scientist

– To identify the cause of death – To explain signs and symptoms of disease

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The First Clinical Applications

• Surgical pathology by surgeons • Laboratory hematology by hematologists • Biochemistry in nephrology and endocrinology • Microbiology in infectious diseases

Louis DN and Young RH: Keen Minds to Explore

the Dark Continents of Disease 2011

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What Has Pathology Become? • Laboratory-based clinical testing

– Focus on QA/QC/GLP

• Microscope-based anatomical pathology • Custodianship of patient samples on behalf of

patient • Representative of patient in Quality of Care

events (M&M rounds) • Minimal or no patient contact

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The Pathology Diagnosis

• The pathological diagnosis is the gold standard that indicates the presence or absence of disease, the type of disease, and its classification

• Therapeutic decisions are based on the pathology diagnosis – a misdiagnosis can result in unnecessary, harmful and

aggressive therapy or inadequate treatment

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BREAST

• Atypia on breast core needle biopsies: reproducibility and significance.

• The impact of inter-observer variation in pathological assessment of node-negative breast cancer on clinical risk assessment and patient selection for adjuvant systemic treatment.

• Inter-observer reproducibility of HER2 immunohistochemical assessment and concordance with fluorescent in situ hybridization (FISH): pathologist assessment compared to quantitative image analysis

Morphologic Pathology is an Interpretive Discipline

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Morphologic Pathology is an Interpretive Discipline

GENITOURINARY

• Interobserver variability between expert urologic pathologists for extraprostatic extension and surgical margin status in radical prostatectomy specimens

• Intraobserver and interobserver variability of fuhrman and modified fuhrman grading systems for conventional renal cell carcinoma

• Intra- and interobserver reproducibility of interpretation of immunohistochemical stains of prostate cancer

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What Does This Mean for Patients?

• Is the diagnosis right? • Is the treatment right? • Is the prognosis right? • Was the trial right? • Are the data reliable?

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Pathology 2000-2010

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Challenges for 2020

• Volume – aging population – higher sensitivity for early disease

• Demand – sophisticated knowledgeable population – Culture of “instant gratification”

• New technologies – genomics – proteomics – informatics – robotics ‘tissue soup’ instead of tissue

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The Challenge for 2020

• Faster • Better

– Higher quality – Personalized

• Cheaper

• Innovative

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The New Paradigm: Faster

• Pathology must be faster – “Same Day” diagnosis

– Automation

– 24/7 labs

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The New Paradigm: Faster • Speech-recognition integrated with LIS means instant reporting without the need for dictatyping

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• Synoptic Reporting – Complete

• Standardized formats (CAP checklists) – Adaptable and flexible

• No more verbose reports that no one reads! – Database technology

• Statistics collection • Administrative tracking • QA monitoring • Academic data mining

The New Paradigm: Better

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What Is “Correct”? • Objective classification by

– mRNA expression – DNA sequencing – Response to therapy

The New Paradigm: Better

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Technologic Advances: “omics”

HT-Sequencing DNA

Microarray Expression Profiling

RNA

Mass Spectrometry Protein

Metabolomics

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The New Paradigm: Better • Subspecialty Pathology

– All cases reported by a pathologist with expertise in the specific subspecialty required

– Benefits: • Better quality and faster patient care • Fiscal responsibility: 1 pathologist per case • Pathologist satisfaction – enhanced academic excellence

– Challenges: • Requirement for appropriate staffing in all areas and

redundancy

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Digital Pathology • Whole slide imaging

• A disruptive enabling technology

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Digital Pathology Enables

• Remote access

• Multiple viewers

• Immediate access to the right pathologist at the right time

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Computer-Assisted Diagnostics

Digital Pathology Enables

• Automated analysis of: – Measurement – Mitoses – Ki67 LI – Other IHC

• intensity • distribution

– Her2 FISH – Hematology

• Cellavision

• QA of technical quality – Section thickness – Stain quality

? Need for Westgard rules in AP?

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• Novel approaches to address issues of inter- and intra-observer variability

GENIE© (GENetic Imagery Exploration) is a GP software system that builds automatic feature extraction algorithms for image analysis, utilizing spectral and spatial signatures of the images

“GENIE© can recognize benign and malignant areas in H&E-stained slides and does not have intra- or inter-observer variation”

Digital Pathology Enables

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A Disruptive Technology

In a time of drastic change it is the learners who inherit

the future. The learned usually find themselves

equipped to live in a world that no longer exists.

Eric Hoffer

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Requirements for Full Adoption

• Workflow integration – From the lab to the pathologist

• LIS integration – Barcodes – Slide tracking and retrieval

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Critical Requirement

$$$ Business Case • Reduced microscope budget • Analysis of time spent

– Finding slides – Matching slides to case – Shipping slides – Retrieving slides for post-hoc review

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Informatics: The LIS

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• LIS as part of the e-chart

• LIS e-orders and processes

• Specimen tracking and management

• Integration of lab data from all disciplines into a consolidated report

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• Patient-Centred Care

• Individualized diagnostics

• Targeted therapies

All based on “omics”

Will “omics” replace pathology?

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The New Paradigm: Personalized

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Targeted Therapies • Hormone receptors in breast cancer • Herceptin

DP does it better ……

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EGF-R Rx in Lung and Colon Cancer

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And When It Doesn’t Work?

• K-ras mutations in Colon Cancer

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What About Next-Gen Sequencing? The Genome Institute at Washington University: Software • BLASTaid – A simple interface for byte indexing a WU-BLAST multi-part report for faster access. • BreakDancer – WashU structural variant (SV) detection algorithm for paired-end data. • CMDS – WashU algorithm for identifying recurrent DNA copy number changes. • cnvHMM – WashU copy number variant (CNV) detection algorithm for Illumina/Solexa data. • ComComb – WashU algorithm for identifying common combinations of mutations across tumor types. • EXOR – Filters mutually exclusive alignment events and defines a position-specific reciprocal best alignment set. • FASTAParse – A light-weight parsing module for handling FASTA formatted sequence within larger perl applications. • Gen Bell – Calculates Bell’s polynomials. • GSTAT – WashU analysis tools • Miropeats – Displays DNA sequence similarity information graphically. • MuSiC – The MuSiC suite is a set of tools aimed at determining the significance of somatic mutations discovered within a given cohort

of cancer samples, incorporating the cohort's alignment data, variant lists and any relevant clinical data. • Overgo Maker – Output overgo sequences ready for ordering from a fasta input file. • Pairoscope – WashU tool for visualizing SVs from Illumina/Solexa paired-end reads. • PathScan – WashU algorithm that assesses significance of gene groups by Boolean tagging each gene as mutated or not mutated. • Pathway Tools – WashU annotation tools. • PolyScan – Automatic indel and SNP detection to the analysis of human re-sequencing data. • R Functions for Correlation Analysis – Some of the functions we use with R. • Semblance – Assess a genome assembly by comparison to finished clones. • SomaticSniper – WashU somatic SNV detection algorithm for whole genome resequencing data. • SWT – WashU Sliding Window Tool for detecting copy number variants from Illumina/Solexa data. • TIGRA_SV – Tigra_sv is a program that conducts targeted local assembly of structural variation (SV) using the iterative graph routing

assembly (TIGRA) algorithm. • UR – A Class Framework and Object/ Relational Mapper (ORM) for Perl. • VarScan – Somatic and germline variant detection for massively parallel sequencing

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The Future of Pathology?

$15.00 each $1000.00 each

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Epigenetic Control: Can it Override the Genotype?

N Engl J Med. 2007 Feb 15;356(7):731-3

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BRAF Mutations in Melanocytes

• ̃80% of benign nevi (? early event) • 50% of cutaneous melanoma

– Both superficial spreading and nodular – Non-overlapping with NRAS mutations

• Epidemiologic evidence of UV-induction – Not supported by T→A transversion – ? Secondary effect of UV damage e.g. ROS

• Not in acral melanoma (Kit mutations) • Not in ocular melanoma (GNAQ or GNA11) • Not in mucosal melanoma (Kit, ? CDKN2A)

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BRAF Inhibition in Melanoma

• Sorafenib – Failed in phase III clinical trial

• Vemurafenib – Success in pivotal phase III study (BRIM-3)

• OS 84% cf 64% with dacarbazine • Estimated median PFS 5.3 mo cf 1.6 mo on dacarbazine

– licensed by the US FDA as Zelboraf for the treatment of metastatic melanoma in August 2011

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• Most common genetic event in thyroid cancer

• Diagnostic marker of PTC • Genotype-phenotype correlations

– BRAFV600E in classical variant PTC (40-50%) – BRAFK601E in FVPTC (rare) – VK600-1E deletion (BRAFVK600-1E) in solid variant (single case)

• Prognostic significance controversial

BRAF Mutation in Thyroid Cancer

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BRAF Kinase Inhibition Arrests Thyroid Cancer Growth In Vivo

Salvatore G et al, Clin Cancer Res 2006;12:1623-9

However ………

Clinical trials have

failed to show

effectiveness of

BRAF inhibitors

in thyroid cancer

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The Importance of Informatics

• Not just to collect data • Not just to analyze data • Not just to report data

The Importance of Data Integration

• To collect, analyze and report integrated data

in the clinical context

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What Is Anatomical Pathology?

• Integrative morphology-based interpretation

Gross Morphology

Chemistry on a glass slide

Immunoassay on a glass slide

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What About Academia?

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Garbage In – Garbage Out

• We have the technical capacity to produce low quality data from low quality analytes with unprecedented efficiency

• We arrive at the wrong answer with unprecedented speed

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The New Paradigm: Innovative • Pathology / Laboratory Medicine

– critical players in ensuring highest quality translational research:

• The right specimen, the right test, the right interpretation

• Biobanking in Translational Research – Value is in technical & diagnostic excellence of specimens

Challenge: • Balance legal, regulatory & institutional requirements

for Diagnostic Tissue vs Biobanking of Research Tissue Cheung, Martin & Asa, CMAJ 2013;185(2):135-9

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Clinical Laboratory

Patient X

Diagnostic stained slides

Diagnostic paraffin blocks

Patient X

Diagnostic frozen

material

Research Biobank

Research frozen

material

Research paraffin blocks

Diagnostic wet tissue(post-sampling)

Diagnostic wet tissue(pre-sampling)

Archived diagnostic tissue

Excess diagnostic tissue

Research stained slides

Weeks

Years

Post-retention excess diagnostic tissue

Research wet tissue from research-only

procedure

Patient X

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• To provide the right diagnosis

• To provide the right material

• To provide the right leads

• To provide the right experiments

• To evaluate the consequences of genetic manipulation

The Expanding Role of Lab Medicine

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Where Are We Heading? • Predictive genetics/epigenetics will define

individual risk and prognosis

• Targeted prevention

• Monitoring for onset with multimodal biomarkers

• Targeted therapies based on host genetics and epigenetics

• Signatures of stage-specific progression

• Mechanisms of escape

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The Uncontestable Trends • Clinicians want increasingly detailed, reliable

and relevant information from specimen analyses that can be translated into optimal treatments

• Pathology must re-educate and re-invent itself if it is to maintain the central role it plays as the ultimate arbiter of treatment

“As is your pathology, so goes your clinical care”

Sir William Osler

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The New Paradigm • Pathology labs must be faster and better

– QA is the sine qua non

• Pathology reports must be comprehensive – Incorporation of molecular, biochemical and other data

is critical to the consultative value of the report

• Pathology data must be synoptic and database-oriented

• Pathology must be innovative

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The Virtual Autopsy

Laboratory Medicine Program After “The Anatomy Lecture of Dr. Nicolaes Tulp” – Rembrandt, 1632

(Courtesy of Dr. Carlos Cordón, New York, USA)

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2020 Vision

• Large automated core laboratories • Electronic support for specimen tracking

and handling, QMS • Highly subspecialized teams providing a

matrix of subject and technical expertise – Biochemistry - Microbiology – Hematology, Transfusion & Hematopathology – Subspecialty Anatomical Pathology – HLA - Molecular/Genetics

“Blurring the lines between AP and CP”

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Critical Elements

• Specimen tracking

• Specimen ID

What next?

• Patient ID

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• Specimen tracking • Workload tracking

and personnel • Supplies and

equipment • QA processes

“………sophisticated refrigerators and Radio Frequency Identification (RFID) technology will be able to monitor the products household members use, create shopping lists, and even communicate with other networked devices to arrange deliveries”

Laboratory Management in the Electronic Era

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Comprehensive integrated reports including: • Incorporation and integration of clinical,

radiologic, and biochemical data • Germline SNPs and mutations

– predisposition, metabolic profiles

• Tumor or tissue somatic events – morphologic, immunohistochemical, flow

cytometric, cytogenetic and molecular data

• Immunologic responses

Laboratory Data Management in the “Next-Gen” Era

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Digital radiology

Digital cardiology

Family and medical history Electronic medical record

PATHOLOGY: the centre of Personalized

Cancer Medicine

Endoscopy

2020 Pathology

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2020 Pathologist

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The Future of Pathology

The best way to predict the future is to invent it

Alan Kay