Impacto de la patología digital

en NGS

Federico Rojo Fundación Jiménez Díaz

Clinical oncology Pathological oncology Molecular oncology Precision oncology

Today

Evolution from Clinical to Precision Oncology

NCCN 2017 Guideline Biomarkers in Solid Tumors Cancer Type Targetable Alterations

Agnostic NTRK MSI (or MMR IHC)

NSCLC EGFR mt BRAF mt ERBB2 mt ALK fusion ROS1 fusion RET fusion MET amp and exon

14 skipping mt PD-L1 expression

Colorectal KRAS mt

exons 2,3,4 NRAS mt

exons 2,3,4 BRAF mt MSI (or MMR IHC) if < 70 or older if relative with CRC < 50 or 2 relatives with CRC

Breast ERBB2

(HER2) amp

BRCA1/2 germline if: • early onset < 45 • triple negative breast cancer < 60 • male breast cancer at any age • dx at any age & family hx

ER, PR exp Proliferation

(Genomic signature)

Gastric & Gastro-esophageal

ERBB2 (HER2) amp

Melanoma BRAF mt KIT mt

GIST KIT mt PDGFRA mt BRAF mt

Ovarian BRCA1/2 germline and somatic

Evolution from Clinical to Precision Oncology

FISH: fluorescence in situ hybridisation; IHC: immunohistochemistry; NGS: next-generation sequencing; PCR: polymerase chain reaction; WES: whole exome sequencing; WGS: whole genome sequencing

Netto, G.J., et al. (2003) Proc Bayl Univ Med Cent. 16:379-83. de Matos, L.L., et al. (2010) Biomark Insights. 5:9-20. Dong, L., et al. (2015) Curr Genomics. 16:253-63.

Breathtaking progress in clinical management Im

pact

on

clin

ical

man

ag

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en

t

Evolution of molecular profiling methodology

IHC

PCR

Hybrid

capture

NGS-based

hotspot testing

Sanger

Traditional molecular testing approaches

First-generation sequencing

Next-generation sequencing

FISH

WES / WGS Impact will increase as

methods become more rapid and less costly, utlimately being used to generate

comprehensive genomic profiles

The evolution of molecular testing

Oncomine Comprehensive Assay v3 Empower your oncology research with proven Ion Torrent technologyThe Ion Torrent™ Oncomine™ Comprehensive Assay v3 is a member of the family of Oncomine™ assays for clinical cancer research. Oncomine assays are next-generation sequencing (NGS)-based multiple-biomarker assays, which have been adopted by leading cancer institutions around the world, used to profile thousands of samples in different translational and clinical research projects, and have consistently delivered reliable results.

The new Oncomine Comprehensive Assay v3 • Content based on latest advances in clinical oncology

research and also enriched for known childhood cancer targets

• Based on robust Ion AmpliSeq™ technology, the assay requires only 10 ng of DNA or RNA per pool, enabling analysis of even small and challenging FFPE samples

• Detects relevant SNVs, CNVs, gene fusions, and indels from 161 unique cancer driver genes in one streamlined workflow

• Optimized and verified for the Ion Chef™ and Ion S5™ Systems with the Ion 540™ Chip, enabling full automation including automated library prep on the Ion Chef System

New: Oncomine™

Comprehensive Assay v3

“The requirement of a lower DNA input for the Oncomine assay is a significant advantage when primary samples are becoming increasingly limited.”

John Bartlett, PhD Director of Transformative Pathology Platform,

Ontario Institute for Cancer Research

The FJD experience:

Clinical impact of NGS analysis in cancer

The FJD experience:

Oncomine Comprehensive Assay

The FJD experience:

Clinical impact of NGS analysis in cancer

0

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Stomach Colorectal Pancreas Hepatobiliary Lung Breast Others

Mea

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Tissue of origin and DNA isolation efficiency: FJD experience

Diagnostic biopsy

Surgical specimen

Proportion of non informatives

Tumor

<30% tumor 54.2

>30% tumor 13.4

Nanodrop

<20ng/ul 50.0

>20ng/ul 11.9

Qubit

<5ng/ul 51.5

>5ng/ul 11.2

QPCR

>6 29.4

4-6 30.8

<4 11.1

Site

FJD 16.0

Outside 25.9

The FJD experience: AmpliSeq NGS

Sanger sensitivity: 20% minimum mutant alleles NGS: 5% minimum mutant alleles

Mutations are present in all tumor cells (clonal) or un a subpopulation of cells (subclonal) 30% of tumor content is necessary

The FJD experience:

Tumor purity limits sensitivity for molecular assays

Tumor cells

Normal cells

Invasive

In situ carcinoma

Normal breast

Tumor purity limits sensitivity for molecular assays

9 pathologists, 47 H&E sections categories 0-5, 6-10, 11-20, 21-30…% 38% of estimations were not accurate

Concordance in evaluation of percentage of tumor cells in tissue sections

10 H&E digital images 20% overestimation of tumor

content in samples in 5.4% of participants

Overestimation of percentage of tumor cells in tissue sections: CAP prospective trial

Dufraing, K et al. J Mol Diagn 2017

Survey in European laboratories for tumor cell content and overestimation in evaluation

43 pathologists determined neoplastic cell content for DNA extraction Consideration of immune cells (N=37), tumor cell distribution (N=33), desmoplastic stroma (N=30), necrosis (N=29), and mucus (N=23) The selected area was highly variable The average difference between the highest and lowest estimation for all samples ranged 51% - 78% The number of overestimations was alarmingly high in samples containing less than 30% tumor cells

60 participants 10 H&E vitual slides 20 H&E conventional slides Percentage of tumor cells: proportion of cells in total tissue section Area of tumor: surface of tissue section occupied by tumor Confusing factors: - Dense lymphocytic infiltrates - Scattered lymphocytic aggregates - Mucinous stroma - Dense stroma enriched in CAFs - Dysplastic or in situ associated lesions - Normal epithelial components

Percentage of tumor cells vs area of tissue occupied by tumor

¿Podemos correlacionar la frecuencia de variantes con el contenido de tumor

en la muestra?

AV

F*

Percentage of tumor cells

The FJD experience:

Correlation* between Allelic Variant Frequency and tumor content in tissue section

*excluding germinal variants

Proyecto de Patología Digital Grupo Quirón

The FJD experience:

Correlation between Allelic Variant Frequency and tumor content in tissue section

The FJD experience:

Correlation* between Allelic Variant Frequency and tumor content in tissue section

*excluding germinal variants

AV

F*

Tumor area mm2

The FJD experience:

Correlation* between Allelic Variant Frequency and tumor content in tissue section

*excluding germinal variants

AV

F*

Tumor area mm2

CN, area The FJD experience:

Correlation between Copy Number Variation and tumor content in tissue section

CN

V

Tumor area mm2 C

NV

Percentage of tumor cells

CN, area The FJD experience:

Correlation between Fusion Reads and tumor content in tissue section

Nu

mb

er

of

read

s

Tumor area mm2 Percentage of tumor cells N

um

be

r o

f re

ads

Mujer de 34 años con clínica de sangrado Histeroscopia: lesión polipoide en transición, con infiltración y rigidez de pared, que se biopsia

Diagnóstico: Fragmentos superficiales de adenocarcinoma con rasgos intermedios endometrioide-endocervical, grado 1 (FIGO)(grado arquitectural 1- grado nuclear 1) Histerectomía con doble anexectomía, sin disección de parametrios

Inmunofenotipo: p53: wild type. Vimentina: positivo. Receptores de estrogenos: +++, de distribución irregular Receptores de progesterona: - p16: heterogéneo, de intensidad variable, discontinuo, focal CK7: positivo parcheado. Ck20: negativo. PTEN: heterogéneo, no interpretable Ki67: 40% Estudio IHQ (MLH1, PMS2L, MSH6, MSH2): Expresión MMR de DNA conservada

Oncomine Comprehensive Assay: Variantes patogénicas: PTEN: exón 5, NM_000314.6: c.389G>A, p.Arg130Gln (Frecuencia: 28.5%) Variantes potencialmente patogénicas: CTNNB1: exón 3, NM_001904.3: c.110C>A, p.Ser37Tyr (Frecuencia: 31.6%)

PTEN

b-CATENINA

b-CATENINA

b-CATENINA

Mujer de 53 años con nódulo palpable en autoexploración en CSE de MD BAG del nódulo

Diagnóstico: Carcinoma infiltrante de mama, NOS (Ductal), grado II Fenotipo: Triple negativo Proliferación Ki67 60% Histerectomía con doble anexectomía, sin disección de parametrios

Estudio de extensión: Nódulos múltiples en LII y LID pulmonares, y LOE hepática BAG con control radiológico de lesión en LLI y hepática

Cromogranina TTF1 GATA3

TP53: exón 5, 480_481delGGinsTT SMARCA4: exón 28, c.3895G>A, p.Asp1299Asn

EGFR: Amplificación = 6,83 KRAS: Amplificación = 30,83

TERT: Amplificación = 5,42

NOTCH1: exón 25, p.Asp1475Asn

MUTACIONES COMUNES

PULMÓN

DISEMINACIÓN METASTÁSICA

MAMA HÍGADO

Oncomine, mutaciones y FA

356 FFPE breast cancer specimens Cancer panel of 450 genes by NGS, aimed to detect CNV Success in good quality libraries and CNV detection were dependent of tumor

content but not of DNA amount and quality and age of fixed tissues Limit of confidence for CNV is 30% of tumor area

CN, area The FJD experience:

Analysis of CNV by NGS on FFPE breast cancer samples

672 regions

0.0e+00 5.0e+07 1.0e+08 1.5e+08 2.0e+08 2.5e+08

22212019181716151413121110987654321

1 2 3 4 1 2 3 4

Chr#

X

Base#

0.0

0.2

0.4

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1.0

-5

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-3

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-1

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log 2

ratio

prob

abili

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chromosomes

X6422

Plot resolution: 10%

1 2 3 4 5 7 9 11 13 16 20

MAD = 026k x 100 kbp

GenInst = 0.01

Instability Genomic

Instability Genomic

Freq

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0.0 0.1 0.2 0.3 0.4

05

1015

2025

• Calculation by patient based on tumor area • Sum of segmented means (logRatio) across the genome, normalized by the number of CNAs • “Percentage” of altered genome • Includes gains and losses

CN, area Neoadjuvant treatment (CNV) effect on genomic instability in early breast cancer GEICAM/2006-03 and GEICAM/2006-14 trials

Comparación de GI en la población pre-tratamiento

por subtipos

P-Value = 0.03 P-Value = 0.0034

Comparación de GI en tumores pareados pre- y post-ttm - all subtypes

Comparación de GI en tumores pareados pre- y post-ttm

Pre Post

CN, area Neoadjuvant treatment (CNV) effect on genomic instability in early breast cancer GEICAM/2006-03 and GEICAM/2006-14 trials

Prospective Clinical Trial without drugs, to determine the HER2 status in the metastasis of patients with primary breast cancer HER2. 236 patients have been recruited and 32 Sites have been taking part in this Clinical Trial. Primary Objective: - To determine prospectively the probability of HER2 conversion between the different subtypes of primary breast cancer and their metastasis. Secondary Objective: - To determine the probability of changes in ER and PR between different subtypes of primary breast cancer and their metastasis. - Evaluate HER2 conversion rate compared to previously received treatment. - Compare DFS and OS of patients with or without conversion of HER2 and ER/PR. - Compare RR and TTP for subsequent anti-tumor treatment of patients with or without conversion of HER2. - Check if there is any change in the molecular subtypes between primary tumors and metastases in patients with HER2 conversion.

GEICAM/2009-03_ConvertHER trial: analysis of clinical phenotypes in paired primary and metastatic breast tumors

Temporal intratumor heterogeneity: Consequences in clinical setting

Mutation

Copy number gain

Copy number loss

CONVERSION NON CONVERSION HR-/HER2+

HR+/HER2-

HR+/HER2+

TNBC

Temporal intratumor heterogeneity: Consequences in molecular alterations

Distribution of mutations of conserved and non-conserved clonal status across concordant

and discordant tumors.

Lluch, A et al. Clin Cancer Res (submitted)

Metastasis

Primary

Temporal intratumor heterogeneity: Consequences in molecular alterations

Clinical subtype Intrinsic subtype A B

Clinical subtype Intrinsic subtype C D

Lluch, A et al. Clin Cancer Res (submitted)

TissueMark1, our validated approach for tumor sufficiency estimation

TissueMark is not intended for diagnostic, monitoring or therapeutic purposes or in any other manner for regular medical practice 1

#4 Customizable workflow

#1 Accurate & reliable

#5 Compliance

#2 Ultra high throughput

#3 Intuitive & Integrated

Tailored workflow to suit routine and research needs

Accurate ROI identification and cellularity guidance powered by deep learning

Designed using principles of GDPR and HIPAA

Rapid algorithm execution in under 60 seconds

Easy case and slide organization

TissueMark1 4.0, our validated approach for tumor sufficiency estimation

Improve the quality of molecular tests with accurate ROI and cellularity guidance

High throughput, intuitive workflow to save valuable time of lab personnel

1 TissueMark is not intended for diagnostic, monitoring or therapeutic purposes or in any other manner for regular medical practice. PathXL is the legal manufacturer and is a Philips company

2

1

Oncotarget27938www.impactjournals.com/oncotarget

w w w .im pact journals.com / oncotarget / Oncotarget , Vol. 6 , No. 2 9

Automated tumor analysis for molecular profiling in lung cancer

Peter W . Ham ilton 1 ,4 ,* Yinhai W ang1 ,4 ,* , Clinton Boyd2 , Jacqueline A. Jam es1 , Maurice

B. Loughrey3 ,1 , Joseph P. Hougton 3 , David P. Boyle 1 , Paul Kelly 3 , Perry Maxw ell1 ,

David McCleary3 , Jam es Diam ond3 , Darragh G. McArt 1 , Jonathon Tunstall3 ,

Peter Bankhead1 , Manuel Salto- Tellez1 ,3

1Centre for Cancer Research and Cell Biology, Queen’s University Belfast, Belfast, UK

2Department of Cellular and Molecular Pathology, Antrim Area Hospital, Antrim, UK

3Institute of Pathology, Royal Victoria Hospital, Belfast, UK

4PathXL Ltd, Northern Ireland Science Park, Belfast, UK

*These authors have contributed equally to this work

Correspondence to:

Peter W. Hamilton, e- m ail: p.hamilton@qub.ac.uk

Keywords: molec ula r pa thology, manua l mac rod issec tion, perc entage tumor, image ana lysis, d ig ita l pa thology

Received: April 09, 2015 Accepted: July 24, 2015 Published: August 03, 2015

ABSTRACT

The discovery and clinical application of molecular biomarkers in solid tumors,

increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent

molecular profiling. This in turn requires the pathological review of haematoxylin

& eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by

visually estimating the percentage tumor nuclei and tumor annotation for manual

macrodissection. I n this study on NSCLC, we demonstrate considerable variation in tumor

nuclei percentage between pathologists, potentially undermining the precision of NSCLC

molecular evaluation and emphasising the need for quantitative tumor evaluation. We

subsequently describe the development and validation of a system called TissueMark for

automated tumor annotation and percentage tumor nuclei measurement in NSCLC using

computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated

tumor annotation of cases using Tissuemark, strong concordance with manually drawn

boundaries and identical EGFR mutational status, following manual macrodissection

from the image analysis generated tumor boundaries. Automated analysis of cell counts

for % tumor measurements by Tissuemark showed reduced variability and significant

correlation ( p < 0.001) with benchmark tumor cell counts. This study demonstrates a

robust image analysis technology that can facilitate the automated quantitative analysis

of t issue sam ples for m olecular profiling in discovery and diagnostics.

INTRODUCTION

Personalised medicine aims to stratify patients’ cancers into new molecular subtypes who can benefit from individualised therapy [1–3]. The translation and validation of new molecular biomarkers in cancer relies heavily on molecular pathology and the investigation of specific

mutations or other genomic anomalies in nucleic

acids extracted from formalin fixe d, paraffin embedded (FFPE) human tissues.

Extracting DNA and RNA from tumor cells in the context of FFPE samples is not straightforward. Most tissues containing tumor also contain a mixture

of cell types such as non-neoplastic epithelial cells, mesenchymal tissue, inflammatory cells and acellular material such as mucin which has an influence on subsequent processes including nucleic acid isolation, PCR amplification and next generation sequencing [4]. Therefore in most studies, it is important to determine the tumor nuclei content by visually estimating the percentage tumor cells and where that falls below a certain threshold, to enrich the tumor cell contents of the sample by manual macrodissection (Figure 1), to a) make the sample suitable depending on the sensitivity of the test, and b) make the molecular analysis as broad as possible to be able to identify “clonal disease”.

H&E slide at 0.5x with heat map indicating tumor density

H&E slide at 14.5x without heat map

H&E slide at 14.5x with heat map indicating tumor density

H&E slide at 20x with cell map indicating tumor/ non tumor

classification