The changing face of cancer diagnosis

George VassiliouNovember 2011

Overview

• Today’s cancer diagnostic lab• The era of cancer genomics• Novel diagnostic applications• Introducing genomics to cancer diagnosis

• Today’s cancer diagnostic lab• The era of cancer genomics• Novel diagnostic applications• Introducing genomics to cancer diagnosis

Overview

The light microscope remains the central cancer diagnostic tool for 400 years

Zacharias and Hans Jansen(ca 1595)

Modern microscope(ca 1995)

Today’s cancer diagnostic lab

Cellular PhenotypingMicroscopy (histology/cytology)ImmunohistochemistryFlow Cytometry

Genetic testsCytogeneticsMolecular Genetics

Genotyping for specific mutations (PCR/RT-PCR)Minimal Residual Disease monitoring(CGH and SNP/LOH genotyping)(Gene Expression Profiling)

Haemato-oncology lab

Microscopy Immunophenotyping Cytogenetics Molecular Genetics

Sample

Integrated report

MICROSCOPY: >80% undifferentiated blastsMorphology of acute lymphoblastic leukaemiaEosinophils, basophils and small megakaryocytes suggest blast phase of chronic

myeloid leukaemia

IMMUNOPHENOTYPE: Blast cells are CD10, CD19, CD79a, CD34, HLA-DR, TdT positive. Weak CD13.They do not express CD33 or myeloperoxidase. DNA index is 1.0Phenotype of B lymphoblastic leukaemia or B lymphoblastic transformation of CML

CYTOGENETICS: Karyotype: 46,XY,t(9;22)(q34;q11) in 10 of 10 metaphasesFISH: BCR/ABL 92% positive

MOLECULAR GENETICS: BCR-ABL fusion transcript type: p210 e13a2 by RT-PCR

OVERALL CONCLUSION: B lymphoblastic blast crisis of chronic myeloid leukaemia

CytologyHistology

Immunohistochemistry

Diagnostic panels KaryotypingFISH

Mutational screeningRT-PCR

qPCR (MRD)

Diagnostic CGH/SNP genotyping

n=241

Diagnostic gene expression profiling

MammaPrint – 70 gene signature (NKI)Lymph node positive breast cancer

CR-UK stratified medicines initiativeTumour type Gene Mutation Drug

Colorectal KRAS Codons 12, 13, 61, 146 Cetuximab/Panitumumab

BRAF V600E/D/K/R/M Sorafenib/Cetuximab

TP53 Exons 2- 11‐

PI3KCA Exons 9 and 20 PI3Kinase inhibitors

UGT1A1 UGT1A1*28 Irinotecan toxicity

Breast PI3KCA Exons 9 and 20

TP53 Exons 2- 11‐

PTEN LOH/mutation hotspots mTOR inhibitors

CYP2D6 5 SNPs Response to tamoxifen

Prostate PTEN LOH/mutation hotspots mTOR inhibitors

TMPRSS- ERG‐ Junction fragment PCR

TLR4 2 SNPs

Lung EGFR Exons 18-21 Erlotinib/gefitinib

EML4- ALK‐ Fusion product PF02341066 ALK/c-Met inhibitor

XRCC2 5 SNPs Response to platinum agents

ERCC1 mRNA expression

RRMI mRNA expression

Ovary PTEN LOH/mutation hotspots mTOR inhibitors

PI3KCA Exons 9 & 20

BRAF V600E/D/K/R/M Sorafenib/Braf inhibitors

Melanoma BRAF V600E/D/K/R/M Sorafenib/Braf inhibitors

CKIT Exons 11,13,17

• Today’s cancer diagnostic lab• The era of cancer genomics• Novel diagnostic applications• Introducing genomics to cancer diagnosis

Overview

Advances in DNA sequencing technologies

102

104

106

108

1010

1012

1014

1016

Outputkbp / run

Capillary (Sanger) Sequencing

Next Generation Sequencing

(NGS)

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

454pyroseq

Solexa/Illumina

ABISOLID

IlluminaHiSeq

Technologies Roche/454Titanium

ABISOLID 3.0

ABIcapillary

IonTorrent

Rapid reduction in sequencing costs

2008 2009 2010 2011

Total yield by week (Gigabases)

Sanger Institute

How Fast is That?

6000 Gb per week (6 Tb) =10,000,000 bases per second

½ hour per 6Gb (= 1x Human Genome)

Genome Sequencing

Sanger (capillary) sequencing

2015? ~1day?? $100

2005~3 years

~$ 20million

2010~1month$9,500

(Illumina)

AM

L

Mel

anom

aS

mal

l-cel

l lun

gB

rea

st

2008~4 months

~$ 1.5million

Lun

g (N

SS

)

Cancer Genomics

2000~10 years

~$ 3.5 billion

Mye

lom

a

Hep

atoc

ellu

lar

CLL

Mou

se A

ML

Next generation sequencing

Analysing cancer genomes

From Ding et al, Hum Mol Gen, 2010

Genomic Circos Plot

Deletions/Insertions

Circos Plot from Pleasance et al, Nature 2010

Substitution density (het)

Substitution density (homo)

Coding SubstitutionsSilentMissenseNonsenseSplice site

Copy number

Regions of LOH

Structural rearrangementsIntrachromosomalInterchromosomal

Genomic coordinates

• 1000s of individual cancer genomes• 100s of recurrent mutations• Aetiological links • Clinico-pathological correlates • Delineation of effects of many mutations• Development of new therapies

> Increasing use of genomics in cancer diagnosis, prognosis & therapy

This decade

• Today’s cancer diagnostic lab• The era of cancer genomics• Novel diagnostic applications• Introducing genomics to cancer diagnosis

Overview

The clinical process in oncologyPre-clinical

phase

Presentation

Diagnosis

Treatment

Assessment of response

Follow-up

Relapse

• Whole genome sequencing (~6Gb)• Exome sequencing (~60Mb)• Selected gene/exon DNA sequencing• Residual disease monitoring (plasma DNA)

New diagnostic applications

Whole genome sequencing

A B

C D

Diagnostic whole genome sequencing

Constitutional genome

Cancergenome

Compare

Clinical Report

Other diagnostic data

Somatic mutationsSubclonal heterogeneity

SubstitutionsIndels

Copy number changesTranslocations

Inherited mutations & polymorphisms

Chr1

NRAS

Exome sequencing: target enrichment

regions covered

“Baits” or PCR amplicons

Diagnostic whole exome sequencing

Constitutional exome

Cancerexome

Compare

Clinical Report

Other diagnostic data

Somatic mutationsSubclonal heterogeneity

SubstitutionsIndels

Copy number changesTranslocations

Inherited mutations & polymorphisms

Selective sequencingexample: an AML toolkit

• ~20 genes known to be recurrently mutated• Prognostic/treatment implications known for some

• Target enrichment Target enrichment by “pull down”by “pull down”

Can detect:Sequence changesCopy number (UPD/LOH)

ASXL1 NF1

CBL NPM1

CEBPA NRAS

CSF1R RUNX1

DNMT3A TET2

FLT3 WT1

IDH1 EZH2

IDH2 KIT

JAK2 KDM6A

KRAS TP53

MLL PTPN11

BRAF

IKZF1

HPRT1

PAX5

PIK3CA

UGT1A1

CYP2D6

TLR4

EGFR

XRCC2

PTEN

Type A (Transcription Factor)

Type B (DNA modification)

Type C (Signal transduction)

PROGNOSIS

AML1 NPM1 DNMT3A R882C FLT3-TKD Intermediate

AML2 TET2 KRAS K117N Intermediate

AML3 CEBPA NRAS G12D Intermediate

AML4 NPM1 IDH1 R132H FLT3-TKD Favourable

AML5 ASXL1 KRAS G12D Poor

AML6 IDH2 R172K Poor

Selective sequencingexample: an AML toolkit

Cancer

Normaltissues

DNA with tumour-specific mutation

Plasma DNA

Slide courtesy of Dr Peter Campbell

Tumour-specific rearrangements

1st round PCR

Nested real-time PCR

Chr20Chr10

Individual Breast Cancer Genome

Relapsing breast cancer

0.1

0.01

1

0.05

0.5

Undiluted patient plasma1:101:1001:10001:10,0001:100,000

NormalWater

0 5 10 15 20 25 30 35 40

Cycles of real-time PCR

Inte

nsity

Non-rearranged genomic region

0.1

0.01

1

0.05

0.5

0 5 10 15 20 25 30 35 40

Cycles of real-time PCR

Inte

nsity

Tumour-specific rearrangement

Slide courtesy of Dr Peter Campbell

150

Serial measurements

Months after diagnosis

Estim

ated

tum

our D

NA

/ m

L se

rum

(pg)

25

50

75

100

125

Undetectable

Detectable atlimit of sensitivity

6 7 8 9 10 11 12 13 14 15 16 175

Rearrangement 1

Rearrangement 2

First-line chemotherapy Second-line Paclitaxel

CT scan: Localiseddeposits around T9-10

Chemotherapy:

CT scan: Widespreadsoft-tissue metastases

Slide courtesy of Dr Peter Campbell

•Multiple biomarker MRD•Methylomics•Transcriptomics (RNAseq)•Cancer screening / Biomarker assays

Other applications of NGS

• Today’s cancer diagnostic lab• The era of cancer genomics• Novel diagnostic applications• Introducing genomics to cancer diagnosis

Overview

Hurdles to the introduction of diagnostic cancer genome sequencing

Technology

• Sample choice/compatibility FFPE, other• Cost $10,000/genome• Sample to sequence delay 8-10 days• Mutation calling Specificity / Sensitivity

Laboratory

• Sequencing equipment Choice/Cost• New personnel Bioinformaticians• Computer storage Petabytes (1015)• Education/training Pathologists, Clinicians

Clinic• Clinical relevance/utility Evolving• Personal genomes/Ethics Being tested

Genome Campus

Sulston Building

Morgan Building

Research Support Facility

Data storage & analysis

Data Centre

European Bioinformatics Institute

Training of pathologists

• Core training in genomics• New sub-specialty e.g. Molecular Pathology?• Impact on other aspects of training• How will the training be delivered?• Training/role of laboratory scientists• Keeping control of the agenda

Diagnostic reporting of genomic data

• Communicating the cancer genome to the clinician– Diagnosis– Recurrently mutated genes– Non-recurrent/private mutations / pathways– Prognostic relevance– Therapeutic relevance– Pharmacogenomics– Constitutional genome– Mutational signatures– Summary / Imagery

Implications for cancer classification

Cellular originMorphology

Differentiation/grading

Mutations: DiagnosisPrognosisTreatment

UnifiedClassification?

Acute Myeloid Leukaemia – a paradigm of evolving classification

Morphology Single entity Various 1950s

Morphology & cytochemistry M0-M7 FAB 1976

Morphology, AML with recurrent cytogenetic translocations WHO 2002

Immunophenotyping & AML with multilineage dysplasia

Cytogenetics AML, therapy related

AML not otherwise categorized

Morphology, AML with recurrent genetic abberations WHO 2008

Immunophenotyping , Provisional entity: AML with mutated NPM1

Cytogenetics & Provisional entity: AML with mutated CEBPA

Genetics Otherwise as 2002

Will there be a paradigm shift ?

?

Summary

• The advent of cancer genomics is changing cancer medicine

• Changes will transform cancer diagnosis and the role of pathologists

• Pathologists need to understand what is coming in order to lead and formulate the future for cancer diagnosis