COMPREHENSIVE MOLECULAR

CHARACTERIZATION OF GASTRIC

ADENOCARCINOMA

JC presented byMohsin 20 - 08- 2014

Journal Club

The Cancer Genome Atlas Research Network ( TCGA)

Nature, July 2014

4th most common cancer world-wide

 fifth most common cancer in india

incidence increases with age (rare under the age of 30)

highest incidence: Eastern Asia (Japan), Eastern Europe, South America

men:women = 2:1

GASTRIC CANCER

Adenocarcinoma gastrointestinal

stromal tumours (GIST)

primary gastric lymphoma

gastric polyps

EPIDEMIOLOGY

H.pylori infection (group 1 gastric carcinogen)

Epstein –Barr virus (EBV) Dietary factors Smoking tobacco Genetic abnormalities

Distribution of histological subtypes of gastric cancer and the frequencies of

H. pylori and EBV associated gastric cancer vary across the globe

Diagram showing the development of gastric cancer associated with H.pylori infection

GASTRIC CANCER

Small minority of gastric cancer cases are associated with germline mutation in E-cadherin (CDH1) or mismatch repair genes (Lynch syndrome)

Sporadic mismatch repair-deficient gastric cancers have epigenetic silencing of MLH1 in the context of a CpG island methylator phenotype (CIMP)

Molecular profiling of gastric cancer has been performed using gene expression or DNA sequencing but has not led to a clear biologic classification scheme

PATHOLOGY ADENOCARCINO

MA

Lauren classification:

• Intestinal type

• Diffuse type

• Gastric adenocarcinoma of intestinal type • Diffuse carcinoma

type

Higher Lower HER2-neu(>25%) HER2-neu

WHO GASTRIC CANCER CLASSIFICATION Classification based on morphologic features* Adenocarcinoma – divided according to the growth

pattern in: - papillary - tubular - mucinous(colloid) - poorly cohesive carcinomas

o These classification systems have little clinical utility,making the development of robust classifiers that can guide patient therapy on urgent priority

o The goals of this study by The Cancer Genome Atlas (TCGA) were to develop a robust molecular classification of gastric cancer and to identify dysregulated pathways and candidate drivers of distinct classes of gastric cancer

THE CANCER GENOME ATLAS (TCGA )

TCGA:•The Cancer Genome Atlas (TCGA ) projects define genetic mutations responsible for cancer, using genome analysis techniques started in 2005.•(In coordination with National Cancer Institute and the National Human Genome Research Institute)

•Initial focus was on 3 type of cancers: glioblastoma, lung, and ovarian cancer

•The project ( Gastric Cancer) is unique in terms of the size of the patient cohort and the number of different techniques used to analyze the patient samples

TCGA: TIMELINE

Pilot Projects: GBM and Ovarian carcinoma (~500 cases ea.)• Establish infrastructure for effective team science • Develop a scalable “pipeline”• Demonstrate the feasibility of a large-scale, high throughput approach to identifying the molecular ‘parts-list’• Make the data publicly and broadly available to the cancer community while protecting patient privacy

GBM Report

2006-2009

Pilot

2005

NCAB Report

9 tumor types closed

Rare ProjectsInitiated

10,000 cases complete

ARRA Funding

OvarianReport

2010-2014

Project Expansion

Expansion 2010 to 2014:• Add 25-35 tumor types• Enhancement of sample acquisition & program staff• Add Genome Data Analysis Centers• Publish “Benchmark Marker Papers”• Established FFPE protocols• Completely characterize 10,000th case

AnalysisCompletion

2015-2016

Analysis Completion 2015-2016:• Finish marker papers on rare & “challenging-to-accrue” tumors • Complete Pan-Cancer Analysis• Broader sharing of tools, analytical methods

TCGA TUMOR TYPES

AML Breast Ductal* Breast Lobular/Breast Other Bladder (pap and non-pap) Cervical adeno & squamous Colorectal* Clear cell kidney* DLBCL Endometrial carcinoma* Esophageal adeno & squamous Gastric adenocarcinoma GBM* Head and Neck Squamous*

• Hepatocellular• Lower Grade Glioma• Lung adenocarcinoma*• Lung squamous*• Melanoma• Ovarian serous

cystadenocarcinoma*• Papillary kidney• Pancreas• Prostate• Sarcoma (dediff lipo, UPS,

leiomyosarcoma)• Papillary Thyroid*

Red- Pilot tumors; *- Reached 500

Multiple data types

• Clinical diagnosis• Treatment history• Histologic diagnosis• Pathologic report/images• Tissue anatomic site• Surgical history• Gene expression/RNA

sequence• Chromosomal copy

number• Loss of heterozygosity• Methylation patterns• miRNA expression• DNA sequence• RPPA (protein)• Subset for Mass Spec

TCGA: “NO PLATFORM LEFT BEHIND”

25* forms of cancer

glioblastoma multiforme(brain)

squamous carcinoma(lung)

serouscystadenocarcinoma

(ovarian)

Etc. Etc. Etc.

Biospecimen CoreResource with more

than 150 Tissue Source Sites

6 Cancer GenomicCharacterization

Centers

3 GenomeSequencing

Centers

7 Genome Data Analysis Centers

Data Coordinating Center

SAMPLE SET AND MOLECULAR CLASSIFICATION

295 gastric adenocaricinoma (primary tumour tissue) not treated with prior chemo/radio therapy

Informed consent take from all patients and approved by Institutional Review boards

Germline DNA from blood or non- malignant gastric mucosa as a reference for detecting somatic alterations

Non-malignant gastric samples collected for DNAmethylation (n =27) and expression(n =29) analyses

METHODS Samples were characterized using six molecular

platforms 1. Array-based somatic copy number analysis 2. whole-exome sequencing 3. array-based DNA methylation profiling 4. messenger RNA(mRNA) sequencing, 5. microRNA (miRNA) sequencing and 6. reverse-phase protein array (RPPA)

77% of the tumours tested by all six platforms Microsatellite instability (MSI) testing was performed

on all tumour DNA, and low-pass whole genome sequencing on 107 tumour /

germline pairs

EBV-ASSOCIATED DNA HYPERMETHYLATION

EBV is found within malignant epithelial cells in 9% of gastric cancers

EBV status was determined using mRNA, miRNA, exome and whole-genome sequencing, yielding highly concordant results

Unsupervised clustering of CpG methylation performed (CIMP) revealed that all EBV-positive tumours clustered together and exhibited extreme CIMP, distinct from that in the MSI subtype

CONTD….

EBV-positive tumours had a higher prevalence of DNA hypermethylation than any cancers reported by TCGA

All EBV-positive tumours assayed displayed CDKN2A (p16 INK4A) promoter hypermethylation, but lacked the MLH1 hyper methylationcharacteristic of MSI-associated CIMP

SOMATIC GENOMIC ALTERATIONS To identify recurrently mutated genes, 215 tumours-

analyzed with mutation rates below 11.4 mutations per megabase (n=63), using used the MutSigCV

identifying 10 significantly mutated genes, including TP53, KRAS, ARID1A, PIK3CA, ERBB3, PTEN and HLA-B

25 significantly mutated genes in non-hypermutated samples

This gene list again included TP53, ARID1A, KRAS, PIK3CA, B2M, RNF43, HLA-B and RNF43, but also genes in the b-catenin pathway (APC and CTNNB1), the TGF-b pathway (SMAD4 and SMAD2), and RASA1, a negative regulator of RAS. ERBB2(HER2-Neu),a therapeutic target, was significantly mutated, with 10 of 15 mutations occurring at known hotspots- that is activating and drug-sensitive

In addition to PIK3CA mutations, EBV-positive tumours had frequent ARID1A (55%) and BCOR (23%) mutations and only rare TP53 mutations. (BCOR, encoding an anti-apoptotic protein, is also mutated leukaemia and medulloblastoma)

patterns of base changes within gastric cancer tumours, noted elevated rates of C to T transitions at CpG dinucleotides and an elevated rate of A to C transversions at the 39 adenine of AA dinucleotides, especially at AAG trinucleotides, as reported in oesophageal adenocarcinoma

RHOA mutation in 16 cases, and these were enriched in the genomically stable subtype

(RHOA, when in the active GTP-bound form, acts through a variety of effectors(ROCK1), to control actin-myosin-dependent cell contractility and cellular motility and STAT3 - tumorigenesis)

GENE EXPRESSION AND PROTEOMIC ANALYSIS

Analysis of each of the expression platforms revealed four mRNA, five mi RNA and three RPPA clusters

Some expression clusters are similar across platforms ( E.g: mRNA cluster 3, miRNA cluster 2 and RPPA cluster 3 are

similar and are associated with the MSI subtype as a group )

Analysis of mRNA sequence data for alternative splicing events showed MET exon 2 skipping in 82 of 272 (30%) cases, associated with increased MET expression

Some novel variants of MET found in which exons 18 and/or 19 were skipped (47/272; 17%)

GENE EXPRESSION AND PROTEOMIC ANALYSIS

Through supervised analysis of RPPA data,- 45 proteins whose expression or phosphorylation was associated with the four molecular subtypes

Phosphorylation of EGFR (pY1068) was significantly elevated in the CIN subtype

Also elevated expression of p53, consistent with frequent TP53 mutation and aneuploidy in the CIN subtype

INTEGRATED PATHWAY ANALYSIS Integrated somatic copy-number aberrations -SCNA

and mutation data to characterize genomic alterations in known signalling pathways, including candidate therapeutic targets

Mutations, copy-number changes and translocations for select gene

Alterations in RTK/RAS and RTK/PI(3)K signalling pathways across molecular subtypes Heatmap shows NCI-PID pathways that are

significantly elevated (red) or decreased (blue) ineach of the four subtypes as compared with

non-malignant gastric mucosa

INTEGRATED PATHWAY ANALYSIS

Focussing on alterations in receptor tyrosine kinases (RTKs) and RAS and PI(3)-kinase signalling. EBV-positive tumours contained PIK3CA mutations and recurrent JAK2 and ERBB2 amplifications

Frequent amplifications of cell cycle mediators (CCNE1, CCND1 and CDK6) suggest the potential for therapeutic inhibition of cyclin-dependent kinases

RESULTS To define molecular subgroups of gastric cancer- first

unsupervised clustering performed on data from each molecular platform

Integrated these results, yielding four groups: First group of tumours was significantly enriched for

high EBV burden, display recurrent PIK3CA mutations , extensive DNA promoter hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also known as PD-L2)

Second group was enriched for MSI and showed elevated mutation rates and hypermethylation (including hypermethylation at the MLH1 promoter)-

(genes encoding targetable oncogenic signalling proteins)

RESULTS Remaining two groups were distinguished by the

presence or absence of extensive somatic copy-number aberrations (SCNAs)

Third group- genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins

Fourth Group tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases

An alternative means to define distinct gastric cancer subgroups, was performed integrative clustering of multiple data types using iCluster

RESULTS

This analysis again indicated that EBV, MSI and the level of SCNAs characterize distinct subgroups

Based upon these results from analysis of all molecular platforms, - a decision tree created to categorize the 295 gastric cancer samples into four subtypes using an approach that could more readily be applied to gastric cancer tumours in clinical care

Tumours were first categorized by EBV-positivity (9%), then by MSI-high status, hereafter called MSI (22%),

RESULTS

RESULTS

And the remaining tumours were distinguished by degree of aneuploidy into those termed genomically stable (20%) or those exhibiting chromosomal instability (CIN; 50%)

Evaluation of the clinical and histological characteristics of these molecular subtypes revealed enrichment of the diffuse histological subtype in the genomically stable group (40/55 = 73%)

RESULTS

Each subtype was found throughout the stomach, but CIN tumours showed elevated frequency in the gastroesophageal junction/cardia (65%, P 50.012), whereas most EBV-positive tumours were present in the gastric fundus or body (62%,

Genomically stable tumours were diagnosed at an earlier age (median age 59 years) whereas MSI tumours were diagnosed at relatively older ages (median 72 years)

MSI patients tended to be female (56%, P = 0.001), but most EBV-positive cases were male (81%, P =0.037)

RESULTS Initial outcome data from this cohort did not

reveal survival differences between the four subgroups

DISCUSSION AND CONCLUSION Gastric cancer - leading cause of cancer deaths,

analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity

Comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project

Through this study of the molecular and genomic basis of gastric cancer, divided gastric cancer into four subtypes

DISCUSSION

This classification may serve as a valuable adjunct to histopathology

These molecular subtypes showed distinct salient genomic features, providing a guide to targeted agents that should be evaluated in clinical trials for distinct populations of gastric cancer patients

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DISCUSSION AND CONCLUSION

Through existing testing for MSI and EBV and the use of emerging genomic assays

classification system developed through this study can be applied to new gastric cancer cases

These results will facilitate the development of clinical trials to explore therapies in defined sets of patients, ultimately improving survival from this deadly disease

THANK YOU …!!!

AJ Bass et al. Nature 000, 1-8 (2014) doi:10.1038/nature13480

Molecular subtypes of gastric cancer.

AJ Bass et al. Nature 000, 1-8 (2014) doi:10.1038/nature13480

Molecular characteristics of EBV-positive gastric cancers.