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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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2
3
4
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.