Comprehensive molecular characterization of gastric adenocarcinoma
The Cancer Genome Atlas Research Network ( TCGA)
Nature, July 2014
JC, by
Mohsin Maqbool, AIIMS
2. 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
4. 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
5. 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
7. 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
8. 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
9. 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 Projects
Initiated
10,000
cases complete
ARRA
Funding
Ovarian
Report
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
Analysis
Completion
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
11. 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)
serous
cystadenocarcinoma
(ovarian)
Etc. Etc. Etc.
Biospecimen Core
Resource with more
than 150 Tissue
Source Sites
6 Cancer Genomic
Characterization
Centers
3 Genome
Sequencing
Centers
7 Genome Data
Analysis Centers
Data Coordinating
Center
12. 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
13. 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
14. 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
15. 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
16. 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
17. 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)
18. 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%)
19. 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
20. 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 subtypesHeatmap shows NCI-PID pathways that are
significantly elevated (red) or decreased (blue) in
each of the four subtypes as compared with
non-malignant gastric mucosa
21. 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
22. 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)
23. 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
24. 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%),
26. 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%)
27. 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)
28. RESULTS
Initial outcome data from this cohort did not
reveal survival differences between the four
subgroups
29. 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
30. 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
1
2
3
4
31. 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