Alterations of signaling pathways in glioblastoma

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Alterations of signaling pathways in glioblastoma

• Niki Schultz
• Chris Sander LabComputational Biology

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Outline

• Overview of the Cancer Genome Atlas
• Results from individual genomic platforms
  analyzing glioblastoma
• Integration with signaling pathways

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The Cancer Genome Atlas (TCGA)
3-year 100 million-dollar pilot project cancer
types brain (glioblastoma multiforme) lung
(squamous carcinoma) ovarian (serous
cystadenocarcinoma) Potentially 1.5 billion
dollars, 50 cancer types
The Cancer Genome Atlas (TCGA) is a comprehensive
and coordinated effort to accelerate our
understanding of the molecular basis of cancer
through the application of genome analysis
technologies, including large-scale genome
sequencing. TCGA is a joint effort of the
National Cancer Institute (NCI) and the National
Human Genome Research Institute (NHGRI), which
are both part of the National Institutes of
Health, U.S. Department of Health and Human
Services. The overarching goal of TCGA is to
improve our ability to diagnose, treat, and
prevent cancer. A pilot project will assess the
feasibility of a full-scale effort to
systematically explore the entire spectrum of
genomic changes involved in human cancer.
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The Cancer Genome Atlas (TCGA)
Clincial annotation
DNA copy number
DNA methylation
DNA sequencingcurrently 1300 genes
Gene expression - mRNA (exon-level) - miRNA
(Proteomics)
Integrative analysis
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Glioblastoma multiforme

• Widespread invasion through the brain
• Resistance to therapy
• Destruction of normal brain tissue
• Certain death

Grade I benign and can be cured if they canbe
surgically resected
Astrocyte
Grade II Astrocytoma Moderate proliferation and
invasion. 5-10 years survival
Progressive pathway
De novo pathway
Grade III Anaplastic Astrocytoma Proliferation,
invasion, angiogenesis,treatment responsive. 2-3
years survival
Grade IV Primary GlioblastomaSignificant
proliferation, invasion, angiogenesis, necrosis.
Treatment refractory.
Grade IV Secondary Glioblastoma Significant
proliferation, invasion, angiogenesis, necrosis.
Treatment refractory.9-14 months survival
9-14 months survival
10 Typically in younger patients (lt45 yrs)
90 Typically in older patients (gt45 yrs)
7 per 100,000 individuals per year, 2 of all
primary tumors
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TCGA data types
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TCGA data types
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
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Clinical annotation
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data

• Age
• Gender
• Treatment
• Survival
• Tumor pathology

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DNA copy number alterations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platforms Agilent CGH 244A (MSKCC
Harvard)Affymetrix SNP 6.0 (Broad)Illumina 550K
SNP (Stanford)
analysis methods GISTICGTSRAE
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DNA copy number alterations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platforms Agilent CGH 244A (MSKCC
Harvard)Affymetrix SNP 6.0 (Broad)Illumina 550K
SNP (Stanford)
analysis methods GISTICGTSRAE
Barry Taylor, Nicholas Socci
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DNA copy number alterations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
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DNA methylation in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platformarray-based high-throughput
single-site CpG resolution platform (Illumina,
run at Johns Hopkins) 1000 genes, 3 probes per
gene Probe selection tricky no correlation
between methylation and mRNA for the majority
of genes measured
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DNA methylation in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platformarray-based high-throughput
single-site CpG resolution platform (Illumina,
run at Johns Hopkins) 1000 genes, 3 probes per
gene Probe selection tricky no correlation
between methylation and mRNA for the majority
of genes measured
MGMT expression regulated by methylation Patients
with low MGMT expression levelsare sensitive to
temozolomide
Kornel Schuebel, Johns Hopkins
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mRNA expression in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platforms Affymetrix U133 (Broad)Agilent Whole
Genome 4x44k (UNC)Affymetrix Exon 1.0 (LBL)
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microRNA expression in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platform Agilent 8 x 15k (UNC)
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Protein mutations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
platformsSanger sequencing at 3 centers
Broad WashU Baylor 454, Biotage and
Sequenom used for validation genes 1300 genes
selected (600 in phase I)
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Protein mutations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
The most frequently mutated genes in glioblastoma
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Protein mutations in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
The most frequently mutated genes in glioblastoma
Boris Reva
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Altered signaling pathways in glioblastoma
DNA copy number
DNA methylation
mRNA expression
miRNA expression
mutations
Clinical data
signaling pathways
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WeiqingWang
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Altered signaling pathways in glioblastoma
Amplificationsand deletions
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Altered signaling pathways in glioblastoma
Amplificationsand deletions
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Altered signaling pathways in glioblastoma
Amplificationsand deletions mutations
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Altered signaling pathways in glioblastoma
Amplificationsand deletions mutations
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Altered signaling pathways in glioblastoma
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Altered signaling pathways in glioblastoma
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Altered signaling pathways in glioblastoma
Larry Donehower, David Wheeler, BCM
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TCGA manuscript
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TCGA manuscript
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Conclusions and future plans

• Deregulation of RB, P53, and RTK/RAS/PI3K
  pathways in almost all samples
• Exact alterations within the pathways may guide
  therapy (potentially more easily applicable to
  other cancer types)
• TCGA plans
• two more cancer types as part of the pilot
  (ovarian, lung)
• integration of next-generation sequencing
  techniques
• Sander group plans
• Further development of pathway analysis methods
  (integration of mRNA expression, improved pathway
  identification)
• Application to other cancer types

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cBio websites and tools
cBio Cancer Genomics websitehttp//cbio.mskcc.org
/cancergenomics/
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cBio websites and tools
cBio Cancer Genomics websitehttp//cbio.mskcc.org
/cancergenomics/
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cBio websites and tools
cBio Cancer Genomics websitehttp//cbio.mskcc.org
/cancergenomics/ Mondrian, the Genomic Data
Mapper Softwarehttp//cbio.mskcc.org/mondrian/ B
enjamin Gross, Ethan Cerami
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Acknowledgements
Baylor College of MedicineLarry DonehowerDavid
Wheeler The TCGA consortium
cBio _at_ MSKCCJenya AntipinEthan CeramiBenjamin
GrossBoris RevaNicholas SocciBarry
TaylorWeiqing Wang Chris Sander MSKCCCameron
BrennanMarc Ladanyi