WorkshopsAn integrative characterization of recurrent molecular aberrations in glioblastoma
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Glioblastoma multiform (GBM) is the most common and malignant primary brain tumor in adults. Decades of investigations and the recent effort of the Cancer Genome Atlas (TCGA) project have mapped many alterations of DNA sequences, copy numbers, methylation states, mRNA and microRNA expressions in GBM cells. Alterations on DNAs may dysregulate gene expressions and drive the malignancy of tumors. It is thus important to uncover causal and statistical dependency between the driver molecular aberrations and passenger gene expressions in GBMs. A rich collection of prior studies attempted to combine copy number variation (CNV) and mRNA expression data. However, systematic methods to integrate multiple types of cancer genomic data - gene mutations, single nucleotide polymorphisms, copy number variations, DNA methylations, mRNA and microRNA expressions, and clinical information – are relative scarce. We propose an algorithm to build association modules linking driver molecular aberrations and passenger gene expressions and apply the module-finding algorithm to the integrated TCGA GBMs. The inferred association modules are validated by 6 tests using external information and datasets of central nervous system tumors: functional enrichment of passenger genes, co-citations between drivers and passengers, coherence of passenger gene expressions and retension of driver-passenger associations in external datasets, recurrence of driver molecular aberrations, and indication of prognostic effects among patients. Modules associated with well-known molecular aberrations of GBMs – such as chromosome 7 amplifications, chromosome 10 deletions, EGFR and NF1 mutations – pass the majority of the validation tests. Furthermore, several modules associated with less-well reported molecular aberrations – such as chromosome 11 CNVs, CD40 and PLXNB1 methylations – are also validated by external information. In particular, modules constituting trans-acting effects with chromosome 11 CNVs and cis-acting effects with chromosome 10 CNVs manifest strong negative and positive associations with survival durations in brain tumors. Functional and survival analyses indicate that immune/inflammatory responses and mesenchymal transitions are among the most important determining processes of prognosis. Finally, we demonstrate that certain molecular aberrations uniquely recur in GBMs but are relatively rare in non-GBM glioma cells. These results justify the utility of an integrative analysis on cancer genomes and provide testable characterizations of driver aberration events in GBMs.
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Nardnisa Sintupisut
2012-07-24
16:30:00 - 17:20:00
308 , Mathematics Research Center Building (ori. New Math. Bldg.)
Glioblastoma multiform (GBM) is the most common and malignant primary brain tumor in adults. Decades of investigations and the recent effort of the Cancer Genome Atlas (TCGA) project have mapped many alterations of DNA sequences, copy numbers, methylation states, mRNA and microRNA expressions in GBM cells. Alterations on DNAs may dysregulate gene expressions and drive the malignancy of tumors. It is thus important to uncover causal and statistical dependency between the driver molecular aberrations and passenger gene expressions in GBMs. A rich collection of prior studies attempted to combine copy number variation (CNV) and mRNA expression data. However, systematic methods to integrate multiple types of cancer genomic data - gene mutations, single nucleotide polymorphisms, copy number variations, DNA methylations, mRNA and microRNA expressions, and clinical information – are relative scarce. We propose an algorithm to build association modules linking driver molecular aberrations and passenger gene expressions and apply the module-finding algorithm to the integrated TCGA GBMs. The inferred association modules are validated by 6 tests using external information and datasets of central nervous system tumors: functional enrichment of passenger genes, co-citations between drivers and passengers, coherence of passenger gene expressions and retension of driver-passenger associations in external datasets, recurrence of driver molecular aberrations, and indication of prognostic effects among patients. Modules associated with well-known molecular aberrations of GBMs – such as chromosome 7 amplifications, chromosome 10 deletions, EGFR and NF1 mutations – pass the majority of the validation tests. Furthermore, several modules associated with less-well reported molecular aberrations – such as chromosome 11 CNVs, CD40 and PLXNB1 methylations – are also validated by external information. In particular, modules constituting trans-acting effects with chromosome 11 CNVs and cis-acting effects with chromosome 10 CNVs manifest strong negative and positive associations with survival durations in brain tumors. Functional and survival analyses indicate that immune/inflammatory responses and mesenchymal transitions are among the most important determining processes of prognosis. Finally, we demonstrate that certain molecular aberrations uniquely recur in GBMs but are relatively rare in non-GBM glioma cells. These results justify the utility of an integrative analysis on cancer genomes and provide testable characterizations of driver aberration events in GBMs.