Mutual exclusivity analysis identifies oncogenic network modules.

By Giovanni Ciriello, Ethan G. Cerami, Christopher Sander, Nikolaus Schultz. 2012

653 citations recorded by the source corpus.

Although individual tumors of the same clinical type have surprisingly diverse genomic alterations, these events tend to occur in a limited number of pathways, and alterations that affect the same pathway tend to not co-occur in the same patient. While pathway analysis has been a powerful tool in cancer genomics, our knowledge of oncogenic pathway modules is incomplete. To systematically identify such modules, we have developed a novel method, Mutual Exclusivity Modules in cancer (MEMo). The method uses correlation analysis and statistical tests to identify network modules by three criteria: (1) Member genes are recurrently altered across a set of tumor samples; (2) member genes are known to or are likely to participate in the same biological process; and (3) alteration events within the modules are mutually exclusive. Applied to data from the Cancer Genome Atlas (TCGA), the method identifies the principal known altered modules in glioblastoma (GBM) and highlights the striking mutual exclusivity of genomic alterations in the PI(3)K, p53, and Rb pathways. In serous ovarian cancer, we make the novel observation that inactivation of BRCA1 and BRCA2 is mutually exclusive of amplification of CCNE1 and inactivation of RB1, suggesting distinct alternative causes of genomic instability in this cancer type; and, we identify RBBP8 as a candidate oncogene involved in Rb-mediated cell cycle control. When applied to any cancer genomics data set, the algorithm can nominate oncogenic alterations that have a particularly strong selective effect and may also be useful in the design of therapeutic combinations in cases where mutual exclusivity reflects synthetic lethality.

Subfields: Computational Theory and Mathematics, Molecular Biology

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Citations in the corpus

EgoNet: identification of human disease ego-network modules (2014, methodology): “To date, many computational methods have been developed to integrate gene expression profiles with protein-protein interaction maps or pathway databases, with the goal of identifying significant subnetwork markers for predicting biological or clinical outcomes [10-18].”
Structure and dynamics of molecular networks: A novel paradigm of drug discovery: A comprehensive review (2012, background): “…of proteins and uses an expansion process, which gradually explores the network beyond the direct neighborhood. http://sourceforge.net/p/alignnemo Ciriello et al., 2012a Differential dependency network analysis Transcriptional networks A set of conditional probabilities is proposed as a local…”
Network-based machine learning and graph theory algorithms for precision oncology (2017, methodology): “The mutual exclusivity module (MEMo) method 59 is another widely used method in the TCGA project.”
The Somatic Genomic Landscape of Glioblastoma (2013, methodology): “Unsupervised analysis of 251 GBMs with both copy number and WES mutation data identified genes sets (modules) in which somatic alterations were significantly mutually exclusive (MEMo; Ciriello et al., 2012).”
Comprehensive molecular portraits of invasive lobular breast cancer (2015, background): “Consistent with these results, we found significant upregulation of a PI3K/Akt pathway-specific protein and phospho-protein expression signature (Akbani et al., 2014) in LumA ILC compared 9, October 8, 2015 ª2015 Elsevier Inc. 511 (A) Recurrent FOXA1 mutations in 817 breast tumors cluster in the For”
Integrated Genomic Characterization of Papillary Thyroid Carcinoma (2014, background): “of Papillary Thyroid Carcinoma”
Integrative approaches for finding modular structure in biological networks (2013, background): “…biomarkers, as demonstrated for the classification of numerous human disorders including Alzheimer’s disease 96 , diabetes 36,97–99 and several forms of cancer including breast cancer 45,55,62,98,100,101 , ovarian cancer 73,102,103 , glioblastoma 67,70,73,74 and others 39,72,94,104,105 .”