Literature DB >> 26072494

MEMCover: integrated analysis of mutual exclusivity and functional network reveals dysregulated pathways across multiple cancer types.

Yoo-Ah Kim1, Dong-Yeon Cho1, Phuong Dao1, Teresa M Przytycka1.   

Abstract

MOTIVATION: The data gathered by the Pan-Cancer initiative has created an unprecedented opportunity for illuminating common features across different cancer types. However, separating tissue-specific features from across cancer signatures has proven to be challenging. One of the often-observed properties of the mutational landscape of cancer is the mutual exclusivity of cancer driving mutations. Even though studies based on individual cancer types suggested that mutually exclusive pairs often share the same functional pathway, the relationship between across cancer mutual exclusivity and functional connectivity has not been previously investigated.
RESULTS: We introduce a classification of mutual exclusivity into three basic classes: within tissue type exclusivity, across tissue type exclusivity and between tissue type exclusivity. We then combined across-cancer mutual exclusivity with interactions data to uncover pan-cancer dysregulated pathways. Our new method, Mutual Exclusivity Module Cover (MEMCover) not only identified previously known Pan-Cancer dysregulated subnetworks but also novel subnetworks whose across cancer role has not been appreciated well before. In addition, we demonstrate the existence of mutual exclusivity hubs, putatively corresponding to cancer drivers with strong growth advantages. Finally, we show that while mutually exclusive pairs within or across cancer types are predominantly functionally interacting, the pairs in between cancer mutual exclusivity class are more often disconnected in functional networks. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

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Mesh:

Year:  2015        PMID: 26072494      PMCID: PMC4481701          DOI: 10.1093/bioinformatics/btv247

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  27 in total

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  28 in total

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3.  A weighted exact test for mutually exclusive mutations in cancer.

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4.  WeSME: uncovering mutual exclusivity of cancer drivers and beyond.

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5.  DriveWays: a method for identifying possibly overlapping driver pathways in cancer.

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6.  Discovery of cancer common and specific driver gene sets.

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7.  Signal-Oriented Pathway Analyses Reveal a Signaling Complex as a Synthetic Lethal Target for p53 Mutations.

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Review 9.  Understanding Genotype-Phenotype Effects in Cancer via Network Approaches.

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Review 10.  Computational approaches for the identification of cancer genes and pathways.

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