Author Manuscript Published OnlineFirst on October 10, 2016; DOI: 10.1158/0008-5472.CAN-16-1740 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Signal-oriented pathway analyses reveal a signaling complex as a synthetic lethal target for p53 mutations Songjian Lu1,2,*, Chunhui Cai1,2,*, Gonghong Yan3,4,5,*, Zhuan Zhou3,6, Yong Wan3,6, Vicky Chen1,2, Lujia Chen1,2, Gregory F. Cooper1,2, Lina M. Obeid7, Yusuf A. Hannun7, Adrian V. Lee2,3,4,5§ and Xinghua Lu1,2,§ 1Department of Biomedical Informatics, 2Center for Causal Discovery, 3University of Pittsburgh Cancer Institute, 4Department of Pharmacology and Chemical Biology, 5Magee-Womens Research Institute, 6Department of Cell Biology, Pittsburgh, PA, 7 Department of Medicine, the State University of New York at Stony Brook, Stony Brook, NY * These authors contributed equally to this work § Corresponding Authors: Xinghua Lu, Adrian V Lee Email:
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[email protected] The authors declare no conflict of interest pertaining to this manuscript. 1 Downloaded from cancerres.aacrjournals.org on September 27, 2021. © 2016 American Association for Cancer Research. Author Manuscript Published OnlineFirst on October 10, 2016; DOI: 10.1158/0008-5472.CAN-16-1740 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited. Abstract Defining processes that are synthetic lethal with p53 mutations in cancer cells may reveal possible therapeutic strategies. In this study, we report the development of a signal-oriented computational framework for cancer pathway discovery in this context. We applied our bipartite- graph-based functional module discovery algorithm to identify transcriptomic modules abnormally expressed in multiple tumors, such that the genes in a module were likely regulated by a common, perturbed signal.