Yoo-Ah Kim1, Dong-Yeon Cho1, Phuong Dao1, Teresa M Przytycka1. 1. National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, Bethesda, MD, 20894, USA.
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.
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.
Authors: Paul Shannon; Andrew Markiel; Owen Ozier; Nitin S Baliga; Jonathan T Wang; Daniel Ramage; Nada Amin; Benno Schwikowski; Trey Ideker Journal: Genome Res Date: 2003-11 Impact factor: 9.043
Authors: Roman K Thomas; Alissa C Baker; Ralph M Debiasi; Wendy Winckler; Thomas Laframboise; William M Lin; Meng Wang; Whei Feng; Thomas Zander; Laura MacConaill; Laura E Macconnaill; Jeffrey C Lee; Rick Nicoletti; Charlie Hatton; Mary Goyette; Luc Girard; Kuntal Majmudar; Liuda Ziaugra; Kwok-Kin Wong; Stacey Gabriel; Rameen Beroukhim; Michael Peyton; Jordi Barretina; Amit Dutt; Caroline Emery; Heidi Greulich; Kinjal Shah; Hidefumi Sasaki; Adi Gazdar; John Minna; Scott A Armstrong; Ingo K Mellinghoff; F Stephen Hodi; Glenn Dranoff; Paul S Mischel; Tim F Cloughesy; Stan F Nelson; Linda M Liau; Kirsten Mertz; Mark A Rubin; Holger Moch; Massimo Loda; William Catalona; Jonathan Fletcher; Sabina Signoretti; Frederic Kaye; Kenneth C Anderson; George D Demetri; Reinhard Dummer; Stephan Wagner; Meenhard Herlyn; William R Sellers; Matthew Meyerson; Levi A Garraway Journal: Nat Genet Date: 2007-02-11 Impact factor: 38.330
Authors: Mark D M Leiserson; Fabio Vandin; Hsin-Ta Wu; Jason R Dobson; Jonathan V Eldridge; Jacob L Thomas; Alexandra Papoutsaki; Younhun Kim; Beifang Niu; Michael McLellan; Michael S Lawrence; Abel Gonzalez-Perez; David Tamborero; Yuwei Cheng; Gregory A Ryslik; Nuria Lopez-Bigas; Gad Getz; Li Ding; Benjamin J Raphael Journal: Nat Genet Date: 2014-12-15 Impact factor: 38.330
Authors: Joris van de Haar; Sander Canisius; Michael K Yu; Emile E Voest; Lodewyk F A Wessels; Trey Ideker Journal: Cell Date: 2019-05-30 Impact factor: 41.582
Authors: Songjian Lu; Chunhui Cai; Gonghong Yan; Zhuan Zhou; Yong Wan; Vicky Chen; Lujia Chen; Gregory F Cooper; Lina M Obeid; Yusuf A Hannun; Adrian V Lee; Xinghua Lu Journal: Cancer Res Date: 2016-10-10 Impact factor: 12.701