Tao Qing1, Hussein Mohsen2, Vincent L Cannataro3, Michal Marczyk1,4, Mariya Rozenblit1, Julia Foldi1, Michael Murray5, Jeffrey P Townsend2,6, Yuval Kluger2,7,8, Mark Gerstein2,9,10,11, Lajos Pusztai1. 1. Breast Medical Oncology, School of Medicine, Yale University, New Haven, CT, USA. 2. Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA. 3. Department of Biology, Emmanuel College, Boston, MA, USA. 4. Department of Data Science and Engineering, Silesian University of Technology, Gliwice, Poland. 5. Department of Genetics, Yale Center for Genomic Health, New Haven, CT, USA. 6. Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. 7. Department of Pathology, School of Medicine, Yale University, New Haven, CT, USA. 8. Applied Mathematics Program, Yale University, New Haven, CT, USA. 9. Department of Molecular Biophysics & Biochemistry, Yale University, New Haven, CT, USA. 10. Department of Computer Science, Yale University, New Haven, CT, USA. 11. Department of Statistics & Data Science, Yale University, New Haven, CT, USA.
Abstract
BACKGROUND: We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional importance in cancer. METHODS: We categorized 12 767 human genes into CCGs (n = 468), 1 (n = 5467), 2 (n = 5573), 3 (n = 915), and more than 3 steps (n = 416) removed from the nearest CCG in the Search Tool for the Retrieval of Interacting Genes/Proteins network. We estimated cancer-relevant functional importance in these neighborhood categories using 1) gene dependency score, which reflects the effect of a gene on cell viability after knockdown; 2) somatic mutation frequency in The Cancer Genome Atlas; 3) effect size that estimates to what extent a mutation in a gene enhances cell survival; and 4) negative selection pressure of germline protein-truncating variants in healthy populations. RESULTS: Cancer biology-related functional importance of genes decreases as their distance from the CCGs increases. Genes closer to cancer genes show greater connectedness in the network, have greater importance in maintaining cancer cell viability, are under greater negative germline selection pressure, and have higher somatic mutation frequency in cancer. Based on these 4 metrics, we provide cancer relevance annotation to known human genes. CONCLUSIONS: A large number of human genes are connected to CCGs and could influence cancer biology to various extent when dysregulated; any given mutation may be functionally important in one but not in another individual depending on genomic context.
BACKGROUND: We hypothesize that genes that directly or indirectly interact with core cancer genes (CCGs) in a comprehensive gene-gene interaction network may have functional importance in cancer. METHODS: We categorized 12 767 human genes into CCGs (n = 468), 1 (n = 5467), 2 (n = 5573), 3 (n = 915), and more than 3 steps (n = 416) removed from the nearest CCG in the Search Tool for the Retrieval of Interacting Genes/Proteins network. We estimated cancer-relevant functional importance in these neighborhood categories using 1) gene dependency score, which reflects the effect of a gene on cell viability after knockdown; 2) somatic mutation frequency in The Cancer Genome Atlas; 3) effect size that estimates to what extent a mutation in a gene enhances cell survival; and 4) negative selection pressure of germline protein-truncating variants in healthy populations. RESULTS: Cancer biology-related functional importance of genes decreases as their distance from the CCGs increases. Genes closer to cancer genes show greater connectedness in the network, have greater importance in maintaining cancer cell viability, are under greater negative germline selection pressure, and have higher somatic mutation frequency in cancer. Based on these 4 metrics, we provide cancer relevance annotation to known human genes. CONCLUSIONS: A large number of human genes are connected to CCGs and could influence cancer biology to various extent when dysregulated; any given mutation may be functionally important in one but not in another individual depending on genomic context.
Authors: Thomas Rolland; Murat Taşan; Benoit Charloteaux; Samuel J Pevzner; Quan Zhong; Nidhi Sahni; Song Yi; Irma Lemmens; Celia Fontanillo; Roberto Mosca; Atanas Kamburov; Susan D Ghiassian; Xinping Yang; Lila Ghamsari; Dawit Balcha; Bridget E Begg; Pascal Braun; Marc Brehme; Martin P Broly; Anne-Ruxandra Carvunis; Dan Convery-Zupan; Roser Corominas; Jasmin Coulombe-Huntington; Elizabeth Dann; Matija Dreze; Amélie Dricot; Changyu Fan; Eric Franzosa; Fana Gebreab; Bryan J Gutierrez; Madeleine F Hardy; Mike Jin; Shuli Kang; Ruth Kiros; Guan Ning Lin; Katja Luck; Andrew MacWilliams; Jörg Menche; Ryan R Murray; Alexandre Palagi; Matthew M Poulin; Xavier Rambout; John Rasla; Patrick Reichert; Viviana Romero; Elien Ruyssinck; Julie M Sahalie; Annemarie Scholz; Akash A Shah; Amitabh Sharma; Yun Shen; Kerstin Spirohn; Stanley Tam; Alexander O Tejeda; Shelly A Trigg; Jean-Claude Twizere; Kerwin Vega; Jennifer Walsh; Michael E Cusick; Yu Xia; Albert-László Barabási; Lilia M Iakoucheva; Patrick Aloy; Javier De Las Rivas; Jan Tavernier; Michael A Calderwood; David E Hill; Tong Hao; Frederick P Roth; Marc Vidal Journal: Cell Date: 2014-11-20 Impact factor: 41.582
Authors: Matthew H Bailey; Collin Tokheim; Eduard Porta-Pardo; Sohini Sengupta; Denis Bertrand; Amila Weerasinghe; Antonio Colaprico; Michael C Wendl; Jaegil Kim; Brendan Reardon; Patrick Kwok-Shing Ng; Kang Jin Jeong; Song Cao; Zixing Wang; Jianjiong Gao; Qingsong Gao; Fang Wang; Eric Minwei Liu; Loris Mularoni; Carlota Rubio-Perez; Niranjan Nagarajan; Isidro Cortés-Ciriano; Daniel Cui Zhou; Wen-Wei Liang; Julian M Hess; Venkata D Yellapantula; David Tamborero; Abel Gonzalez-Perez; Chayaporn Suphavilai; Jia Yu Ko; Ekta Khurana; Peter J Park; Eliezer M Van Allen; Han Liang; Michael S Lawrence; Adam Godzik; Nuria Lopez-Bigas; Josh Stuart; David Wheeler; Gad Getz; Ken Chen; Alexander J Lazar; Gordon B Mills; Rachel Karchin; Li Ding Journal: Cell Date: 2018-08-09 Impact factor: 66.850