Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors.
Discovering functional modules by identifying recurrent and mutually exclusive mutational patterns in tumors.
复制标题
通过识别肿瘤中的复发和相互排斥的突变模式来发现功能模块。
DOI：
10.1186/1755-8794-4-34
复制
发表时间：
2011-04-14
影响因子：
2.7
通讯作者：
Milosavljevic A
中科院分区：
文献类型：
--
作者：
Miller CA;Settle SH;Sulman EP;Aldape KD;Milosavljevic A
多个肿瘤样本的分析经常揭示复发性基因组畸变，包括影响单个基因的点突变和拷贝数改变。超出单个基因的分析通常仅限于检查已知的途径，相互作用和功能模块。我们提出了一种方法，确定功能模块没有任何信息以外的模式的复发和相互排斥的畸变（RME模式），出现由于积极选择的关键癌症表型。我们的算法有效地构建和搜索网络的潜在的相互作用，并确定显着的模块（RME模块），通过使用算法的显着性测试。我们将该方法应用于145个胶质母细胞瘤样本的TCGA收集，从而扩展了已知的通路并发现了新的功能模块。该方法预测了以前在胶质母细胞瘤中未知的EP300的作用。我们通过验证EP300的表达是预后性的，可以独立于诊断时的年龄和肿瘤分级来预测生存率，从而证明了这些结果的临床相关性。我们已经开发了一种灵敏，简单，快速的方法，用于自动检测功能模块在肿瘤的基础上复发性基因组畸变的模式。由于它能够分析大量不同的数据，我们希望它在不久的将来应用于许多计划进行检测的肿瘤组时越来越有用。
Assays of multiple tumor samples frequently reveal recurrent genomic aberrations, including point mutations and copy-number alterations, that affect individual genes. Analyses that extend beyond single genes are often restricted to examining pathways, interactions and functional modules that are already known. We present a method that identifies functional modules without any information other than patterns of recurrent and mutually exclusive aberrations (RME patterns) that arise due to positive selection for key cancer phenotypes. Our algorithm efficiently constructs and searches networks of potential interactions and identifies significant modules (RME modules) by using the algorithmic significance test. We apply the method to the TCGA collection of 145 glioblastoma samples, resulting in extension of known pathways and discovery of new functional modules. The method predicts a role for EP300 that was previously unknown in glioblastoma. We demonstrate the clinical relevance of these results by validating that expression of EP300 is prognostic, predicting survival independent of age at diagnosis and tumor grade. We have developed a sensitive, simple, and fast method for automatically detecting functional modules in tumors based solely on patterns of recurrent genomic aberration. Due to its ability to analyze very large amounts of diverse data, we expect it to be increasingly useful when applied to the many tumor panels scheduled to be assayed in the near future.
登录
查看更多内容
影响因子：
4.8
作者：
Dornan, D;Shimizu, H;Hupp, TR
通讯作者：
Hupp, TR
影响因子：
30.8
作者：
Segal, E;Friedman, N;Regev, A
通讯作者：
Regev, A
影响因子：
2.1
作者：
Olshen, AB;Venkatraman, ES;Wigler, M
通讯作者：
Wigler, M
影响因子：
56.9
作者：
Tomlins, SA;Rhodes, DR;Chinnaiyan, AM
通讯作者：
Chinnaiyan, AM
影响因子：
64.8
作者：
Chin, L.;Meyerson, M.;Aldape, K.;Bigner, D.;Mikkelsen, T.;VandenBerg, S.;Kahn, A.;Penny, R.;Ferguson, M. L.;Gerhard, D. S.;Getz, G.;Brennan, C.;Taylor, B. S.;Winckler, W.;Park, P.;Ladanyi, M.;Hoadley, K. A.;Verhaak, R. G. W.;Hayes, D. N.;Spellman, Paul T.;Absher, D.;Weir, B. A.;Ding, L.;Wheeler, D.;Lawrence, M. S.;Cibulskis, K.;Mardis, E.;Zhang, Jinghui;Wilson, R. K.;Donehower, L.;Wheeler, D. A.;Purdom, E.;Wallis, J.;Laird, P. W.;Herman, J. G.;Schuebel, K. E.;Weisenberger, D. J.;Baylin, S. B.;Schultz, N.;Yao, Jun;Wiedemeyer, R.;Weinstein, J.;Sander, C.;Gibbs, R. A.;Gray, J.;Kucherlapati, R.;Lander, E. S.;Myers, R. M.;Perou, C. M.;McLendon, Roger;Friedman, Allan;Van Meir, Erwin G;Brat, Daniel J;Mastrogianakis, Gena Marie;Olson, Jeffrey J;Lehman, Norman;Yung, W. K. Alfred;Bogler, Oliver;Berger, Mitchel;Prados, Michael;Muzny, Donna;Morgan, Margaret;Scherer, Steve;Sabo, Aniko;Nazareth, Lynn;Lewis, Lora;Hall, Otis;Zhu, Yiming;Ren, Yanru;Alvi, Omar;Yao, Jiqiang;Hawes, Alicia;Jhangiani, Shalini;Fowler, Gerald;San Lucas, Anthony;Kovar, Christie;Cree, Andrew;Dinh, Huyen;Santibanez, Jireh;Joshi, Vandita;Gonzalez-Garay, Manuel L.;Miller, Christopher A.;Milosavljevic, Aleksandar;Sougnez, Carrie;Fennell, Tim;Mahan, Scott;Wilkinson, Jane;Ziaugra, Liuda;Onofrio, Robert;Bloom, Toby;Nicol, Rob;Ardlie, Kristin;Baldwin, Jennifer;Gabriel, Stacey;Fulton, Robert S.;McLellan, Michael D.;Larson, David E.;Shi, Xiaoqi;Abbott, Rachel;Fulton, Lucinda;Chen, Ken;Koboldt, Daniel C.;Wendl, Michael C.;Meyer, Rick;Tang, Yuzhu;Lin, Ling;Osborne, John R.;Dunford-Shore, Brian H.;Miner, Tracie L.;Delehaunty, Kim;Markovic, Chris;Swift, Gary;Courtney, William;Pohl, Craig;Abbott, Scott;Hawkins, Amy;Leong, Shin;Haipek, Carrie;Schmidt, Heather;Wiechert, Maddy;Vickery, Tammi;Scott, Sacha;Dooling, David J.;Chinwalla, Asif;Weinstock, George M.;O'Kelly, Michael;Robinson, Jim;Alexe, Gabriele;Beroukhim, Rameen;Carter, Scott;Chiang, Derek;Gould, Josh;Gupta, Supriya;Korn, Josh;Mermel, Craig;Mesirov, Jill;Monti, Stefano;Nguyen, Huy;Parkin, Melissa;Reich, Michael;Stransky, Nicolas;Garraway, Levi;Golub, Todd;Protopopov, Alexei;Perna, Ilana;Aronson, Sandy;Sathiamoorthy, Narayan;Ren, Georgia;Kim, Hyunsoo;Kong, Sek Won;Xiao, Yonghong;Kohane, Isaac S.;Seidman, Jon;Cope, Leslie;Pan, Fei;Van Den Berg, David;Van Neste, Leander;Yi, Joo Mi;Li, Jun Z.;Southwick, Audrey;Brady, Shannon;Aggarwal, Amita;Chung, Tisha;Sherlock, Gavin;Brooks, James D.;Jakkula, Lakshmi R.;Lapuk, Anna V.;Marr, Henry;Dorton, Shannon;Choi, Yoon Gi;Han, Ju;Ray, Amrita;Wang, Victoria;Durinck, Steffen;Robinson, Mark;Wang, Nicholas J.;Vranizan, Karen;Peng, Vivian;Van Name, Eric;Fontenay, Gerald V.;Ngai, John;Conboy, John G.;Parvin, Bahram;Feiler, Heidi S.;Speed, Terence P.;Socci, Nicholas D.;Olshen, Adam;Lash, Alex;Reva, Boris;Antipin, Yevgeniy;Stukalov, Alexey;Gross, Benjamin;Cerami, Ethan;Wang, Wei Qing;Qin, Li-Xuan;Seshan, Venkatraman E.;Villafania, Liliana;Cavatore, Magali;Borsu, Laetitia;Viale, Agnes;Gerald, William;Topal, Michael D.;Qi, Yuan;Balu, Sai;Shi, Yan;Wu, George;Bittner, Michael;Shelton, Troy;Lenkiewicz, Elizabeth;Morris, Scott;Beasley, Debbie;Sanders, Sheri;Sfeir, Robert;Chen, Jessica;Nassau, David;Feng, Larry;Hickey, Erin;Schaefer, Carl;Madhavan, Subha;Buetow, Ken;Barker, Anna;Vockley, Joseph;Compton, Carolyn;Vaught, Jim;Fielding, Peter;Collins, Francis;Good, Peter;Guyer, Mark;Ozenberger, Brad;Peterson, Jane;Thomson, Elizabeth
通讯作者：
Thomson, Elizabeth