Abstract 3168: Helios identifies novel oncogenes in breast cancer by integrating genomic characterization of primary tumors and functional shRNA-screens.
Authors: Garcia Felix Sanchez , Villagrasa Patricia , Matsui Junji , Chen Bo-Juen , Kotliar Dylan , Castro Veronica , Silva Jose M. , Pe'er Dana 
Published: August 2014

Abstract
Genomic profiling of tumors has uncovered a staggering diversity of recurrent aberrations. However, inferring functionally important driver genes from this data remains difficult_particularly in the case of copy-number aberrations (CNAs) that often span many genes. Genome-wide functional shRNA screens have been a useful orthogonal approach for discovering drivers. The integration of observational data from primary tumors with functional data on cell lines provides an unprecedented opportunity for the identification of driver genes. Unfortunately, most current analysis is limited to naïve intersection of top scoring candidates and thus more powerful computational methods are needed. We have developed Helios, a novel Bayesian algorithm that integrates genomic data from primary tumors with functional shRNA screens in cell lines, gaining unprecedented sensitivity and specificity in identifying drivers. Applying Helios to TCGA breast cancer data led to the recapitulation of many known oncogenes as well as to the identification and validation of two novel oncogenes involved in chromatin regulation. Importantly, many of the drivers pinpointed by Helios were not identified on the basis of any one data type alone.
Helios uses shRNA data in a novel fashion by employing a new score measuring oncogene addiction, a phenotype associated with many key cancer drivers. It integrates this with CNA, sequence mutation, and RNA expression data into a single probabilistic score for each gene which is then used to assess the most-likely driver gene in a region of recurrent CNA.
We applied Helios to TCGA breast cancer data paired with two independent genome-wide shRNA screens on breast cancer cell lines. This identified many previously known oncogenes including FOXA1, ERBB2, PIK3CA, CCND1, IGF1R, BCL2, CDK4, ESR1, MYC, EGFR, GAB1, CCNE1, FGFR2, FGFR3, MYC as the top-scoring candidates in their respective amplified regions. We validated a number of novel predictions in vitro and selected two candidate oncogenes involved in chromatin remodeling for in depth follow up. The contribution of both genes to cancer was confirmed in vitro and in vivo, enhancing colony formation in agar and increasing tumor size in mouse models. One novel oncogene showed evidence of association with invasion and metastasis in a lung-cancer model. Another novel oncogene resides in a frequently amplified region in several epithelial cancers such as lung, bladder, stomach and ovarian carcinomas. Taken together, we have demonstrated that Helios is a powerful “in-silico” screen that can accelerate discovery of driver mutations in cancer.
Citation Format: Felix Sanchez Garcia, Patricia Villagrasa, Junji Matsui, Bo-Juen Chen, Dylan Kotliar, Veronica Castro, Jose M. Silva, Dana Pe'er. Helios identifies novel oncogenes in breast cancer by integrating genomic characterization of primary tumors and functional shRNA-screens. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3168. doi:10.1158/1538-7445.AM2013-3168