Abstract 1592: Identifying novel drivers of the epithelial-to-mesenchymal transition across multiple cancer types: from bioinformatics to the bench

To emigrate from a primary tumor to a distant site, a proliferating cancer cell must acquire the phenotypic traits necessary for migration and invasion. This shift from “growing” to “going,” termed epithelial-to-mesenchymal transition (EMT), may be a genetic or epigenetic phenomenon, ultimately characterized by altered cellular function that promotes metastasis. In addition to its role in malignant progression, EMT is integral in development and for healthy wound healing. EMT has been described in all carcinomas, and, because it of its established physiologic role, we hypothesize that there are a set of central EMT regulators that are universal to all carcinoma types. To identify global regulators of EMT, we integrated data from 15 published gene expression microarray studies that include a total of 49 epithelial and 46 mesenchymal cell line samples across 6 malignant tissue types (breast, prostate, colon, esophageal, liver, retinal pigment) and with various in vitro EMT induction strategies. While accounting for batch effects and other technical variability inherent in gene expression data, we performed differential expression analysis to identify genes that vary significantly between epithelial and mesenchymal states. Importantly, we found differential expression of established EMT markers (e.g. CDH1, ZEB1) validating our approach. We also identified genes that had not previously been implicated in cancer progression, representing novel candidate drivers of EMT, for example SARG (C1orf116). We found that SARG expression is decreased in high-grade cancer and metastatic disease, and is negatively associated with chemotherapy resistance across multiple cancer types (Oncomine). In an in vitro model of prostate cancer EMT, we found that SARG had >5-fold increased RNA and protein expression in PC3-epithelial cells. Knockdown of SARG expression in PC3-epithelial cells resulted in decreased gene expression of the epithelial-marker CDH1 and elevated expression of the mesenchymal marker CDH2, suggesting a role as a driver of the epithelial phenotype. In parallel with functional in vitro experiments, we have applied a Bayesian network learning approach to identify differentially expressed genes that are likely to play regulatory roles in EMT with causal influence on other genes. Importantly, this analysis provides valuable information regarding novel downstream effectors of known key regulators of EMT such as CDH1 and ELF3. Moreover, we also identified new EMT regulators such as CEP170 that have not been previously described. Experiments are underway to further explore the functional implications of these gene networks. This integrative approach of global gene expression analysis, network learning, and functional validation may identify causal genes and regulatory interactions in EMT, both expanding upon current knowledge and identifying novel drivers of this key metastatic process. Citation Format: Sarah R. Amend, Princy Parsana, James Hernandez, Alexis Battle, Kenneth J. Pienta. Identifying novel drivers of the epithelial-to-mesenchymal transition across multiple cancer types: from bioinformatics to the bench. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1592.