CONCORD biomarker prediction for novel drug introduction to different cancer types

// Youngchul Kim 1 , Patrick M. Dillon 2 , Taesung Park 3 and Jae K. Lee 1 1 Department of Biostatistics and Bioinformatics, Moffitt Cancer Center, Tampa, FL, USA 2 Division of Hematology/Oncology, University of Virginia, Charlottesville, VA, USA 3 Department of Statistics, Seoul National University, Seoul, Korea Correspondence to: Jae K. Lee, email: jae.lee@moffitt.org Keywords: gene expression model; drug repositioning; anticancer compound screening; cancer cell line; anti-cancer drug response prediction Received: November 18, 2016      Accepted: November 13, 2017      Published: December 09, 2017 ABSTRACT Many cancer therapeutic agents have shown to be effective for treating multiple cancer types. Yet major challenges exist toward introducing a novel drug used in one cancer type to different cancer types, especially when a relatively small number of patients with the other cancer type often benefit from anti-cancer therapy with the drug. Recently, many novel agents were introduced to different cancer types together with companion biomarkers which were obtained or biologically assumed from the original cancer type. However, there is no guarantee that biomarkers from one cancer can directly predict a therapeutic response in another. To tackle this challenging question, we have developed a concordant expression biomarker-based technique (“CONCORD”) that overcomes these limitations. CONCORD predicts drug responses from one cancer type to another by identifying concordantly co-expressed biomarkers across different cancer systems. Application of CONCORD to three standard chemotherapeutic agents and two targeted agents demonstrated its ability to accurately predict the effectiveness of a drug against new cancer types and predict therapeutic response in patients.