title: Development of a Drug-Response Modeling Framework to Identify Cell Line Derived Translational Biomarkers That Can Predict Treatment Outcome to Erlotinib or Sorafenib.
abstract: Development of drug responsive biomarkers from pre-clinical data is a critical step in drug discovery, as it enables patient stratification in clinical trial design. Such translational biomarkers can be validated in early clinical trial phases and utilized as a patient inclusion parameter in later stage trials. Here we present a study on building accurate and selective drug sensitivity models for Erlotinib or Sorafenib from pre-clinical in vitro data, followed by validation of individual models on corresponding treatment arms from patient data generated in the BATTLE clinical trial. A Partial Least Squares Regression (PLSR) based modeling framework was designed and implemented, using a special splitting strategy and canonical pathways to capture robust information for model building. Erlotinib and Sorafenib predictive models could be used to identify a sub-group of patients that respond better to the corresponding treatment, and these models are specific to the corresponding drugs. The model derived signature genes reflect each drug's known mechanism of action. Also, the models predict each drug's potential cancer indications consistent with clinical trial results from a selection of globally normalized GEO expression datasets.
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: Bin
authors.initials: B
authors.lastname: Li
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: Hyunjin
authors.initials: H
authors.lastname: Shin
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Georgy
authors.initials: G
authors.lastname: Gulbekyan
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Olga
authors.initials: O
authors.lastname: Pustovalova
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Yuri
authors.initials: Y
authors.lastname: Nikolsky
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Andrew
authors.initials: A
authors.lastname: Hope
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Marina
authors.initials: M
authors.lastname: Bessarabova
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: Matthew
authors.initials: M
authors.lastname: Schu
authors.affiliation: Thomson Reuters, 777 E. Eisenhower Parkway, Ann Arbor, Michigan, 48108, United States of America.
authors.forename: Elona
authors.initials: E
authors.lastname: Kolpakova-Hart
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: David
authors.initials: D
authors.lastname: Merberg
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: Andrew
authors.initials: A
authors.lastname: Dorner
authors.affiliation: Department of Translational Medicine, Takeda Pharmaceuticals International Co., 35 Landsdowne St., Cambridge, Massachusetts, 02139, United States of America.
authors.forename: William L
authors.initials: WL
authors.lastname: Trepicchio
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology*; D054316:Biomarkers, Pharmacological; D045744:Cell Line, Tumor; D017322:Clinical Trials, Phase II as Topic; D004353:Drug Evaluation, Preclinical; D019008:Drug Resistance, Neoplasm / Q000235:genetics; D000069347:Erlotinib Hydrochloride / Q000494:pharmacology*; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000188:drug therapy* / Q000235:genetics / Q000401:mortality / Q000473:pathology; D009536:Niacinamide / Q000031:analogs & derivatives* / Q000494:pharmacology; D010671:Phenylurea Compounds / Q000494:pharmacology*; D015398:Signal Transduction; D000077157:Sorafenib; D016019:Survival Analysis
chemical_list: D000970:Antineoplastic Agents; D054316:Biomarkers, Pharmacological; D010671:Phenylurea Compounds; D009536:Niacinamide; D000077157:Sorafenib; D000069347:Erlotinib Hydrochloride