title: Cancer in silico drug discovery: a systems biology tool for identifying candidate drugs to target specific molecular tumor subtypes.
abstract: Large-scale cancer datasets such as The Cancer Genome Atlas (TCGA) allow researchers to profile tumors based on a wide range of clinical and molecular characteristics. Subsequently, TCGA-derived gene expression profiles can be analyzed with the Connectivity Map (CMap) to find candidate drugs to target tumors with specific clinical phenotypes or molecular characteristics. This represents a powerful computational approach for candidate drug identification, but due to the complexity of TCGA and technology differences between CMap and TCGA experiments, such analyses are challenging to conduct and reproduce. We present Cancer in silico Drug Discovery (CiDD; scheet.org/software), a computational drug discovery platform that addresses these challenges. CiDD integrates data from TCGA, CMap, and Cancer Cell Line Encyclopedia (CCLE) to perform computational drug discovery experiments, generating hypotheses for the following three general problems: (i) determining whether specific clinical phenotypes or molecular characteristics are associated with unique gene expression signatures; (ii) finding candidate drugs to repress these expression signatures; and (iii) identifying cell lines that resemble the tumors being studied for subsequent in vitro experiments. The primary input to CiDD is a clinical or molecular characteristic. The output is a biologically annotated list of candidate drugs and a list of cell lines for in vitro experimentation. We applied CiDD to identify candidate drugs to treat colorectal cancers harboring mutations in BRAF. CiDD identified EGFR and proteasome inhibitors, while proposing five cell lines for in vitro testing. CiDD facilitates phenotype-driven, systematic drug discovery based on clinical and molecular data from TCGA.
authors.affiliation: The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas. Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas.
authors.forename: F Anthony
authors.initials: FA
authors.lastname: San Lucas
authors.affiliation: Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas.
authors.forename: Jerry
authors.initials: J
authors.lastname: Fowler
authors.affiliation: The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas.
authors.forename: Kyle
authors.initials: K
authors.lastname: Chang
authors.affiliation: The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas. Department of Gastrointestinal Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas.
authors.forename: Scott
authors.initials: S
authors.lastname: Kopetz
authors.affiliation: The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas. Department of Gastrointestinal Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas. Department of Clinical Cancer Prevention, The University of Texas M.D. Anderson Cancer Center, Houston, Texas. pscheet@alum.wustl.edu EVilar@mdanderson.org.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Vilar
authors.affiliation: The Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas. Department of Epidemiology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas. pscheet@alum.wustl.edu EVilar@mdanderson.org.
authors.forename: Paul
authors.initials: P
authors.lastname: Scheet
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology / Q000627:therapeutic use; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D066264:Datasets as Topic; D055808:Drug Discovery; D020869:Gene Expression Profiling; D006801:Humans; D009154:Mutation; D009369:Neoplasms / Q000188:drug therapy / Q000235:genetics*; D048493:Proto-Oncogene Proteins B-raf / Q000235:genetics; D015203:Reproducibility of Results; D012984:Software; D049490:Systems Biology / Q000379:methods*; D057188:Workflow
chemical_list: D000970:Antineoplastic Agents; C482119:BRAF protein, human; D048493:Proto-Oncogene Proteins B-raf