This proposal focuses on those drugs that are commonly utilized for the treatment of adult solid tumors, including both modern "targeted" oncology drugs, as well as cytotoxic agents. This includes studies of new candidate genes identified through recently completed genome-wide studies, both clinical and in the HapMap lymphoblastoid cell lines (LCLs). A central strategy of the proposal is the development of endophenotypes that are intermediate between clinical phenotypes, such as adverse events and measures of efficacy, and the genetic variants that affect their risk. All research projects are classified as primarily phenotype-centric, drug-centric, or gene-centric. The phenotype-centric studies will focus on markers of gene activity, such as the transcriptome, or potentially serum proteomic markers. The drug-centric studies will focus on drugs of importance for adult solid tumors. The gene-centric studies generally focus in a detailed way on candidate genes identified through these other studies. The overall goal is to identify functional relationships at the intersection of drug, gene, and phenotype, particularly those phenotypes that are affected by one or more functional polymorphisms when patients are treated with a specific anticancer drug (at a clinically relevant dose). Mathematically, this can be described by a multidimensional matrix (to be made publicly available through a PGScore database) of variation in a specific gene (or polymorphism) on the effects of a drug as measured by a specific phenotype. A consistent framework is utilized to address questions relevant to six interrelated Themes (Cytotoxicity, Transcriptome, Irinotecan, Angiogenesis, UGT, and EGFR), supported by two Platforms (Clinical Studies and Functional Studies) and four Cores (Management, Genetics-Informatics-Statistics, Liver, and LCL). Extensive collaborative clinical studies are proposed with CALGB, as well as other current PGRN Groups. Other ongoing collaborations will be continued, including studies of glucuronidation and LCLs. In addition, a new Network Resource is proposed. Cell Lines as a Resource for Pharmacogenomic Studies.
There is marked variability in pharmacological response to anticancer agents, which historically have been characterized by severe toxicity and inconsistent efficacy. This proposal aims to characterize the genomic basis for this variability through a series of interrelated studies addressing a breadth of modern and classical anticancer agents. This will include both laboratory and translational clinical studies.
|Hansel, Marc C; Davila, Julio C; Vosough, Massoud et al. (2016) The Use of Induced Pluripotent Stem Cells for the Study and Treatment of Liver Diseases. Curr Protoc Toxicol 67:14.13.1-14.13.27|
|Gammal, R S; Court, M H; Haidar, C E et al. (2016) Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for UGT1A1 and Atazanavir Prescribing. Clin Pharmacol Ther 99:363-9|
|Crona, D J; Ramirez, J; Qiao, W et al. (2016) Clinical validity of new genetic biomarkers of irinotecan neutropenia: an independent replication study. Pharmacogenomics J 16:54-9|
|Morrison, Gladys; Liu, Cong; Wing, Claudia et al. (2016) Evaluation of inter-batch differences in stem-cell derived neurons. Stem Cell Res 16:140-8|
|French, Juliet D; Johnatty, Sharon E; Lu, Yi et al. (2016) Germline polymorphisms in an enhancer of PSIP1 are associated with progression-free survival in epithelial ovarian cancer. Oncotarget 7:6353-68|
|Geeleher, Paul; Cox, Nancy J; Huang, R Stephanie (2016) Cancer biomarker discovery is improved by accounting for variability in general levels of drug sensitivity in pre-clinical models. Genome Biol 17:190|
|Hertz, Daniel L; Owzar, Kouros; Lessans, Sherrie et al. (2016) Pharmacogenetic Discovery in CALGB (Alliance) 90401 and Mechanistic Validation of a VAC14 Polymorphism that Increases Risk of Docetaxel-Induced Neuropathy. Clin Cancer Res 22:4890-4900|
|Morrison, Gladys; Lenkala, Divya; LaCroix, Bonnie et al. (2016) Utility of patient-derived lymphoblastoid cell lines as an ex vivo capecitabine sensitivity prediction model for breast cancer patients. Oncotarget 7:38359-38366|
|Gamazon, Eric R; Wheeler, Heather E; Shah, Kaanan P et al. (2015) A gene-based association method for mapping traits using reference transcriptome data. Nat Genet 47:1091-8|
|Wassenaar, Catherine A; Conti, David V; Das, Soma et al. (2015) UGT1A and UGT2B genetic variation alters nicotine and nitrosamine glucuronidation in european and african american smokers. Cancer Epidemiol Biomarkers Prev 24:94-104|
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