The principle investigator's career goal is to be a successful translational researcher in the field of Clinical Pharmacology. With this Award, she plans to further her training in systems biology, statistical genetics and bioinformatics. She proposes to extend a genome-wide model developed during her fellowship to broader therapeutic application beyond chemotherapy and validate her findings in patient samples. The PI's long-term goal is to combine her patient care knowledge from Pharmacy school and research knowledge through her work in Pharmacogenetics to eventually improve the quality of life for patients. Dr. Eileen Dolan (Internationally recognized researcher in pharmacogenomics) will serve as the PI's main mentor;while Drs. Nancy Cox (internationally recognized statistical geneticist) and Mark Ratain (internationally recognized leader in pharmacogenetics and phase I trial design) will co-mentor the PI's scientific and career development. Her advisory committee consists of Drs. Scott Weiss, Julian Solway and Kelan Tantisira, who will provide scientific guidance in utilizing patient samples in studying pharmacogenomics markers for glucocorticoid (GC) sensitivity in asthma. An objective of this proposal is to take a concerted translational effort to elucidate the underlying cause for the inter-individual differences in sensitivity to GCs, one of the most commonly used agents in treating inflammatory diseases such as asthma, inflammatory bowel disease and arthritis. Our hypothesis is that a novel genome-wide model developed using International HapMap lymphoblastoid cell lines (LCLs) are suitable in identification of genetic polymorphisms as predictors of cellular sensitivity to GCs.
Our specific aims are 1) To develop and refine GC sensitivity phenotypic assays to quantify in vitro GC response and toxicity;2) To identify genetic polymorphisms that are associated with GC susceptibility phenotypes through gene expression;3) To validate candidate genetic variants/genes in patient samples. Our long-term goal is to predict patients "at risk" for adverse events and/or non-response prior to administration of GCs.
This proposal is intended to better understand how genetic variation contributes to individual sensitivity to GCs. The long term goal is to identify patients, using their genetic make up, that are at risk for toxicities and non- response associated with GCs with the intent to reduce their chances of an adverse event and improve their care.
|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|
|Wang, Fan; Chang, Jeremy T-H; Kao, Chester Jingshiu et al. (2016) High Expression of miR-532-5p, a Tumor Suppressor, Leads to Better Prognosis in Ovarian Cancer Both In Vivo and In Vitro. Mol Cancer Ther 15:1123-31|
|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|
|Chapin, William J; Lenkala, Divya; Mai, Yifeng et al. (2015) Peripheral blood IRF1 expression as a marker for glucocorticoid sensitivity. Pharmacogenet Genomics 25:126-33|
|Chang, Jeremy T-H; Lee, Yee Ming; Huang, R Stephanie (2015) The impact of the Cancer Genome Atlas on lung cancer. Transl Res 166:568-85|
|Lenkala, Divya; Gamazon, Eric R; LaCroix, Bonnie et al. (2015) MicroRNA biogenesis and cellular proliferation. Transl Res 166:145-51|
|Delaney, Christopher; Frank, Samuel; Huang, R Stephanie (2015) Pharmacogenomics of EGFR-targeted therapies in non-small cell lung cancer: EGFR and beyond. Chin J Cancer 34:149-60|
|Geeleher, Paul; Loboda, Andrey; Lenkala, Divya et al. (2015) Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics. J Natl Cancer Inst 107:|
|Geeleher, Paul; Cox, Nancy J; Huang, R Stephanie (2014) Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines. Genome Biol 15:R47|
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