Grant Details
Grant Number: |
5R01CA161608-08 Interpret this number |
Primary Investigator: |
Reif, David |
Organization: |
North Carolina State University Raleigh |
Project Title: |
Genetic Etiology of Cancer Drug Response |
Fiscal Year: |
2020 |
Abstract
Abstract:
Important progress continues to be made in the treatment of most common cancers, but therapeutic benefit
remains difficult to predict and severe or fatal adverse events occur frequently. The Human Genome Project
has fueled the notion that genetic information can produce effective and cost-efficient selection of therapies for
individual patients, but validated genetic signatures that predict response to most chemotherapy regimens
remain to be identified. Numerous genes potentially influence drug response, but current candidate-gene
approaches are limited by the requirement of a priori knowledge about the genes involved and the moderate
size of most clinical trials often limits the power of in vitro genome wide association studies (GWAS) for cancer
pharmacogenomics discovery.
In response to these limitations, we have undertaken a thorough, pharmacogenomic assessment of cytotoxic
effect of the majority of FDA approved anti-cancer compounds using an ex vivo model system to determine the
heritability of drug-induced cell killing to prioritize drugs for pharmacogenomic mapping. These results are an
important first step, and while high heritability of a trait does not guarantee successful association mapping
results, it represents an important first step and the results will be used to prioritize drugs with high heritabilities
for genome-wide association mapping. In the current proposal, GWAS mapping of cytotoxic agents will be
performed in a European American population, and then replication GWAS mapping will be performed in an
East Asian population. In addition to discovering and validating genetic variants that predict drug response,
the wealth of data collected will be used to dissect the underlying etiology of drug response traits, including
assessing the relative contribution of genetic, environmental, and interaction components of variation. These
results will provide crucial insight to prioritize genetic variants for follow-up in precious clinical population
resources, and potentially reveal new insight into the overall etiology of drug responses.
Publications