Journal
GENOME BIOLOGY
Volume 15, Issue 3, Pages -Publisher
BMC
DOI: 10.1186/gb-2014-15-3-r47
Keywords
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Funding
- Wellcome Trust Sanger Institute
- National Institutes of Health/National Institute of General Medical Science (Pharmacogenomics of Anticancer Agents grant) [U01GM61393]
- National Institute of General Medical Science [K08 (GM089941)]
- Circle of Service Foundation Early Career Investigator award
- National Cancer Institute [R21 (CA139278)]
- University of Chicago Cancer Center Support Grant [P30 CA14599]
- University of Chicago Breast Cancer SPORE Career Development Award [CA125183]
- Conquer Cancer Foundation of ASCO
- National Center for Advancing Translational Sciences of the National Institutes of Health [UL1RR024999]
- NATIONAL CANCER INSTITUTE [P50CA125183, P30CA014599, R21CA139278] Funding Source: NIH RePORTER
- NATIONAL CENTER FOR RESEARCH RESOURCES [UL1RR024999] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U01GM061393, K08GM089941] Funding Source: NIH RePORTER
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We demonstrate a method for the prediction of chemotherapeutic response in patients using only before-treatment baseline tumor gene expression data. First, we fitted models for whole-genome gene expression against drug sensitivity in a large panel of cell lines, using a method that allows every gene to influence the prediction. Following data homogenization and filtering, these models were applied to baseline expression levels from primary tumor biopsies, yielding an in vivo drug sensitivity prediction. We validated this approach in three independent clinical trial datasets, and obtained predictions equally good, or better than, gene signatures derived directly from clinical data.
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