Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines
Top Cited Papers
Open Access
- 3 March 2014
- journal article
- research article
- Published by Springer Science and Business Media LLC in Genome Biology
- Vol. 15 (3), R47
- https://doi.org/10.1186/gb-2014-15-3-r47
Abstract
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.Keywords
This publication has 50 references indexed in Scilit:
- Gene Expression Classification of Colon Cancer into Molecular Subtypes: Characterization, Validation, and Prognostic ValuePLoS Medicine, 2013
- Machine Learning Prediction of Cancer Cell Sensitivity to Drugs Based on Genomic and Chemical PropertiesPLOS ONE, 2013
- Systematic identification of genomic markers of drug sensitivity in cancer cellsNature, 2012
- The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivityNature, 2012
- Intrinsic Subtypes of Gastric Cancer, Based on Gene Expression Pattern, Predict Survival and Respond Differently to ChemotherapyGastroenterology, 2011
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive modelsNature Biotechnology, 2010
- New response evaluation criteria in solid tumours: Revised RECIST guideline (version 1.1)European Journal of Cancer, 2009
- The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurementsNature Biotechnology, 2006
- A Gene-Expression Signature as a Predictor of Survival in Breast CancerThe New England Journal of Medicine, 2002
- CRITERIA FOR EVALUATING DISEASE RESPONSE AND PROGRESSION IN PATIENTS WITH MULTIPLE MYELOMA TREATED BY HIGH‐DOSE THERAPY AND HAEMOPOIETIC STEM CELL TRANSPLANTATIONBritish Journal of Haematology, 1998