RT Journal Article
SR Electronic
T1 Modeling cellular response in large-scale radiogenomic databases to advance precision radiotherapy
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 449793
DO 10.1101/449793
A1 Venkata SK. Manem
A1 Meghan Lambie
A1 Petr Smirnov
A1 Victor Kofia
A1 Mark Freeman
A1 Marianne Koritzinsky
A1 Mohamed E. Abazeed
A1 Benjamin Haibe-Kains
A1 Scott V. Bratman
YR 2018
UL http://biorxiv.org/content/early/2018/10/22/449793.abstract
AB Radiotherapy is integral to the care of a majority of cancer patients. Despite differences in tumor responses to radiation (radioresponse), dose prescriptions are not currently tailored to individual patients. Recent large-scale cancer cell line databases hold the promise of unravelling the complex molecular arrangements underlying cellular response to radiation, which is critical to novel predictive biomarker discovery. Here, we present RadioGx, a computational platform for integrative analyses of radioresponse using radiogenomic databases. We first used RadioGx to investigate the robustness of radioresponse assays and indicators. We then combined radioresponse and genome-wide molecular data with established radiobiological models to predict molecular pathways that are relevant for individual tissue types and conditions. We also applied RadioGx to pharmacogenomic data to identify several classes of drugs whose effects correlate with radioresponse. RadioGx provides a unique computational toolbox to advance preclinical research for radiation oncology and precision medicine.