RadioGx Computational Platform to Predict Radiation Response Genetic Markers

<h1>Radiation Response Genetic Markers study</h1> <p>This study presents an innovative approach to improving the prediction of radiation sensitivity in cancer treatments by developing genomic predictors using large-scale radiogenomics datasets and focusing on the integral of the radiation dose-response curve (AUC) as a measure of intrinsic radiation sensitivity. Researchers built and utilized the computational platform RadioGx for the study.</p> <h1>Results</h1> <p>By analyzing radiogenomic datasets containing 511 and 60 cancer cell lines, the research highlights the superiority of AUC over traditional SF2 (survival fraction at 2 Gy) in capturing a broader range of molecular processes affecting radiation response.</p> <p><a href="https://medium.medicalnewsobserver.com/radiogx-computational-platform-to-predict-radiation-response-genetic-markers-c7912b5dee65"><strong>Website</strong></a></p>