Modelling of radiation therapeutic effects on cancer cell lines
Radiotherapy is the foundation of curative treatment regimens for many cancer types and is often delivered with drugs to produce synergistic effects. There is a need for greater personalization of radiation delivery, both with regard to radiation dose as well as selection of the most appropriate drugs. To support preclinical discovery of biomarker-directed radiation dose and drug combinations, we developed a computational platform, RadioGx, for integrating and investigating radiogenomics data sets. In this talk, I will present some of the key results based on the efficacy of radiation therapy on cancer cell lines using the RadioGx platform. Our results show that the radiation responses are concordant using traditional and high-throughput
clonogenic assays. In addition, we found that drugs that have genetic dependencies similar to radiation under normoxia are enriched in mitosis, DNA replication and Cytoskeleton pharmacological classes. Additionally, the pathway analysis revealed 74 and 53 pathways (False Discovery Rate<5%) that are enriched using Area Under the Curve (AUC) under the linear quadratic model and Surviving fraction at 2Gy (SF2) respectively, out of which 41 are in common, indicating the biological plausibility and robustness of the clinical radioresponse indicators. Using the oxygen modification factor in established radiobiological models, the pathway analysis of radiation response under hypoxia revealed two key DNA repair pathways, namely, DNA double strand break repair by NHEJ and DNA damage-induced 14-3-3, to be enriched compared to normoxic conditions.
Our platforms facilitates the analysis of preclinical models of radiation response using in vitro survival and transcriptomic data. Our results support the need to analyze preclinical models before translating to the clinic to build an assay that can predict radiation sensitivity. We envision that our computational platform coupled with Pharmacogx will influence the preclinical decisions of radiation response, and help validate the predictive power for efficacy of radiotherapy in interventional preclinical studies with appropriate biological endpoints.