Approximately 50% of cancer patients receiving ionizing radiation suffer from radiation-induced normal tissue injury that significantly affects quality of life and presents potentially life-threatening consequences in 5-10% of the cases. Due to a large range of interpatient variability, the amount of radiation delivered to all patients is largely guided by the tolerance of more radiosensitive individuals. Significant associations with biological genetic determinates of interpatient variability to radiation responses from alleles with differing frequencies by population ancestry will form the basis of our study. A better understanding of genetic factors that might contribute to a deterministic radiation response would mitigate unwanted medical complications. The a priori identification of genetic variants associated with increased radiation damage would be immensely useful for optimizing radiation dose through predictive screening to allow creation of novel patient cohorts. We will use an in vitro approach and apply genomics, transcriptomics, and functional modeling towards advanced determination of individual genotypes most at risk for enhanced radiation sensitivity. An in-house panel of 100 normal-tissue derived epithelial cell cultures from prostate and breast cancer patients will be used with exposure to ionizing irradiation. A focus on individuals with differing genetic ancestry will be used for this purpose. Radiation response will be quantified individually and in groups as continuous variables dependent on genetic variants and gene expression following radiation exposure in association with statistical modeling to find genetic loci and epistatic SNP-SNP interactions. In order to enlarge the scope and clinical relevance of our study, we will correlate our findings to previously acquired germline DNA samples from patients treated with radiation with available clinical data as well as radiation toxicity scores. The specific aims are: 1) to quantify the association of interpatient radiation resistance and sensitivity with polygenic exome coding germline variants and gene expression using a radiation associated senescence-associated secretory phenotype that is associated with pro-inflammatory cytokines and 2) screen DNA samples from radiation therapy patients with known toxicity scores and perform preliminary functional testing to modulate radiation sensitivity in vitro for germline radiation associated variants. The results of this proposal will provide a novel platform to screen for predictive variants in animal models and patients. This will bring us one step closer to genomically guided radiation treatment and enable the investigation novel mechanisms involved in radiation sensitivity.