Breast cancer is the most frequently diagnosed cancer and the second leading cause of cancer death in American women. Postoperative adjuvant radiotherapy (RT) significantly reduces local-regional recurrence and breast cancer death. However, some patients experience moist desquamation as early adverse skin reactions (EASRs) and fibrosis as late effect. Underserved minorities are less likely than Whites to receive the recommended adjuvant RT and if treated, have a higher risk for developing RT-related EASRs and worse clinical outcomes. Therefore, to achieve our long-term goals in improving quality of life and reducing breast cancer mortality, the primary objective of the proposed research is to develop and validate two immune and inflammatory biomarkers in predicting RT-induced EASRs and quality of life. We will test the overall working hypothesis that worse clinical outcomes, such as RT-induced EASRs, late effects, and recurrence occur more frequently in women with: (i) modulated immune response and (ii) stimulated inflammation and hyper-radio-sensitivity. We will test a new paradigm that combined immune and inflammatory responses contribute to individual variations in radio-sensitivity that may predict RT-induced adverse reactions and clinical outcomes. Investigating this new paradigm will develop powerful tools in identifying high-risk populations and targets for personalized intervention and therapeutic strategies, such as immunotherapies and anti-inflammatory agents. Capitalizing on existing plasma samples and extensive clinical data from 1,200 breast cancer patients (400 black or African Americans, 400 Hispanic Whites, and 400 non-Hispanic Whites), this extremely cost-effective proposed research will be the first and the largest tri-racial/ethnic study evaluating th association between RT- induced EASRs and: (i) a pleiotropic immunosuppressive cytokine, transforming growth factor-beta (TGF-), (ii) an inflammatory biomarker, C-reactive protein (CRP), and (iii) the combined effects of TGF- and CRP after adjustment for potential confounders or effect modifiers, such as age, race/ethnicity, body mass index, tumor stage, smoking status, other medical conditions, RT dose, and breast volume. Capitalizing on the existing samples and clinical data from a large breast cancer patient population, promising pilot data, strong institutional support, and established laboratory assays, we are in an exceptional position to carry out the proposed research. Overall Impact: Using a hypothesis-driven strategy to rationally design the proposed research, the anticipated outcome will significantly impact the desperately needed innovative biomarker development and validation for basic, preventative, diagnostic, translational, epidemiological, health disparities, and clinical cancer research. As we learn more about underlined molecular mechanisms of RT-induced EASRs and clinical outcomes, the knowledge gained will significantly impact precision medicine and ensure that every breast cancer patient gets the most optimal treatment(s) with maximal efficacy and minimal side effects, particularly in underserved minorities with worse treatment response, side effects, and survival.