Precision Medicine: Biomarkers of Genome Integrity in Guiding Better Lung Cancer Outcomes

Abstract

Lung cancer remains the leading cause of cancer mortality, and standard treatments such as radiotherapy (RT) and chemotherapy act through DNA damage. Yet patients show substantial variability in both treatment response and side effects. Because DNA repair is central to maintaining genome integrity and differs across individuals and life stages, assessing genome integrity could help identify which patients will benefit most from therapy while minimizing harmful outcomes. My dissertation focuses on developing and applying genome-integrity biomarkers to better understand treatment response and prognosis in lung cancer. I focused on three complementary domains: functional DNA repair capacity measured by fluorescence multiplex host cell reactivation (FM-HCR), telomere length dynamics during and after RT, and germline genetic variation. Across this work, I established strategies to adapt functional DNA repair assays for population studies, demonstrating that they capture meaningful inter-individual differences. I showed that changes in telomere length over the course of treatment provide stronger signals for predicting side effects than single, static measurements. And by integrating genetic data with functional measures, I found that certain genetic variants influence repair capacity and contribute to differences in treatment toxicity and prognosis. Together, these studies highlight the value of linking functional and genomic measures of genome integrity. By bringing these approaches together, my work provides a framework for using genome-integrity biomarkers to guide more personalized RT decisions and improve long-term outcomes in lung cancer patients.