2816 - Evaluating Genomic Changes as Biomarkers of Chemoradiation Therapy Response in Locally Advanced Cervical Cancer
Presenter(s)
B. Nolasco1, S. F. Ehsan2, R. Wang2, X. Wu3, M. B. El Alam2, A. Fontillas2, J. K. Bronk2, T. Karpinets3, C. Kapadia4, X. Song3, P. A. Futreal3, J. Zhang3, A. H. Klopp5, and L. Colbert5; 1Albert Einstein College of Medicine, Bronx, NY, 2Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 3Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, 4Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX, 5Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX
Purpose/Objective(s): Cervical cancer remains a major global health burden, with over 650,000 new cases and 350,000 deaths annually. While concurrent chemoradiotherapy (CRT) is the standard of care, 30–40% of patients fail to achieve a complete response, and no validated biomarkers currently exist to predict treatment outcomes. Since most LACC patients receive CRT rather than surgery, opportunities for longitudinal genomic analyses are also limited. Unlike prior genomic studies that focus on treatment-naïve samples, this study tracks genomic changes before and after treatment, capturing shifts in response to CRT. Here, we employ a non-invasive tumor swab-based sampling technique (similar to a pap smear) to evaluate genomic changes before and after 5 weeks of CRT. We analyzed tumor mutational burden (TMB), predicted neoantigen (PNA) counts, predicted high-affinity NA (HPNA) counts, and APOBEC mutation fraction to determine their association with CRT response.
Materials/Methods: Seventy-six patients with histologically confirmed LACC underwent tumor swab collection at baseline and post-CRT. Samples were obtained using Isohelix DNA swabs of the cervical tumor, followed by whole-exome sequencing (WES) to assess TMB, PNA, HPNA, and APOBEC mutation fraction. CRT response was defined as a complete resolution of FDG activity at three-month PET/CT. We evaluated genomic changes pre- and post-CRT using paired t-tests, and independent t-tests to determine associations with CRT response and clinical characteristics. We generated Kaplan-Meier survival curves to identify associations between genomic features and recurrence-free (RFS) and overall survival (OS), while Cox models evaluated independent associations, adjusting for smoking status. Receiver operating characteristic (ROC) curves were used to identify potential predictive cutoffs for CRT response.
Results: All genomic features significantly decreased post-CRT (p < 0.001), reflecting reduced tumor burden. Higher baseline TMB and PNA counts were associated with CRT response in univariate analysis, with ROC analyses suggesting potential thresholds for response prediction. However, TMB and PNA were not independent predictors of RFS or OS in multivariable models. Never smoking was significantly associated with improved RFS (HR = 0.43, p = 0.04), but not OS (p = 0.87).
Conclusion: These findings highlight genomic changes observed before and after CRT in cervical cancer. While TMB and PNA were not independent survival predictors, their treatment-related decline and ROC-defined thresholds suggest a potential role in response prediction. Further validation is needed to determine their clinical utility in guiding CRT outcomes.