Identifying a molecular profile to predict the risk of recurrence in high‐intermediate risk endometrial cancer. (2nd November 2021) - Arend, Rebecca C.; Scalise, Carly B.; Dholakia, Jhalak; Kamal, Maahum Z.; Thigpen, Haley B.; Crossman, David; Huh, Warner K.; Leath, Charles A.
Abstract: Background: Patients with high‐intermediate risk endometrial cancer (H‐IR EMCA) have an elevated risk of recurrence compared to low‐risk counterparts. Many H‐IR EMCA patients are treated with radiation or chemotherapy, but their overall survival is not significantly impacted by treatment. The objective of this study was to compare molecular profiles of H‐IR EMCA patients with disease recurrence to those without to identify characteristics that could better predict patient outcomes. Methods: Tissue was acquired from H‐IR EMCA patients with disease recurrence (n=15) and without disease recurrence (n=15) who had not received adjuvant therapy and performed DNA and RNA analyses. Results: In recurrent population, 5 patients had matchingrecurrent and initial tumor tissues. Of note, 5/7 (71%) African Americanpatients had disease recurrence compared to 10/23 (43%) White patients. Inaddition, several new mutations were found in individual patient's recurrentcompared to initial tumors. Conclusions: Currently the treatment ofendometrial cancer is rapidly changing with molecular profiling becoming partof the standard of care. Additionally, it and is being incorporated intoclinical trials in this group of patients. The specific gene mutations and RNAexpression signatures that were observed in our small cohort need to bevalidated in larger cohorts to determine their impact. Abstract : In gynecologic oncology, endometrial cancer (EMCA) patients considered high‐intermediate risk (H‐IR) have elevated recurrence compared to low‐risk patients. In this study, we compared changes in DNA and RNA between 15 H‐IR patients with disease recurrence to 15 H‐IR patients without disease recurrence. This comparison allowed for us to highlight the specific players that contributed to a patient's disease recurrence, and in doing so, expose vulnerable parts of the cancer that we could use to better predict patient treatment strategies and outcomes.