Abstract B04: Immune modeling analysis identifies ICOS and CTLA-4 as predictive biomarkers in serous epithelial ovarian cancer

Objective: The goal of this study is to comprehensively determine the most clinically relevant immune checkpoint receptor in epithelial ovarian cancer (EOC). Methods: Stage III, Grade III EOC formalin-fixed, paraffin-embedded (FFPE) tumors from ten patients were submitted to Cofactor Genomics to undergo RNA sequencing and machine learning analysis to determine immune cell content and levels of the ten most studied immune escape genes. Patient samples were stratified by high progression-free survival (PFS) of 65 months or greater (n=5) and low PFS of 7 months or less (n=5). All patient tumors submitted were from primary debulking surgery and were naive to chemotherapy. Immunohistochemistry (IHC) was employed to validate findings. Results: The two immune escape genes ICOS and CTLA-4 were found to be the most predictive biomarkers differentiating short and long PFS. ICOS median transcripts per million (TPM) were 418 and 1,621 in patients with short and long PFS, respectively (p Conclusions: Immune modeling analysis revealed ICOS and CTLA-4 as the most predictive immune biomarkers for PFS in EOC. Interestingly, it was discovered that levels of both activating and inhibitory immune checkpoint receptors correlate to a higher percentage of immune cell populations, indicating overall immune content is important in predicting improved outcomes. Future directions include repeating this assay in a larger patient cohort to validate the predictive threshold determined for ICOS and CTLA-4. Citation Format: Nicole James, Matthew Oliver, Joyce Ou, Jenna Emerson, Katherine Miller, Erin Lips, Ashley Borgstadt, Paul DiSilvestro, Jennifer Ribeiro. Immune modeling analysis identifies ICOS and CTLA-4 as predictive biomarkers in serous epithelial ovarian cancer [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr B04.