Abstract 7347: A transcriptome correlation network analysis of the high grade serous ovarian tumor immune microenvironment

Abstract High Grade Serous Ovarian Cancer (HGSOC) affects many women and is the most common and lethal histopathological type of ovarian cancer. The molecular subtypes delineated by TCGA–mesenchymal, proliferative, immunoreactive, and differentiated subtypes, offer a sophisticated and innovative framework for HGSOC classification. These subtypes not only provide a detailed molecular characterization but also contribute to understanding the HGSOC Tumor Immune Microenvironment (TIME), comprised of both immune and tumor cells. The interplay within the TIME significantly influences pro- or anti-tumor responses, creating an important link between molecular landscape and dynamic immune-tumor interactions. Currently, there is a lack of understanding for the key drivers of clinical outcomes, molecular phenotypes, and diagnostic biomarkers for HGSOC. Here, we answer the question, does immune cell type, and proportion, drive clinical and molecular subtyping of primary HGSOC? Primary ovarian tumor samples from The Cancer Genome Atlas, TCGA (n=358) samples were collected and RNA-sequenced. FPKM values were used to construct the Weighted Gene Correlation Network Analysis (WGCNA), Gene Ontology (GO) and Proportion Estimations of Immune and Cancer cells (EPIC). Enrichment of HGSOC network module overlaps using a Fischer Exact Test were used to identify novel components of HGSOC progression that were significantly associated with clusters of highly correlated gene expression profiles, HGSOC stage, grade, and molecular phenotypes. We show genes associated with T cell proliferation (CD84) and B cell regulation (CD37), epithelial to mesenchymal transition (DOCK2), adaptor proteins present in T cells and myeloid cells (LCP2), inflammatory and metabolic signaling modulators (AIF1, CD53, SASH3), immunosuppressors of T lymphocytes and dendritic cells (FGL2), cell proliferation (PI3K) and relevant tertiary lymphoid structure gene (TNFAIP8L2) significantly correlated with HGSOC progression in both estimated tumor and proportions of immune cells. Future studies aim to confirm phosphorylation cascades associated with the aggressive molecular phenotypes of HGSOC and immune cell pathobiology. Citation Format: Kaylin M. Carey, Eric B. Dammer, Corey Young, Rajesh Singh, Ti'ara Griffen, James W. Lillard. A transcriptome correlation network analysis of the high grade serous ovarian tumor immune microenvironment abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 7347.