Abstract LB-C18: An integrated multiplexing approach for the immunoprofiling of the tumor microenvironment of ovarian granulosa cell tumors

Abstract

Abstract Background: Granulosa cell tumors (GCTs) are rare tumor in ovaries accounting for 2-5% of all ovarian cancers. The main current treatment for GCT is surgery, however a subset require chemotherapy for residual and recurrent disease. GCT malignancies are often low-grade with a five-year survival rate up to 90%, however a clinical characteristic of these tumors is a tendency for late recurrence and a high recurrent rate is the most critical factor for GCT death. As the onset of recurrence is unpredictable, future research should focus on identifying both biomarkers for prognosis prediction, as well as targets that could help guide clinical trials in the development of targeted therapies for this rare indication. As GCTs are rare tumors and tissue availability is very limited, we used a dual multiplexing approach in order to maximize the data output from a total of 14 FFPE tumor samples (6 primary tumors, and 8 recurrent tumors). With this approach we used a single 4 μm section to detect 15 markers in an IF multiplexing assay, and an adjacent 10 μm section to analyze expression of 770 immuno-related cancer genes with the aim to spatially profile T cell subsets, tumor-associated macrophages (TAMs), B cells, tumor proliferation, angiogenic vessels, as well as markers differentially expressed between primary and recurrent tumors. Methods: For protein multiplexing we have used MultiOmyx™, an immunofluorescence (IF) multiplexing assay utilizing a pair of directly conjugated Cyanine dye-labeled (Cy3, Cy5) antibodies per round of staining. Each round of staining is imaged and followed by dye inactivation, and deep learning based cell classification algorithms identify positive cells for each biomarker to identify a 15-marker panel consisting of CD3, CD4, CD8, FoxP3, CD68, CD163, HLA-DR, CD34, CTLA-4, PD-1, PD-L1, Ki67, vimentin, S100, and Pan Cytokeratin. Gene expression analysis was done using the Nanostring nCounter assay, specifically the 770 gene PanCancer Immune Panel. RNA was extracted from the adjacent 10μm section and then proceeded with hybridization, purification and immobilization and count based on manufacturer’s protocol. Results: On protein level we confirmed previous findings that ovarian GCTs are so-called “cold” tumors, with a very low density of T cell infiltration. Likewise, levels of both CTLA-4, PD-1, and PD-L1 were very low in all GCTs. We are currently analyzing gene expression signatures for tumor antigens, defects in antigen presentation, and absence of T cell activation in order to detect some of the mechanisms behind the low T cell infiltration in this tumor type. When we analyzed the presence of TAMs in the tumor microenvironment (TME) however, we found a 113% increase in TAM density in recurrent tumors compared to primary tumors, and when doing a nearest neighbor analysis of the proximity between M2-type TAMs and angiogenic vessels in the TME, we found M2 TAMS to be much closer associated with the vessels. Interestingly, on gene level we found SPP1 (the gene coding for osteopontin) to have a 9-fold higher expression in recurrent versus primary GCT tumors, while VEGFA was found to have a 3-fold higher expression. As a pro-inflammatory cytokine osteopontin is thought to both facilitate the recruitment of TAMs and to stimulate angiogenesis by inducing VEGF expression in endothelial cells, suggesting that osteopontin could be a therapeutic target in patients with recurrent GCT. Citation Format: Anna Juncker-Jensen, Tyvette S Hilliard, Nicholas Stavrou, Mate Nagy, Erinn Parnell, Judy Kuo, Eric Leones, Sharon Stack. An integrated multiplexing approach for the immunoprofiling of the tumor microenvironment of ovarian granulosa cell tumors [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr LB-C18. doi:10.1158/1535-7163.TARG-19-LB-C18