Abstract B62: Integrating highly-multiplexed imaging with multi-omics data to uncover immunologic vulnerabilities in high-grade serous ovarian cancer

Abstract

Abstract A key event in cancer progression is the establishment of an immunosuppressive environment that prevents the immune system from effectively attacking the cancer cells. In this study we aim to characterize the cellular determinants and the spatial features of immune suppressive mechanisms in high-grade serous ovarian cancer (HGSOC) via integrating tissue Cyclic Immunofluorescence (tCycIF), a novel highly multiplexed single-cell spatial proteomics platform with multi-omics data, including state-of-the-art single-cell RNA sequencing. We have conducted a comprehensive analysis of a unique dataset consisting of 23 HGSOC samples, including 7 pairs of treatment-naïve and post-chemotherapy samples, using tCycIF, single-cell, and bulk RNA sequencing coupled with novel deconvolution algorithms and whole-genome sequencing. All samples were prospectively collected from patients treated at Turku University Hospital, Finland, as a part of the HERCULES consortium. Our preliminary findings suggest that tCycIF can reliably capture tumor microenvironment composition in HGSOC. Overall, there was a good correlation with tumor purity between all the methods used. In tCycIF, scRNAseq and bulk deconvolution macrophages were the most common immune cell type in the HGSOC microenvironment. However, specific immune subpopulations, such as CD8+T-cells, had a larger proportion in tCycIF compared to single-cell RNA sequencing and bulk-deconvoluted RNAseq data. Further, the immune profiling based on RNAseq deconvolution algorithm showed highly variable results based on the algorithm used. We are in the process of using our complete dataset to compare state-of-the-art methods and improve algorithms for HGSOC immunophenotyping. tCycIF’s spatial proteomic data in single-cell resolution allows us to gain new insights into the tumor microenvironment and discover the previously latent cell-to-cell interactions that make up the immunosuppressive milieus in HGSOC tumors. The improvement of novel reliable single-cell immunophenotyping methods is critical to develop more effective immunotherapies to improve the outcomes and survival of patients with HGSOC. Citation Format: Miikka K. Kilkkila, Julia Casado, Connor Jacobson, Antti Hakkinen, Erdogan Erkai, Jun Dai, Kaiyang Zhan, Zoltan Maliga, Olli Carpen, Rainer Lehtonen, Sampsa Hautaniemi, Peter Sorger, Anna Vaharautio, Anniina Farkkila. Integrating highly-multiplexed imaging with multi-omics data to uncover immunologic vulnerabilities in high-grade serous 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 B62.