Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model. Issue 10 (12th October 2021)

• Record Type: Journal Article
• Authors: Pisano, Simone; Lenna, Stefania; Healey, Gareth D.; Izardi, Fereshteh; Meeks, Lucille; Jimenez, Yajaira S.; Velazquez, Oscar S; Gonzalez, Deyarina; Conlan, Robert Steven; Corradetti, Bruna
• Is Part Of: Clinical and translational medicine. Volume 11:Issue 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-10-12
• Subjects: ascites -- CyTOF -- immunotherapy -- mass cytometry -- model -- ovarian cancer -- peritoneal cancers; Clinical medicine -- Periodicals; Medicine, Experimental -- Periodicals; Medical innovations -- Periodicals; Molecular biology -- Periodicals; Pathology, Molecular -- Periodicals; 616.027
• DOI: 10.1002/ctm2.551
• Languages: English
• ISSNs: 2001-1326

Abstract

Abstract: Background: Ovarian cancer (OC) is typically diagnosed late, associated with high rates of metastasis and the onset of ascites during late stage disease. Understanding the tumor microenvironment and how it impacts the efficacy of current treatments, including immunotherapies, needs effective in vivo models that are fully characterized. In particular, understanding the role of immune cells within the tumor and ascitic fluid could provide important insights into why OC fails to respond to immunotherapies. In this work, we comprehensively described the immune cell infiltrates in tumor nodules and the ascitic fluid within an optimized preclinical model of advanced ovarian cancer. Methods: Green Fluorescent Protein (GFP)‐ID8 OC cells were injected intraperitoneally into C57BL/6 mice and the development of advanced stage OC monitored. Nine weeks after tumor injection, mice were sacrificed and tumor nodules analyzed to identify specific immune infiltrates by immunohistochemistry. Ascites, developed in tumor bearing mice over a 10‐week period, was characterized by mass cytometry (CyTOF) to qualitatively and quantitatively assess the distribution of the immune cell subsets, and their relationship to ascites from ovarian cancer patients. Results: Tumor nodules in the peritoneal cavity proved to be enriched in T cells, antigen presenting cells and macrophages, demonstrating an active immune environment and cell‐mediated immunity. Assessment of the immune landscape in the ascites showed the predominance of CD8 +, CD4 +, B –, and memory T cells, among others, and the coexistance of different immune cell types within the same tumor microenvironment. Conclusions: We performed, for the first time, a multiparametric analysis of the ascitic fluid and specifically identify immune cell populations in the peritoneal cavity of mice with advanced OC. Data obtained highlights the impact of CytOF as a diagnostic tool for this malignancy, with the opportunity to concomitantly identify novel targets, and define personalized therapeutic options. Abstract : – An ascites‐bearing, metastatic ovarian cancer model was created in mice – For the first time, cytometry by time of fly (CyTOF) technology was used to delineate the immune landscape of the ascitic fluid – Our data suggest that the application of this innovative tool will benefit advanced ovarian cancer diagnosis and treatment.