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Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model

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...

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Autores principales: Pisano, Simone, Lenna, Stefania, Healey, Gareth D., Izardi, Fereshteh, Meeks, Lucille, Jimenez, Yajaira S., Velazquez, Oscar S, Gonzalez, Deyarina, Conlan, Robert Steven, Corradetti, Bruna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506632/
https://www.ncbi.nlm.nih.gov/pubmed/34709744
http://dx.doi.org/10.1002/ctm2.551
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author Pisano, Simone
Lenna, Stefania
Healey, Gareth D.
Izardi, Fereshteh
Meeks, Lucille
Jimenez, Yajaira S.
Velazquez, Oscar S
Gonzalez, Deyarina
Conlan, Robert Steven
Corradetti, Bruna
author_facet Pisano, Simone
Lenna, Stefania
Healey, Gareth D.
Izardi, Fereshteh
Meeks, Lucille
Jimenez, Yajaira S.
Velazquez, Oscar S
Gonzalez, Deyarina
Conlan, Robert Steven
Corradetti, Bruna
author_sort Pisano, Simone
collection PubMed
description 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.
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spelling pubmed-85066322021-10-18 Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model Pisano, Simone Lenna, Stefania Healey, Gareth D. Izardi, Fereshteh Meeks, Lucille Jimenez, Yajaira S. Velazquez, Oscar S Gonzalez, Deyarina Conlan, Robert Steven Corradetti, Bruna Clin Transl Med Research Articles 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. John Wiley and Sons Inc. 2021-10-12 /pmc/articles/PMC8506632/ /pubmed/34709744 http://dx.doi.org/10.1002/ctm2.551 Text en © 2021 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Pisano, Simone
Lenna, Stefania
Healey, Gareth D.
Izardi, Fereshteh
Meeks, Lucille
Jimenez, Yajaira S.
Velazquez, Oscar S
Gonzalez, Deyarina
Conlan, Robert Steven
Corradetti, Bruna
Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title_full Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title_fullStr Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title_full_unstemmed Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title_short Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
title_sort assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8506632/
https://www.ncbi.nlm.nih.gov/pubmed/34709744
http://dx.doi.org/10.1002/ctm2.551
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