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

Simone Pisano, Stefania Lenna, Gareth Healey Orcid Logo, Fereshteh Izardi, Lucille Meeks, Yajaira S. Jimenez, Oscar S Velazquez, Deya Gonzalez Orcid Logo, Steve Conlan Orcid Logo, Bruna Corradetti

Clinical and Translational Medicine, Volume: 11, Issue: 10

Swansea University Authors: Simone Pisano, Gareth Healey Orcid Logo, Deya Gonzalez Orcid Logo, Steve Conlan Orcid Logo, Bruna Corradetti

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DOI (Published version): 10.1002/ctm2.551

Abstract

BackgroundOvarian 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 m...

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Published in: Clinical and Translational Medicine
ISSN: 2001-1326 2001-1326
Published: Wiley 2021
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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.MethodsGreen 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.ResultsTumor 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&#x2013;, and memory T cells, among others, and the coexistance of different immune cell types within the same tumor microenvironment.ConclusionsWe 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><type>Journal Article</type><journal>Clinical and Translational Medicine</journal><volume>11</volume><journalNumber>10</journalNumber><paginationStart/><paginationEnd/><publisher>Wiley</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint>2001-1326</issnPrint><issnElectronic>2001-1326</issnElectronic><keywords>ascites; CyTOF; immunotherapy; mass cytometry; model; ovarian cancer; peritoneal cancers</keywords><publishedDay>12</publishedDay><publishedMonth>10</publishedMonth><publishedYear>2021</publishedYear><publishedDate>2021-10-12</publishedDate><doi>10.1002/ctm2.551</doi><url/><notes/><college>COLLEGE NANME</college><department>Medicine, Health and Life Science - Faculty</department><CollegeCode>COLLEGE CODE</CollegeCode><DepartmentCode>FGMHL</DepartmentCode><institution>Swansea University</institution><apcterm/><funders>European Union&#x2019;s Horizon 2020 Research and Innovation Program, Grant/Award Number: 663830</funders><projectreference/><lastEdited>2022-10-26T15:17:35.1012503</lastEdited><Created>2021-10-12T13:21:15.2190074</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Simone</firstname><surname>Pisano</surname><order>1</order></author><author><firstname>Stefania</firstname><surname>Lenna</surname><order>2</order></author><author><firstname>Gareth</firstname><surname>Healey</surname><orcid>0000-0001-9531-1220</orcid><order>3</order></author><author><firstname>Fereshteh</firstname><surname>Izardi</surname><order>4</order></author><author><firstname>Lucille</firstname><surname>Meeks</surname><order>5</order></author><author><firstname>Yajaira S.</firstname><surname>Jimenez</surname><order>6</order></author><author><firstname>Oscar S</firstname><surname>Velazquez</surname><order>7</order></author><author><firstname>Deya</firstname><surname>Gonzalez</surname><orcid>0000-0002-1838-6752</orcid><order>8</order></author><author><firstname>Steve</firstname><surname>Conlan</surname><orcid>0000-0002-2562-3461</orcid><order>9</order></author><author><firstname>Bruna</firstname><surname>Corradetti</surname><order>10</order></author></authors><documents><document><filename>58302__21358__3cb24df0ca544182a96f0b3f6c70ad22.pdf</filename><originalFilename>58302.pdf</originalFilename><uploaded>2021-10-28T16:48:40.5871711</uploaded><type>Output</type><contentLength>19577190</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>&#xA9; 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License.</documentNotes><copyrightCorrect>true</copyrightCorrect><language>eng</language><licence>http://creativecommons.org/licenses/by/4.0/</licence></document></documents><OutputDurs/></rfc1807>
spelling 2022-10-26T15:17:35.1012503 v2 58302 2021-10-12 Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model 4c4284743c846288b5a5312d3d49464b Simone Pisano Simone Pisano true false 5926519f89187489cfd5e1478aa188b1 0000-0001-9531-1220 Gareth Healey Gareth Healey true false bafdf635eb81280304eedf4b18e65d4e 0000-0002-1838-6752 Deya Gonzalez Deya Gonzalez true false 0bb6bd247e32fb4249de62c0013b51cb 0000-0002-2562-3461 Steve Conlan Steve Conlan true false aa6a235c9e53c5b9b00e751422db5277 Bruna Corradetti Bruna Corradetti true false 2021-10-12 FGMHL BackgroundOvarian 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.MethodsGreen 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.ResultsTumor 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.ConclusionsWe 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. Journal Article Clinical and Translational Medicine 11 10 Wiley 2001-1326 2001-1326 ascites; CyTOF; immunotherapy; mass cytometry; model; ovarian cancer; peritoneal cancers 12 10 2021 2021-10-12 10.1002/ctm2.551 COLLEGE NANME Medicine, Health and Life Science - Faculty COLLEGE CODE FGMHL Swansea University European Union’s Horizon 2020 Research and Innovation Program, Grant/Award Number: 663830 2022-10-26T15:17:35.1012503 2021-10-12T13:21:15.2190074 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Simone Pisano 1 Stefania Lenna 2 Gareth Healey 0000-0001-9531-1220 3 Fereshteh Izardi 4 Lucille Meeks 5 Yajaira S. Jimenez 6 Oscar S Velazquez 7 Deya Gonzalez 0000-0002-1838-6752 8 Steve Conlan 0000-0002-2562-3461 9 Bruna Corradetti 10 58302__21358__3cb24df0ca544182a96f0b3f6c70ad22.pdf 58302.pdf 2021-10-28T16:48:40.5871711 Output 19577190 application/pdf Version of Record true © 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution License. true eng http://creativecommons.org/licenses/by/4.0/
title Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
spellingShingle Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
Simone Pisano
Gareth Healey
Deya Gonzalez
Steve Conlan
Bruna Corradetti
title_short 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_sort Assessment of the immune landscapes of advanced ovarian cancer in an optimized in vivo model
author_id_str_mv 4c4284743c846288b5a5312d3d49464b
5926519f89187489cfd5e1478aa188b1
bafdf635eb81280304eedf4b18e65d4e
0bb6bd247e32fb4249de62c0013b51cb
aa6a235c9e53c5b9b00e751422db5277
author_id_fullname_str_mv 4c4284743c846288b5a5312d3d49464b_***_Simone Pisano
5926519f89187489cfd5e1478aa188b1_***_Gareth Healey
bafdf635eb81280304eedf4b18e65d4e_***_Deya Gonzalez
0bb6bd247e32fb4249de62c0013b51cb_***_Steve Conlan
aa6a235c9e53c5b9b00e751422db5277_***_Bruna Corradetti
author Simone Pisano
Gareth Healey
Deya Gonzalez
Steve Conlan
Bruna Corradetti
author2 Simone Pisano
Stefania Lenna
Gareth Healey
Fereshteh Izardi
Lucille Meeks
Yajaira S. Jimenez
Oscar S Velazquez
Deya Gonzalez
Steve Conlan
Bruna Corradetti
format Journal article
container_title Clinical and Translational Medicine
container_volume 11
container_issue 10
publishDate 2021
institution Swansea University
issn 2001-1326
2001-1326
doi_str_mv 10.1002/ctm2.551
publisher Wiley
college_str Faculty of Medicine, Health and Life Sciences
hierarchytype
hierarchy_top_id facultyofmedicinehealthandlifesciences
hierarchy_top_title Faculty of Medicine, Health and Life Sciences
hierarchy_parent_id facultyofmedicinehealthandlifesciences
hierarchy_parent_title Faculty of Medicine, Health and Life Sciences
department_str Swansea University Medical School - Medicine{{{_:::_}}}Faculty of Medicine, Health and Life Sciences{{{_:::_}}}Swansea University Medical School - Medicine
document_store_str 1
active_str 0
description BackgroundOvarian 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.MethodsGreen 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.ResultsTumor 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.ConclusionsWe 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.
published_date 2021-10-12T04:14:43Z
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