Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer

Ovarian cancer (OC) is a devastating malignancy with a poor prognosis. The complex tumor immune microenvironment results in only a small number of patients benefiting from immunotherapy. To explore the different factors that lead to immune invasion and determine prognosis and response to immune chec...

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Autores principales:	Zhao-Cong Zhang, Jun-Nan Guo, Ning Zhang, Zhi-Qiang Wang, Ge Lou, Bin-Bin Cui, Chang Yang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	ovarian cancer immune-related genes (IRGs) prognosis tumor immune microenvironment immune checkpoint inhibitors (ICI) Immunologic diseases. Allergy RC581-607
Acceso en línea:	https://doaj.org/article/104798d4f0724b14be7ad8eba7809f57
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spelling	oai:doaj.org-article:104798d4f0724b14be7ad8eba7809f572021-11-22T06:25:27ZIdentification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer1664-322410.3389/fimmu.2021.763791https://doaj.org/article/104798d4f0724b14be7ad8eba7809f572021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fimmu.2021.763791/fullhttps://doaj.org/toc/1664-3224Ovarian cancer (OC) is a devastating malignancy with a poor prognosis. The complex tumor immune microenvironment results in only a small number of patients benefiting from immunotherapy. To explore the different factors that lead to immune invasion and determine prognosis and response to immune checkpoint inhibitors (ICIs), we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify key prognostic IRGs. Patients were divided into high-risk and low-risk groups according to their immune and stromal scores. We used a bioinformatics method to identify four key IRGs that had differences in expression between the two groups and affected prognosis. We evaluated the sensitivity of treatment from three aspects, namely chemotherapy, targeted inhibitors (TIs), and immunotherapy, to evaluate the value of prediction models and key prognostic IRGs in the clinical treatment of OC. Univariate and multivariate Cox regression analyses revealed that these four key IRGs were independent prognostic factors of overall survival in OC patients. In the high-risk group comprising four genes, macrophage M0 cells, macrophage M2 cells, and regulatory T cells, observed to be associated with poor overall survival in our study, were higher. The high-risk group had a high immunophenoscore, indicating a better response to ICIs. Taken together, we constructed a PRSM and identified four key prognostic IRGs for predicting survival and response to ICIs. Finally, the expression of these key genes in OC was evaluated using RT-qPCR. Thus, these genes provide a novel predictive biomarker for immunotherapy and immunomodulation.Zhao-Cong ZhangJun-Nan GuoNing ZhangZhi-Qiang WangGe LouBin-Bin CuiChang YangFrontiers Media S.A.articleovarian cancerimmune-related genes (IRGs)prognosistumor immune microenvironmentimmune checkpoint inhibitors (ICI)Immunologic diseases. AllergyRC581-607ENFrontiers in Immunology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	ovarian cancer immune-related genes (IRGs) prognosis tumor immune microenvironment immune checkpoint inhibitors (ICI) Immunologic diseases. Allergy RC581-607
spellingShingle	ovarian cancer immune-related genes (IRGs) prognosis tumor immune microenvironment immune checkpoint inhibitors (ICI) Immunologic diseases. Allergy RC581-607 Zhao-Cong Zhang Jun-Nan Guo Ning Zhang Zhi-Qiang Wang Ge Lou Bin-Bin Cui Chang Yang Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
description	Ovarian cancer (OC) is a devastating malignancy with a poor prognosis. The complex tumor immune microenvironment results in only a small number of patients benefiting from immunotherapy. To explore the different factors that lead to immune invasion and determine prognosis and response to immune checkpoint inhibitors (ICIs), we established a prognostic risk scoring model (PRSM) with differential expression of immune-related genes (IRGs) to identify key prognostic IRGs. Patients were divided into high-risk and low-risk groups according to their immune and stromal scores. We used a bioinformatics method to identify four key IRGs that had differences in expression between the two groups and affected prognosis. We evaluated the sensitivity of treatment from three aspects, namely chemotherapy, targeted inhibitors (TIs), and immunotherapy, to evaluate the value of prediction models and key prognostic IRGs in the clinical treatment of OC. Univariate and multivariate Cox regression analyses revealed that these four key IRGs were independent prognostic factors of overall survival in OC patients. In the high-risk group comprising four genes, macrophage M0 cells, macrophage M2 cells, and regulatory T cells, observed to be associated with poor overall survival in our study, were higher. The high-risk group had a high immunophenoscore, indicating a better response to ICIs. Taken together, we constructed a PRSM and identified four key prognostic IRGs for predicting survival and response to ICIs. Finally, the expression of these key genes in OC was evaluated using RT-qPCR. Thus, these genes provide a novel predictive biomarker for immunotherapy and immunomodulation.
format	article
author	Zhao-Cong Zhang Jun-Nan Guo Ning Zhang Zhi-Qiang Wang Ge Lou Bin-Bin Cui Chang Yang
author_facet	Zhao-Cong Zhang Jun-Nan Guo Ning Zhang Zhi-Qiang Wang Ge Lou Bin-Bin Cui Chang Yang
author_sort	Zhao-Cong Zhang
title	Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
title_short	Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
title_full	Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
title_fullStr	Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
title_full_unstemmed	Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer
title_sort	identification and validation of immune-related gene for predicting prognosis and therapeutic response in ovarian cancer
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/104798d4f0724b14be7ad8eba7809f57
work_keys_str_mv	AT zhaocongzhang identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT junnanguo identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT ningzhang identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT zhiqiangwang identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT gelou identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT binbincui identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer AT changyang identificationandvalidationofimmunerelatedgeneforpredictingprognosisandtherapeuticresponseinovariancancer
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Identification and Validation of Immune-Related Gene for Predicting Prognosis and Therapeutic Response in Ovarian Cancer

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