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Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data

Ovarian cancer (OC) is one the most life-threatening cancers affecting women’s health worldwide. Immunotherapy has become a promising treatment for a variety of cancers, but the therapeutic effects in OC remain limited. In this study, we constructed a macrophage risk score (MRS) based on M1 and M2 m...

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Autores principales: Wang, Sixue, Wang, Xi, Xia, Xiaomeng, Zhang, Tingting, Yi, Mingyu, Li, Zeying, Jiang, Li, Yang, Yalan, Fu, Jie, Fang, Xiaoling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9346122/
https://www.ncbi.nlm.nih.gov/pubmed/35918500
http://dx.doi.org/10.1038/s41598-022-17645-7
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author Wang, Sixue
Wang, Xi
Xia, Xiaomeng
Zhang, Tingting
Yi, Mingyu
Li, Zeying
Jiang, Li
Yang, Yalan
Fu, Jie
Fang, Xiaoling
author_facet Wang, Sixue
Wang, Xi
Xia, Xiaomeng
Zhang, Tingting
Yi, Mingyu
Li, Zeying
Jiang, Li
Yang, Yalan
Fu, Jie
Fang, Xiaoling
author_sort Wang, Sixue
collection PubMed
description Ovarian cancer (OC) is one the most life-threatening cancers affecting women’s health worldwide. Immunotherapy has become a promising treatment for a variety of cancers, but the therapeutic effects in OC remain limited. In this study, we constructed a macrophage risk score (MRS) based on M1 and M2 macrophages and a gene risk score (GRS) based on the prognostic genes associated with MRS. Next, cell–cell communication analysis was performed using single-cell RNA (scRNA) sequencing data. Survival status and immune characteristics were compared between the high- and low-score groups separated by MRS or GRS. Our results suggested that MRS and GRS can identify the immune subtypes of OC patients with better overall survival (OS) and inflammatory immune microenvironment. Moreover, M1 and M2 macrophages may affect the prognosis of OC patients through signal communication with CD8 T cells. Finally, functional differences between the two groups separated by GRS were elucidated. Taken together, this study constructed two useful models for the identification of immune subtypes in OC, which has a better prognosis and may have a sensitive response to immune checkpoint inhibitors (ICIs). The hub genes for the construction of GRS may be potential synergetic targets for immunotherapy in OC patients.
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spelling pubmed-93461222022-08-04 Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data Wang, Sixue Wang, Xi Xia, Xiaomeng Zhang, Tingting Yi, Mingyu Li, Zeying Jiang, Li Yang, Yalan Fu, Jie Fang, Xiaoling Sci Rep Article Ovarian cancer (OC) is one the most life-threatening cancers affecting women’s health worldwide. Immunotherapy has become a promising treatment for a variety of cancers, but the therapeutic effects in OC remain limited. In this study, we constructed a macrophage risk score (MRS) based on M1 and M2 macrophages and a gene risk score (GRS) based on the prognostic genes associated with MRS. Next, cell–cell communication analysis was performed using single-cell RNA (scRNA) sequencing data. Survival status and immune characteristics were compared between the high- and low-score groups separated by MRS or GRS. Our results suggested that MRS and GRS can identify the immune subtypes of OC patients with better overall survival (OS) and inflammatory immune microenvironment. Moreover, M1 and M2 macrophages may affect the prognosis of OC patients through signal communication with CD8 T cells. Finally, functional differences between the two groups separated by GRS were elucidated. Taken together, this study constructed two useful models for the identification of immune subtypes in OC, which has a better prognosis and may have a sensitive response to immune checkpoint inhibitors (ICIs). The hub genes for the construction of GRS may be potential synergetic targets for immunotherapy in OC patients. Nature Publishing Group UK 2022-08-02 /pmc/articles/PMC9346122/ /pubmed/35918500 http://dx.doi.org/10.1038/s41598-022-17645-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Wang, Sixue
Wang, Xi
Xia, Xiaomeng
Zhang, Tingting
Yi, Mingyu
Li, Zeying
Jiang, Li
Yang, Yalan
Fu, Jie
Fang, Xiaoling
Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title_full Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title_fullStr Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title_full_unstemmed Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title_short Identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
title_sort identification of the immune subtype of ovarian cancer patients by integrated analyses of transcriptome and single-cell sequencing data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9346122/
https://www.ncbi.nlm.nih.gov/pubmed/35918500
http://dx.doi.org/10.1038/s41598-022-17645-7
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