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Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers

Accumulating evidence has recognized that cancer-associated fibroblasts (CAFs) are major players in the desmoplastic stroma of ovarian cancer, modulating tumor progression and therapeutic response. However, it is unclear regarding the signatures of CAFs could be utilized to predict the clinical outc...

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Autores principales: Zhao, Yan, Mei, Song, Huang, Yixuan, Chen, Junru, Zhang, Xinlei, Zhang, Peng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679440/
https://www.ncbi.nlm.nih.gov/pubmed/36420154
http://dx.doi.org/10.1016/j.csbj.2022.11.025
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author Zhao, Yan
Mei, Song
Huang, Yixuan
Chen, Junru
Zhang, Xinlei
Zhang, Peng
author_facet Zhao, Yan
Mei, Song
Huang, Yixuan
Chen, Junru
Zhang, Xinlei
Zhang, Peng
author_sort Zhao, Yan
collection PubMed
description Accumulating evidence has recognized that cancer-associated fibroblasts (CAFs) are major players in the desmoplastic stroma of ovarian cancer, modulating tumor progression and therapeutic response. However, it is unclear regarding the signatures of CAFs could be utilized to predict the clinical outcomes of ovarian cancer patients. To fill in this gap, we explored the intratumoral compartment of ovarian cancer by analyzing the single-cell RNA-sequencing (scRNA-seq) datasets of ovarian carcinoma samples, and identified two distinct CAFs (tumor-promoting CAF_c1 subtype and myofibroblasts-like CAF_c2 subtype). The clinical significance of CAF subtypes was further validated in The Cancer Genomics Atlas (TCGA) database and other independent immunotherapy response datasets, and the results revealed that the patients with a higher expression of CAF_c1 signatures had a worse prognosis and showed a tendency of resistance to immunotherapy. This work uncovered the signatures of the CAF_c1 subtype that could serve as a novel prognostic indicator and predictive marker for immunotherapy.
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spelling pubmed-96794402022-11-22 Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers Zhao, Yan Mei, Song Huang, Yixuan Chen, Junru Zhang, Xinlei Zhang, Peng Comput Struct Biotechnol J Special Issue articles from "Computational single cell omics and drug discovery" edited by Pingzhao Hu Accumulating evidence has recognized that cancer-associated fibroblasts (CAFs) are major players in the desmoplastic stroma of ovarian cancer, modulating tumor progression and therapeutic response. However, it is unclear regarding the signatures of CAFs could be utilized to predict the clinical outcomes of ovarian cancer patients. To fill in this gap, we explored the intratumoral compartment of ovarian cancer by analyzing the single-cell RNA-sequencing (scRNA-seq) datasets of ovarian carcinoma samples, and identified two distinct CAFs (tumor-promoting CAF_c1 subtype and myofibroblasts-like CAF_c2 subtype). The clinical significance of CAF subtypes was further validated in The Cancer Genomics Atlas (TCGA) database and other independent immunotherapy response datasets, and the results revealed that the patients with a higher expression of CAF_c1 signatures had a worse prognosis and showed a tendency of resistance to immunotherapy. This work uncovered the signatures of the CAF_c1 subtype that could serve as a novel prognostic indicator and predictive marker for immunotherapy. Research Network of Computational and Structural Biotechnology 2022-11-14 /pmc/articles/PMC9679440/ /pubmed/36420154 http://dx.doi.org/10.1016/j.csbj.2022.11.025 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Special Issue articles from "Computational single cell omics and drug discovery" edited by Pingzhao Hu
Zhao, Yan
Mei, Song
Huang, Yixuan
Chen, Junru
Zhang, Xinlei
Zhang, Peng
Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title_full Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title_fullStr Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title_full_unstemmed Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title_short Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
title_sort integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers
topic Special Issue articles from "Computational single cell omics and drug discovery" edited by Pingzhao Hu
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9679440/
https://www.ncbi.nlm.nih.gov/pubmed/36420154
http://dx.doi.org/10.1016/j.csbj.2022.11.025
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