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Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer

Ovarian cancer (OvCa) is one of the most widespread malignant tumors, which has the highest morbidity and unsatisfactory clinical outcomes among all gynecological malignancies in the world. Previous studies found that cancer-associated fibroblasts (CAFs) play significant roles in tumor growth, progr...

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Autores principales: Zeng, Li, Wang, Xuehai, Wang, Fengxu, Zhao, Xinyuan, Ding, Yiqian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298777/
https://www.ncbi.nlm.nih.gov/pubmed/35873482
http://dx.doi.org/10.3389/fgene.2022.925231
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author Zeng, Li
Wang, Xuehai
Wang, Fengxu
Zhao, Xinyuan
Ding, Yiqian
author_facet Zeng, Li
Wang, Xuehai
Wang, Fengxu
Zhao, Xinyuan
Ding, Yiqian
author_sort Zeng, Li
collection PubMed
description Ovarian cancer (OvCa) is one of the most widespread malignant tumors, which has the highest morbidity and unsatisfactory clinical outcomes among all gynecological malignancies in the world. Previous studies found that cancer-associated fibroblasts (CAFs) play significant roles in tumor growth, progression, and chemoresistance. In the current research, weighted gene co-expression network analysis (WGCNA), univariable COX regression, and the least absolute shrinkage and selection operator (LASSO) analysis were applied to recognize CAF-specific genes. After multiple bioinformatic analyses, four genes (AXL, GPR176, ITGBL1, and TIMP3) were identified as OvCa-specific CAF markers and used to construct the prognostic signature (CAFRS). Furthermore, the specificity of the four genes' expression was further validated at the single-cell level, which was high-selectively expressed in CAFs. In addition, our results showed that CAFRS is an independent significant risk factor affecting the clinical outcomes of OvCa patients. Meanwhile, patients with higher CAFRS were more likely to establish chemoresistance to platinum. Besides, the CAFRS were notably correlated with well-known signal pathways that were related to tumor progression. In summary, our study identifies four CAF-specific genes and constructs a novel prognostic signature, which may provide more insights into precise prognostic assessment in OvCa.
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spelling pubmed-92987772022-07-21 Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer Zeng, Li Wang, Xuehai Wang, Fengxu Zhao, Xinyuan Ding, Yiqian Front Genet Genetics Ovarian cancer (OvCa) is one of the most widespread malignant tumors, which has the highest morbidity and unsatisfactory clinical outcomes among all gynecological malignancies in the world. Previous studies found that cancer-associated fibroblasts (CAFs) play significant roles in tumor growth, progression, and chemoresistance. In the current research, weighted gene co-expression network analysis (WGCNA), univariable COX regression, and the least absolute shrinkage and selection operator (LASSO) analysis were applied to recognize CAF-specific genes. After multiple bioinformatic analyses, four genes (AXL, GPR176, ITGBL1, and TIMP3) were identified as OvCa-specific CAF markers and used to construct the prognostic signature (CAFRS). Furthermore, the specificity of the four genes' expression was further validated at the single-cell level, which was high-selectively expressed in CAFs. In addition, our results showed that CAFRS is an independent significant risk factor affecting the clinical outcomes of OvCa patients. Meanwhile, patients with higher CAFRS were more likely to establish chemoresistance to platinum. Besides, the CAFRS were notably correlated with well-known signal pathways that were related to tumor progression. In summary, our study identifies four CAF-specific genes and constructs a novel prognostic signature, which may provide more insights into precise prognostic assessment in OvCa. Frontiers Media S.A. 2022-07-06 /pmc/articles/PMC9298777/ /pubmed/35873482 http://dx.doi.org/10.3389/fgene.2022.925231 Text en Copyright © 2022 Zeng, Wang, Wang, Zhao and Ding. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Zeng, Li
Wang, Xuehai
Wang, Fengxu
Zhao, Xinyuan
Ding, Yiqian
Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title_full Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title_fullStr Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title_full_unstemmed Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title_short Identification of a Gene Signature of Cancer-Associated Fibroblasts to Predict Prognosis in Ovarian Cancer
title_sort identification of a gene signature of cancer-associated fibroblasts to predict prognosis in ovarian cancer
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298777/
https://www.ncbi.nlm.nih.gov/pubmed/35873482
http://dx.doi.org/10.3389/fgene.2022.925231
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