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

Authors :
Zhao Y
Mei S
Huang Y
Chen J
Zhang X
Zhang P
Source :
Computational and structural biotechnology journal [Comput Struct Biotechnol J] 2022 Nov 14; Vol. 20, pp. 6403-6411. Date of Electronic Publication: 2022 Nov 14 (Print Publication: 2022).
Publication Year :
2022

Abstract

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.<br />Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Yixuan Huang and Xinlei Zhang are employees of Beijing Cloudna Technology Co., Ltd., and the other authors declare no competing financial interests.<br /> (© 2022 The Author(s).)

Details

Language :
English
ISSN :
2001-0370
Volume :
20
Database :
MEDLINE
Journal :
Computational and structural biotechnology journal
Publication Type :
Academic Journal
Accession number :
36420154
Full Text :
https://doi.org/10.1016/j.csbj.2022.11.025