Residential College | false |
Status | 已發表Published |
Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers | |
Zhao, Yan1; Mei, Song2; Huang, Yixuan3; Chen, Junru4; Zhang, Xinlei3; Zhang, Peng5,6 | |
2022-11-14 | |
Source Publication | Computational and Structural Biotechnology Journal |
ISSN | 2001-0370 |
Volume | 20Pages:6403-6411 |
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. |
Keyword | Bio-marker Cafs Gene Signature Immunotherapy Ovarian Cancer Prognosis Single-cell Sequencing |
DOI | 10.1016/j.csbj.2022.11.025 |
URL | View the original |
Language | 英語English |
Scopus ID | 2-s2.0-85142204455 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | Institute of Chinese Medical Sciences |
Corresponding Author | Zhang, Peng |
Affiliation | 1.Beijing Tongren Hospital, Capital Medical University and Beijing Institute of Otolaryngology, Beijing, China 2.Shanghai Institute of Immunology, Shanghai Jiao Tong University School of Medicine, Shanghai, China 3.Beijing Cloudna Technology Co., Ltd., Beijing, China 4.Institute of Chinese Medical Sciences, University of Macau, Macau, China 5.Beijing Pediatric Research Institute, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China 6.University of Maryland School of Medicine, Baltimore, United States |
Recommended Citation GB/T 7714 | Zhao, Yan,Mei, Song,Huang, Yixuan,et al. Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers[J]. Computational and Structural Biotechnology Journal, 2022, 20, 6403-6411. |
APA | Zhao, Yan., Mei, Song., Huang, Yixuan., Chen, Junru., Zhang, Xinlei., & Zhang, Peng (2022). Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers. Computational and Structural Biotechnology Journal, 20, 6403-6411. |
MLA | Zhao, Yan,et al."Integrative analysis deciphers the heterogeneity of cancer-associated fibroblast and implications on clinical outcomes in ovarian cancers".Computational and Structural Biotechnology Journal 20(2022):6403-6411. |
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