Comprehensive characterization of the alternative splicing landscape in ovarian cancer reveals novel events associated with tumor-immune microenvironment. Issue 2 (25th February 2022)

• Record Type: Journal Article
• Authors: Sun, Dan; Zhao, Xingping; Yu, Yang; Li, Waixing; Gu, Pan; Zhi, Zhifu; Xu, Dabao
• Is Part Of: Bioscience reports. Volume 42:Issue 2(2022)
• Publication Date: 2022-02-25
• Subjects: alternative splicing -- genome-wide analysis -- ovarian cancer -- prognosis -- tumor-immune microenvironment; Molecular biology -- Periodicals; Cytology -- Periodicals; 572.8
• DOI: 10.1042/BSR20212090
• Languages: English
• ISSNs: 0144-8463

Abstract

Abstract: Background: Ovarian cancer (OV) is a serious threat to women's health. Immunotherapy is a new approach. Alternative splicing (AS) of messenger RNA (mRNA) and its regulation are highly relevant for understanding every cancer hallmark and may offer a broadened target space. Methods: We downloaded the clinical information and mRNA expression profiles of 587 tumor tissues from The Cancer Genome Atlas (TCGA) database. We constructed a risk score model to predict the prognosis of OV patients. The association between AS-based clusters and tumor-immune microenvironment features was further explored. The ESTIMATE algorithm was also carried out on each OV sample depending on the risk score groups. A total of three immune checkpoint genes that have a significant correlation with risk scores were screened. Results: The AS-events were a reliable and stable independent risk predictor in the OV cohort. Patients in the high-risk score group had a poor prognosis ( P <0.001). Mast cells activated, NK cells resting, and Neutrophils positively correlated with the risk score. The number of Macrophages M1 was also more numerous in the low-risk score group ( P <0.05). Checkpoint genes CD274, CTLA-4, and PDCD1LG2, showed a negative correlation with the risk score of AS in OV. Conclusions: The proposed AS signature is a promising biomarker for estimating overall survival (OS) in OV. The AS-events signature combined with tumor-immune microenvironment enabled a deeper understanding of the immune status of OV patients, and also provided new insights for exploring novel prognostic predictors and precise therapy methods.