Identification and Validation of M5c-related LncRNA Risk Model for Ovarian Cancer

Overview

Journal J Ovarian Res

Publisher Biomed Central

Specialties Gynecology & Obstetrics
Reproductive Medicine

Date 2023 May 14

PMID 37183262

Authors

Chong Wang

Chunxiao Zhang

Shimin Yang

Jiangdong Xiang

Dongmei Zhou

Xiaowei Xi

Affiliations

Soon will be listed here.

Abstract

Ovarian cancer (OC) is one of the common malignant tumors that seriously threaten women's health, and there is a lack of clinical prognostic predictors, while m5c and lncRNA have been shown to be predictive of multiple cancers, including OC. Therefore, our goal was to construct a risk model for OC based on m5c-related lncRNA.340 m5c-related lncRNA were identified and a novel risk model of OC ground on nine m5C-related lncRNA was constructed using LASSO-COX regression analysis. Kaplan-Meier analysis showed there was a significant difference in prognosis between risk groups. We established a nomogram which was a good predictor of overall survival. In addition, GSEA was enriched in multiple pathways and immune function analysis suggested that immune infiltration varies depending on the risk group. In vitro experiments show that AC005562.1, a key lncRNA of the risk model, is highly expressed in OC cells and promotes OC cell proliferation. Finally, we further explored the potential biological markers of m5c-related lncRNA in OC with WGCNA analysis and established a ceRNA network. In conclusion,we have developed a reliable m5c-related prediction model and performed systematic validation and exploration of various aspects. These results can be used for the assessment of OC prognosis and the discovery of novel biomarkers.

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