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- Title
Construction of a Prognostic Risk Prediction Model Based on m6A-Associated Long Non-Coding RNAs in Cholangiocarcinoma.
- Authors
Dai, Y.; Zhang, S.; Zhang, X. X.; Xu, J. M.; He, Q.
- Abstract
To screen long non-coding RNAs (lncRNAs) associated with the N6-methyladenosine (m6A) gene and create a prognostic risk model for cholangiocarcinoma (CCA). Based on the expression levels of lncRNAs and m6A genes, the lncRNAs that related to m6A genes were chosen from the TCGA and EBI databases. Using univariate and multivariate cox regression analysis, lncRNAs associated with prognosis were discovered. A risk score (RS) system was constructed. The correlation between the immune cell infiltration and prognostic risk grouping was further investigated. Finally, the functions of risk-related factors were studied by constructing a ceRNA regulatory network. From the two datasets, 1040 and 410 m6A-associated lncRNAs were identified, respectively. Six m6A-associated lncRNAs (ALDH1L1-AS2, SLC8A1-AS1, FAM27E3, NOP14-AS1, HIF1A-AS2 and F10-AS1) associated with CCA prognosis were obtained. A prognostic risk prediction model was constructed with six m6A-associated lncRNAs. A significant correlation between the low-risk and high-risk groups and actual prognosis. Kaplan–Meier survival curve showed that the higher the RS value of CCA patients, the worse the clinical prognosis. Five significantly different immune cell types were obtained between the low-risk and high-risk groups. Additionally, the immune, ESTIMATE, and stromal scores exhibited significant differences between the two risk groups. Finally, a ceRNA network involving six m6A-associated lncRNAs was constructed. In our study, a prognostic signature consisting of six m6A-associated lncRNAs was constructed with high accuracy for the prediction of prognosis of CCA patients.
- Subjects
PROGNOSTIC models; CHOLANGIOCARCINOMA; DISEASE risk factors; COMPETITIVE endogenous RNA; SURVIVAL analysis (Biometry); ADENOSINES
- Publication
Russian Journal of Genetics, 2024, Vol 60, Issue 5, p682
- ISSN
1022-7954
- Publication type
Article
- DOI
10.1134/S1022795424700091