Development and Validation of a Prognostic Model Based on M6A-related LncRNAs to Predict Prognosis for Papillary Renal Cell Cancer Patients

Overview

Journal Sci Rep

Specialty Science

Date 2024 Dec 29

PMID 39732963

Authors

Xianlu Zhang

Jiyuan Hu

Haoyuan Zheng

Jiayi Ren

Siyu Mu

Yiming Chen

Guoli Song

Ya-Ang Chen

Gejun Zhang

Affiliations

Soon will be listed here.

Abstract

To evaluate the predictive utility of N6-methyladenosine (m6A)-associated long non-coding RNAs (lncRNAs) for the prognosis and immunotherapy response in papillary renal cell carcinoma (pRCC). Transcriptomic data of pRCC samples were extracted from the TCGA database. The m6A-related lncRNAs were identified by Pearson correlation analysis. Univariate and LASSO regression analyses were used to develop a risk model. The discrimination and predictive ability were evaluated through survival analysis, ROC analysis and consensus clustering. Tumor mutation burden (TMB) and immune infiltration of the risk groups were compared. A prognostic nomogram was constructed using six m6A-related lncRNAs, and validated through calibration and decision curve analysis (DCA). The lncRNAs HCG25 and NOP14-AS1 were knocked down in a human pRCC cell line using specific siRNA constructs, and the proliferation and migration rates were assessed by the CCK-8 and transwell assays. We identified a total of 153 m6A-related lncRNAs in pRCC datasets, of which six were selected for constructing a m6A-related lncRNA pRCC prognostic model. Mutations in the SETD2 gene correlated with worse prognosis. Significant differences were observed in immune cell infiltration between the two risk groups. A clinical prognostic nomogram for pRCC was further established based on clinical variables. In vitro assays further showed that HCG25 and NOP14-AS1 regulate the proliferation and migration of pRCC cells. The results validated the discrimination ability of both the m6A-related lncRNA pRCC prognostic model and the pRCC clinical prognostic nomogram. We developed a clinical prognostic nomogram for pRCC using pRCC prognostic-associated m6A-related lncRNAs, which can be utilized for predicting the prognosis and immune landscape of pRCC patients.

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