Development and validation of a prognostic model based on m6A-related lncRNAs to predict prognosis for papillary renal cell cancer patients

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.