Comprehensive analysis of necroptosis-related lncRNA signature with potential implications in tumor heterogeneity and prediction of prognosis in clear cell renal cell carcinoma

Abstract

Abstract Background Necroptosis has been reported to play a critical role in occurrence and progression of cancer. The dysregulation of long non-coding RNAs (lncRNAs) is associated with the progression and metastasis of clear cell renal cell carcinoma (CCRCC). However, research on necroptosis-related lncRNAs in the tumor heterogeneity and prognosis of CCRCC is not completely unclear. This study aimed to analysis the tumor heterogeneity among CCRCC subgroups and construct a CCRCC prognostic signature based on necroptosis-related lncRNAs. Methods Weighted gene co-expression network analysis (WGCNA) was performed to identify necroptosis-related lncRNAs. A preliminary classification of molecular subgroups was performed by non-negative matrix factorization (NMF) consensus clustering analysis. Comprehensive analyses, including fraction genome altered (FGA), tumor mutational burden (TMB), DNA methylation alterations, copy number variations (CNVs), and single nucleotide polymorphisms (SNPs), were performed to explore the potential factors for tumor heterogeneity among the three subgroups. Subsequently, we constructed a predictive signature by multivariate Cox regression. Nomogram, calibration curves, decision curve analysis (DCA), and time-dependent receiver-operating characteristics (ROC) were used to validate and evaluate the signature. Finally, immune correlation analyses, including immune-related signaling pathways, immune cell infiltration status and immune checkpoint gene expression level, were also performed. Results Seven necroptosis-related lncRNAs were screened out by WGCNA, and three subgroups were classified by NMF consensus clustering analysis. There were significant differences in survival prognosis, clinicopathological characteristics, enrichments of immune-related signaling pathway, degree of immune cell infiltration, and expression of immune checkpoint genes in the various subgroups. Most importantly, we found that 26 differentially expressed genes (DEGs) among the 3 subgroups were not affected by DNA methylation alterations, CNVs and SNPs. On the contrary, these DEGs were associated with the seven necroptosis-related lncRNAs. Subsequently, the identified RP11-133F8.2 and RP11-283G6.4 by multivariate Cox regression analysis were involved in the risk model, which could serve as an independent prognostic factor for CCRCC. Finally, qRT-PCR confirmed the differential expression of the two lncRNAs. Conclusions These findings contributed to understanding the function of necroptosis-related lncRNAs in CCRCC and provided new insights of prognostic evaluation and optimal therapeutic strategy for CCRCC.