A novel pyroptosis-related LncRNA signature predicts prognosis and indicates tumor immune microenvironment in skin cutaneous melanoma
- PMID: 35940218
- DOI: 10.1016/j.lfs.2022.120832
A novel pyroptosis-related LncRNA signature predicts prognosis and indicates tumor immune microenvironment in skin cutaneous melanoma
Abstract
Aims: To explore the correlation between the pyroptosis-related lncRNAs (PRlncRNAs) and the prognosis of skin cutaneous melanoma (SKCM), and clarify the effects of the PRlncRNAs on the tumor immune infiltration.
Main methods: In this study, we utilized RNA-seq and clinical characteristics data obtained from TCGA and GEO database to perform co-expression analysis and LASSO Cox regression analysis to construct a 12-PRlncRNA prognostic prediction model. We also performed functional analysis, immune infiltration analysis and drug sensitivity analysis, as well as correlation analysis with autophagy/ferroptosis genes, tumor mutational burden, and PD-1/PD-L1 genes.
Key finding: The model based on the 12-PRlncRNA signature could effectively predict the prognosis of SKCM. Low risk group had a higher anti-tumor immune level generally compared with high-risk group. The signature was correlated with the expression of autophagy/ferroptosis-related genes and PD1/PD-L1 genes and tumor mutational burden. Additionally, drug sensitivity analysis indicated potential therapeutic targets.
Significance: Our study demonstrated the impact of PRlncRNAs on SKCM. The model established based on the 12-PRlncRNA showed significant prognostic value for SKCM and may be instructive in pyroptosis-related targeted therapy in the clinic.
Keywords: Long non-coding RNAs; Prognosis; Pyroptosis; Skin cutaneous melanoma (SKCM); Tumor immune microenvironment.
Copyright © 2022. Published by Elsevier Inc.
Conflict of interest statement
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Medical
Research Materials
