An Immune-related lncRNAs Model for Prognostic of SKCM Patients Base on Cox Regression and Coexpression Analysis

TL;DR

This study developed a 4-lncRNA immune-related model using Cox regression and coexpression analysis to predict SKCM patient prognosis, demonstrating high predictive accuracy and potential biological significance.

Contribution

The paper introduces a novel 4-lncRNA prognostic model for SKCM based on immune-related lncRNAs, improving prediction accuracy over existing models.

Findings

The model predicts 30-year survival with an AUC of 0.749.

Patients are stratified into high- and low-risk groups based on the model.

Identified four key lncRNAs potentially involved in SKCM carcinogenesis.

Abstract

SKCM is the most dangerous one of skin cancer, its high degree of malignant, is the leading cause of skin cancer. And the level of radiation treatment and chemical treatment is minimal, so the mortality is high. Because of its complex molecular and cellular heterogeneity, the existing prediction model of skin cancer risk is not ideal. In this study, we developed an immune-related lncRNAs model to predict the prognosis of patients with SKCM. Screening for SKCM-related differential expression of lncRNA from TCGA. Identified immune-related lncRNAs and lncRNA-related mRNA based on the co-expression method. Through univariate and multivariate analysis, an immune-related lncRNA model is established to analyze the prognosis of SKCM patients. A 4-lncRNA skin cancer prediction model was constructed, including MIR155HG, AL137003.2, AC011374.2, and AC009495.2. According to the model, SKCM samples were divided into a high-risk group and low-risk group, and predict the survival of the two groups in 30 years. The area under the ROC curve is 0.749, which shows that the model has excellent performance. We constructed a 4-lncRNA model to predict the prognosis of patients with SKCM, indicating that these lncRNAs may play a unique role in the carcinogenesis of SKCM.