A novel immune-related LncRNA prognostic signature for cutaneous melanoma

Backgrounds Among tumor microenvironment, the immune components in it have an important influence on gene expression and clinical efficacy. We aim to find out the role of those in skin cutaneous melanoma (SKCM). Objectives Gene expression profile and homologous clinical information of SKCM patients...

Full description

Saved in:
Bibliographic Details
Published in:Molecular & cellular toxicology 2024, 20(2), , pp.377-387
Main Authors: Hu, Nan, Huang, Cancan, He, Yancheng, Li, Shuyang, Yuan, Jingyi, Zhong, Guishu, Chen, Yan
Format: Article
Language:English
Subjects:
Biomedical and Life Sciences
Cell Biology
Gene expression
Genomes
Infiltration
Life Sciences
Medical prognosis
Melanoma
Metastases
Non-coding RNA
Original Article
Patients
Pharmacology/Toxicology
Prediction models
Tumor microenvironment
생물학
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Backgrounds Among tumor microenvironment, the immune components in it have an important influence on gene expression and clinical efficacy. We aim to find out the role of those in skin cutaneous melanoma (SKCM). Objectives Gene expression profile and homologous clinical information of SKCM patients were obtained by TCGA (The Cancer Genome Atlas) and UCSC Toil. SsGSEA method was used to evaluate the immune cell infiltration of 468 TCGA-SKCM samples divided into high immune cell infiltration group (HICI) and low immune cell infiltration group (LICI). We used the Edger packet to conduct difference analysis on normal samples (GTEx) and cancer samples (TCGA), and combined it with the difference of the HICI group and LICI group, to find out the common differential expression of lncRNA in both groups. The prognostic value of immune-related lncRNAs was studied by univariate Cox, Lasso-Cox and multivariate Cox regression analysis, and a prognostic model was established. C index and calibration diagram were used to judge the accuracy of the model, and DCA was used to judge the net benefit. Results Six prognostic markers of immune-related lncRNA genes were established, which could be used as independent prognostic factors. The net benefit and prediction accuracy are significantly higher than TNM Stage. Conclusion The prognostic model identified in this study is a reliable biomarker for SKCM. The Nomogram survival prediction model based on it is a reliable way to predict the median survival time of patients, which may lay the foundation for future treatment of this disease.
ISSN:1738-642X
2092-8467
DOI:10.1007/s13273-023-00351-4