Gene Instability-Related lncRNA Prognostic Model of Melanoma Patients via Machine Learning Strategy.

ABSTRACT:

Background

Melanoma is a common tumor characterized by a high mortality rate in its late stage. After metastasis, current treatment methods are relatively ineffective. Many studies have shown that long noncoding RNA (lncRNA) may participate in gene mutation and genomic instability in cancer.

Methods

We downloaded transcriptome data, mutation data, and clinical follow-up data of melanoma patients from The Cancer Genome Atlas. We divided samples into groups according to the number of somatic cell mutations and then performed a differential analysis to screen out the differentially expressed genes. We then divided samples into genomic unstable and genomic stable groups. We compared lncRNA expression profiles in these groups and constructed a protein-coding genes network coexpre

SUBMITTER: Yan K 

PROVIDER: S-EPMC8169244 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature