Four-copy number alteration (CNA)-related lncRNA prognostic signature for liver cancer

Abstract

The objective of this study was to identify CNA-related lncRNAs that can better evaluate the prognosis of patients with liver cancer. Prognostic molecular subtypes were identified, followed by tumor mutation and differential expression analyses. Genomic copy number anomalies and their association with lncRNAs were also evaluated. A risk model was built based on lncRNAs, as well as a nomogram, and the differences in the tumor immune microenvironment and drug sensitivity between the High_ and Low_risk groups were compared. Weighted gene co-expression network analysis was used to identify modules with significant enrichment in prognostic-related lncRNAs. In total, two subtypes were identified, TP53 and CTNNB1 were common high-frequency mutated genes in the two subtypes. A total of 8,372 differentially expressed (DE) mRNAs and 798 DElncRNAs were identified between cluster1 and cluster2. In addition, a four-lncRNA signature was constructed, and statistically significant differences between the Low_ and High_risk groups were found in terms of CD8 T cells, resting memory CD4 T cells, etc. Enrichment analysis showed that prognostic-related lncRNAs were involved in the cell cycle, p53 signaling pathway, non-alcoholic fatty liver disease, etc. A prognostic prediction signature, based on four-CNA-related lncRNAs, could contribute to a more accurate prognosis of patients with liver cancer.

Multi-Omics Mining of lncRNAs with Biological and Clinical Relevance in Cancer

“…Indeed, this aspect was consistent with our knowledge that the differential gene expressions of the protein-coding cancer driver genes were significantly correlated with the CNAs [82,91]. As a consequence, researchers have begun to delineate the correlation between the SCNAs and expression levels as useful parameters for defining the gain or loss of function of lncRNAs with oncogenic or tumor suppressor functions and for potentially associating them with the clinical outcome for different tumors [47][48][49][50]56,57,82].…”

Vesicle-mediated transport-related genes predict the prognosis and immune microenvironment in hepatocellular carcinoma

“…While liver transplantation, local ablation, chemoembolization and targeted therapies are available for LIHC, the clinical outcome remains modest [25]. Researchers have used various signatures, including DNA repair-related genes, RNA modification-related genes, cell death-related genes, ligand-receptor pair-related genes, copy number alteration-related lncRNAs, microenvironment-related lncRNAs and exosomerelated lncRNAs, to predict the prognosis of LIHC [26][27][28][29][30][31]. However, more precise prognostic signatures are still lacking.…”