Identification and Verification of an Alternative Polyadenylation-Related lncRNA Prognostic Signature for Glioma

TL;DR

This paper presents a new glioma prognosis model using alternative polyadenylation-related lncRNAs, which helps assess patient outcomes and immune suppression.

Contribution

A novel lncRNA-based prognostic signature for glioma is developed, linking APA-related genes to immune suppression and patient survival.

Findings

The APA-related lncRNA model effectively separates glioma patients into high- and low-risk groups with distinct survival outcomes.

High-risk patients show increased immune suppression markers like CTLA4, LAG3, and PD1/PDL1 expression.

The model reflects immune cell infiltration and signaling pathway enrichment in cellular immunity and immune transduction.

Abstract

Due to the high mortality and modality of glioma, it was urgently needed to develop a glioma prognostic assessment system. Previous studies demonstrated that alternative polyadenylation- (APA-) related genes are important in immune response and oncogenesis. mRNA and lncRNA expression information of glioma samples were acquired from CGGA and TCGA databases, and lncRNAs associated with APA were selected through correlation analysis. The prognosis model of APA-related lncRNAs was built by the univariate Cox, random forest, and univariate Cox regression analyses. Glioma samples were assigned into high- and low-risk groups. Independence and effectiveness of the prognostic model were evaluated by Kaplan-Meier analysis, ROC curve, and Cox regression analyses. GO, KEGG enrichment, and GSEA analyses showed that the mainly involved signaling pathways were enriched in cellular immunity and immune signal transduction. We further analyzed expression differences of negative immune regulatory genes and immune cell infiltration degree between two groups. Immune checkpoints CTLA4 and LAG3 and immune suppressors TGFB, IL10, NOS3, and IDO1 and immune cell infiltration were notably upregulated in the high-risk group. The PD1/PDL1 expression was significantly correlated with risk score, showing that the prognostic model of APA-related lncRNA could effectively assess the tumor immune suppression. In conclusion, we established a risk assessment model of APA-related lncRNA in glioma, which could effectively evaluate prognosis of patients with glioma and tumor immune suppression and could provide guidance for clinical treatment.

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