IFI30 as a prognostic biomarker and correlation with immune infiltrates in glioma

• Published in: Annals of translational medicine Vol. 9; no. 22; p. 1686
• Main Authors: Jiang, Wei, Zheng, Feifei, Yao, Taotao, Gong, Fang, Zheng, Wenjie, Yao, Ninghua
• Format: Journal Article
• Language: English
• Published: China AME Publishing Company 01-11-2021
• Subjects: Original; glioma; tumour immune infiltration; prognosis; Interferon-gamma-inducible protein 30 (IFI30)
• ISSN: 2305-5839; 2305-5839
• DOI: 10.21037/atm-21-5569

Increased evidence indicates that the tumour microenvironment (TME) plays an essential role in the development, treatment and prognosis of glioma. High expression of interferon-gamma-inducible protein 30 (
) is associated with the malignant phenotype, but the effect of
on the tumour immune microenvironment and its potential role in the carcinogenesis of glioma remain unknown.
The RNA sequencing (RNA-seq) data of 33 types of human cancer were obtained from The Cancer Genome Atlas (TCGA) Genomic Data Commons (GDC). R software was used to perform analyses, such as the expression of
in pan-cancer, evaluation of
as a prognostic biomarker in glioma, the relationship between
expression and clinical characteristics, and immune checkpoint. TIMER was used to analyse the correlation of
expression level with immune cell infiltration, and also to conduct survival analysis for immune cells and
in low grade glioma (LGG). DAVID was used for Gene Ontology (GO) functional annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) for pathway analysis of the genes similar to
in glioma. The differentially expressed genes (DEGs) between the high- and low-
expression groups were determined by DESeq2. Gene set enrichment analysis (GSEA) was then conducted to identify
-related functional significance based on the hallmark gene set.
Dysregulated expression of
was associated with human cancers. High
expression was associated with poor overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). Univariate and multivariate analyses identified
as an independent predictor for glioma. Meanwhile,
overexpression significantly correlated with high-grade tumours, poor OS, and immune infiltration. In addition,
-associated genes significantly enriched the hallmark tumour progression-related clusters and cancer pathways.
is a prognostic biomarker correlated with immune infiltrates and acts as an oncogene in glioma.