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

Wei Jiang; Feifei Zheng; Taotao Yao; Fang Gong; Wenjie Zheng; Ninghua Yao

doi:10.21037/atm-21-5569

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

Ann Transl Med. 2021 Nov;9(22):1686. doi: 10.21037/atm-21-5569.

Authors

Wei Jiang^#¹, Feifei Zheng^#², Taotao Yao^#³, Fang Gong², Wenjie Zheng⁴, Ninghua Yao⁵

Affiliations

¹ Department of Neurology, the Second People's Hospital of Wuxi, Wuxi, China.
² Department of Laboratory Medicine, Affiliated Hospital of Jiangnan University, Wuxi, China.
³ Rehabilitation Center, the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou, China.
⁴ Research Center of Clinical Medicine, Affiliated Hospital of Nantong University, Nantong, China.
⁵ Department of Oncology, Affiliated Hospital of Nantong University, Nantong, China.

^# Contributed equally.

Abstract

Background: 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 (IFI30) is associated with the malignant phenotype, but the effect of IFI30 on the tumour immune microenvironment and its potential role in the carcinogenesis of glioma remain unknown.

Methods: 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 IFI30 in pan-cancer, evaluation of IFI30 as a prognostic biomarker in glioma, the relationship between IFI30 expression and clinical characteristics, and immune checkpoint. TIMER was used to analyse the correlation of IFI30 expression level with immune cell infiltration, and also to conduct survival analysis for immune cells and IFI30 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 IFI30 in glioma. The differentially expressed genes (DEGs) between the high- and low-IFI30 expression groups were determined by DESeq2. Gene set enrichment analysis (GSEA) was then conducted to identify IFI30-related functional significance based on the hallmark gene set.

Results: Dysregulated expression of IFI30 was associated with human cancers. High IFI30 expression was associated with poor overall survival (OS), disease-specific survival (DSS) and progression-free interval (PFI). Univariate and multivariate analyses identified IFI30 as an independent predictor for glioma. Meanwhile, IFI30 overexpression significantly correlated with high-grade tumours, poor OS, and immune infiltration. In addition, IFI30-associated genes significantly enriched the hallmark tumour progression-related clusters and cancer pathways.

Conclusions: IFI30 is a prognostic biomarker correlated with immune infiltrates and acts as an oncogene in glioma.

Keywords: Interferon-gamma-inducible protein 30 (IFI30); glioma; prognosis; tumour immune infiltration.