Identification of ISG15 and ZFP36 as novel hypoxia- and immune-related gene signatures contributing to a new perspective for the treatment of prostate cancer by bioinformatics and experimental verification

• Published in: Journal of translational medicine Vol. 20; no. 1; p. 202
• Main Authors: Lyu, Fang, Li, Yunxue, Yan, Zhecheng, He, Qingliu, Cheng, Lulin, Zhang, Pu, Liu, Bing, Liu, Chunyu, Song, Yarong, Xing, Yifei
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 10.05.2022; BioMed Central; BMC
• Subjects: Algorithms; Analysis; Bioinformatics; Cancer; Cancer therapies; Care and treatment; Computational biology; Correlation analysis; Diagnosis; Genes; Genetic aspects; Genomes; Helper cells; Hypoxia; Hypoxia-related genes; Immune-related genes; Immunohistochemistry; Infiltration; ISG15; Laboratories; Leukocyte migration; Leukocytes (eosinophilic); Leukocytes (neutrophilic); Lymphocytes T; Medical prognosis; Metastases; Metastasis; Molecular modelling; Nomograms; Overexpression; Patients; Prostate cancer; Radiation therapy; Regression analysis; Risk factors; Risk groups; Statistical analysis; Survival analysis; Tumor-infiltrating lymphocytes; Wound healing; ZFP36; China; United States > US; ZFP36; ISG15; Hypoxia-related genes; Bioinformatics; Prostate cancer; Immune-related genes
• ISSN: 1479-5876; 1479-5876
• DOI: 10.1186/s12967-022-03398-4

Prostatic cancer (PCa) is one of the most common malignant tumors in men worldwide. Emerging evidence indicates significance of hypoxia and immunity in PCa invasion and metastasis. This study aimed to develop a hypoxia- and immune-related gene risk signature and explore the molecular mechanisms to formulate a better prognostic tool for PCa patients. The hypoxia and immune scores of all PCa patients in The Cancer Genome Atlas (TCGA) dataset were calculated via the maximally selected rank statistics method and the ESTIMATE algorithm. From common genes identified overlapping hypoxia- and immune-related differentially expressed genes (DE-HRGs and DE-IRGs), a hypoxia- and immune-related gene risk signature was developed utilizing univariate and multivariate Cox regression analyses, and validated in the Memorial Sloan Kettering Cancer Centre (MSKCC) database. The immune cell infiltration level of PCa samples were evaluated with ssGSEA algorithm. Differential expression of prognostic genes was evidenced by immunohistochemistry and western blot (WB) in paired PCa samples. Expression levels of these genes and their variations under regular and hypoxic conditions were examined in cell lines. The functional effects of the prognostic gene on PCa cells were examined by wound healing and transwell assays. A hypoxia- and immune-related gene risk signature constructed by ISG15 and ZFP36 displays significant predictive potency, with higher risk score representing worse survival. A nomogram based on independent prognostic factors including the risk score and Gleason score exhibited excellent clinical value in the survival prediction of PCa. Infiltration levels of eosinophils, neutrophils, Tcm, Tem, TFH, Th1 cells, and Th17 cells were significantly lower in the high-risk group. Conversely, aDC, pDC, T helper cells, and Tregs were significantly higher. Additionally, the two prognostic genes were closely correlated with the tumor-infiltrating immune cell subset in PCa progression. RT-qPCR and WB presented higher and lower expression of ISG15 and ZFP36 in PCa cells, respectively. They were correspondingly increased and decreased in PCa cells under hypoxic conditions. Wound healing and transwell assays showed that over-expression of ISG15 promoted the migration and invasion of PCa cells. Our study identified a novel hypoxia- and immune-related gene signature, contributing a new perspective to the treatment of PCa.