Establishment of a risk model by integrating hypoxia genes in predicting prognosis of esophageal squamous cell carcinoma

Abstract Esophageal squamous cell carcinoma (ESCC) has a dismal prognosis and hypoxia plays a key role in metastasis and proliferation of ESCC. Thus, we aimed to develop a hypoxia-based gene signature to assist in the diagnosis and prognosis. We performed consensus clustering analysis based on differentially expressed hypoxia related genes (HRGs) acquired from the GSE53625 dataset and The Cancer Genome Atlas (TCGA), and used weighted gene co-expression network analysis to filter out candidate modules which were then intersected with differentially expressed genes from clustered subgroups to obtain HRGs. The HRGs were used for stepAIC algorithm to construct risk score models and validated in TCGA database. Independent prognostic factors after univariate and multivariate COX analyses were used to construct the prognostic nomogram. Immunohistochemical were used to detect protein expression levels of relevant genes. And the relationship between risk scores and tumor microenvironment was explored. A hypoxia risk model containing 6 genes (PNPLA1, CARD18, IL-18, SLC37A2, ADAMTS18 and FAM83C) was constructed by screening key HRGs. Poorer prognosis in the high-risk group than in the low-risk group. And Cox regression analysis showed that risk score was independent prognostic factors. Nomogram based on risk scores could well predict 1-, 3-, and 5-year survival. P53, Wnt, and hypoxia signaling pathways may be some regulatory mechanisms of hypoxia associated with tumor microenvironment. In addition, we confirmed the high expression of BGN and low expression of IL-18 in ESCC tissues. Our study determined the prognostic value of a 6-hypoxia gene signature and a prognostic model, providing potential prognostic predictors and therapeutic targets for ESCC.