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

BACKGROUND: 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 treatment decisions and prognosis. METHODS: We performed consensus clustering analysis on samples from GSE53625 dataset from the Gene Expression Omnibus (GEO) database 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 hypoxia‐related genes (HRGs). After that, the aforementioned genes were used to construct risk score models and validated in The Cancer Genome Atlas (TCGA) database and Cox regression analysis were used to construct a nomogram. Immunohistochemical was used to detect protein expression levels of relevant genes. Moreover, the relationship between risk scores and tumor microenvironment was explored. RESULTS: A hypoxia risk model containing six 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 an independent prognostic factor. The 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 the tumor microenvironment. In addition, we confirmed the high expression of BGN and low expression of IL‐18 in ESCC tissues. CONCLUSIONS: 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.