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Identification of a Hypoxia-Related Gene Signature and Establishment of a Nomogram for Predicting Prognosis in Esophageal Squamous Cell Carcinoma


 BackgroundEsophageal squamous cell carcinoma (ESCC), the major subtype of esophageal cancer in China, has a dismal prognosis. Tumor hypoxia, a typical characteristic of many solid tumors, leads to tumor invasion and poor prognosis. We aimed to develop a hypoxia-based gene signature to assist in the diagnosis and prognosis prediction of ESCC.MethodsWe integrated gene expression files from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases to identify potential hypoxia-related genes (HRGs). Euclidean-based consensus clustering was performed on the GSE53625 ESCC samples. Immune cell infiltration, differential expression, and Kaplan-Meier survival analyses were performed. Candidate modules were screened using weighted gene coexpression network analysis and then intersected with differentially expressed genes from clustered subgroups to construct the gene signatures that were verified in internal and external datasets. A nomogram was developed with risk scores and clinicopathological variables. Finally, immunohistochemistry was used to detect the protein expression level of relevant genes. Additionally, the relationships between risk scores and the tumor microenvironment were explored.ResultsA total of 5 potential differentially expressed HRGs and 6 critical HRGs were identified. A prognostic model was constructed by screening key HRGs, and higher risk scores were associated with poorer prognosis. The nomogram based on risk scores predicted the 1-, 3-, and 5-year survival rates well, thus determining prognostic risk stratification. The p53, Wnt, and hypoxia signaling pathways may be some of the regulatory mechanisms of hypoxia associated with the tumor microenvironment. Furthermore, the high expression of BGN and low expression of IL-18 in ESCC tissues was verified and was associated with a shorter survival time.ConclusionsOur study systematically explored HRGs and determined the prognostic value of a 6-hypoxia gene signature. A prognostic model was developed and validated based on this, providing potential prognostic predictors and therapeutic targets for ESCC.