Abstract
BACKGROUND Numerous studies have shown that esophageal cancer (ESCA) contains areas of intertumoral hypoxia. It is widely accepted that the association of hypoxia with cancer stemness in the tumor microenvironment of ESCA is of profound clinical significance. However, reliable prognostic signatures based on hypoxia and cancer stemness are still lacking in ESCA. MATERIAL AND METHODS The t-SNE algorithm was used to estimate the hypoxia status based on the transcriptome profiles of the discovery cohort in the TCGA database. Median values of the stemness index were used to group and identify stemness-associated differentially expressed genes (DEGs). The LASSO method and Cox regression model were combined to screen for prognostic genes and to establish a genetic signature based on hypoxia-stemness. The robustness of the prognostic model was then tested in an external independent validation cohort of the GEO database. RESULTS A total of 8 genes - FBLN2, IL17RB, CYP2W1, AMTN, FABP1, FOXA2, GAS1, and CTSF - were identified to construct a gene signature for ESCA risk stratification. Overall survival was significantly lower in the high-risk group than in the low-risk group in both the internal discovery set and the external validation set. The risk score was found to be an independent prognostic factor for ESCA patients. In addition, a higher risk score was significantly associated with the sensitivity of ESCA patients to gefitinib, bexarotene, dasatinib, and imatinib. CONCLUSIONS The hypoxia-stemness-based genetic signature established for the first time in our study could be a promising tool for ESCA cancer risk stratification.