Identification and characterization of survival-dependent genes in esophageal cancer via the DepMap database: unraveling their association with immune infiltration.

Abstract

Background: Esophageal cancer ranks as the 11th most diagnosed cancer worldwide and the 7th leading cause of cancer-related deaths, mainly due to late-stage diagnosis. Identifying novel biomarkers is essential for enhancing prognostic evaluations and targeting patients for immunotherapy.

Methods: We used the DepMap database to identify survival-dependent genes in esophageal carcinoma cells. A prognostic model was developed using univariate and multivariate Cox regression and LASSO, validated with the GEO dataset. WGCNA and GSEA analyses were conducted to explore mechanisms, alongside ESTIMATE and ssGSEA for prognosis.

Results: We constructed a novel four-gene prognostic signature (CPSF6, IGBP1, MTG2, TCP1) based on SDG expression and survival data. This signature stratified esophageal cancer patients into high- and low-risk groups with significantly different survival, with the high-risk group showing shorter survival. WGCNA and GSEA analyses linked prognosis to immune pathways, including interferon-γ response and IL6-JAK-STAT3 signaling. ssGSEA revealed reduced infiltration of 19 immune cell types in high-risk patients, and ESTIMATE analysis confirmed the association between immune infiltration and poor prognosis.

Conclusion: This study establishes a four-gene survival signature for esophageal cancer that distinguishes high-risk from low-risk populations, providing novel prognostic indicators. Immune response pathways were downregulated in high-risk patients, offering potential targets for understanding esophageal cancer mechanisms and developing immunotherapeutic strategies.