Esophageal squamous cell carcinoma (ESCC) presents a five-year survival rate below 20%, underscoring the need for improved prognostic markers. Our study analyzed ESCC-specific datasets to identify consistently differentially expressed genes. A Venn analysis followed by gene network interactions revealed 23 key genes, from which we built a prognostic model using the COX algorithm (p = 0.000245, 3-year AUC = 0.967). This model stratifies patients into risk groups, with high-risk individuals showing worse outcomes and lower chemotherapy sensitivity. Moreover, a link between risk scores and M2 macrophage infiltration, as well as significant correlations with immune checkpoint genes (e.g., SIGLEC15, PDCD1LG2, and HVCR2), was discovered. High-risk patients had lower Tumor Immune Dysfunction and Exclusion (TIDE) values, suggesting potential responsiveness to immune checkpoint blockade (ICB) therapy. Our efficient 23-gene prognostic model for ESCC indicates a dual utility in assessing prognosis and guiding therapeutic decisions, particularly in the context of ICB therapy for high-risk patients.
Keywords: Esophageal squamous cell carcinoma; gene signature; immunotherapy; prognosis.