Esophageal cancer (EC) is a highly aggressive malignancy, with esophageal squamous cell carcinoma (ESCC) accounting for the majority of cases worldwide. Despite advances in treatment, the prognosis for ESCC remains poor, underscoring the urgent need for reliable prognostic biomarkers to guide clinical decision-making. In this study, we constructed a novel prognostic model by integrating cuproptosis-related genes with ferroptosis and immune-associated genes-three critical pathways implicated in tumor progression and immune modulation. Gene expression and clinical data from ESCC patients were obtained from the GSE53625 and TCGA-ESCC cohorts. Ferroptosis- and immune-related genes (FIRGs) were sourced from FerrDb and ImmPort databases, and their association with cuproptosis-related genes was determined via Pearson correlation, yielding a set of cuproptosis-associated FIRGs (FI-CRGs). Thirteen prognostically relevant FI-CRGs were identified through Cox regression analysis and used to develop a risk score model (FI-CRS). The FI-CRS demonstrated robust predictive performance in both the training cohort (GSE53625, n = 179) and the independent validation cohort (TCGA-ESCC, n = 81), where high-risk patients exhibited significantly reduced overall survival (p < 0.05). Functional enrichment analyses (GO and KEGG) revealed strong associations between high FI-CRS and immunoregulatory pathways. Further investigation showed notable differences in immune cell infiltration and drug sensitivity between risk groups. Additionally, a prognostic nomogram incorporating clinical features (age, gender, TNM staging, and FI-CRS) was established to enhance individualized survival prediction. Altogether, this study presents a novel, integrative in silico framework that not only offers promising biomarkers for prognosis but also provides mechanistic insights into ESCC biology, potentially informing future therapeutic strategies.
