Convergent molecular evidence identifies a robust seven-gene signature in esophageal squamous cell carcinoma

Esophageal Squamous Cell Carcinoma (ESCC) is an aggressive gastrointestinal malignancy with unfavorable clinical outcomes, and current molecular biomarkers offer limited clinical utility for early detection and precise risk stratification. In this study, we integrated multi-cohort transcriptomic profiling with systems-level network analysis and causal inference to identify robust candidate biomarkers. Differential expression analysis across four independent datasets revealed consistent transcriptional alterations in ESCC. Several co-expression modules derived from the core dataset remained stable across independent cohorts and demonstrated significant correlations with tumor status. Mendelian Randomization (MR) analysis of module-derived genes prioritized 18 candidates with genetically supported associations with ESCC risk. These candidates were further refined using Least Absolute Shrinkage and Selection Operator (LASSO) regression, yielding a seven-gene diagnostic signature comprising LMBRD1, ZNF365, NPEPPS, CCNB1, TFRC, COL4A1, and TIMELESS. The resulting signature demonstrated strong discriminatory performance in both training and independent validation cohorts. To strengthen biological relevance, MR-prioritized genes were additionally supported by protein-level evidence from four independent ESCC proteomic studies. Collectively, this integrative analytic framework highlights convergent molecular features of ESCC and identifies a seven-gene signature with strong diagnostic performance. Ultimately, experimental validation in cellular and clinical cohorts will be essential to translate these computational findings into clinically actionable strategies for ESCC.