Dengyun Zhao, Xinyu He, Yaping Guo, Huifang Wei, Zigang Dong, Kangdong Liu. Advances in Multi-Omics for Esophageal Squamous Cell Carcinoma: Diagnostic, Prognostic, and Therapeutic PerspectivesJ. Protein&Cell.
Citation: Dengyun Zhao, Xinyu He, Yaping Guo, Huifang Wei, Zigang Dong, Kangdong Liu. Advances in Multi-Omics for Esophageal Squamous Cell Carcinoma: Diagnostic, Prognostic, and Therapeutic PerspectivesJ. Protein&Cell.

Advances in Multi-Omics for Esophageal Squamous Cell Carcinoma: Diagnostic, Prognostic, and Therapeutic Perspectives

  • Esophageal squamous cell carcinoma (ESCC) remains a major health burden, particularly in Asia, with poor patient prognosis despite advancements in radiotherapy, chemotherapy, and immunotherapy. The marked inter-patient and intra-tumor heterogeneity of ESCC underscores the need for molecularly informed diagnostic and therapeutic strategies. Recent high-throughput omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have substantially advanced our understanding of ESCC biology. Genomic profiling has revealed recurrent alterations such as TP53 and NOTCH1 mutations, as well as actionable targets including PIK3CA, FGFR1, and SOX2 amplifications, which provide new opportunities for precision therapy. Epigenomic and transcriptomic analyses have identified methylation-based early detection markers (e.g., PAX9, SIM2) and immune-related transcriptomic subtypes associated with prognosis and immunotherapy responsiveness. Proteomic and metabolomic studies have further uncovered cell cycle and spliceosome pathway activation and altered lactate metabolism, offering additional biomarker and therapeutic insights. In this review, we synthesize these multi-omics advances and highlight how they collectively inform improved diagnostic, prognostic, and therapeutic strategies for ESCC. Despite these developments, the clinical translation of multi-omics findings remains limited due to the lack of standardized analytical pipelines, insufficient multi-center validation, and the high cost and technical complexity of integrating multi-omics data into routine clinical workflows. Future research integrating artificial intelligence with multi-omics data holds promise for enhancing diagnostic accuracy and enabling more precise therapeutic decision-making in ESCC.
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