Data-Driven Molecular Typing: A New Frontier in Esophageal Cancer Management

数据驱动的分子分型:食管癌治疗的新前沿

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Abstract

BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is a predominant and highly lethal form of esophageal cancer, with a five-year survival rate below 20%. Despite advancements, most patients are diagnosed at advanced stages, limiting effective treatment options. Multi-omics integration, encompassing somatic genomic alterations, inherited genetic mutations, transcriptomics, proteomics, metabolomics, and single-cell sequencing, has enabled the identification of distinct molecular subtypes of ESCC. METHOD: This article systematically reviewed the current status of molecular subtyping of ESCC based on big data, summarized unique subtypes with differing treatment responses and prognostic outcomes. RESULT: Key findings included subtype-specific genetic mutations, signaling pathway alterations, and metabolomic profiles, which offer novel biomarkers and therapeutic targets. Furthermore, this review discusses the link between molecular subtypes and immunotherapy efficacy, chemotherapy response, and drug development. CONCLUSION: These insights highlight the potential of omics-based molecular typing to transform ESCC management and facilitate personalized treatment strategies.

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