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Nasopharyngeal carcinoma is characterized by marked biological and clinical heterogeneity that is only partly captured by conventional anatomical staging. This narrative review examines how circulating biomarkers, radiomics, artificial intelligence (AI), molecular profiling, and functional tumor models may complement tumor-node-metastasis (TNM)-based risk stratification in nasopharyngeal carcinoma (NPC). Relevant literature was identified through searches of PubMed, ScienceDirect, and Google Scholar, primarily covering 2016–2026, with earlier landmark studies retained when relevant. Plasma Epstein–Barr virus (EBV) DNA is an established prognostic biomarker that complements anatomical staging, while longitudinal measurements provide information on treatment response and recurrence risk. Radiomics and AI offer additional possibilities for prognostic modeling, although their use in treatment selection remains investigational. Genomic, epigenomic, transcriptomic, single-cell, spatial, proteomic, and phosphoproteomic studies characterize tumor and microenvironmental heterogeneity. Organoids, xenografts, humanized models, and engineered three-dimensional systems provide complementary platforms for functional investigation.
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Marin et al. (2026) studied this question.
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