Biomarkers have transformed cancer care by linking molecular insights to personalized treatment strategies. This review first surveys the spectrum of detection modalities, including tissue genomics and histopathology; liquid biopsies such as circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and extracellular vesicles; imaging and radiomics; and multi-omic approaches spanning epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics. We then critically appraise the translational challenges that hinder clinical implementation, assay standardization, data integration, analytical and clinical validation, regulatory pathways, and cost-effectiveness. Finally, we explore emerging solutions, including artificial intelligence (AI)-driven multi-modal phenotyping, adaptive trial designs, and point-of-care assays, and outline future directions for expanding access and equitable adoption. By emphasizing the central role of biomarkers in guiding targeted and immune-based therapies, we underscore their potential to overcome tumor heterogeneity, preempt resistance, and ultimately improve patient outcomes.
生物标志物通过将分子层面的洞察与个体化治疗策略相连接，已深刻改变了癌症诊疗模式。本文首先系统梳理了各类检测技术体系，涵盖组织基因组学与病理学分析；以循环肿瘤DNA（ctDNA）、循环肿瘤细胞（CTCs）和细胞外囊泡为代表的液体活检技术；影像组学方法；以及横跨表观基因组学、转录组学、蛋白质组学、代谢组学和微生物组学的多组学整合策略。继而深入剖析了阻碍临床转化的关键挑战，包括检测标准化、数据整合、分析验证与临床验证、监管审批路径及成本效益等问题。最后，我们探讨了人工智能驱动的多模态表型分析、适应性临床试验设计和床旁检测等新兴解决方案，并展望了提升技术可及性与公平性应用的未来方向。通过强调生物标志物在指导靶向治疗和免疫治疗中的核心作用，本文揭示了其在克服肿瘤异质性、预测耐药机制以及最终改善患者预后方面的巨大潜力。
肿瘤(癌症)患者之家