Circulating tumor DNA dynamics predict pathological response and guide therapy personalization in the neoadjuvant setting

循环肿瘤DNA动态变化可预测病理反应,并指导新辅助治疗中的个体化治疗。

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Abstract

Neoadjuvant therapy is a cornerstone of modern oncology, yet its efficacy is traditionally assessed only after treatment completion, creating a "black box" period where patients may receive ineffective, toxic therapies. This review explores the transformative potential of circulating tumor DNA (ctDNA) as a dynamic biomarker to overcome this limitation. The short half-life of ctDNA allows for real-time, non-invasive monitoring of tumor burden through serial liquid biopsies. A substantial body of evidence across breast, lung, colorectal, and other solid tumors demonstrates that on-treatment ctDNA dynamics are a powerful predictor of pathological response and long-term survival. Rapid ctDNA clearance is strongly associated with favorable outcomes, providing a rationale for treatment de-escalation, while persistent ctDNA identifies non-responders who may benefit from therapy intensification. Despite its promise, the clinical adoption of ctDNA is hindered by challenges including a lack of assay standardization, the existence of low-shedding tumors, and biological confounders like clonal hematopoiesis. The future of precision neoadjuvant care lies in integrating ctDNA with imaging and other biological data within a multimodal framework, leveraging artificial intelligence to guide personalized, response-adapted treatment strategies. This paradigm shift from static to dynamic assessment promises to unlock the full potential of neoadjuvant therapy, maximizing efficacy while minimizing toxicity for individual patients.

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