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

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Authors: Hani Moslem Ahmed, Ali Fawzi Al-Hussainy, Wael Waleed Mustafa, S. Renuka Jyothi, Priya Priyadarshini Nayak, J. Bethanney Janney, Gurjant Singh, Aashna Sinha, Hayder Naji Sameer, Rasim Mahdi Salih, Mohaned Adil, Pouria Salajegheh
Cited by: 6
References: 201

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.

Fields of Study & Subjects

Cancer Genomics and Diagnostics Cancer Cells and Metastasis Single-cell and spatial transcriptomics

Publication details

Journal / source
Discover Oncology
Publisher
Springer Science and Business Media LLC
Volume
17
Issue
1
Publication date
29 January 2026
Language
EN