The EACR’s ‘Highlights in Cancer Research’ is a regular summary of the most interesting and impactful recent papers in cancer research, curated by the Board of the European Association for Cancer Research (EACR).
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Beddowes, E.J. et al. Molecular Oncology. 19: 3518-3534. (2025).
doi: 10.1002/1878-0261.70015.
Summary of the findings
Monitoring circulating tumour DNA (ctDNA) in blood offers a practical, non-invasive way to track cancer in real time. In this real-world study, we evaluated whether repeated ctDNA measurements could predict treatment response in patients with metastatic breast cancer.
We analysed 1,013 serial blood samples from 149 patients treated in routine clinical practice, using a rapid and low-cost sequencing method to estimate the proportion of tumour DNA in the bloodstream. We identified a 7% tumour DNA threshold that stratified patients by risk of disease progression, consistent across breast cancer subtypes and treatments, and outperforming standard blood tests and targeted sequencing.
Using longitudinal ctDNA data, we developed a Bayesian machine learning model to predict treatment response with good accuracy. This approach enables dynamic, patient-specific risk assessment over time.
These findings show that real-world ctDNA monitoring, combined with machine learning, can provide early and clinically meaningful insight into treatment effectiveness. This strategy has the potential to support more timely, data-driven treatment decisions and improve patient outcomes, and warrants prospective evaluation in large-scale clinical trials.
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