A cfDNA fragmentomics-based machine learning model for predicting treatment response and recurrence in locally advanced rectal cancer after neoadjuvant chemoradiotherapy
A blood test based on DNA patterns distinguished treatment response in rectal cancer and may help predict recurrence risk.
We analyzed 102 patients with LARC treated with nCRT followed by surgery, using 510 longitudinal plasma samples collected at five perioperative time points. Fragmentia-AI Response is a mutation-independent cfDNA fragmentomics model that showed reproducible discrimination of pathological response and associations with recurrence risk in LARC, supporting further evaluation as a minimally invasive biomarker for treatment stratification and surveillance.
What the study was
- Study design
- Observational/Cohort Study
- Population
- Neoadjuvant chemoradiotherapy (nCRT) is standard treatment for locally advanced rectal cancer (LARC)
- Sample size
- 102
- Category
- Early Detection
- Maturity
- Validated
- Journal
- The journal of liquid biopsy
Why it surfaced
Primary method is liquid biopsy/ctDNA/cfDNA for cancer detection; moderate relevance to watchlist
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