A machine learning–based transcriptomic signature for predicting tumor recurrence after curative resection in T1 colorectal cancer: a retrospective multicenter cohort study (The Tw1CE trial)

Key Points

• Accurate prediction of tumor recurrence enhances post-surgery care and monitoring.
• The machine learning-based transcriptomic classifier uses data from endoscopic resection specimens effectively.
• Further assessment of the biomarker panel may enable personalized surveillance strategies following surgery.
• Risk-adapted approaches could guide decisions on additional therapy to prevent recurrence.