Blood Test May Predict Colorectal Cancer Recurrence
Researchers from KAIST and partner hospitals have developed a new method to predict colorectal cancer recurrence by analyzing networks of circulating amino acids in the blood. This metabolic mapping approach demonstrates higher predictive accuracy than traditional CEA-only models.
Why it matters
Improved predictive tools for cancer recurrence could lead to more personalized treatment plans and better patient outcomes by identifying high-risk individuals earlier.
A single preoperative blood sample may help improve the prediction of recurrence or metastasis in patients with colorectal cancer. A joint research team from KAIST, Gangnam Severance Hospital, and Asan Medical Center has shown that, as colorectal cancer advances, the network of relationships among circulating amino acids (a kind of metabolic map) undergoes systematic remodeling. Building on this finding, the researchers developed an analytical method that showed higher predictive performance than a CEA-only model and models based solely on individual amino acid levels.
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