#AI Reads Urine# Urine-based metabolomics approach for multi-cancer screening and tumor origin prediction
Published 03 January, 2025
"Development of a urine-based metabolomics approach for multi-cancer screening and tumor origin prediction" was published in *Frontiers in Immunology*. It developed a method for multi-cancer screening and tumor origin prediction based on urine metabolomics.
Cancer is a major cause of death globally, and early diagnosis requires non-invasive screening. Multi-cancer early detection (MCED) tests can identify multiple cancers simultaneously, but a urine-based metabolomics screening strategy was lacking.
This study aimed to develop a urine metabolomics approach for multi-cancer diagnosis. It included 911 cancer patients (548 with lung cancer, 177 with gastric cancer, 186 with colorectal cancer), 563 with non-cancerous benign diseases, and 229 healthy controls. Participants were randomly divided into discovery and validation cohorts.
The study identified 360 metabolites in urine samples. Using the LASSO regression algorithm, 18 metabolites were selected as urinary metabolic biomarkers. The screening model (MP-SVM) had excellent discriminative performance, with an AUC of 0.96 in the validation cohort, outperforming the traditional tumor marker CEA. It also showed good classification of cancers from non-cancerous groups.
For tumor origin prediction, two non-overlapping metabolic panels were selected. One differentiated lung cancer from non-lung cancer with an AUC of 0.87 in the validation cohort, and the other differentiated gastric cancer from colorectal cancer with an AUC of 0.83. The overall accuracy of predicting the origin of three lethal cancers was 0.75.
In conclusion, this study demonstrated the potential of urine-based metabolomics for multi-cancer early detection, offering a non-invasive and promising screening method, though further validation and expansion are needed.
Front. Immunol., 13 December 2024. https://doi.org/10.3389/fimmu.2024.1449103
Youhe Gao
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