US EditionMachine Learning Tool Identifies Metabolic Clues in Colorectal Cancer
- Researchers at Ohio State University developed a machine-learning tool that distinguishes metabolic differences in colorectal cancer patients using samples from over 1,000 individuals as of May 2025.
- This effort built on large biological sample collections and combined partial least squares-discriminant analysis with artificial neural networks to improve molecular profile classification.
- The analysis revealed metabolic changes linked to disease progression and genetic factors increasing cancer risk, emphasizing purine metabolism activity differences across patient stages.
- Co-Senior author Jiangjiang Zhu emphasized that metabolic biomarkers identified through this approach have potential not only for diagnosing colorectal cancer but also for tracking the success of ongoing treatments.
- Further validation with additional samples is planned to refine this noninvasive biomarker pipeline before clinical application, aiming to enhance colorectal cancer diagnosis and progression assessment.
14 Articles
14 Articles
Machine learning tool identifies metabolic clues in colorectal cancer
Scientists aiming to advance cancer diagnostics have developed a machine learning tool that is able to identify metabolism-related molecular profile differences between patients with colorectal cancer and healthy people.
Key mechanism in embryonic development makes colorectal cancer more aggressive, study finds
Tumor cells in colorectal cancer exploit an important signaling pathway that normally controls embryo development. Researchers have now shown how a protein that controls the development of the arms and heart contributes to making colorectal cancer cells more aggressive and likely to spread.
Colon Tumors, in Metastases the Mutations of DNA Put the "Turbo" in. New Study of the "IRCSS" of Candiol
As the tumor to the colon progresses, it also increases the rate of mutation of its DNA. The aim of the research is to understand what are the elements that distinguish the aggressive forms from the indolent ones to calibrate the cures
DNA “Time Bomb” – Common Childhood Bacteria Linked To Surge in Early-Onset Colorectal Cancer
A UC San Diego-led study linked early childhood exposure to the bacterial toxin colibactin with the rise in early-onset colorectal cancer, finding distinct DNA mutations in younger patients. The discovery points to a microbial influence on cancer risk from an early age. An international team of researchers, led by the University of California San Diego, [...]
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