Machine Learning Enhances Diagnosis and Monitoring of Colorectal Cancer
A novel machine learning platform developed by researchers enhances the diagnosis and monitoring of colorectal cancer through metabolic biomarker analysis, offering a promising noninvasive approach to early detection and disease progression assessment.
Researchers have developed an innovative machine learning platform aimed at improving the diagnosis and monitoring of colorectal cancer. This advanced tool analyzes metabolic differences in biological samples from over 1,000 individuals, distinguishing between patients with colorectal cancer and healthy controls. The study identified specific metabolic shifts that correlate with disease severity and genetic risk factors, offering promising avenues for noninvasive diagnostics.
The platform, named PANDA (PLS-ANN-DA), integrates partial least squares-discriminant analysis (PLS-DA) and artificial neural networks (ANN) to enhance predictive accuracy. Using blood samples from large-scale research initiatives, the team examined metabolites—products of biochemical reactions—and transcriptomic data, providing a comprehensive view of molecular alterations associated with cancer.
Although not intended to replace colonoscopy, the current gold standard for screening, this biomarker discovery pipeline could significantly aid early detection and disease progression monitoring. Its potential also extends to assessing treatment responses more rapidly than traditional methods, such as pathology or protein markers.
The researchers emphasize that further validation with additional samples is necessary before clinical application. This approach also offers insights into cancer biology, especially pathways involving purines, which are crucial for DNA synthesis and repair. The study demonstrates a robust advancement in machine learning and bioinformatics, opening pathways for future diagnostic technologies in colorectal cancer management.
This groundbreaking work was published in iMetaOmics, with contributions from researchers at Ohio State University and the City of Hope National Cancer Center. Additional insights from this study could revolutionize how clinicians diagnose, monitor, and understand colorectal cancer in the future.
Source: https://medicalxpress.com/news/2025-05-machine-tool-colorectal-cancer.html
Stay Updated with Mia's Feed
Get the latest health & wellness insights delivered straight to your inbox.
Related Articles
Resurgence of a Forgotten Opioid as a Deadly Street Drug
Nitazenes, highly potent synthetic opioids, have resurfaced as a major and often unseen threat in the overdose crisis due to their extreme potency and detection challenges. Experts emphasize the need for increased awareness, testing, and harm reduction strategies to combat this emerging public health emergency.
Innovative Nonviral Gene Therapy Shows Promise for Age-Related Heart Disease
Exploring innovative nonviral gene therapy, scientists at Ohio State have demonstrated potential in reversing age-related decline in heart function by increasing beneficial fat-derived molecules, offering hope for combating cardiovascular disease in aging populations.
Critical Role of a Nine-Amino Acid Microexon in Neuronal Memory Function in Mice
Research reveals a tiny nine-amino acid microexon in neurons crucial for memory formation in mice. Its regulation impacts synaptic connections and cognitive function, offering potential insights into neurodevelopmental disorders.
The Role of Robots in Supporting Healthy Aging and Independence
Explore how socially assistive robots are transforming aging by supporting independence, mental well-being, and daily living for seniors. Learn about the benefits, challenges, and future prospects of robotic assistance in elder care.