GlycA Biomarker for Colorectal Cancer Risk Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current biomarkers, such as carcinoembryonic antigen (CEA) and inflammatory markers, are inadequate for accurately predicting or assessing the risk of developing colorectal cancer (CRC) or mortality due to low specificity and inconsistent results.
Innovation Solution
The use of protein glycan N-acetyl groups (GlycA) as a novel systemic inflammatory biomarker to determine the risk of CRC incidence or mortality by measuring its concentration in biological samples, particularly through NMR analysis, and incorporating additional proteins like hsCRP, fibrinogen, and sICAM-1 to create a CRC risk index.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If CEA is used to identify incident CRC, then monitoring CRC recurrence and prognosis is improved, but specificity for CRC identification deteriorates due to low specificity
Solution Approach 1:
The patent transitions from using CEA protein levels to measuring GlycA (N-acetyl group signal from glycoproteins) as a new parameter. This parameter change resolves the contradiction by providing a biomarker that maintains reliability for CRC monitoring while improving specificity for incident CRC identification, as GlycA reflects systemic inflammation more accurately than CEA.
2Reliability
If inflammatory biomarkers like hsCRP are used to predict CRC risk, then CRC risk prediction is attempted, but consistency of associations deteriorates due to inconsistent results
Solution Approach 1:
The patent replaces traditional inflammatory biomarkers (hsCRP, fibrinogen) with GlycA as the measurement parameter. This change resolves the inconsistency issue because GlycA, measured by NMR spectroscopy, provides a more stable and consistent association with incident CRC risk across different populations and studies, unlike the variable results obtained with conventional inflammatory markers.
3Measurement precision
If a novel biomarker like GlycA is introduced, then CRC risk prediction accuracy is improved, but device complexity increases due to NMR analysis requirements
Solution Approach 1:
The patent leverages the universality of NMR spectroscopy, which is already widely used for lipid profiling and metabolic studies. By measuring GlycA using the same NMR platform that clinicians already employ for routine metabolic assessments, the patent achieves high measurement precision without requiring entirely new complex equipment, thus reducing the practical barrier to implementation.
Data Source
AI summary
Disclosed are methods and systems that uses GlycA concentration in biosamples to evaluate risks of CRC incidence and mortality.


