Autoantibody Panels for Early Colorectal Disorder Classification
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Solution Overview
Problem
Colorectal cancer is often diagnosed late due to inadequate screening methods like colonoscopy, leading to high mortality rates, and existing blood-based tests lack sensitivity and specificity for early detection of colon cell proliferative disorders.
Innovation Solution
Development of autoantibody panels and machine learning models using specific autoantibodies to antigens like NME5, USP16, UBE2S, and others to differentiate between healthy individuals and those with colon cell proliferative disorders, such as adenomas and colorectal cancer, and a system for processing these autoantibodies to classify subjects accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If colonoscopy is performed for screening, then detection capability is improved, but patient compliance and accessibility deteriorate due to invasiveness and cost
Solution Approach 1:
The patent replaces the mechanical/invasive colonoscopy procedure with a non-invasive blood-based autoantibody assay. The system uses automated machine learning models to analyze autoantibody profiles from simple blood samples, eliminating the need for complex mechanical procedures while maintaining high detection accuracy for colon cell proliferative disorders
Solution Approach 2:
The patent introduces autoantibodies as intermediary biomarkers that mediate between the disease state and detection. Instead of directly observing colon tissue through colonoscopy, the system detects autoantibody responses in blood that indirectly indicate the presence of colon cell proliferative disorders, making the screening process non-invasive while preserving diagnostic capability
2Ease of operation
If existing blood-based tests are used, then accessibility is improved, but sensitivity and specificity deteriorate for early detection
Solution Approach 1:
The patent segments the detection process into multiple independent autoantibody measurements across different antigens (e.g., CDK4, MTCP1, PCOLCE, ZBTB2). By analyzing multiple discrete autoantibody markers rather than a single test, the system achieves both high sensitivity and specificity while maintaining the accessibility of blood-based testing
Solution Approach 2:
The patent transitions from single-marker blood tests to multi-dimensional autoantibody profiling across multiple antigens and immunoglobulin classes (IgG, IgM). This dimensional expansion of the detection space enables simultaneous improvement of sensitivity, specificity, and accessibility by capturing complex immune responses to colon cell proliferative disorders
3Reliability
If diagnostic tests are performed later, then false positives are reduced, but mortality rates increase due to late diagnosis
Solution Approach 1:
The patent enables preliminary detection of colon cell proliferative disorders at early stages through sensitive autoantibody profiling before symptoms manifest or lesions progress. By detecting disease markers in advance through blood-based autoantibody assays, the system allows for early intervention while maintaining test reliability, thus reducing both loss of time and mortality rates
Data Source
AI summary
Systems, media, compositions, methods, and kits disclosed herein relate to a panel of autoantibody biomarkers for the early detection of colon cell proliferative disorders, including colorectal cancer. The presence or levels of the autoantibodies in a biological sample for the autoantibody panels described herein may be used for classifier generation, and as inputs in machine learning models useful to classify subjects in a population for the detection of colon cell proliferative disorders.