Microbial Nucleic Acid Profiling for Cancer Site Classification
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Solution Overview
Problem
Current cancer diagnostics fail to accurately identify the tissue/body site location and detect somatic mutations associated with cancer, lacking sensitivity and specificity, especially in early stages, and do not provide comprehensive data for medical intervention.
Innovation Solution
A method using nucleic acids from non-human origin in combination with human somatic mutations, employing machine learning to diagnose cancer location and predict therapeutic responses by analyzing k-mers and somatic mutations in biological samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If liquid biopsy-based diagnostics detect cancer-associated somatic mutations, then sensitivity for detecting cancer presence is improved, but ability to identify tissue/body site location deteriorates
Solution Approach 1:
The patent combines two previously separate diagnostic approaches into a single integrated system: (1) detection of cancer-associated somatic mutations and (2) identification of tissue/body site location through microbial nucleic acid patterns. By simultaneously analyzing both mutation data and microbial signature data from the same liquid biopsy sample, the system recovers both sensitivity for cancer detection and information about tissue location, eliminating the trade-off that existed when these functions were separated into different diagnostic categories
2Loss of information
If liquid biopsy-based diagnostics detect tissue-unique molecular patterns, then ability to identify tissue/body site location is improved, but detection of somatic mutations deteriorates
Solution Approach 1:
The integrated diagnostic system merges the analysis of tissue-unique molecular patterns (for location identification) with simultaneous detection of somatic mutations (for cancer characterization). By processing both types of molecular information from the same sequencing data and integrating them through a unified analytical framework, the system maintains high precision in somatic mutation detection while also recovering tissue location information that would otherwise be lost
3Measurement precision
If existing diagnostics provide specialized cancer detection, then sensitivity for specific cancer type is improved, but comprehensiveness of diagnostic data deteriorates
Solution Approach 1:
The patent creates a universal diagnostic platform that performs multiple functions simultaneously: detecting cancer presence, identifying tissue/body site location, characterizing somatic mutations, and providing data for treatment selection. This multi-functional system eliminates the need for separate specialized tests by integrating all these diagnostic capabilities into a single comprehensive analysis of microbial nucleic acids and somatic mutations from liquid biopsy samples
Data Source
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AI summary
Provided are systems and methods for the diagnosis and classification of cancer by taxonomy-independent classifications of microbial nucleic acids and somatic mutations.