MSI Marker Scoring From Homopolymer and STR Histograms
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Solution Overview
Problem
Existing methods for detecting microsatellite instability (MSI) are not sensitive enough, particularly for long homopolymers and short tandem repeats (STRs), and require tumor-normal tissue pairs, limiting their accuracy and applicability.
Innovation Solution
A method and system for detecting MSI using nucleic acid sequencing data, which involves aligning flank sequences with reference flanks, calculating homopolymer signal histograms, determining scores based on histogram features, and combining scores to form a total MSI score, utilizing primers to amplify MSI marker regions, and employing flow space signal measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional capillary electrophoresis is used for MSI detection, then the method is simple to implement, but the sensitivity and accuracy are insufficient especially for long homopolymers and STRs
Solution Approach 1:
The patent replaces traditional capillary electrophoresis (mechanical separation method) with next-generation sequencing technology that uses fluorescently labeled nucleotides and optical detection. This substitution enables accurate detection of MSI markers including long homopolymers and STRs by capturing sequence information directly rather than relying on migration time differences, thereby improving sensitivity while managing system complexity through automated bioinformatics analysis.
2Measurement precision
If a larger number of MSI markers are evaluated, then the detection accuracy improves, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary actions by designing and implementing optimized bioinformatics pipelines that pre-process sequencing data, automatically align reads to reference sequences, and efficiently calculate MSI scores across multiple markers. The system pre-defines marker panels and analysis parameters, enabling rapid simultaneous evaluation of tens to hundreds of MSI markers without proportionally increasing analysis time, as the computational framework is prepared in advance.
Solution Approach 2:
The patent changes key parameters including using tumor-only samples instead of requiring tumor-normal pairs, implementing optimized scoring algorithms that process multiple markers in parallel, and adjusting sequencing depth requirements. These parameter changes enable efficient evaluation of numerous markers by reducing per-marker analysis time while maintaining or improving overall detection accuracy through aggregated marker information.
3Adaptability or versatility
If tumor-normal tissue pairs are required for MSI detection, then the traditional method provides a baseline for comparison, but the applicability is limited when normal tissue is unavailable
Solution Approach 1:
The patent inverts the traditional approach by using tumor-only samples instead of requiring tumor-normal pairs. The methodology establishes accuracy through optimized bioinformatics analysis that identifies MSI characteristics directly from tumor sequencing data, using reference databases and statistical models rather than direct comparison to patient-matched normal tissue. This inversion significantly improves adaptability to clinical scenarios where normal tissue is unavailable while maintaining detection accuracy.
Data Source
AI summary
Methods for evaluating microsatellite instability (MSI) analyze nucleic acid sequence reads corresponding to a plurality of marker regions for MSI. The marker regions may include long homopolymers and/or short tandem repeats (STRs). For a target homopolymer, a histogram of homopolymer signal values is calculated based on flow space signal measurements for the homopolymer region in the sequence reads. A score per marker based on features of the histogram of homopolymer signal values is determined for each marker region corresponding to the target homopolymers. For a target STR, the method includes calculating a histogram of repeat lengths for sequence reads corresponding to the marker region of the target STR. A score per STR marker is calculated based on features of the histogram of repeat lengths. A plurality of per marker scores may be combined to form a total MSI score for the sample.