Cell-Free DNA MSI Detection with Site-Specific Trained Thresholds
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Solution Overview
Problem
Current methods for detecting microsatellite instability (MSI) in cell-free DNA (cfDNA) samples are underdeveloped, and the impact of variable tumor shedding on MSI detection has not been adequately evaluated, limiting the ability to assess MSI status and guide treatment decisions.
Innovation Solution
A method involving quantifying repeat lengths at microsatellite loci, generating site scores, and classifying MSI status using trained thresholds, with probabilistic log likelihood-based scores to discriminate biological signals from noise, enabling accurate MSI determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If plasma-based next generation DNA sequencing is used for comprehensive genomic profiling, then the ability to detect MSI status from cell-free DNA is improved, but the methods remain underdeveloped and variable tumor shedding impacts detection accuracy
Solution Approach 1:
The method performs preliminary actions by quantifying repeat lengths at multiple microsatellite loci and generating site scores before final MSI classification. This preliminary quantification and scoring process enables more accurate and reliable MSI detection from cell-free DNA samples, addressing the underdeveloped nature of current methods
Solution Approach 2:
The method implements feedback mechanisms by comparing site scores against trained thresholds and using the results to refine MSI status determination. This feedback loop improves detection consistency by continuously evaluating detection quality and adjusting classification decisions based on accumulated evidence from multiple loci
2Reliability
If conventional PCR-based MSI assessment approaches are used, then the methods are well-established, but they lack the comprehensive genomic profiling capability and sensitivity of next generation sequencing
Solution Approach 1:
The method substitutes conventional PCR-based mechanical assessment with next generation sequencing technology. This replacement maintains the reliability of established assessment while dramatically improving measurement precision and sensitivity through comprehensive genomic profiling of multiple microsatellite loci simultaneously
Solution Approach 2:
The method changes key parameters by transitioning from PCR-based detection to NGS-based detection, enabling quantification of repeat lengths and generation of site scores with higher precision. This parameter change allows for more sensitive MSI detection while maintaining clinical reliability through validated thresholds
Data Source
AI summary
Provided herein are methods for determining the microsatellite instability status of samples. In one aspect, the methods include quantifying a number of different repeat lengths present at each of a plurality of microsatellite loci from sequence information to generate a site score for each of the plurality of the microsatellite loci. The methods also include comparing the site score of a given microsatellite locus to a site specific trained threshold for the given microsatellite locus for each of the plurality of the microsatellite loci and calling the given microsatellite locus as being unstable when the site score of the given microsatellite locus exceeds the site specific trained threshold for the given microsatellite locus to generate a microsatellite instability score, which includes a number of unstable microsatellite loci from the plurality of the microsatellite loci.