Microsatellite Instability Classification via Weighted Low-Pass Sequencing
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Solution Overview
Problem
Current diagnostic techniques for classifying tumors as microsatellite stable (MSS) or microsatellite instable (MSI) are inefficient due to the repetitive nature of microsatellites and high mutation rates, leading to challenges in accurate analysis and treatment implications.
Innovation Solution
Low-pass whole genome sequencing is used to aggregate sequence information from all microsatellite loci, applying different statistical weights to each locus, allowing for accurate classification of tumors as MSI or MSS with high accuracy and low cost, even at extremely low sequencing coverage rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If low-pass whole genome sequencing is used to classify tumors, then sequencing coverage requirements are reduced and cost is decreased, but measurement precision and reliability of MSI classification may be compromised
Solution Approach 1:
The patent segments the genome analysis into two distinct approaches: low-pass whole genome sequencing for identifying structural variations and copy number changes, and targeted high-coverage sequencing for detecting point mutations and indels. This segmentation allows each method to operate at its optimal coverage level, reducing overall sequencing costs while maintaining classification accuracy through complementary data types.
Solution Approach 2:
The patent merges multiple sequencing data types (low-pass WGS, high-coverage targeted sequencing, and RNA-seq) and integrates them through a unified classification algorithm. By combining information from different sequencing approaches with different strengths, the system achieves high classification accuracy without requiring uniformly high coverage across the entire genome.
2Measurement precision
If comprehensive genome sequencing is performed to ensure accurate MSI classification, then measurement precision improves, but cost and complexity of the diagnostic process increase
Solution Approach 1:
The patent divides the sequencing workflow into distinct segments with different coverage requirements: low-pass WGS for structural analysis, high-coverage targeted sequencing for mutation detection, and RNA-seq for transcriptional analysis. This segmentation reduces overall complexity by allowing each segment to be optimized independently rather than requiring uniformly high coverage across the entire genome.
Solution Approach 2:
The patent introduces a multi-layered bioinformatics pipeline that acts as an intermediary between raw sequencing data and clinical interpretation. This pipeline includes specialized algorithms for low-pass WGS analysis, integration modules that combine multiple data types, and a classification system that synthesizes results from different sequencing approaches, thereby simplifying the overall process.
3Ease of operation
If traditional PCR or immunohistochemistry methods are used for MSI detection, then ease of operation is maintained, but measurement precision and reliability of classification are insufficient
Solution Approach 1:
The patent replaces traditional mechanical and chemical methods (PCR amplification, immunohistochemistry staining) with sequencing-based detection methods. By substituting these established but less precise methods with next-generation sequencing technologies, the system achieves superior measurement precision while maintaining operational feasibility through automated workflows.
Solution Approach 2:
The patent changes the fundamental detection parameters from indirect methods (PCR amplification efficiency, antibody binding intensity) to direct sequencing read counts and variant allele frequencies. This parameter change enables more precise and objective measurement of MSI status, transforming the diagnostic approach from qualitative/semi-quantitative to quantitative analysis.
4Measurement precision
If high-coverage sequencing is applied to all microsatellite loci, then measurement precision improves, but cost and sequencing depth requirements increase significantly
Solution Approach 1:
The patent applies different sequencing coverage qualities to different genomic regions: high coverage is concentrated on specific microsatellite loci and cancer-related genes where precision is critical, while the rest of the genome receives low-pass coverage sufficient for structural analysis. This local quality differentiation optimizes resource allocation by providing high precision only where necessary.
Solution Approach 2:
The patent implements partial high-coverage sequencing focused specifically on microsatellite regions and cancer genes, rather than uniformly high coverage across the entire genome. This partial action approach achieves the necessary measurement precision for MSI classification while significantly reducing overall sequencing depth requirements and associated costs.
Data Source
AI summary
The present disclosure relates to detecting microsatellite indels in cancer patients and those at high risk for cancer, and is useful for early detection of specific types of cancer and early onset of relapse. More particularly, the present disclosure relates to compositions, methods, and kits for classifying and treating neoplasia and tumors with microsatellite instability. The instant classifier identifies preferred therapeutic options, including combination therapies, for MSI tumor or cancer, and is particularly useful for patient stratification so that patients who would be treatable by immunotherapy drugs may be identified at a very low cost.