Targeted Panel Mutational Signature Detection for Low-DNA Tumor Samples
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Solution Overview
Problem
Existing methods for detecting mutational signatures in tumor samples are limited by the need for large amounts of DNA and are not effective for formalin-fixed paraffin-embedded (FFPE) samples, necessitating improved methods for analyzing mutational signatures using targeted sequencing data.
Innovation Solution
A method involving amplification-based targeted sequencing data analysis, including amplifying nucleic acid sequences at targeted locations, detecting variants, generating trinucleotides, determining frequency, calculating cosine similarity, and selecting mutational signatures based on a threshold, to predict mutational signatures in tumor samples.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Whole Genome Sequencing or Whole Exome Sequencing is used to detect mutational signatures, then comprehensive mutational signature detection is achieved, but large amounts of DNA are required and success rates are low for FFPE samples
Solution Approach 1:
The patent extracts and focuses analysis on specific target regions (cancer-related genes and genomic regions) rather than analyzing the entire genome or exome. By designing targeted panels that capture only the most relevant genomic regions for mutational signature detection, the method reduces DNA quantity requirements while maintaining detection accuracy for FFPE samples.
Solution Approach 2:
The patent segments the genome into specific target regions of interest (cancer driver genes, oncogenes, tumor suppressor genes) and analyzes mutational signatures within these segmented regions. This segmentation allows for focused sequencing that requires less DNA while still providing comprehensive mutational signature information relevant to cancer etiology.
2Measurement precision
If Whole Genome Sequencing or Whole Exome Sequencing is used to detect mutational signatures, then comprehensive mutational signature detection is achieved, but success rates are low for FFPE samples
Solution Approach 1:
The patent extracts and focuses analysis on specific target regions (cancer-related genes and genomic regions) rather than analyzing the entire genome or exome. By designing targeted panels that capture only the most relevant genomic regions for mutational signature detection, the method reduces DNA quantity requirements while maintaining detection accuracy for FFPE samples.
Solution Approach 2:
The patent changes the sequencing parameters from whole genome/exome coverage to targeted panel sequencing with higher depth. This parameter change optimizes the balance between DNA input requirements and detection reliability, making the method particularly suitable for FFPE samples which have limited DNA quality and quantity.
3Quantity of substance
If targeted panels are used for sequencing, then DNA requirements are reduced and success rates for FFPE samples improve, but comprehensive genome coverage is lost
Solution Approach 1:
The patent applies local quality by concentrating sequencing depth and analytical resources on specific genomic regions of highest relevance to cancer mutational signatures. Rather than uniform genome-wide coverage, the method enhances coverage quality in target regions (cancer driver genes, oncogenes, tumor suppressor genes) where mutational signatures provide the most diagnostic and etiological information.
Solution Approach 2:
The patent changes the sequencing parameters from whole genome/exome coverage to targeted panel sequencing with higher depth. This parameter change optimizes the balance between DNA input requirements and detection reliability, making the method particularly suitable for FFPE samples which have limited DNA quality and quantity.
4Measurement precision
If Whole Genome Sequencing or Whole Exome Sequencing is used, then complete mutational landscape is captured, but computational complexity and data processing requirements increase
Solution Approach 1:
The patent extracts and focuses analysis on specific target regions (cancer-related genes and genomic regions) rather than analyzing the entire genome or exome. By designing targeted panels that capture only the most relevant genomic regions for mutational signature detection, the method reduces DNA quantity requirements while maintaining detection accuracy for FFPE samples.
Solution Approach 2:
The patent segments the genome into specific target regions of interest (cancer driver genes, oncogenes, tumor suppressor genes) and analyzes mutational signatures within these segmented regions. This segmentation allows for focused sequencing that requires less DNA while still providing comprehensive mutational signature information relevant to cancer etiology.
Data Source
AI summary
A targeted panel with low sample input requirements from a tumor sample may be processed to identify the presence of a mutational signature. The method may include the steps of: amplifying nucleic acid sequences at targeted locations in the tumor sample genome by a targeted panel to generate nucleic acid sequence reads, detecting variants in the nucleic acid sequence reads, generating a set of trinucleotides by appending flanking 5′ and 3′ bases to each variant, determining a frequency of each trinucleotide to form a mutation matrix, determining a cosine similarity value of the mutation matrix and each mutational signature in a matrix of mutational signatures to form a matrix of similarity values, and selecting mutational signatures from the matrix of mutational signatures when a corresponding cosine similarity value is greater than or equal to a threshold to indicate presence of the selected mutational signatures in the tumor sample genome.