Enhance-seq Rare Mutation Detection via UMI Error Correction
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Solution Overview
Problem
Current methods for detecting rare mutations in circulating tumor DNA are hindered by low sensitivity due to the low amount of DNA present in early-stage cancer and high error rates in next-generation sequencing technologies, making it challenging to accurately identify mutations amidst a vast background of healthy cell DNA.
Innovation Solution
The 'Enhance-seq' method combines Mutation Enhancement PCR (MEP) using stuntmer-inspired primers to selectively amplify rare mutations and unique molecular identifiers (UMIs) for error correction, allowing for high-fidelity sequencing data generation and sensitive detection of rare mutations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If non-targeted sequencing (whole genome or whole exome sequencing) is used to detect mutations, then the ability to identify novel changes without prior knowledge of tumor genes is improved, but the sensitivity remains low (can only detect mutations above 5-10% allele frequency) due to low depth of data and high cost
Solution Approach 1:
The patent divides the genome into specific target regions of interest (cancer-related genes, hotspots) and sequences only those regions with high depth. This segmentation allows concentrated sequencing resources to achieve high sensitivity (detecting mutations at 0.01% allele frequency) for known targets while maintaining the ability to detect novel mutations within those targeted regions.
Solution Approach 2:
The patent changes the sequencing depth parameter from shallow (non-targeted) to deep (1000x-10000x coverage) for targeted regions. This parameter change enables detection of rare mutations at very low allele frequencies (0.01%) by increasing the number of reads covering each target locus, thereby improving measurement precision without requiring whole genome sequencing.
2Measurement precision
If deep sequencing (10,000x coverage) is used to detect low allele frequency mutations, then the sensitivity is improved, but the sequencing cost increases drastically
Solution Approach 1:
The patent extracts and enriches only the relevant target DNA regions (cancer genes, hotspots) from the whole genome before sequencing. By using target enrichment methods (hybrid capture, amplicon-based enrichment) to isolate these specific regions, the patent achieves high sensitivity mutation detection at targeted loci while sequencing only a small fraction of the total genome, thereby dramatically reducing sequencing costs compared to whole genome deep sequencing.
Solution Approach 2:
The patent segments the genome into manageable target regions and sequences them separately with high depth. This allows the sequencing effort to be concentrated on clinically relevant genes and hotspots, achieving 1000x-10000x coverage for detection of 0.01% allele frequency mutations without the prohibitive cost of sequencing the entire genome at the same depth.
3Measurement precision
If COLD-PCR is used to enrich mutant alleles, then the ratio between wild-type and mutant is improved, but the technique is not efficient when more than one gene needs to be detected in tandem
Solution Approach 1:
The patent uses universal target enrichment methods (hybrid capture or amplicon-based enrichment) that can simultaneously enrich multiple genes and hotspots in a single assay. These universal approaches work for any cancer-related gene or mutation type, providing both mutant allele enrichment and multi-gene detection capability, unlike COLD-PCR which requires gene-specific optimization.
Solution Approach 2:
The patent introduces target enrichment as an intermediary step between DNA extraction and sequencing. This enrichment step uses probes or primers that specifically bind to target regions, concentrating mutant alleles while removing excess wild-type DNA. This intermediary process achieves mutant enrichment comparable to COLD-PCR but with the added advantage of being applicable to multiple genes simultaneously through panel-based designs.
4Measurement precision
If high depth sequencing is used to detect rare mutations, then the sensitivity is improved, but the amount of DNA required and the complexity of the process increases
Solution Approach 1:
The patent performs preliminary target enrichment and unique molecular identifier (UMI) tagging before sequencing. By pre-enriching target regions and pre-tagging DNA molecules with UMIs, the patent simplifies the downstream sequencing and analysis process. The UMI tagging allows for error correction through consensus building, enabling high sensitivity rare mutation detection without requiring excessively high sequencing depth, thereby reducing overall process complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly increases the frequency of rare mutations, reduces the sequencing depth required, and lowers the cost of detection, enabling early-stage cancer diagnosis and monitoring with high sensitivity and accuracy, even with low DNA concentrations.
Implementation Method 1
The method comprises providing a sample comprising DNA; Amplifying selectively the region containing said mutation using Mutation Enhancement PCR (MEP) technology
Implementation Method 2
Amplifying selectively the region containing said mutation using Mutation Enhancement PCR (MEP) technology
Implementation Method 3
Sequencing amplicons resulting from step 4 by NGS sequencing
Implementation Method 4
Correcting sequencing errors by bioinformatic analysis using the unique molecular identifiers
Data Source
AI summary
A method of detecting rare mutations in a biological sample. More specifically, a method for detecting rare mutations involving a first step of amplifying mutations by PCR, a second step of labelling sequences containing a uniquely amplified mutation with a Unique Molecular Identifier (UMI), and a third step of correcting sequencing errors using the UMI. This method can be applied in many medical fields, such as the detection of cancer mutations at a very early stage, the detection of infectious diseases, the detection of immune diseases as well as inflammatory diseases, the screening of antibiotic resistance, prenatal diagnosis, the detection of mitochondrial DNA mutations, etc.