Liquid Biopsy Variant Detection Using cfDNA Fragment Size
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Solution Overview
Problem
Existing liquid biopsy methods for cancer diagnosis face limitations in sensitivity and specificity due to the low levels of circulating tumor DNA (ctDNA) and sequencing biases.
Innovation Solution
The method exploits the difference in fragment lengths between ctDNA and cfDNA by combining size and sequence information to enhance analytical sensitivity and specificity for detecting cancer-associated variants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional liquid biopsy methods are used to detect ctDNA, then cancer diagnosis can be performed, but sensitivity is insufficient due to limited levels of ctDNA
Solution Approach 1:
The patent changes the parameter of fragment size selection, specifically enriching for shorter cfDNA fragments (e.g., 100-170 bp) that are characteristic of ctDNA. This parameter change allows the method to selectively analyze fragments more likely to originate from tumor cells, thereby improving detection sensitivity even when overall ctDNA levels are low
Solution Approach 2:
The patent applies local quality by focusing analysis on specific subsets of cfDNA fragments with particular size characteristics rather than analyzing all cfDNA uniformly. By targeting fragments in specific size ranges that show higher tumor origin probability, the method improves local detection quality in regions of the data most likely to contain tumor signals
2Reliability
If conventional liquid biopsy methods are used to detect ctDNA, then cancer diagnosis can be performed, but sequencing bias reduces reliability
Solution Approach 1:
The patent extracts and removes the harmful element of sequencing bias by applying computational corrections and by selecting fragment size ranges that are less susceptible to bias. The method separates the analysis into size-selected subsets, taking out the biased portions and focusing on size ranges with more reliable tumor detection characteristics
Solution Approach 2:
The patent implements feedback mechanisms through iterative computational analysis that adjusts for sequencing biases. The system uses observed fragment size distributions and variant allele frequencies to refine detection thresholds and correct for technical artifacts, continuously improving reliability based on the data characteristics
3Measurement precision
If only sequence information is used for variant detection, then the method is simple, but analytical sensitivity is insufficient
Solution Approach 1:
The patent merges two types of information - fragment size data and sequence variant data - into a unified analysis framework. By combining these complementary data types, the method achieves higher analytical sensitivity than either approach alone, as size information helps enrich for tumor-derived fragments while sequence information identifies specific variants
4Measurement precision
If only sequence information is used for variant detection, then the method is simple, but specificity is limited
Solution Approach 1:
The patent combines size and sequence information to achieve synergistic improvement in specificity. The size filtering step reduces background noise from non-tumor cfDNA, while sequence analysis identifies true tumor variants, together providing more specific cancer detection than sequence analysis alone
Data Source
AI summary
Methods and systems are provided for determining a variant of interest by analyzing sizes and sequences of cfDNA fragments obtained from a test sample. The methods and systems provided herein implement processes that synergistically combine size and sequence information, thereby improving specificity and sensitivity of assays over conventional methods.