Urine cfDNA Fragmentation Profiling for Disease Response Detection
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Solution Overview
Problem
Current methods for detecting and monitoring diseases, particularly cancer, using urine samples are hindered by the degradation and variable size of cfDNA fragments, limiting their use for genomic analysis and treatment monitoring.
Innovation Solution
A method utilizing whole genome sequencing (WGS) of cfDNA in urine samples to analyze fragmentation profiles, including distribution of start and end sites, nucleotide frequency, and nucleosome positioning, to detect diseases and monitor treatment response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If urine samples are used for cfDNA analysis, then non-invasive collection and larger volumes are achieved, but cfDNA fragments are degraded and of variable size
Solution Approach 1:
The patent applies parameter changes by analyzing cfDNA fragmentation patterns rather than attempting to preserve original fragment sizes. The method transforms the variable size characteristic into a diagnostic parameter by examining the distribution of fragment lengths and their association with nucleosome positioning, thereby converting a reliability problem into a useful measurement parameter for disease detection
Solution Approach 2:
The patent replaces traditional mechanical/preservation-based approaches to maintaining cfDNA integrity with a computational/bioinformatic approach. Instead of using physical methods to preserve fragment size, the invention uses whole genome sequencing combined with computational analysis of fragmentation patterns and nucleosome footprinting to extract diagnostic information, substituting physical preservation with information-based analysis
2Measurement precision
If whole genome sequencing is performed on cfDNA fragments, then sensitivity and precision of disease detection are enhanced, but complexity of analysis increases
Solution Approach 1:
The patent extracts and focuses on specific diagnostic features from the whole genome sequencing data, namely the fragmentation pattern and nucleosome positioning information. Rather than analyzing all genomic data equally, the method isolates and analyzes the specific characteristics (fragment size distribution, end site positions relative to nucleosomes) that are most informative for disease detection, thereby reducing analytical complexity while maintaining high sensitivity
Solution Approach 2:
The patent segments the cfDNA analysis into distinct analytical components: fragmentation pattern analysis, nucleosome positioning determination, and disease state comparison. This segmentation allows the complex sequencing data to be processed in manageable, independent analytical steps, reducing overall complexity while preserving the comprehensive diagnostic capability
Data Source
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AI summary
Methods are provided for detecting/generating cell-free DNA (cfDNA) profiles from a sample, e.g., plasma, urine, or both. The disclosure also provides methods of detecting disease in a subject, including detecting tissue types and subtypes based on the cfDNA profiles generated. In certain specific aspects, the methods disclosed provide for the detection of diseases, such as, cancer, diabetes, hypertension, etc. and also detect the responsiveness of a subject to treatment, and/or progression of such diseases.