DNA Methylation Profiling for Sensitive Liquid Biopsy Cancer Detection
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Solution Overview
Problem
Current methods for detecting cancer-specific DNA methylation markers in liquid biopsies are limited by low sensitivity and are biased towards preselected recurrent mutations, failing to capture tumor heterogeneity and requiring invasive tissue biopsies, which are not feasible for all patients.
Innovation Solution
A method that clusters sub-sequences from DNA sequences into groups, aligns them based on CpG dinucleotides, and determines methylation status to generate CpG methylation profiles, using machine learning algorithms to distinguish between healthy and cancerous profiles, particularly targeting repetitive elements like LINE-1 retrotransposons for high sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current methods are used to detect cancer-specific DNA methylation markers in liquid biopsies, then the detection process is simple, but the sensitivity is low and tumor heterogeneity is not captured
Solution Approach 1:
The patent segments the detection process into multiple steps: (1) clustering subsequences from DNA sequences into groups, (2) aligning clustered subsequences based on CpG dinucleotides, (3) determining methylation status of aligned sequences, and (4) generating CpG methylation profiles. This segmentation enables comprehensive analysis of tumor heterogeneity while maintaining systematic complexity management.
Solution Approach 2:
The patent transitions from analyzing individual DNA sequences to analyzing CpG methylation profiles across multiple dimensions - clustering subsequences, aligning them by CpG positions, and generating multi-dimensional methylation profiles. This dimensional expansion captures tumor heterogeneity that single-sequence methods miss.
2Measurement precision
If tissue biopsies are performed to obtain accurate cancer diagnosis, then diagnostic accuracy is high, but the procedure is invasive and not feasible for all patients
Solution Approach 1:
The patent uses liquid biopsy as an intermediary approach - analyzing circulating cell-free DNA methylation profiles from blood samples instead of directly sampling tissue. This intermediary method provides diagnostic accuracy comparable to tissue biopsy while being non-invasive and feasible for all patients.
3Ease of operation
If methods target preselected recurrent mutations to simplify detection, then the detection process is easier, but tumor heterogeneity is not captured
Solution Approach 1:
The patent creates a universal detection method that analyzes CpG methylation profiles across all DNA sequences rather than targeting preselected mutations. This multi-functional approach simultaneously detects various cancer types and captures tumor heterogeneity while maintaining ease of operation through standardized clustering and alignment procedures.
4Measurement precision
If DNA samples from liquid biopsies are analyzed with current methods, then the sample preparation is simple, but the detection sensitivity is insufficient for early-stage tumors
Solution Approach 1:
The patent performs preliminary actions on DNA samples by clustering subsequences and aligning them by CpG dinucleotides before methylation analysis. These preliminary processing steps organize the data structure to enhance detection sensitivity for early-stage tumors while managing analysis complexity through systematic procedures.
Data Source
AI summary
The invention relates to methods for determining the methylation profile of DNA sequences of interest and methods for accurately distinguishing between a healthy methylation profile and a cancerous methylation profile, as well as to kits to implement them.