Methods and systems for tissue informed differentially methylated region analysis

A method using a universal panel of genomic regions and advanced sequencing techniques for ctDNA analysis addresses the challenge of low ctDNA fraction in blood, enabling accurate cancer detection and monitoring with high sensitivity and specificity.

WO2025179073A1 Publication Date: 2025-08-28ADELA INC
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Patent Information

Application Number
PCT/US2025/016672
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Priority Date
2024-10-24
Filing Date
2025-02-20
Publication Date
2025-08-28

AI Technical Summary

Technical Problem

Existing methods for analyzing circulating tumor DNA (ctDNA) as a non-invasive biomarker for cancer detection face challenges due to the low fraction of ctDNA in blood-derived samples and the need for improved methods to accurately identify differentially methylated regions (DMRs) for early cancer detection and monitoring.

Method used

A method involving the use of a universal panel of genomic regions to enrich and analyze nucleic acid molecules from samples, including sequencing at a depth of up to 50 million single reads, and comparing these regions to reference sets to generate methylation scores for cancer detection and monitoring, utilizing techniques such as Support Vector Machine and logistic regression.

Benefits of technology

This approach enables accurate detection and monitoring of cancer with high specificity, allowing for the identification of minimal residual disease and guiding therapy decisions, with sensitivity and specificity up to 90%.

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Abstract

The present disclose provides a method for classifying a sample derived from a subject. The method may comprise obtaining a sample comprising nucleic acid molecules from the subject. The method can comprise assaying the nucleic acid molecules to generate a data set comprising methylation states of one or more genomic regions. The one or more genomic regions can comprise differentially methylation regions (DMRs). The method can comprise processing at least a portion of the data set to generate an output indicative of cancer in the subject. The portion of the data set can pertain to a set of DMRs specific to the subject.
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