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Whole-genome bisulfite sequencing analysis of circulating tumour DNA for the detection and molecular classification of cancer. | LitMetric

AI Article Synopsis

  • The study focuses on using circulating tumor DNA (ctDNA) methylation as a non-invasive biomarker for early cancer detection, specifically in breast cancer patients, tackling challenges like low ctDNA availability and complex DNA variations.
  • Researchers analyzed three cohorts from hospitals in China, developing a specialized ctDNA sequencing technology that requires minimal plasma input and offers comprehensive genome-wide coverage.
  • Results showed that a diagnostic signature of 15 ctDNA methylation markers can accurately identify both early and advanced breast cancer stages, as well as discern estrogen receptor status and differentiate between various cancer types.

Article Abstract

Background: Cancer cell-specific variation and circulating tumour DNA (ctDNA) methylation are promising biomarkers for non-invasive cancer detection and molecular classification. Nevertheless, the applications of ctDNA to the early detection and screening of cancer remain highly challenging due to the scarcity of cancer cell-specific ctDNA, the low signal-to-noise ratio of DNA variation, and the lack of non-locus-specific DNA methylation technologies.

Methods: We enrolled three cohorts of breast cancer (BC) patients from two hospitals in China (BC: n = 123; healthy controls: n = 40). We developed a ctDNA whole-genome bisulfite sequencing technology employing robust trace ctDNA capture from up to 200 μL plasma, mini-input (1 ng) library preparation, unbiased genome-wide coverage and comprehensive computational methods.

Results: A diagnostic signature comprising 15 ctDNA methylation markers exhibited high accuracy in the early (area under the curve [AUC] of 0.967) and advanced (AUC of 0.971) BC stages in multicentre patient cohorts. Furthermore, we revealed a ctDNA methylation signature that discriminates estrogen receptor status (Training set: AUC of 0.984 and Test set: AUC of 0.780). Different cancer types, including hepatocellular carcinoma and lung cancer, could also be well distinguished.

Conclusions: Our study provides a toolset to generate unbiased whole-genome ctDNA methylomes with a minimal amount of plasma to develop highly specific and sensitive biomarkers for the early diagnosis and molecular subtyping of cancer.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9398227PMC
http://dx.doi.org/10.1002/ctm2.1014DOI Listing

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