News & Insights

Validation of a Reflex cfDNA Methylation-based Multi-Cancer Early Detection (MCED) Blood Test for Tumors Lacking Routine Screening in Asymptomatic Adults

ESMO

This work evaluates performance of a reflex cfDNA methylation–based MCED assay through Harbinger’s Cancer Origin Epigenetics–Harbinger Health (CORE-HH) study. Results demonstrate high specificity and clinically meaningful sensitivity across multiple cancers that lack effective screening options, supporting a scalable strategy for earlier cancer detection in asymptomatic populations.

News & Insights

GEM: A deep generative framework for synthetic generation of plasma cfDNA methylation profiles

ASHG

This work introduces Generative Epigenomic Modeling (GEM), a model for generating biologically realistic synthetic cfDNA methylation data, addressing the need for scalable, high-fidelity datasets to support data augmentation, rare condition modeling, and the simulation of controlled signal-to-noise datasets, among other applications.

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Using Cell Type Deconvolution to Add Immune, Metastatic, and Health Context toMethylation-based Early Cancer Detection

ASHG

The study introduced a methylation-based cell type deconvolution method that analyzes cfDNA and WBC composition to reflect individual immune health and improve tissue-of-origin determination. This approach enhances and complements multi-cancer early detection (MCED) assays by providing deeper biological context for cancer detection and classification.

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D-Fract Enhances Detection of Tumor-Derived cfDNA Fragments and Cancer Tissue Signal in Liquid Biopsy

AACR special Conference in cancer research: AI/ML

The study introduced D-Fract, a diffusion-based model that filters cfDNA to better detect tumor-derived fragments. This approach significantly increased the estimated tumor fraction and improved tissue-of-origin classification accuracy by 9%, highlighting its potential to boost the performance of multi-cancer early detection (MCED) diagnostics.

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Novel performance quantification of MCED testing to aid clinical decisions: Analysis of a sequential reflex blood-based methylated ctDNA test

AACR Annual Meeting

This study demonstrated a cancer-specific stastical analysis framework to evaluate performance of a reflex cfDNA methylation–based MCED assay through Harbinger’s Cancer Origin Epigenetics–Harbinger Health (CORE-HH) study.

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Sharpening the Signal: Enhancing Liquid Biopsy Specificity Through Intra-Individual Methylation Analysis

AACR Annual Meeting

This study evaluated a method using a paired intra-individual analysis (IIA)—comparing plasma-derived cfDNA to matched WBC-derived genomic DNA (gDNA)—to help differentiate ctDNA signal from background somatic noise and thereby improve disease characterization.

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A methylation state specific targeted background depletion technique for enrichment of ctDNA fraction

AACR Special Conference in Cancer Research: Liquid Biopsy

The study demonstrated a CRISPR/Cas12a technology that selectively removes unmethylated “non-cancer” DNA while preserving methylated “cancer” signals, enhancing detection accuracy. This multiplexable method improves the sensitivity of rare methylation event detection in both qPCR and sequencing assays.

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A real-time PCR method for the detection of cancer-specific methylation patterns in cfDNA

AACR Special Conference in Cancer Research: Liquid Biopsy

This work evaluated a quantitative methylation-specific PCR (qPCR) method with locked nucleic acid (LNA) bases to detect pan-cancer methylation biomarkers, supporting use of this method as a cost-effective and scalable solution for early cancer detection.

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Transfer learning for accurate tissue of origin classification from cfDNA methylation

AACR Special Conference in Cancer Research: Liquid Biopsy

This study demonstrated a transfer learning model that uses tissue biopsy methylation data to improve tissue-of-origin classification in blood-based liquid biopsies, supporting a scalable and adaptable diagnostic solution for early cancer detection.

News & Insights

Liquid biopsy-based detection of triple negative breast cancer at 0.5% tumor content using DNA methylation biomarkers

AACR Special Conference in Cancer Research: Liquid Biopsy

This study discovered novel methylation biomarkers in cell-free DNA that were used to accurately detect triple-negative breast cancer through Harbinger’s assay. High sensitivity at low tumor fractions suggests the potential for improved patient outcomes through early cancer detection.