Evidence map›Paper›PMID 42666404›Full record

ArticleComputational and structural biotechnology journal2026

Global Hypomethylation in Cell-Free DNA Enables Noninvasive Colorectal Cancer Screening: Results from a Retrospective Validation Study.

Shahdeep Kaur, Shefali Lathwal, Smita Agrawal, Tina Mahmoudi, Shalini Gupta

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shahdeep KaurAsima Health Inc., Kitchener, ON N2G 4Z5, Canada.ORCID https://orcid.org/0000-0002-8052-4693
Shefali Lathwal101GenAI Inc., San Jose, CA 94123, USA.ORCID https://orcid.org/0009-0002-3615-8427
Smita Agrawal101GenAI Inc., San Jose, CA 94123, USA.ORCID https://orcid.org/0009-0007-6489-1518
Tina MahmoudiAsima Health Inc., Kitchener, ON N2G 4Z5, Canada.
Shalini GuptaAsima Health Inc., Kitchener, ON N2G 4Z5, Canada.ORCID https://orcid.org/0000-0003-1382-0254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Global DNA hypomethylation is a defining hallmark of colorectal cancer (CRC) but is poorly captured by existing cell-free DNA (cfDNA) technologies, which typically interrogate only a fraction of CpG sites and are biased toward CpG islands. Asima Rev is a rapid, label-free, whole-genome electrical impedance cfDNA assay previously characterized across 216 clinical samples spanning 15 cancer types, from which a diagnostic threshold was established. The assay differentiates healthy individuals from those with cancer by measuring cfDNA aggregation patterns associated with methylation state, enabling functional detection of genome-wide hypomethylation. In this study, this prespecified threshold (adjusted to the present electrode geometry via cell constant normalization) is applied without modification to an independently collected cohort of 46 treatment-naïve patients with CRC and 33 controls, constituting a disease-specific retrospective validation of the assay. Only 4 samples overlapped between the 2 cohorts; all remaining samples were independently collected, processed, and analyzed. Asima Rev achieved 95.65% sensitivity (95% confidence interval, 85.47% to 99.23%) and 93.94% specificity (95% confidence interval, 80.39% to 98.92%), with longitudinal monitoring in 6 patients fully concordant with clinical outcomes. Interrogation of 11 public methylation array datasets showed that whole-array analyses underestimate global changes. Restricting analyses to OpenSea regions, where cfDNA is enriched, however, revealed patterns consistent with Asima Rev and a significant 5.8% global hypomethylation in CRC tissue compared to adjacent normal tissue. Hypomethylation was not observed in immune cell genomic DNA, a major contributor to cfDNA, supporting a predominantly tumor-derived contribution to the observed cfDNA signal. Together, these results demonstrate that Asima Rev captures a cfDNA signal consistent with true global methylation loss and outperforms locus-specific assays by measuring structural consequences of pan-genomic epigenetic alterations.

Identifiers

PMID42666404
PMCPMC13522562

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.