Evidence map›Paper›PMID 36387135›Full record

ArticleFrontiers in oncology2022

DNA methylation topology differentiates between normal and malignant in cell models, resected human tissues, and exfoliated sputum cells of lung epithelium.

Jian Tajbakhsh, Fariborz Mortazavi, Nirdesh K Gupta

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

5 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Exon 4 and intron 4Biomedical reports · 2025
    Article
  4. Epigenetic Modulation of Estrogen Receptor Signaling in Ovarian Cancer.International journal of molecular sciences · 2024
    Review
  5. Article
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

3 authors at 2 institutions in 1 country.

Jian TajbakhshDepartment of Surgery, Cedars-Sinai, Los Angeles, CA, United States.
Fariborz MortazaviDivision of Hematology/Oncology, West Los Angeles Veterans Affairs (VA) Medical Center, Los Angeles, CA, United States.
Nirdesh K Gupta3rd Street Diagnostics, Cedars-Sinai, Los Angeles, CA, United States.
Cedars-Sinai Medical Center · USUniversity of California, Los Angeles · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Global DNA hypomethylation is a prominent feature of cancer cells including lung cancer, that has not been widely explored towards cancer diagnosis. In this study we assess the comparative distribution of global DNA methylation in normal cells versus cancer cells in various specimen models. Methods: We used Results: By introducing 5mC/DAPI colocalization index as a metric we could distinguish between normal epithelial cells and aberrantly hypomethylated cancer cells. Cultured lung cancer cells (H157 and A549) had significantly lower indices compared to normal cells (BEAS-2B). Furthermore, we were able to identify such extensively hypomethylated low-index cells in tumor tissues and the matching sputum from cancer patients. In contrast, the indices of cells derived from sputum of healthy individuals had more similarity to epithelial cells of normal parenchyma and the phenotypically normal BEAS-2B cells. Conclusions: The results suggest that 5mC topology using high-resolution image cytometry shows potential for identifying hypomethylated cancerous cells in human tissues and amongst normal cells in matching sputum, which may render a valuable surrogate for biopsied tissues. This promising feature deserves further validation in more comprehensive studies.

Indexed as

3D image cytometry5-methylcytosineconfocal microscopyglobal DNA methylationlung cancernuclear topologysingle-cell analysissputum

Identifiers

PMID36387135
PMCPMC9647067
OpenAlexW4307633691

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.