Evidence map›Paper›PMID 19945765›Full record

Trial reportLung cancer (Amsterdam, Netherlands)2010

DNA hypermethylation of tumors from non-small cell lung cancer (NSCLC) patients is associated with gender and histologic type.

Stephen E Hawes, Joshua E Stern, Qinghua Feng, Linda W Wiens, Janet S Rasey, Hiep Lu, Nancy B Kiviat, Hubert Vesselle

Open access · greenAbstract readClinical Trial
In one paragraph

Trial report in Lung cancer (Amsterdam, Netherlands), 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 5 pooled it
2.6field-weighted citation impact, top 11% 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

29 citing papers in PubMed, 5 syntheses or guidelines pooled it, 65 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Sex and gender differences in cancer pathogenesis and pharmacology.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Review
  13. Noninvasive Diagnostics for Early Detection of Lung Cancer: Challenges and Potential with a Focus on Changes in DNA Methylation.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2020
    Review
  14. Article
  15. Article
  16. Review
  17. Review
  18. Methylation analyses in liquid biopsy.Translational lung cancer research · 2016
    Review
  19. Article
  20. Validation of SCT Methylation as a Hallmark Biomarker for Lung Cancers.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2016
    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

8 authors at 1 institution in 1 country.

Stephen E HawesDepartment of Epidemiology, School of Public Health, University of Washington, Box 359933, Seattle, WA 98195, USA. hawes@u.washington.edu
Joshua E Stern
Qinghua Feng
Linda W Wiens
Janet S Rasey
Hiep Lu
Nancy B Kiviat
Hubert Vesselle
University of Washington · US

Funding

Lung Cancer Prognosis: FLT PET and DNA HypermethylationR01CA115559 · NCI · UNIVERSITY OF WASHINGTON · PI VESSELLE, HUBERT J · 2005 to 2009
$2.7M
FLT PET to Plan the Best Therapy for Lung CancerR01CA107264 · NCI · UNIVERSITY OF WASHINGTON · PI VESSELLE, HUBERT J · 2004 to 2008
$2.0M
THE BIOLOGY OF LUNG CANCER-- FDG AND FLUOROTHYMIDINE PETR01CA080907 · NCI · UNIVERSITY OF WASHINGTON · PI VESSELLE, HUBERT J · 2000 to 2004
$1.8M
NCI NIH HHS CA107264NCI NIH HHS CA115559NCI NIH HHS CA80907NCI NIH HHS R01 CA080907NCI NIH HHS R01 CA107264NCI NIH HHS R01 CA115559
6 · The paper itself

Abstract

backgroundWe previously identified a number of genes which were methylated significantly more frequently in the tumor compared to the non-cancerous lung tissues from non-small cell lung cancer (NSCLC) patients. Detection of methylation profiles of genes in NSCLC could provide insight into differential pathways to malignancy and lead to strategies for better treatment of individuals with NSCLC.

methodsWe determined the DNA methylation status of 27 genes using quantitative MethyLight assays in lung tumor samples from 117 clinically well-characterized NSCLC patients.

resultsHypermethylation was detected in one of more of the genes in 106 (91%) of 117 cases and was detected at high levels (percentage methylation reference (PMR)> or =4%) in 79% of NSCLC cases. Methylation of APC, CCND2, KCNH5 and, RUNX was significantly more frequent in adenocarcinomas compared to squamous cell carcinomas (SCC), while methylation of CDKN2A was more common in SCC. Hypermethylation of KCNH5, KCNH8, and RARB was more frequent in females compared to males. Hypermethylation of APC and CCND2 was inversely associated with proliferation score assessed by Ki-67 level.

conclusionsOur findings of differential gene hypermethylation frequencies in tumor tissues from patients with adenocarcinoma or squamous cell cancers and in females compared to males suggests that further investigation is warranted in order to more fully understand the potential disparate pathways and/or risk factors for NSCLC associated with histologic type and gender.

Indexed as

DNA MethylationSex FactorsAgedBiopsyCarcinoma, Non-Small-Cell LungCell DifferentiationCell ProliferationCyclin D2DNAFemaleGenes, APCHumansLung NeoplasmsMaleMiddle AgedReceptors, Retinoic AcidCCND2 protein, humanCyclin D2DNAReceptors, Retinoic Acidretinoic acid receptor beta

Identifiers

PMID19945765
PMCPMC2888601
OpenAlexW2030947105

What OpenQuestion holds

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LicenceTDM
Read underepoch 390

Registered trials

None linked

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.