Evidence map›Paper›PMID 20535589›Full record

ArticleMedical oncology (Northwood, London, England)2011

Qualitative and quantitative promoter hypermethylation patterns of the P16, TSHR, RASSF1A and RARβ2 genes in papillary thyroid carcinoma.

Javad Mohammadi-asl, Bagher Larijani, Zhamak Khorgami, Seyed Mohammad Tavangar, Vahid Haghpanah, Majid Kheirollahi, Parvin Mehdipour

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Article in Medical oncology (Northwood, London, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 3 pooled it
0.7field-weighted citation impact, top 27% 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

31 citing papers in PubMed, 3 syntheses or guidelines pooled it, 51 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. The Role ofJournal of clinical medicine · 2022
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  8. Methylation as a critical epigenetic process during tumor progressions among Iranian population: an overview.Genes and environment : the official journal of the Japanese Environmental Mutagen Society · 2021
    Review
  9. Alterations of regulatory factors and DNA methylation pattern in thyroid cancer.Cancer biomarkers : section A of Disease markers · 2020
    Article
  10. Oncometabolites: A new insight for oncology.Molecular genetics & genomic medicine · 2019
    Article
  11. The Emerging Role of Succinate Dehyrogenase Genes (SDHx) in Tumorigenesis.International journal of hematology-oncology and stem cell research · 2019
    Article
  12. DNA methylation alterations as therapeutic prospects in thyroid cancer.Journal of endocrinological investigation · 2019
    Review
  13. Article
  14. Article
  15. Personalized treatment options for thyroid cancer: current perspectives.Pharmacogenomics and personalized medicine · 2019
    Review
  16. Review
  17. Review
  18. Adrenal Collision Tumor Composed of Pheochromocytoma and Diffuse Large B-Cell Lymphoma: A Case Report.International journal of hematology-oncology and stem cell research · 2018
    Article
  19. Liquid Biopsy in Thyroid Cancer: New Insight.International journal of hematology-oncology and stem cell research · 2018
    Review
  20. Circulating tumor DNA (ctDNA) in the era of personalized cancer therapy.Journal of diabetes and metabolic disorders · 2018
    Review
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

7 authors at 2 institutions in 1 country.

Javad Mohammadi-aslDepartment of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, and Department of Surgery, Shariati Hospital, Tehran, Iran.
Bagher Larijani
Zhamak Khorgami
Seyed Mohammad Tavangar
Vahid Haghpanah
Majid Kheirollahi
Parvin Mehdipour
Tehran University of Medical Sciences · IRShariati Hospital · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of this study was to evaluate the frequency (as qualitative analysis) and level (as quantitative analysis) of promoter hypermethylation of four genes, P16, TSHR, RASSF1A and RARβ2, and to assess their diagnostic or prognostic values in papillary thyroid tumors. Fifty formalin-fixed paraffin-embedded (FFPE) samples consisting of 25 malignant tumors and 25 non-malignant thyroid tumors were analyzed using COBRA method. Promoter hypermethylation of P16, TESH, RASSF1A and RARB2 genes was noted not only in 10, 7, 19 and 13 cases of malignant tumors, but also it was detected in 7, 11, 23 and 8 cases of benign tumors, respectively, limiting its diagnostic usefulness. The quantitative hypermethylation level was significantly higher in malignant tumors compared to benign tumors for P16 (P<0.004), TSHR (P<0.006) and RASSF1A (P<0.001), but the methylation level of RARβ2 (P<0.31) showed considerable overlap between the two groups. The mean levels of hypermethylation of P16, TSHR and RASSF1A genes were significantly higher in malignant papillary thyroid tumors compared to benign tumors and by choosing the appropriate cutoff for each gene, we could distinguish 9, 9 and 8 PTCs from 25 cases by P16, RASSF1A and TSHR methylation analysis, respectively. According to our results, these three genes, in combination, may be useful as molecular markers. The findings of present study imply that the P16, TSHR and RASSF1A gene promoter hypermethylation may play important roles in the pathogenesis of PTC and can be a potential biomarker for selecting patients with PTC.

Indexed as

Adenocarcinoma, PapillaryBiomarkers, TumorDNA MethylationFemaleGenes, p16HumansLaser Capture MicrodissectionMaleMiddle AgedPolymerase Chain ReactionPromoter Regions, GeneticReceptors, Retinoic AcidReceptors, ThyrotropinThyroid NeoplasmsTumor Suppressor ProteinsBiomarkers, TumorRARB2 protein, humanRASSF1 protein, humanReceptors, Retinoic AcidReceptors, ThyrotropinTumor Suppressor Proteins

Identifiers

PMID20535589
OpenAlexW2007723310

What OpenQuestion holds

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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.