Evidence map›Paper›PMID 23583283›Full record

ArticleThe American journal of pathology2013

Genome-wide methylation analysis of prostate tissues reveals global methylation patterns of prostate cancer.

Jian-Hua Luo, Ying Ding, Rui Chen, George Michalopoulos, Joel Nelson, George Tseng, Yan P Yu

Open access · bronzeAbstract read
In one paragraph

Article in The American journal of pathology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

33 citing papers in PubMed, 45 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Genes · 2020
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

7 authors at 1 institution in 1 country.

Jian-Hua LuoDepartment of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania 15261, USA.
Ying Ding
Rui Chen
George Michalopoulos
Joel Nelson
George Tseng
Yan P Yu
University of Pittsburgh · US

Funding

University of Pittsburgh Clinical and Translational Science InstituteUL1TR000005 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$50.8M
University of Pittsburgh Clinical and Translational Science InstitutionKL2TR000146 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2012 to 2015
$8.7M
The Role of Myopodin in Invasive Prostate CancersR01CA098249 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LUO, JIANHUA · 2003 to 2014
$2.6M
NCATS NIH HHS KL2 TR000146NCATS NIH HHS UL1 TR000005NCI NIH HHS R01 CA098249
6 · The paper itself

Abstract

Altered genome methylation is a hallmark of human malignancies. In this study, high-throughput analyses of concordant gene methylation and expression events were performed for 91 human prostate specimens, including prostate tumor (T), matched normal adjacent to tumor (AT), and organ donor (OD). Methylated DNA in genomic DNA was immunoprecipitated with anti-methylcytidine antibodies and detected by Affymetrix human whole genome SNP 6.0 chips. Among the methylated CpG islands, 11,481 islands were found located in the promoter and exon 1 regions of 9295 genes. Genes (7641) were methylated frequently across OD, AT, and T samples, whereas 239 genes were differentially methylated in only T and 785 genes in both AT and T but not OD. Genes with promoter methylation and concordantly suppressed expression were identified. Pathway analysis suggested that many of the methylated genes in T and AT are involved in cell growth and mitogenesis. Classification analysis of the differentially methylated genes in T or OD produced a specificity of 89.4% and a sensitivity of 85.7%. The T and AT groups, however, were only slightly separated by the prediction analysis, indicating a strong field effect. A gene methylation prediction model was shown to predict prostate cancer relapse with sensitivity of 80.0% and specificity of 85.0%. These results suggest methylation patterns useful in predicting clinical outcomes of prostate cancer.

Indexed as

DNA MethylationCpG IslandsDNA, NeoplasmGenes, NeoplasmGenome-Wide Association StudyHumansMalePrognosisPromoter Regions, GeneticProstatic NeoplasmsRecurrenceSensitivity and SpecificityDNA, Neoplasm

Identifiers

PMID23583283
PMCPMC3668028
OpenAlexW2022052582

What OpenQuestion holds

Textmetadata
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.