Evidence map›Paper›PMID 24980822›Full record

ArticleOncotarget2014

An epigenetic marker panel for recurrence risk prediction of low grade papillary urothelial cell carcinoma (LGPUCC) and its potential use for surveillance after transurethral resection using urine.

Leonel Maldonado, Mariana Brait, Christina Michailidi, Enrico Munari, Tina Driscoll, Luciana Schultz, Trinity Bivalacqua, Mark Schoenberg, David Sidransky, George J Netto and 1 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.0field-weighted citation impact, top 24% 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

13 citing papers in PubMed, 23 citations in OpenAlex.

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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

11 authors at 2 institutions in 1 country.

Leonel MaldonadoDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA. These authors contributed equally to this work.
Mariana BraitDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA. These authors contributed equally to this work.
Christina MichailidiDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
Enrico MunariDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA. Department of Pathology, Johns Hopkins University, Baltimore, Maryland, USA.
Tina DriscollDepartment of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
Luciana SchultzDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, USA.
Trinity BivalacquaDepartment of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
Mark SchoenbergDepartment of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
David SidranskyDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA.
George J NettoDepartment of Pathology, Johns Hopkins University, Baltimore, Maryland, USA. Department of Urology, Johns Hopkins University, Baltimore, Maryland, USA.
Mohammad Obaidul HoqueDepartment of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA. Department of Urology, Johns Hopkins University, Baltimore, Maryland, USA. Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

Discovery and Characterization of Methylation MarkersR01CA163594 · NCI · JOHNS HOPKINS UNIVERSITY · PI SIDRANSKY, DAVID · 2012 to 2016
$1.8M
NCI NIH HHS R01 CA163594
6 · The paper itself

Abstract

By a candidate gene approach, we analyzed the promoter methylation (PM) of 8 genes genes (ARF, TIMP3, RAR-β2, NID2, CCNA1, AIM1, CALCA and CCND2) by quantitative methylation specific PCR (QMSP) in DNA of 17 non-recurrent and 19 recurrent noninvasive low grade papillary urothelial cell carcinoma (LGPUCC) archival tissues. Among the genes tested, by establishing an empiric cutoff value, CCND2, CCNA1, NID2, and CALCA showed higher frequency of methylation in recurrent than in non-recurrent LGPUCC: CCND2 10/19 (53%) vs. 2/17 (12%) (p=0.014); CCNA1 11/19 (58%) vs. 4/17 (23.5%) (p=0.048); NID2 13/19 (68%) vs. 3/17 (18%) (p=0.003) and CALCA 10/19 (53%) vs. 4/17 (23.5%) (p=0.097), respectively. We further analyzed PM of CCND2, CCNA1, and CALCA in urine DNA from UCC patients including LGPUCC and controls. The frequency of CCND2, CCNA1 and CALCA was significantly higher (p<0.0001) in urine of UCC cases [ 38/148 (26%), 50/73 (68%) and 94/148 (63.5%) respectively] than controls [0/56 (0%), 10/60 (17%) and 16/56 (28.5%), respectively)]. Most importantly we found any one of the 3 markers methylation positive in 25 out of 30 (83%) cytology negative LGPUCC cases. We also explored the biological function of CCNA1 in UCC. Prospective confirmatory studies are needed to develop a reliable tool for prediction of recurrence using primary LGPUCC tissues and/or urine.

Indexed as

AdultAgedAged, 80 and overAzacitidineBiomarkers, TumorCase-Control StudiesCyclin A1Cyclin D2DecitabineDNA MethylationEpigenesis, GeneticFemaleGenetic Predisposition to DiseaseHumansHydroxamic AcidsMaleAzacitidineBiomarkers, TumorCCNA1 protein, humanCCND2 protein, humanCyclin A1Cyclin D2DecitabineHydroxamic Acidstrichostatin A

Identifiers

PMID24980822
PMCPMC4170626
OpenAlexW2098510617

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.