Evidence map›Paper›PMID 32923859›Full record

ArticleJCO precision oncology2019

DNA Methylation Profiling Reveals Prognostically Significant Groups in Pediatric Adrenocortical Tumors: A Report From the International Pediatric Adrenocortical Tumor Registry.

Michael R Clay, Emilia M Pinto, Cynthia Cline, Quynh T Tran, Tong Lin, Michael A Dyer, Lei Shi, Huiyun Wu, Stanley B Pounds, Gerard P Zambetti and 2 more

Abstract read
In one paragraph

Article in JCO precision oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
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

12 citing papers in PubMed.

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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

12 authors.

Michael R ClaySt Jude Children's Research Hospital, Memphis, TN.
Emilia M PintoSt Jude Children's Research Hospital, Memphis, TN.
Cynthia ClineSt Jude Children's Research Hospital, Memphis, TN.
Quynh T TranSt Jude Children's Research Hospital, Memphis, TN.
Tong LinSt Jude Children's Research Hospital, Memphis, TN.
Michael A DyerSt Jude Children's Research Hospital, Memphis, TN.
Lei ShiSt Jude Children's Research Hospital, Memphis, TN.
Huiyun WuSt Jude Children's Research Hospital, Memphis, TN.
Stanley B PoundsSt Jude Children's Research Hospital, Memphis, TN.
Gerard P ZambettiSt Jude Children's Research Hospital, Memphis, TN.
Brent A OrrSt Jude Children's Research Hospital, Memphis, TN.
Raul C RibeiroSt Jude Children's Research Hospital, Memphis, TN.

Funding

Viral Vector Technology (VVTSR)P30CA021765 · NCI · ST. JUDE CHILDREN'S RESEARCH HOSPITAL · PI CHARLES ROBERTS · 1985 to 2026
$166.9M
NCI NIH HHS P30 CA021765
6 · The paper itself

Abstract

purposePediatric adrenocortical carcinomas (ACCs) are aggressive; the overall survival of patients with ACCs is 40%-50%. Appropriate staging and histologic classification are crucial because children with incomplete resections, metastases, or relapsed disease have a dismal prognosis. The clinical course of pediatric adrenocortical tumors (ACTs) is difficult to predict using the current classification schemas, which rely on subjective microscopic and gross macroscopic variables. Recent advances in adult ACT studies have revealed distinct DNA methylation patterns with prognostic significance that have not been systematically interrogated in the pediatric population. PATIENTS AND

methodsWe performed DNA methylation analyses on 48 newly diagnosed ACTs from the International Pediatric Adrenocortical Tumor Registry and 12 pediatric adrenal controls to evaluate for distinct methylation groups. Pediatric methylation data were also compared systematically with the adult ACC cohort from The Cancer Genome Atlas (TCGA).

resultsTwo pediatric ACT methylation groups were identified and showed differences in selected clinicopathologic and outcome characteristics. The A1 group was enriched for

conclusionOur results indicate DNA methylation analysis can enhance current diagnostic algorithms. A combination of methylation and histologic classification produced the strongest prediction model and may prove useful in future risk-adapted therapeutic trials.

Identifiers

PMID32923859
PMCPMC7446418

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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.