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Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers

Overview of attention for article published in Genome Biology, October 2012
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (91st percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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8 X users
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138 Mendeley
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2 CiteULike
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Title
Genome-wide promoter methylation analysis in neuroblastoma identifies prognostic methylation biomarkers
Published in
Genome Biology, October 2012
DOI 10.1186/gb-2012-13-10-r95
Pubmed ID
Authors

Anneleen Decock, Maté Ongenaert, Jasmien Hoebeeck, Katleen De Preter, Gert Van Peer, Wim Van Criekinge, Ruth Ladenstein, Johannes H Schulte, Rosa Noguera, Raymond L Stallings, An Van Damme, Geneviève Laureys, Joëlle Vermeulen, Tom Van Maerken, Frank Speleman, Jo Vandesompele

Abstract

ABSTRACT: BACKGROUND: Accurate outcome prediction in neuroblastoma, which is necessary to enable the optimal choice of risk-related therapy, remains a challenge. To improve neuroblastoma patient stratification, this study aimed to identify prognostic tumor DNA methylation biomarkers. RESULTS: To identify genes silenced by promoter methylation, we first applied two independent genome-wide methylation screening methodologies to eight neuroblastoma cell lines. Specifically, we used re-expression profiling upon 5-aza-2'-deoxycytidine (DAC) treatment and massively parallel sequencing after capturing with a methyl-CpG-binding domain (MBD-seq). Putative methylation markers were selected from DAC-upregulated genes through a literature search and an upfront methylation-specific PCR on 20 primary neuroblastoma tumors, as well as through MBD- seq in combination with publicly available neuroblastoma tumor gene expression data. This yielded 43 candidate biomarkers that were subsequently tested by high-throughput methylation-specific PCR on an independent cohort of 89 primary neuroblastoma tumors that had been selected for risk classification and survival. Based on this analysis, methylation of KRT19, FAS, PRPH, CNR1, QPCT, HIST1H3C, ACSS3 and GRB10 was found to be associated with at least one of the classical risk factors, namely age, stage or MYCN status. Importantly, HIST1H3C and GNAS methylation was associated with overall and/or event-free survival. CONCLUSIONS: This study combines two genome-wide methylation discovery methodologies and is the most extensive validation study in neuroblastoma performed thus far. We identified several novel prognostic DNA methylation markers and provide a basis for the development of a DNA methylation-based prognostic classifier in neuroblastoma.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 2 1%
Belgium 2 1%
United States 2 1%
France 1 <1%
Austria 1 <1%
Czechia 1 <1%
United Kingdom 1 <1%
Egypt 1 <1%
Germany 1 <1%
Other 4 3%
Unknown 122 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 39 28%
Researcher 33 24%
Student > Master 16 12%
Professor > Associate Professor 7 5%
Student > Postgraduate 6 4%
Other 24 17%
Unknown 13 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 56 41%
Medicine and Dentistry 25 18%
Biochemistry, Genetics and Molecular Biology 22 16%
Computer Science 7 5%
Neuroscience 4 3%
Other 7 5%
Unknown 17 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 April 2015.
All research outputs
#2,372,943
of 25,374,917 outputs
Outputs from Genome Biology
#1,933
of 4,467 outputs
Outputs of similar age
#16,262
of 191,479 outputs
Outputs of similar age from Genome Biology
#29
of 55 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 56% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 191,479 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 55 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.