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Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage

Overview of attention for article published in BMC Genomics, March 2017
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Title
Exploring the nature of prediagnostic blood transcriptome markers of chronic lymphocytic leukemia by assessing their overlap with the transcriptome at the clinical stage
Published in
BMC Genomics, March 2017
DOI 10.1186/s12864-017-3627-4
Pubmed ID
Authors

Jelle Vlaanderen, Max Leenders, Marc Chadeau-Hyam, Lützen Portengen, Soterios A. Kyrtopoulos, Ingvar A. Bergdahl, Ann-Sofie Johansson, Dennie D.G.A.J. Hebels, Theo M.C.M. de Kok, Paolo Vineis, Roel C.H. Vermeulen

Abstract

We recently identified 700 genes whose expression levels were predictive of chronic lymphocytic leukemia (CLL) in a genome-wide gene expression analysis of prediagnostic blood from future cases and matched controls. We hypothesized that a large fraction of these markers were likely related to early disease manifestations. Here we aim to gain a better understanding of the natural history of the identified markers by comparing results from our prediagnostic analysis, the only prediagnostic analysis to date, to results obtained from a meta-analysis of a series of publically available transcriptomics profiles obtained in incident CLL cases and controls. We observed considerable overlap between the results from our prediagnostic study and the clinical CLL signals (p-value for overlap Bonferroni significant markers 0.01; p-value for overlap nominal significant markers < 2.20e-16). We observed similar patterns with time to diagnosis and similar functional annotations for the markers that were identified in both settings compared to the markers that were only identified in the prediagnostic study. These results suggest that both gene sets operate in similar pathways. An overlap exists between expression levels of genes predictive of CLL identified in prediagnostic blood and expression levels of genes associated to CLL at the clinical stage. Our analysis provides insight in a set of genes for which expression levels can be used to follow the time-course of the disease; providing an opportunity to study CLL progression in more detail in future studies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 22%
Student > Ph. D. Student 6 19%
Student > Master 6 19%
Student > Bachelor 1 3%
Professor 1 3%
Other 3 9%
Unknown 8 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 22%
Biochemistry, Genetics and Molecular Biology 5 16%
Medicine and Dentistry 3 9%
Environmental Science 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 5 16%
Unknown 9 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 23 March 2017.
All research outputs
#20,411,380
of 22,961,203 outputs
Outputs from BMC Genomics
#9,311
of 10,686 outputs
Outputs of similar age
#269,894
of 309,711 outputs
Outputs of similar age from BMC Genomics
#168
of 201 outputs
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