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Genomic Hallmarks of Genes Involved in Chromosomal Translocations in Hematological Cancer

Overview of attention for article published in PLoS Computational Biology, December 2012
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Title
Genomic Hallmarks of Genes Involved in Chromosomal Translocations in Hematological Cancer
Published in
PLoS Computational Biology, December 2012
DOI 10.1371/journal.pcbi.1002797
Pubmed ID
Authors

Mikhail Shugay, Iñigo Ortiz de Mendíbil, José L. Vizmanos, Francisco J. Novo

Abstract

Reciprocal chromosomal translocations (RCTs) leading to the formation of fusion genes are important drivers of hematological cancers. Although the general requirements for breakage and fusion are fairly well understood, quantitative support for a general mechanism of RCT formation is still lacking. The aim of this paper is to analyze available high-throughput datasets with computational and robust statistical methods, in order to identify genomic hallmarks of translocation partner genes (TPGs). Our results show that fusion genes are generally overexpressed due to increased promoter activity of 5' TPGs and to more stable 3'-UTR regions of 3' TPGs. Furthermore, expression profiling of 5' TPGs and of interaction partners of 3' TPGs indicates that these features can help to explain tissue specificity of hematological translocations. Analysis of protein domains retained in fusion proteins shows that the co-occurrence of specific domain combinations is non-random and that distinct functional classes of fusion proteins tend to be associated with different components of the gene fusion network. This indicates that the configuration of fusion proteins plays an important role in determining which 5' and 3' TPGs will combine in specific fusion genes. It is generally accepted that chromosomal proximity in the nucleus can explain the specific pairing of 5' and 3' TPGS and the recurrence of hematological translocations. Using recently available data for chromosomal contact probabilities (Hi-C) we show that TPGs are preferentially located in early replicated regions and occupy distinct clusters in the nucleus. However, our data suggest that, in general, nuclear position of TPGs in hematological cancers explains neither TPG pairing nor clinical frequency. Taken together, our results support a model in which genomic features related to regulation of expression and replication timing determine the set of candidate genes more likely to be translocated in hematological tissues, with functional constraints being responsible for specific gene combinations.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 2 2%
United Kingdom 1 1%
Portugal 1 1%
Unknown 77 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 33%
Researcher 16 20%
Student > Bachelor 8 10%
Student > Doctoral Student 7 9%
Student > Master 7 9%
Other 11 14%
Unknown 5 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 39 48%
Biochemistry, Genetics and Molecular Biology 21 26%
Medicine and Dentistry 7 9%
Computer Science 4 5%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 3 4%
Unknown 5 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 09 December 2012.
All research outputs
#15,740,207
of 25,374,647 outputs
Outputs from PLoS Computational Biology
#6,754
of 8,960 outputs
Outputs of similar age
#176,109
of 286,578 outputs
Outputs of similar age from PLoS Computational Biology
#81
of 132 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,960 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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 286,578 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 132 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.