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Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach

Overview of attention for article published in Human Genomics, June 2015
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8 X users

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46 Mendeley
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Title
Identification of cancer predisposition variants in apparently healthy individuals using a next-generation sequencing-based family genomics approach
Published in
Human Genomics, June 2015
DOI 10.1186/s40246-015-0034-2
Pubmed ID
Authors

Ioannis Karageorgos, Clint Mizzi, Efstathia Giannopoulou, Cristiana Pavlidis, Brock A. Peters, Zoi Zagoriti, Peter D. Stenson, Konstantinos Mitropoulos, Joseph Borg, Haralabos P. Kalofonos, Radoje Drmanac, Andrew Stubbs, Peter van der Spek, David N. Cooper, Theodora Katsila, George P. Patrinos

Abstract

Cancer, like many common disorders, has a complex etiology, often with a strong genetic component and with multiple environmental factors contributing to susceptibility. A considerable number of genomic variants have been previously reported to be causative of, or associated with, an increased risk for various types of cancer. Here, we adopted a next-generation sequencing approach in 11 members of two families of Greek descent to identify all genomic variants with the potential to predispose family members to cancer. Cross-comparison with data from the Human Gene Mutation Database identified a total of 571 variants, from which 47 % were disease-associated polymorphisms, 26 % disease-associated polymorphisms with additional supporting functional evidence, 19 % functional polymorphisms with in vitro/laboratory or in vivo supporting evidence but no known disease association, 4 % putative disease-causing mutations but with some residual doubt as to their pathological significance, and 3 % disease-causing mutations. Subsequent analysis, focused on the latter variant class most likely to be involved in cancer predisposition, revealed two variants of prime interest, namely MSH2 c.2732 T>A (p.L911R) and BRCA1 c.2955delC, the first of which is novel. KMT2D c.13895delC and c.1940C>A variants are additionally reported as incidental findings. The next-generation sequencing-based family genomics approach described herein has the potential to be applied to other types of complex genetic disorder in order to identify variants of potential pathological significance.

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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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 45 98%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 11 24%
Researcher 10 22%
Student > Ph. D. Student 9 20%
Student > Master 8 17%
Student > Doctoral Student 2 4%
Other 3 7%
Unknown 3 7%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 37%
Agricultural and Biological Sciences 13 28%
Medicine and Dentistry 4 9%
Computer Science 3 7%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 2 4%
Unknown 5 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 18 September 2015.
All research outputs
#6,571,725
of 25,373,627 outputs
Outputs from Human Genomics
#153
of 564 outputs
Outputs of similar age
#70,494
of 278,563 outputs
Outputs of similar age from Human Genomics
#6
of 13 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one has gotten more attention than average, scoring higher than 72% 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 278,563 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 74% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.