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HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures

Overview of attention for article published in Nature Medicine, March 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Citations

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229 Dimensions

Readers on

mendeley
536 Mendeley
citeulike
6 CiteULike
Title
HRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signatures
Published in
Nature Medicine, March 2017
DOI 10.1038/nm.4292
Pubmed ID
Authors

Helen Davies, Dominik Glodzik, Sandro Morganella, Lucy R Yates, Johan Staaf, Xueqing Zou, Manasa Ramakrishna, Sancha Martin, Sandrine Boyault, Anieta M Sieuwerts, Peter T Simpson, Tari A King, Keiran Raine, Jorunn E Eyfjord, Gu Kong, Åke Borg, Ewan Birney, Hendrik G Stunnenberg, Marc J van de Vijver, Anne-Lise Børresen-Dale, John W M Martens, Paul N Span, Sunil R Lakhani, Anne Vincent-Salomon, Christos Sotiriou, Andrew Tutt, Alastair M Thompson, Steven Van Laere, Andrea L Richardson, Alain Viari, Peter J Campbell, Michael R Stratton, Serena Nik-Zainal

Abstract

Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (∼1-5%) who could have selective therapeutic sensitivity to PARP inhibition.

Twitter Demographics

The data shown below were collected from the profiles of 269 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 536 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Sweden 1 <1%
Italy 1 <1%
Ghana 1 <1%
Netherlands 1 <1%
Finland 1 <1%
Canada 1 <1%
Argentina 1 <1%
Spain 1 <1%
Other 1 <1%
Unknown 524 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 171 32%
Student > Ph. D. Student 98 18%
Student > Master 48 9%
Student > Bachelor 41 8%
Other 36 7%
Other 77 14%
Unknown 65 12%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 198 37%
Agricultural and Biological Sciences 124 23%
Medicine and Dentistry 84 16%
Computer Science 14 3%
Pharmacology, Toxicology and Pharmaceutical Science 7 1%
Other 35 7%
Unknown 74 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 507. 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 27 February 2020.
All research outputs
#20,198
of 15,132,971 outputs
Outputs from Nature Medicine
#100
of 7,015 outputs
Outputs of similar age
#894
of 260,070 outputs
Outputs of similar age from Nature Medicine
#3
of 67 outputs
Altmetric has tracked 15,132,971 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,015 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 49.2. This one has done particularly well, scoring higher than 98% 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 260,070 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 99% of its contemporaries.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.