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Methylation patterns in serum DNA for early identification of disseminated breast cancer

Overview of attention for article published in Genome Medicine, December 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#11 of 1,477)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
65 news outlets
twitter
21 X users
patent
2 patents
facebook
3 Facebook pages
googleplus
1 Google+ user
video
1 YouTube creator

Citations

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55 Dimensions

Readers on

mendeley
162 Mendeley
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Title
Methylation patterns in serum DNA for early identification of disseminated breast cancer
Published in
Genome Medicine, December 2017
DOI 10.1186/s13073-017-0499-9
Pubmed ID
Authors

Martin Widschwendter, Iona Evans, Allison Jones, Shohreh Ghazali, Daniel Reisel, Andy Ryan, Aleksandra Gentry-Maharaj, Michal Zikan, David Cibula, Johannes Eichner, Marianna Alunni-Fabbroni, Julian Koch, Wolfgang J. Janni, Tobias Paprotka, Timo Wittenberger, Usha Menon, Benjamin Wahl, Brigitte Rack, Harri Lempiäinen

Abstract

Monitoring treatment and early detection of fatal breast cancer (BC) remains a major unmet need. Aberrant circulating DNA methylation (DNAme) patterns are likely to provide a highly specific cancer signal. We hypothesized that cell-free DNAme markers could indicate disseminated breast cancer, even in the presence of substantial quantities of background DNA. We used reduced representation bisulfite sequencing (RRBS) of 31 tissues and established serum assays based on ultra-high coverage bisulfite sequencing in two independent prospective serum sets (n = 110). The clinical use of one specific region, EFC#93, was validated in 419 patients (in both pre- and post-adjuvant chemotherapy samples) from SUCCESS (Simultaneous Study of Gemcitabine-Docetaxel Combination adjuvant treatment, as well as Extended Bisphosphonate and Surveillance-Trial) and 925 women (pre-diagnosis) from the UKCTOCS (UK Collaborative Trial of Ovarian Cancer Screening) population cohort, with overall survival and occurrence of incident breast cancer (which will or will not lead to death), respectively, as primary endpoints. A total of 18 BC specific DNAme patterns were discovered in tissue, of which the top six were further tested in serum. The best candidate, EFC#93, was validated for clinical use. EFC#93 was an independent poor prognostic marker in pre-chemotherapy samples (hazard ratio [HR] for death = 7.689) and superior to circulating tumor cells (CTCs) (HR for death = 5.681). More than 70% of patients with both CTCs and EFC#93 serum DNAme positivity in their pre-chemotherapy samples relapsed within five years. EFC#93-positive disseminated disease in post-chemotherapy samples seems to respond to anti-hormonal treatment. The presence of EFC#93 serum DNAme identified 42.9% and 25% of women who were diagnosed with a fatal BC within 3-6 and 6-12 months of sample donation, respectively, with a specificity of 88%. The sensitivity with respect to detecting fatal BC was ~ 4-fold higher compared to non-fatal BC. Detection of EFC#93 serum DNAme patterns offers a new tool for early diagnosis and management of disseminated breast cancers. Clinical trials are required to assess whether EFC#93-positive women in the absence of radiological detectable breast cancers will benefit from anti-hormonal treatment before the breast lesions become clinically apparent.

X Demographics

X Demographics

The data shown below were collected from the profiles of 21 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 162 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 162 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 27 17%
Student > Bachelor 19 12%
Student > Master 17 10%
Student > Ph. D. Student 13 8%
Other 12 7%
Other 24 15%
Unknown 50 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 50 31%
Medicine and Dentistry 18 11%
Agricultural and Biological Sciences 13 8%
Nursing and Health Professions 6 4%
Unspecified 3 2%
Other 11 7%
Unknown 61 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 527. 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 17 December 2020.
All research outputs
#42,319
of 23,963,877 outputs
Outputs from Genome Medicine
#11
of 1,477 outputs
Outputs of similar age
#1,030
of 446,741 outputs
Outputs of similar age from Genome Medicine
#3
of 32 outputs
Altmetric has tracked 23,963,877 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 1,477 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.4. This one has done particularly well, scoring higher than 99% 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 446,741 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 32 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 93% of its contemporaries.