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Comprehensive molecular biomarker identification in breast cancer brain metastases

Overview of attention for article published in Journal of Translational Medicine, December 2017
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  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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9 X users

Citations

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79 Dimensions

Readers on

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108 Mendeley
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Title
Comprehensive molecular biomarker identification in breast cancer brain metastases
Published in
Journal of Translational Medicine, December 2017
DOI 10.1186/s12967-017-1370-x
Pubmed ID
Authors

Hans-Juergen Schulten, Mohammed Bangash, Sajjad Karim, Ashraf Dallol, Deema Hussein, Adnan Merdad, Fatma K. Al-Thoubaity, Jaudah Al-Maghrabi, Awatif Jamal, Fahad Al-Ghamdi, Hani Choudhry, Saleh S. Baeesa, Adeel G. Chaudhary, Mohammed H. Al-Qahtani

Abstract

Breast cancer brain metastases (BCBM) develop in about 20-30% of breast cancer (BC) patients. BCBM are associated with dismal prognosis not at least due to lack of valuable molecular therapeutic targets. The aim of the study was to identify new molecular biomarkers and targets in BCBM by using complementary state-of-the-art techniques. We compared array expression profiles of three BCBM with 16 non-brain metastatic BC and 16 primary brain tumors (prBT) using a false discovery rate (FDR) p < 0.05 and fold change (FC) > 2. Biofunctional analysis was conducted on the differentially expressed probe sets. High-density arrays were employed to detect copy number variations (CNVs) and whole exome sequencing (WES) with paired-end reads of 150 bp was utilized to detect gene mutations in the three BCBM. The top 370 probe sets that were differentially expressed between BCBM and both BC and prBT were in the majority comparably overexpressed in BCBM and included, e.g. the coding genes BCL3, BNIP3, BNIP3P1, BRIP1, CASP14, CDC25A, DMBT1, IDH2, E2F1, MYCN, RAD51, RAD54L, and VDR. A number of small nucleolar RNAs (snoRNAs) were comparably overexpressed in BCBM and included SNORA1, SNORA2A, SNORA9, SNORA10, SNORA22, SNORA24, SNORA30, SNORA37, SNORA38, SNORA52, SNORA71A, SNORA71B, SNORA71C, SNORD13P2, SNORD15A, SNORD34, SNORD35A, SNORD41, SNORD53, and SCARNA22. The top canonical pathway was entitled, role of BRCA1 in DNA damage response. Network analysis revealed key nodes as Akt, ERK1/2, NFkB, and Ras in a predicted activation stage. Downregulated genes in a data set that was shared between BCBM and prBT comprised, e.g. BC cell line invasion markers JUN, MMP3, TFF1, and HAS2. Important cancer genes affected by CNVs included TP53, BRCA1, BRCA2, ERBB2, IDH1, and IDH2. WES detected numerous mutations, some of which affecting BC associated genes as CDH1, HEPACAM, and LOXHD1. Using complementary molecular genetic techniques, this study identified shared and unshared molecular events in three highly aberrant BCBM emphasizing the challenge to detect new molecular biomarkers and targets with translational implications. Among new findings with the capacity to gain clinical relevance is the detection of overexpressed snoRNAs known to regulate some critical cellular functions as ribosome biogenesis.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 108 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 18%
Student > Bachelor 17 16%
Student > Master 8 7%
Researcher 7 6%
Other 6 6%
Other 19 18%
Unknown 32 30%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 26%
Medicine and Dentistry 13 12%
Agricultural and Biological Sciences 10 9%
Engineering 4 4%
Veterinary Science and Veterinary Medicine 3 3%
Other 12 11%
Unknown 38 35%
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 14 September 2019.
All research outputs
#6,264,289
of 24,505,736 outputs
Outputs from Journal of Translational Medicine
#1,003
of 4,396 outputs
Outputs of similar age
#117,502
of 451,488 outputs
Outputs of similar age from Journal of Translational Medicine
#18
of 61 outputs
Altmetric has tracked 24,505,736 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 4,396 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done well, scoring higher than 77% 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 451,488 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 73% of its contemporaries.
We're also able to compare this research output to 61 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.