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Multi-omics of 34 colorectal cancer cell lines - a resource for biomedical studies

Overview of attention for article published in Molecular Cancer, July 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)

Mentioned by

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8 tweeters

Citations

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172 Dimensions

Readers on

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425 Mendeley
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Title
Multi-omics of 34 colorectal cancer cell lines - a resource for biomedical studies
Published in
Molecular Cancer, July 2017
DOI 10.1186/s12943-017-0691-y
Pubmed ID
Authors

Kaja C. G. Berg, Peter W. Eide, Ina A. Eilertsen, Bjarne Johannessen, Jarle Bruun, Stine A. Danielsen, Merete Bjørnslett, Leonardo A. Meza-Zepeda, Mette Eknæs, Guro E. Lind, Ola Myklebost, Rolf I. Skotheim, Anita Sveen, Ragnhild A. Lothe

Abstract

Colorectal cancer (CRC) cell lines are widely used pre-clinical model systems. Comprehensive insights into their molecular characteristics may improve model selection for biomedical studies. We have performed DNA, RNA and protein profiling of 34 cell lines, including (i) targeted deep sequencing (n = 612 genes) to detect single nucleotide variants and insertions/deletions; (ii) high resolution DNA copy number profiling; (iii) gene expression profiling at exon resolution; (iv) small RNA expression profiling by deep sequencing; and (v) protein expression analysis (n = 297 proteins) by reverse phase protein microarrays. The cell lines were stratified according to the key molecular subtypes of CRC and data were integrated at two or more levels by computational analyses. We confirm that the frequencies and patterns of DNA aberrations are associated with genomic instability phenotypes and that the cell lines recapitulate the genomic profiles of primary carcinomas. Intrinsic expression subgroups are distinct from genomic subtypes, but consistent at the gene-, microRNA- and protein-level and dominated by two distinct clusters; colon-like cell lines characterized by expression of gastro-intestinal differentiation markers and undifferentiated cell lines showing upregulation of epithelial-mesenchymal transition and TGFβ signatures. This sample split was concordant with the gene expression-based consensus molecular subtypes of primary tumors. Approximately ¼ of the genes had consistent regulation at the DNA copy number and gene expression level, while expression of gene-protein pairs in general was strongly correlated. Consistent high-level DNA copy number amplification and outlier gene- and protein- expression was found for several oncogenes in individual cell lines, including MYC and ERBB2. This study expands the view of CRC cell lines as accurate molecular models of primary carcinomas, and we present integrated multi-level molecular data of 34 widely used cell lines in easily accessible formats, providing a resource for preclinical studies in CRC.

Twitter Demographics

The data shown below were collected from the profiles of 8 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 425 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 425 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 24%
Researcher 66 16%
Student > Master 44 10%
Student > Bachelor 38 9%
Student > Doctoral Student 29 7%
Other 50 12%
Unknown 94 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 173 41%
Agricultural and Biological Sciences 54 13%
Medicine and Dentistry 38 9%
Pharmacology, Toxicology and Pharmaceutical Science 18 4%
Immunology and Microbiology 7 2%
Other 28 7%
Unknown 107 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 16 April 2018.
All research outputs
#3,013,617
of 12,808,036 outputs
Outputs from Molecular Cancer
#145
of 1,078 outputs
Outputs of similar age
#73,268
of 261,492 outputs
Outputs of similar age from Molecular Cancer
#1
of 1 outputs
Altmetric has tracked 12,808,036 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,078 research outputs from this source. They receive a mean Attention Score of 3.5. This one has done well, scoring higher than 86% 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 261,492 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 71% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them