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Expression of MicroRNAs in the NCI-60 Cancer Cell-Lines

Overview of attention for article published in PLOS ONE, November 2012
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Title
Expression of MicroRNAs in the NCI-60 Cancer Cell-Lines
Published in
PLOS ONE, November 2012
DOI 10.1371/journal.pone.0049918
Pubmed ID
Authors

Santosh K. Patnaik, Jesper Dahlgaard, Wiktor Mazin, Eric Kannisto, Thomas Jensen, Steen Knudsen, Sai Yendamuri

Abstract

The NCI-60 panel of 60 human cancer cell-lines of nine different tissues of origin has been extensively characterized in biological, molecular and pharmacological studies. Analyses of data from such studies have provided valuable information for understanding cellular processes and developing strategies for the diagnosis and treatment of cancer. Here, Affymetrix® GeneChip™ miRNA version 1 oligonucleotide microarrays were used to quantify 847 microRNAs to generate an expression dataset of 495 (58.4%) microRNAs that were identified as expressed in at least one cell-line of the NCI-60 panel. Accuracy of the microRNA measurements was partly confirmed by reverse transcription and polymerase chain reaction assays. Similar to that seen among the four existing NCI-60 microRNA datasets, the concordance of the new expression dataset with the other four was modest, with mean Pearson correlation coefficients of 0.37-0.54. In spite of this, comparable results with different datasets were noted in clustering of the cell-lines by their microRNA expression, differential expression of microRNAs by the lines' tissue of origin, and correlation of specific microRNAs with the doubling-time of cells or their radiation sensitivity. Mutation status of the cell-lines for the TP53, PTEN and BRAF but not CDKN2A or KRAS cancer-related genes was found to be associated with changes in expression of specific microRNAs. The microRNA dataset generated here should be valuable to those working in the field of microRNAs as well as in integromic studies of the NCI-60 panel.

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Geographical breakdown

Country Count As %
Chile 2 3%
India 2 3%
Brazil 1 2%
Denmark 1 2%
Spain 1 2%
Unknown 56 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 35%
Researcher 16 25%
Professor 4 6%
Student > Bachelor 3 5%
Other 3 5%
Other 10 16%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 41%
Biochemistry, Genetics and Molecular Biology 12 19%
Medicine and Dentistry 9 14%
Computer Science 2 3%
Psychology 2 3%
Other 4 6%
Unknown 8 13%