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Evaluation of MicroRNA Expression in Patient Bone Marrow Aspirate Slides

Overview of attention for article published in PLOS ONE, August 2012
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Title
Evaluation of MicroRNA Expression in Patient Bone Marrow Aspirate Slides
Published in
PLOS ONE, August 2012
DOI 10.1371/journal.pone.0042951
Pubmed ID
Authors

Leah Morenos, Richard Saffery, Francoise Mechinaud, David Ashley, Ngaire Elwood, Jeffrey M. Craig, Nicholas C. Wong

Abstract

Like formalin fixed paraffin embedded (FFPE) tissues, archived bone marrow aspirate slides are an abundant and untapped resource of biospecimens that could enable retrospective molecular studies of disease. Historically, RNA obtained from slides is limited in utility because of their low quality and highly fragmented nature. MicroRNAs are small (≈ 22 nt) non-coding RNA that regulate gene expression, and are speculated to preserve well in FFPE tissue. Here we investigate the use of archived bone marrow aspirate slides for miRNA expression analysis in paediatric leukaemia. After determining the optimal method of miRNA extraction, we used TaqMan qRT-PCR to identify reference miRNA for normalisation of other miRNA species. We found hsa-miR-16 and hsa-miR-26b to be the most stably expressed between lymphoblastoid cell lines, primary bone marrow aspirates and archived samples. We found the average fold change in expression of hsa-miR-26b and two miRNA reportedly dysregulated in leukaemia (hsa-miR-128a, hsa-miR-223) was <0.5 between matching archived slide and bone marrow aspirates. Differential expression of hsa-miR-128a and hsa-miR-223 was observed between leukaemic and non-leukaemic bone marrow from archived slides or flash frozen bone marrow. The demonstration that archived bone marrow aspirate slides can be utilized for miRNA expression studies offers tremendous potential for future investigations into the role miRNA play in the development and long term outcome of hematologic, as well as non-hematologic, diseases.

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Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 42%
Student > Ph. D. Student 3 12%
Student > Doctoral Student 2 8%
Student > Postgraduate 2 8%
Student > Master 2 8%
Other 4 15%
Unknown 2 8%
Readers by discipline Count As %
Medicine and Dentistry 8 31%
Biochemistry, Genetics and Molecular Biology 6 23%
Agricultural and Biological Sciences 4 15%
Neuroscience 2 8%
Social Sciences 1 4%
Other 1 4%
Unknown 4 15%