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Identification of molecular genetic contributants to canine cutaneous mast cell tumour metastasis by global gene expression analysis.

Authors :
Kelly Bowlt Blacklock
Zeynep Birand
Deborah Biasoli
Elena Fineberg
Sue Murphy
Debs Flack
Joyce Bass
Stefano Di Palma
Laura Blackwood
Jenny McKay
Trevor Whitbread
Richard Fox
Tom Eve
Stuart Beaver
Mike Starkey
Source :
PLoS ONE, Vol 13, Iss 12, p e0208026 (2018)
Publication Year :
2018
Publisher :
Public Library of Science (PLoS), 2018.

Abstract

Cutaneous mast cell tumours are one of the most common canine cancers. Approximately 25% of the tumours metastasise. Activating c-kit mutations are present in about 20% of tumours, but metastases occur in the absence of mutations. Tumour metastasis is associated with significantly diminished survival in spite of adjuvant chemotherapy. Available prognostic tests do not reliably predict whether a tumour will metastasise. In this study we compared the global expression profiles of 20 primary cutaneous mast cell tumours that metastasised with those of 20 primary tumours that did not metastasise. The objective was to identify genes associated with mast cell tumour metastatic progression that may represent targets for therapeutic intervention and biomarkers for prediction of tumour metastasis. Canine Gene 1.1 ST Arrays were employed for genome-wide expression analysis of formalin-fixed, paraffin-embedded biopsies of mast cell tumours borne by dogs that either died due to confirmed mast cell tumour metastasis, or were still alive more than 1000 days post-surgery. Decreased gene expression in the metastasising tumours appears to be associated with a loss of cell polarity, reduced cell-cell and cell-ECM adhesion, and increased cell deformability and motility. Dysregulated gene expression may also promote extracellular matrix and base membrane degradation, suppression of cell cycle arrest and apoptosis, and angiogenesis. Down-regulation of gene expression in the metastasising tumours may be achieved at least in part by small nucleolar RNA-derived RNA and microRNA-effected gene silencing. Employing cross-validation, a linear discriminant analysis-based classifier featuring 19 genes that displayed two-fold differences in expression between metastasising and non-metastasising tumours was estimated to classify metastasising and non-metastasising tumours with accuracies of 90-100% and 70-100%, respectively. The differential expression of 9 of the discriminator genes was confirmed by quantitative reverse transcription-PCR.

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
13
Issue :
12
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.175c247d569b4ddd9c9b64553c0c2949
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0208026