Abstract
Prognosis and therapeutic management of dogs with cutaneous mast cell tumors (MCTs) depend on clinical stage and histological grade. However, the prognostic value of this latter is still questionable. In the present study, MCT transcriptome was analyzed to identify a set of candidate genes potentially useful for predicting the biological behavior of MCTs. Fifty-one canine MCT biopsies were analyzed. Isolated and purified total RNAs were individually hybridized to the Agilent Canine V2 4x44k DNA microarray. The comparison of reference differentiated and undifferentiated MCT transcriptome revealed a total of 597 differentially expressed genes (147 down-regulated and 450 up-regulated). The functional analysis of this set of genes provided evidence that they were mainly involved in cell cycle, DNA replication, p53 signaling pathway, nucleotide excision repair and pyrimidine metabolism. Class prediction analysis identified 13 transcripts providing the greatest accuracy of class prediction and divided samples into two categories (differentiated and undifferentiated), harboring a different prognosis. The Principal Component Analysis of all samples, made by using the selected 13 markers, confirmed MCT classification. The first three components accounted for 99.924% of the total variance. This molecular classification significantly correlated with survival time (p = 0.0026). Furthermore, among all marker genes, a significant association was found between mRNA expression and MCT-related mortality for FOXM1, GSN, FEN1 and KPNA2 (p<0.05). Finally, marker genes mRNA expression was evaluated in a cohort of 22 independent samples. Data obtained enabled to identify MCT cases with different prognosis. Overall, the molecular characterization of canine MCT transcriptome allowed the identification of a set of 13 transcripts that clearly separated differentiated from undifferentiated MCTs, thus predicting outcome regardless of the histological grade. These results may have clinical relevance and warrant future validation in a prospective study.
Highlights
Nowadays, molecular profiling technologies provide the potential to comprehend relevant biological networks underlying the cellular and molecular origin of cancer as well as to tailor medical care, both at tumor and patient levels [1,2]
The aim of the present study was to characterize the mast cell tumors (MCTs) transcriptome by using DNA microarray technology, in order to define a fingerprint of aggressiveness that could predict the biological behavior, possibly overcoming the pitfalls of histological grading
The transcriptome of canine cutaneous MCT was characterized for the first time by using a DNA microarray approach
Summary
Molecular profiling technologies provide the potential to comprehend relevant biological networks underlying the cellular and molecular origin of cancer as well as to tailor medical care, both at tumor and patient levels [1,2]. Gene expression profiling has shown a great potential in cancer research, providing a detailed view on the molecular changes involved in tumor progression, leading to a better understanding of the pathophysiological process, discovering new prognostic markers and novel therapeutic targets [1]. In 2011, a new grading system was proposed by Kiupel and coauthors, aiming at improving concordance among pathologists [20]. This two-tier histologic grading system was demonstrated to be more accurate at predicting metastasis development and tumor mortality than the Patnaik system [20]. Approximately 15% of dogs with Kiupel low grade MCTs have nodal involvement at presentation (Marconato, personal data), indicating that this grading system possesses some gaps
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
