Feasibility of using gene expression analysis to study canine soft tissue sarcomas

Feasibility of using gene expression analysis to study canine soft tissue sarcomas The prognosis given for canine soft tissue sarcomas (STSs) is based primarily on histopathologic grade. The decision to administer adjuvant chemotherapy is difficult since less than half of patients with high-grade STSs develop metastatic disease. We hypothesize that there is a gene signature that will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus nonmetastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed, and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of the differences between gene expression in metastatic STSs and in nonmetastatic STSs is likely to identify genes that are important in the development of metastatic disease and improve our ability to prognosticate for individual patients. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Mammalian Genome Springer Journals

Feasibility of using gene expression analysis to study canine soft tissue sarcomas

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Publisher
Springer-Verlag
Copyright
Copyright © 2010 by Springer Science+Business Media, LLC
Subject
Life Sciences; Zoology ; Anatomy; Cell Biology
ISSN
0938-8990
eISSN
1432-1777
D.O.I.
10.1007/s00335-010-9298-y
Publisher site
See Article on Publisher Site

Abstract

The prognosis given for canine soft tissue sarcomas (STSs) is based primarily on histopathologic grade. The decision to administer adjuvant chemotherapy is difficult since less than half of patients with high-grade STSs develop metastatic disease. We hypothesize that there is a gene signature that will improve our ability to predict development of metastatic disease in STS patients. The objective of this study was to determine the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) analysis to determine gene expression patterns in metastatic versus nonmetastatic canine STSs, given the inherent heterogeneity of this group of tumors. Five STSs from dogs with metastatic disease were evaluated in comparison to eight STSs from dogs without metastasis. Tumor RNA was extracted, processed, and labeled for application to the Affymetrix Canine Genechip 2.0 Array. Array fluorescence was normalized using D-Chip software and data analysis was performed with JMP/Genomics. Differential gene expression was validated using qRT-PCR. Over 200 genes were differentially expressed at a false discovery rate of 5%. Differential gene expression was validated for five genes upregulated in metastatic tumors. Quantitative RT-PCR confirmed increased relative expression of all five genes of interest in the metastatic STSs. Our results demonstrate that microarray and qRT-PCR are feasible methods for comparing gene signatures in canine STSs. Further evaluation of the differences between gene expression in metastatic STSs and in nonmetastatic STSs is likely to identify genes that are important in the development of metastatic disease and improve our ability to prognosticate for individual patients.

Journal

Mammalian GenomeSpringer Journals

Published: Nov 13, 2010

References

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