Dataset Information

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

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.

SUBMITTER: Mahoney JA

PROVIDER: S-EPMC3810003 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

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

Mahoney Jennifer A JA Fisher Julie C JC Snyder Stacey A SA Hauck Marlene L ML

Mammalian genome : official journal of the International Mammalian Genome Society 20101113 11-12

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 P ...[more]

PMID: 21076837

Similar Datasets

Project description:The heterogeneity that soft tissue sarcomas (STS) exhibit in their clinical behavior, even within histological subtypes, complicates patient care. Histological appearance is determined by gene expression. Morphologic features are generally good predictors of biologic behavior, however, metastatic propensity, tumor growth, and response to chemotherapy may be determined by gene expression patterns that do not correlate well with morphology. One approach to identify heterogeneity is to search for genetic markers that correlate with differences in tumor behavior. Alternatively, subsets may be identified based on gene expression patterns alone, independent of knowledge of clinical outcome. We have reported gene expression patterns that distinguish two subgroups of clear cell renal carcinoma (ccRCC), and other gene expression patterns that distinguish heterogeneity of serous ovarian carcinoma (OVCA) and aggressive fibromatosis (AF). In this study, gene expression in 53 samples of STS and AF [including 16 malignant fibrous histiocytoma (MFH), 9 leiomyosarcoma, 12 liposarcoma, 4 synovial sarcoma, and 12 samples of AF] was determined at Gene Logic Inc. (Gaithersburg, MD) using Affymetrix GeneChip U_133 arrays containing approximately 40,000 genes/ESTs. Gene expression analysis was performed with the Gene Logic Genesis Enterprise System Software and Expressionist software. Hierarchical clustering of the STS using our three previously reported gene sets, each generated subgroups within the STS that for some subtypes correlated with histology, and also suggested the existence of subsets of MFH. All three gene sets also recognized the same two subsets of the fibromatosis samples that we had found in our earlier study of AF. These results suggest that these subgroups may have biological significance, and that these gene sets may be useful for sub-classification of STS. In addition, several genes that are targets of some anti-tumor drugs were found to be differentially expressed in particular subsets of STS.

Dataset Information

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

Publications

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

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets