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

Area of Science:

• Veterinary oncology
• Molecular biology
• Genomics

Background:

• Prognosis for canine soft tissue sarcomas (STSs) relies on histopathologic grade.
• Predicting metastasis in high-grade STSs is challenging, impacting treatment decisions.
• Identifying predictive biomarkers for STS metastasis is crucial for personalized treatment.

Purpose of the Study:

• To assess the feasibility of using cDNA microarray and quantitative real-time PCR (qRT-PCR) to identify gene expression patterns in metastatic versus non-metastatic canine STSs.
• To determine if gene signatures can improve the prediction of metastatic disease in canine STSs.
• To explore the heterogeneity of STSs and its impact on gene expression.

Main Methods:

• Comparison of gene expression profiles in five metastatic and eight non-metastatic canine STSs.
• RNA extraction, labeling, and analysis using Affymetrix Canine Genechip 2.0 Array.
• Normalization with D-Chip software, data analysis with JMP/Genomics, and validation via qRT-PCR.

Main Results:

• Over 200 genes showed differential expression between metastatic and non-metastatic STSs (false discovery rate of 5%).
• Five specific genes were validated as upregulated in metastatic tumors using qRT-PCR.
• Confirmed increased relative expression of all five target genes in metastatic STSs.

Conclusions:

• Microarray and qRT-PCR are feasible for comparing gene signatures in canine STSs.
• Identifying key genes involved in STS metastasis can enhance prognostic accuracy for individual dogs.
• Further research into differential gene expression will improve the prediction of metastatic disease.