Affiliations 

  • 1 Department of Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, University of Utrecht, Yalelaan 104, 3584, CM, Utrecht, The Netherlands. gayathri@upm.edu.my
  • 2 Department of Clinical Sciences of Companion Animals, Faculty of Veterinary Medicine, University of Utrecht, Yalelaan 104, 3584, CM, Utrecht, The Netherlands
BMC Vet Res, 2017 Nov 25;13(1):354.
PMID: 29178874 DOI: 10.1186/s12917-017-1281-3

Abstract

BACKGROUND: Quantitative PCR (qPCR) is a common method for quantifying mRNA expression. Given the heterogeneity present in tumor tissues, it is crucial to normalize target mRNA expression data using appropriate reference genes that are stably expressed under a variety of pathological and experimental conditions. No studies have validated specific reference genes in canine osteosarcoma (OS). Previous gene expression studies involving canine OS have used one or two reference genes to normalize gene expression. This study aimed to validate a panel of reference genes commonly used for normalization of canine OS gene expression data using the geNorm algorithm. qPCR analysis of nine canine reference genes was performed on 40 snap-frozen primary OS tumors and seven cell lines.

RESULTS: Tumors with a variety of clinical and pathological characteristics were selected. Gene expression stability and the optimal number of reference genes for gene expression normalization were calculated. RPS5 and HNRNPH were highly stable among OS cell lines, while RPS5 and RPS19 were the best combination for primary tumors. Pairwise variation analysis recommended four and two reference genes for optimal normalization of the expression data of canine OS tumors and cell lines, respectively.

CONCLUSIONS: Appropriate combinations of reference genes are recommended to normalize mRNA levels in canine OS tumors and cell lines to facilitate standardized and reliable quantification of target gene expression, which is essential for investigating key genes involved in canine OS metastasis and for comparative biomarker discovery.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.