High-Throughput Screening of Alternative Micro-Metastasis-Specific Gene Predictors of Circulating Osteosarcoma Cells

Abstract Background Current techniques to identify circulating-tumor cells (CTCs) in osteosarcoma (OS), which are an indication of a poor prognosis in cases of intermediate levels of metastasis, are complicated and time-consuming. This study investigated the efficacy of quantitative reverse transcription PCR (qRT-PCR), a molecular technique that is available in most laboratories, for detection of CTCs in buffy coat samples of OS patients and healthy donors. Methods Previously published reports on data-reviewing and retrieval of data by calculation of differential gene expression from the Gene Expression Omnibus (GEO) database repository were reviewed identify candidate genes. Following analysis of the expression of the candidate genes identified a diagnostic model for detection of specific gene expression was derived using binary logistic regression with a multivariable fractional polynomial (MFP) algorithm. Results A model incorporating VIM, ezrin, COL1A2, and PLS3 exhibited an outstanding discriminative ability as determined by the receiver operating characteristic curve (AUC = 0.9896, 95%CI 0.9695, 1.000). At the probability cut-off value 0.2943, the sensitivity and the specificity of the model for detection of OS were 100% (95%CI 94.8, 100.0) and 96.49% (95%CI 87.9, 99.6), respectively. Conclusion The qRT-PCR can identify the existence of OS circulating cells by detection of potential candidate genes (VIM, Ezrin, COL1A2 and PLS3). Thus, these genes are worthy to be considered diagnostic biomarkers and alternative micro-metastasis predictors for OS.