Comparison of cPCR, PCR-HRM, qPCR, and microarray for detecting GSTM1 and GSTT1 deletions and copy number variations:...

Copy number variations (CNVs) are clinically relevant as they may influence gene expression, enzymatic activity, and interindividual variability in drug response. Among these, deletions affecting the glutathione S-transferase (GST) genes GSTM1 and GSTT1 are of particular interest due to their potential implications for pharmacogenetic research. However, comparative evidence to guide the selection of the most appropriate method for CNV detection in different laboratory settings remains limited. Therefore, this study compared four molecular techniques, microarray, conventional PCR (cPCR), high-resolution melting PCR (PCR-HRM), and quantitative PCR (qPCR) for detecting CNVs in GSTM1 and GSTT1. Germline DNA samples from participants diagnosed with ovarian cancer were analyzed by all genotyping methods. A total of 80 participants were included for the cross-method agreement analysis. Agreement was assessed using Cohen's kappa coefficient, with 95% confidence intervals estimated using the Wilson score method. qPCR and microarray showed perfect concordance for both GSTM1 and GSTT1 qualitative and copy-number (CN) assessment. PCR-HRM showed perfect qualitative performance for GSTT1, whereas cPCR exhibited slightly lower agreement for both genes, despite maintaining high overall concordance. For those two genes, cPCR had the lowest entry cost, PCR-HRM combined qualitative robustness with workflow simplicity, qPCR was the most suitable targeted approach for CN estimation, and microarray was most advantageous when broader pharmacogenomic profiling was also intended. These findings indicate that method selection should be guided not only by analytical performance but also by the intended analytical objective and the available technical and financial resources.