ABSTRACT
INTRODUCTION: Standardization of BCR-ABL1 messenger RNA quantification by real-time PCR on the International Scale (IS) is critical for monitoring therapy response in chronic myelogenous leukaemia. Since 2006, BCR-ABL1 IS standardization is propagated along reference laboratories by calculating a laboratory-specific conversion factor (CF), co-ordinated in Europe through the European Treatment and Outcome Study project. Although this process has proven successful to some extent, it has not been achievable for all laboratories due to the complexity of the process and the stringent requirements in terms of numbers of samples to be exchanged. In addition, several BCR-ABL1 IS quantification methods and secondary reference materials became commercially available. However, it was observed that different IS methods generate consistently different results. METHODS: To overcome these difficulties, we have developed an alternative and simple approach of CF calculation, based on the retrospective analysis of existing external quality assessment (EQA) data. Our approach does not depend on the exchange of samples and is solely based on the mathematical CF calculation using EQA results. RESULTS AND CONCLUSION: We have demonstrated by thorough statistical validation that this approach performs well in converting BCR-ABL1 measurements to improve IS estimation. In expectation of a true golden standard method for BCR-ABL1 IS quantification, the proposed method is a valuable alternative.
Subject(s)
Fusion Proteins, bcr-abl/genetics , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/diagnosis , RNA, Messenger/analysis , Genetic Testing , International Cooperation , Leukemia, Myelogenous, Chronic, BCR-ABL Positive/genetics , Methods , Observer Variation , Reference Standards , Retrospective StudiesABSTRACT
An improved cDNA-AFLP method for genome-wide expression analysis has been developed. We demonstrate that this method is an efficient tool for quantitative transcript profiling and a valid alternative to microarrays. Unique transcript tags, generated from reverse-transcribed messenger RNA by restriction enzymes, were screened through a series of selective PCR amplifications. Based on in silico analysis, an enzyme combination was chosen that ensures that at least 60% of all the mRNAs were represented by an informative sequence tag. The sensitivity and specificity of the method allows one to detect poorly expressed genes and distinguish between homologous sequences. Accurate gene expression profiles were determined by quantitative analysis of band intensities, and subtle differences in transcriptional activity were revealed. A detailed screen for cell cycle-modulated genes in tobacco demonstrates the usefulness of the technology for genome-wide expression analysis.
