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Real-time quantitation of bcr-abl transcripts in haematological malignancies
R Saffroy1, A Lemoine, P Brézillon
1Service de Biochimie et Biologie moléculaire-UPRES-EA 1596, Hôpital Paul Brousse and Faculté de Médecine Paris Sud Université Paris XI, Villejuif, France.
European Journal of Haematology
|November 10, 2000
Summary
An automated real-time quantitative PCR assay effectively detects the t(9;22) translocation in blood cancers. This method aids in diagnosing and monitoring patients with chronic myeloid leukemia and other related malignancies.
Area of Science:
- Hematology
- Molecular Biology
- Oncology
Background:
- The t(9;22) translocation, also known as the Philadelphia chromosome, is a hallmark genetic abnormality in several hematological malignancies.
- Accurate detection and monitoring of this translocation are crucial for diagnosis, prognosis, and treatment management.
Purpose of the Study:
- To evaluate an automated real-time quantitative PCR assay for detecting t(9;22)-positive cells in hematological malignancies.
- To assess the assay's utility in diagnosis and patient follow-up.
Main Methods:
- Application of an automated real-time quantitative PCR assay using a double-labeled fluorogenic probe.
- Quantification of chimeric bcr-abl transcripts relative to abl transcripts.
- Comparison of results with conventional nested RT-PCR and cytogenetics.
Main Results:
- The assay demonstrated high reproducibility for t(9;22)-positive K562 RNA.
- Detection limits included ten copies of bcr-abl DNA and one positive cell in 10^4.
- Real-time quantitative RT-PCR values showed good correlation with conventional methods.
- The assay identified early relapse or blastic transformation in some cases through kinetic analysis.
Conclusions:
- Automated real-time quantitative PCR is a sensitive and reproducible method for detecting the t(9;22) translocation.
- This technique is suitable for the diagnosis and follow-up of patients with t(9;22)-positive hematological malignancies.
- Real-time quantitative RT-PCR offers valuable insights into disease kinetics, aiding in early relapse detection.