Mary Alikian1,2, Alexandra S Whale3, Susanna Akiki4, Kim Piechocki4, Celia Torrado5, Thet Myint5, Simon Cowen6, Michael Griffiths4, Alistair G Reid5,2, Jane Apperley2,7, Helen White8, Jim F Huggett3,9, Letizia Foroni2,7. 1. Imperial Molecular Pathology, Imperial Healthcare Trust, Hammersmith Hospital, London, UK; m.alikian@imperial.ac.uk. 2. Centre for Haematology, Faculty of Medicine, Imperial College London, London, UK. 3. Molecular and Cell Biology Team, LGC, Queens Road, Teddington, UK. 4. West Midlands Regional Genetics Laboratories, Birmingham Women's NHS Foundation Trust, Birmingham, UK. 5. Imperial Molecular Pathology, Imperial Healthcare Trust, Hammersmith Hospital, London, UK. 6. Statistics Team, LGC, Queens Road, Teddington, UK. 7. Clinical Haematology, Imperial College Healthcare NHS Trust, London, UK. 8. National Genetics Reference Laboratory (Wessex), Salisbury District Hospital, Salisbury, UK. 9. School of Biosciences & Medicine, Faculty of Health & Medical Science, University of Surrey, Guildford, UK.
Abstract
BACKGROUND: Tyrosine kinase inhibitors (TKIs) are the cornerstone of successful clinical management of patients with chronic myeloid leukemia (CML). Quantitative monitoring of the percentage of the fusion transcript BCR-ABL1 (breakpoint cluster region-c-abl oncogene 1, non-receptor tyrosine kinase) BCR-ABL1IS (%BCR-ABL1IS) by reverse transcription-quantitative PCR (RT-qPCR) is the gold standard strategy for evaluating patient response to TKIs and classification into prognostic subgroups. However, this approach can be challenging to perform in a reproducible manner. Reverse-transcription digital PCR (RT-dPCR) is an adaptation of this method that could provide the robust and standardized workflow needed for truly standardized patient stratification. METHODS: BCR-ABL1 and ABL1 transcript copy numbers were quantified in a total of 102 samples; 70 CML patients undergoing TKI therapy and 32 non-CML individuals. 3 commercially available digital PCR platforms (QS3D, QX200 and Raindrop) were compared with the platform routinely used in the clinic for RT-qPCR using the EAC (Europe Against Cancer) assay. RESULTS: Measurements on all instruments correlated well when the %BCR-ABL1IS was ≥0.1%. In patients with residual disease below this level, greater variations were measured both within and between instruments limiting comparable performance to a 4 log dynamic range. CONCLUSIONS: RT-dPCR was able to quantify low-level BCR-ABL1 transcript copies but was unable to improve sensitivity below the level of detection achieved by RT-qPCR. However, RT-dPCR was able to perform these sensitive measurements without use of a calibration curve. Adaptions to the protocol to increase the amount of RNA measured are likely to be necessary to improve the analytical sensitivity of BCR-ABL testing on a dPCR platform.
BACKGROUND: Tyrosine kinase inhibitors (TKIs) are the cornerstone of successful clinical management of patients with chronic myeloid leukemia (CML). Quantitative monitoring of the percentage of the fusion transcript BCR-ABL1 (breakpoint cluster region-c-abl oncogene 1, non-receptor tyrosine kinase) BCR-ABL1IS (%BCR-ABL1IS) by reverse transcription-quantitative PCR (RT-qPCR) is the gold standard strategy for evaluating patient response to TKIs and classification into prognostic subgroups. However, this approach can be challenging to perform in a reproducible manner. Reverse-transcription digital PCR (RT-dPCR) is an adaptation of this method that could provide the robust and standardized workflow needed for truly standardized patient stratification. METHODS:BCR-ABL1 and ABL1 transcript copy numbers were quantified in a total of 102 samples; 70 CMLpatients undergoing TKI therapy and 32 non-CML individuals. 3 commercially available digital PCR platforms (QS3D, QX200 and Raindrop) were compared with the platform routinely used in the clinic for RT-qPCR using the EAC (Europe Against Cancer) assay. RESULTS: Measurements on all instruments correlated well when the %BCR-ABL1IS was ≥0.1%. In patients with residual disease below this level, greater variations were measured both within and between instruments limiting comparable performance to a 4 log dynamic range. CONCLUSIONS: RT-dPCR was able to quantify low-level BCR-ABL1 transcript copies but was unable to improve sensitivity below the level of detection achieved by RT-qPCR. However, RT-dPCR was able to perform these sensitive measurements without use of a calibration curve. Adaptions to the protocol to increase the amount of RNA measured are likely to be necessary to improve the analytical sensitivity of BCR-ABL testing on a dPCR platform.
Authors: Carmen Fava; Simona Bernardi; Enrico Marco Gottardi; Roberta Lorenzatti; Laura Galeotti; Francesco Ceccherini; Francesco Cordoni; Filomena Daraio; Emilia Giugliano; Aleksandar Jovanovski; Jessica Petiti; Marta Varotto; Davide Barberio; Giovanna Rege-Cambrin; Paola Berchialla; Veronica Sciannameo; Michele Malagola; Giuseppe Saglio; Domenico Russo Journal: Diseases Date: 2021-05-05