Monitoring of Minimal Residual Disease (MRD) in Chronic Myeloid Leukemia: Recent Advances.
Cosimo CumboLuisa AnelliGiorgina SpecchiaFrancesco AlbanoPublished in: Cancer management and research (2020)
Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm caused by the BCR-ABL1 fusion gene generation as a consequence of the t(9;22)(q34;q11) rearrangement. The identification of the BCR-ABL1 transcript was of critical importance for both CML diagnosis and minimal residual disease (MRD) monitoring. In this review, we report the recent advances in the CML MRD monitoring based on RNA, DNA and protein analysis. The detection of the BCR-ABL1 transcript by the quantitative reverse-transcriptase polymerase chain reaction is the gold standard method, but other systems based on digital PCR or on GeneXpert technology have been developed. In the last years, DNA-based assays showed high sensitivity and specificity, and flow cytometric approaches for the detection of the BCR-ABL1 fusion protein have also been tested. Recently, new MRD monitoring systems based on the detection of molecular markers other than the BCR-ABL1 fusion were proposed. These approaches, such as the identification of CD26+ leukemic stem cells, microRNAs and mitochondrial DNA mutations, just remain preliminary and need to be implemented. In the precision medicine era, the constant improvement of the CML MRD monitoring practice could allow clinicians to choose the best therapeutic algorithm and a more accurate selection of CML patients eligible for the tyrosine kinase inhibitors discontinuation.
Keyphrases
- chronic myeloid leukemia
- mitochondrial dna
- stem cells
- copy number
- real time pcr
- healthcare
- machine learning
- acute myeloid leukemia
- ejection fraction
- high resolution
- end stage renal disease
- cell free
- primary care
- circulating tumor
- newly diagnosed
- deep learning
- chronic kidney disease
- genome wide
- cell therapy
- palliative care
- gene expression
- mesenchymal stem cells
- tyrosine kinase
- mass spectrometry
- nucleic acid
- data analysis
- binding protein