Monitoring MRD in ALL: Methodologies, technical aspects and optimal time points for measurement
Jack Bartram1, Bela Patel2, Adele K Fielding3
1Department of Haematology, Great Ormond Street Hospital for Children, London, UK; Cancer Section, DBC Programme, University College London, London, UK.
Abstract:
The accurate determination of minimal or measurable residual disease (MRD) during the early months of therapy in acute lymphoblastic leukemia is well established as the most important independent prognostic biomarker, predicting response to combination chemotherapy. Stratification based on MRD maximizes treatment effectiveness while minimizing adverse effects. Allele-specific real-time quantitative PCR of clone-defining immunoglobin/T-cell receptor gene rearrangements in the patients' leukemic clones and/or multiparametric flow cytometric tracking of leukemia-associated immunophenotypes are considered standard of care. Following recent advances in high throughput sequencing (HTS; next generation sequencing), much attention has been devoted to the development of HTS-based MRD assays, which can increase sensitivity; theoretically only limited by the number of cells input into the assay. Knowledge of the methods and limitations of each technology, along with awareness of the sensitivity and specificity of MRD at particular treatment time points is important in interpretation of the MRD value. MRD negativity at pre-established protocol-appropriate time points guides continuance with consolidation/maintenance chemotherapy, whereas positivity leads to a change to a biological therapy such as blinatumomab and intensification of therapy to allogeneic stem cell transplant. Positivity after maintenance may herald impending relapse enabling treatment intervention. MRD has been integral to the introduction of novel agents and cellular therapies into clinical trials and standard of care, but the long-term predictive value of MRD on outcome of novel therapies is not yet established. Integration of somatic genetics with MRD may further improve accurate identification of patients with the lowest and highest risk of relapse.
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