DNA sequencing-based detection of residual disease has been found to accurately predict which acute lymphoblastic leukaemia patients will eventually relapse.
CAR-T
Tisagenlecleucel (KYMRIAH) is a CD19-directed genetically modified autologous T cell immunotherapy. It is used to treat acute lymphoblastic leukaemia (ALL) and lymphoma. The emergence of this therapy has led to a paradigm shift in therapeutic choices. Around 80% of ALL patients treated with this CAR-T treatment experience complete remission. However, around half of the patients who experience remission eventually relapse and require additional treatment e.g., bone marrow transplant.
As the CD19 receptor is also expressed on normal B cells, the CAR-T results in B-cell aplasia (depletion of B cells). Currently, monitoring B-cell aplasia alone is not sufficient to monitor relapse as it only picks up part of the relapse risk. Recurrence can sometimes happen even in the absence of B-cell recovery (signifies loss of functional CAR-T cells).
Unfortunately, there are no reliable markers to predict relapse in ALL patients receiving CAR-T. Accurately predicting this could allow patients who need a transplant to begin treatment before the disease actually recurs. It could also identify patients who are heading toward longer-term benefit who may not need further therapies.
Using DNA sequencing to predict leukaemia relapse
In a recent study, published in Blood Cancer Discovery, researchers assessed minimal residual disease (MRD) detection and B-cell aplasia in ALL patients after tisagenlecleucel therapy to define biomarkers predictive of relapse. The team used blood and bone marrow samples collected from the ELIANA and ENSIGN phase II clinical trials.
The researchers used flow cytometry to test for the presence of several receptors on the cell surface. They also used next-generation DNA sequencing MRD (NGS-MRD) monitoring to analyse IgH, IgK and IgL for rearrangement and translocations.
The team found that flow cytometry could detect approximately one cancer cell per 10,000 blood cells. However, NGS-MRD was far more sensitive, being able to detect one cancer cell per 1 to 10 million blood cells. This resulted in 131% more positive samples detected via NGS-MRD compared with flow cytometry.
NGS-MRD of bone marrow samples was also more accurate in predicting relapse than flow cytometry. It was able to identify those individuals at risk well in advance of relapse. For example, those who had NGS-MRD positivity at the lowest levels relapsed a median of 168 days after the positive test. The assay detected 100% of the relapses. In comparison, flow cytometry was positive at a median 52 days prior to relapse and missed 50% of the relapses.
NGS-MRD was also more accurate than B-cell aplasia at predicting relapse. For example, three months after treatment, B-cell recovery was not predictive of recurrence, while patients with a positive NGS sample had a 12-fold higher risk of recurrence. The authors recommended that NGS-MRD should be used alongside monitoring of B-cell aplasia.
Overall, these findings highlight that NGS provides more sensitive measurements with sufficient time prior to relapse to begin therapeutic intervention. Nonetheless, the authors noted that the wider applicability of this approach will need further validation.
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