Abstract 109P
Background
The small population of cancerous cells that remain following treatment, known as measurable residual disease (MRD), is the major cause of relapse in acute myeloid leukemia (AML). Usually, these refractory cells have gained additional resistance mutations or changed their surface immunophenotypes in ways that preclude detection and phasing by current gold standard flow cytometry or bulk NGS assays. For this reason, a multiomic single-cell MRD (scMRD) assay could offer a more comprehensive indicator of relapse and the potential for faster response.
Methods
Here, we present a new scMRD assay with a 0.01% limit of detection that provides single-cell clonal architecture and immunophenotyping to not only identify residual leukemia cells, but also identify putative DNA or protein targets for salvage therapy. The assay enables rare-cell detection on a standard Mission Bio Tapestri run by adding (i) an upfront bead-based protocol to enrich for blast cells, (ii) a DNA and protein panel specifically designed for AML MRD diagnosis and treatment, and (iii) a new, automated analysis pipeline to evaluate single-cell multiomics output. By utilizing Mission Bio’s single-molecule DNA sensitivity for single cells, this pipeline can identify and correlate co-occurring de novo variants, thereby reducing false positive rates. It furthermore can create phylogenetic trees of the detected MRD cells and present their surface protein signature and arm-level copy number. In addition, the multiplexing of up to three patient samples combined in one run via germline identification further reduces per sample costs and increases throughput.
Results
To demonstrate these features, we applied the scMRD assay to banked bone marrow aspirate samples from 3 patients. The scMRD assay resolved the clonal architecture identifying multiple co-occurring mutations and readily distinguished pre-leukemic from leukemic clones. The integration of genotype and immunophenotypic further enhanced MRD detection by identifying genotype-specific protein expression patterns.
Conclusions
By combining high sensitivity with multiomics, this assay offers a potential scalable solution for comprehensive MRD detection that guides therapeutic decision-making.
Editorial acknowledgement
Clinical trial identification
Legal entity responsible for the study
The authors.
Funding
Mission Bio.
Disclosure
All authors have declared no conflicts of interest.
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