Abstract
Background: Acute Myeloid Leukemia (AML) is a heterogeneous malignancy in which impaired myeloid differentiation, particularly toward the monocytic lineage, contributes to disease progression and therapeutic resistance. Monocytic AML subtypes are especially resistant to venetoclax-based regimens, partly due to altered mitochondrial metabolism and reduced Bcl-2 dependency. However, objective and scalable tools for quantifying monocytic differentiation in clinical samples are lacking. CyTOF enables high-dimensional single-cell profiling, offering a unique opportunity to systematically assess myeloid maturation and its relationship to treatment response.
Methods: To develop an unbiased, quantitative metric of monocytic differentiation, we designed a 50-parametric AML-focused CyTOF panel incorporating surface markers, intracellular proteins, and key signaling molecules relevant to myeloid maturation and leukemogenesis. Following rigorous antibody validation, we applied this panel to 35 longitudinal bone marrow samples from 12 AML patients enrolled in two clinical trials: one combining a FLT3 inhibitor with an MDM2 inhibitor, and the other using venetoclax plus azacitidine. Data was acquired on the Helios mass cytometry platform.
Single-cell data were analyzed using unsupervised clustering and UMAP dimensionality reduction to robustly identify and gate blast populations, enabling clear separation from other hematopoietic subsets. For each cell, we calculated the Myeloid Differentiation Index (denoted as MDX) by integrating the weighted expression of canonical monocytic markers (CD14, CD68, CD11b, CD36, CD33) and stemness-associated markers (CD34, CD123, MEIS1, HOXA9). The MDX was validated by its ability to distinguish immature blasts from more differentiated myeloid cells across all patient samples. Aggregate MDX scores were then compared across clinical subgroups and analyzed in relation to treatment response, as defined by complete remission (CR) status. Additionally, we combined MDX scoring with apoptosis-related marker analysis to explore mechanisms of therapeutic resistance.
Results: The MDXeffectively captured a continuum of myeloid maturation states. High-scoring cells exhibited increased expression of monocytic differentiation markers (e.g., CD14, CD68, CD11b, CD36) and HLA-DR, accompanied by decreased expression of stemness and progenitor markers such as CD34 and CD123. This scoring framework enabled clear delineation of immature blasts from more differentiated myeloid subsets across all patients.
In two independent AML cohorts, we observed that patients who responded to therapy exhibited a significant increase in MDX over the course of treatment. In the FLT3 inhibitor plus MDM2 inhibitor trial, patients achieving CR showed an average MDX increase of 200 units, while non-responders displayed minimal changes (average increase <10 units). Similarly, in the venetoclax plus azacitidine cohort, MDX dynamics reflected differentiation induction in clinical responders.
As expected, the bone marrow blast frequency was inversely correlated with MDX (Spearman's rho = –0.78, p = 1.12X10-5), indicating that higher MDX values correspond to decreased leukemic burden and increased myeloid maturation.
To further investigate potential mechanisms of treatment resistance, we leveraged our novel MDX scoring system in combination with unsupervised clustering analysis to objectively assess apoptosis-related changes following therapy. Interestingly, in the FLT3 inhibitor plus MDM2 inhibitor cohort, we observed that MCL1 expression increased in parallel with rising MDX, suggesting a shift towards MCL1 dependency in differentiated monocytic-like cells. In the venetoclax plus azacitidine cohort, increased MDX was associated with upregulation of both, MCL1 and BCL-XL, indicating compensation by alternative anti-apoptotic pathways during monocytic differentiation.
Conclusions:The CyTOF-based single-cell Myeloid Differentiation Index (MDX) provides a robust, single-cell quantitative metric of monocytic differentiation in AML. It correlates with treatment response, reflects leukemic burden, and reveals therapy-induced apoptogenic and differentiation-related adaptations. This scoring system offers a valuable tool for immune and differentiation profiling in AML, with potential to guide rational combination therapies in future clinical trials, although validation in larger, independent cohorts is needed.
