Cell state transitions drive the evolution of disease progression in B-lymphoblastic leukemia

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Cell state transitions drive the evolution of disease progression in B-lymphoblastic leukemia

Authors

Gravenmier, C.; Marzban, S.; Tang, Y.-H.; Gillis, N.; Shah, B. D.; Moscinski, L.; Zhang, L.; West, J.

Abstract

Cancer stem cells (CSCs) are hypothesized to promote tumor progression through innate chemoresistance and self-renewal. CSCs reside in the CD34+/CD38- immunophenotypic subpopulation of acute myeloid leukemia (AML); correspondingly, the size of this subpopulation has a strong negative impact on overall survival. Isolation of CSCs from B-lymphoblastic leukemia (B-ALL) has proven difficult, and the cells of interest apparently are not isolated to the CD34+/CD38- compartment. This may be explained, in part, by temporal variations of CD34 and CD38 expression which result in stochastic cell state transitions (e.g., from CD34+/CD38+ to CD34+/CD38-). We present a mathematical model of these transitions and correlate salient findings with BCR::ABL1 status, minimal residual disease (MRD), and relapse in adult B-ALL. As the CSC hypothesis is well supported in AML, we focus on transitions to and from the hematopoietic stem cell compartment (CD34+/CD38-), which our findings suggest can be estimated from peripheral blood or bone marrow samples. Additionally, we find that BCR::ABL1 positive patient samples are associated with high transition rates into the CD34+/CD38- compartment, including self-renewal. In contrast, BCR::ABL1 negative patient samples have low CD34+/CD38-self-renewal rates and either high CD34+/CD38+ or CD34-/CD38+ incoming rates. High CD34+/CD38- self renewal is also associated with MRD post-induction chemotherapy. We find a lack of observable changes in cell state transitions between diagnosis and relapse specimens. Our analysis provide evidence of de-differentiation transitions to a CD34+/CD38- stem cell-like immunophenotype in leukemia samples collected from B-ALL patients, and the tendency for these transitions is especially strong for B-ALL with BCR::ABL1. The modeling framework used here is a novel, useful tool to infer both prognosis and genotype from routine flow cytometry data.

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