Author ORCID Identifier
0000-0002-8364-7971
Date of Graduation
12-2023
Document Type
Thesis (MS)
Program Affiliation
Biomedical Sciences
Degree Name
Masters of Science (MS)
Advisor/Committee Chair
Koichi Takahashi
Committee Member
Simona Colla
Committee Member
Ken Chen
Committee Member
Linghua Wang
Committee Member
Ziyi Li
Abstract
Venetoclax is a small molecule inhibitor targeting BCL-2. Since its approval, the combination therapy of hypomethylating agents and Venetoclax (HMA+Ven) has become a standard of care for acute myeloid leukemia (AML) patients unfit for intensive chemotherapy. Nonetheless, clinical challenges persist as patients either do not respond or eventually relapse, and the underlying mechanisms of these outcomes are not yet fully understood. Prior studies have identified genetic factors (TP53 and RTK/RAS pathway mutations) and phenotypic factors (monocytic differentiation) to be associated with resistance. In this light, we hypothesized that integrative assessment of genetic and phenotypic factors could further elucidate the unknown mechanisms of resistance to the HMA+Ven treatment.
To identify the predictors of intrinsic resistance, we examined the baseline characteristics of 208 newly diagnosed, secondary, and relapse/refractory AML patients treated with Decitabine and Venetoclax (Dec+Ven). We found that genetic factors, such as complex cytogenetics, KRAS and TP53 mutations, were significantly associated with initial treatment resistance. However, phenotypic factors, including bone marrow differentials and French-American-British (FAB) classifications, were not significantly associated with the initial treatment response.
To examine the mutational and immunophenotypic features of the resistant cell populations, we employed single-cell DNA-Antibody sequencing (DAb-seq) on 33 AML patients from the clinical cohort, analyzing a total of 60 bone marrow samples that were sequentially collected from these patients. All five baseline-relapse pairs underwent phenotypic shifts, in which stem-like cells were largely eradicated and replaced by more differentiated cells such as erythrocytes or monocytes. Three patients had monocytic shifts, one had an erythroid shift, and one had a mixed monocytic-erythroid shift. We did not always observe the outgrowth of genetic mutations at relapse. However, in one case, a patient showed an expansion of NRAS mutation accompanied by an erythroid shift. In another case, a patient exhibited the acquirement of KRAS and FLT3 mutations accompanied by a monocytic shift.
To delve into the mechanisms driving these transitions, we profiled the expression levels of various BCL2 family proteins through single-cell RNA sequencing. We studied four patients who had displayed the phenotypic shifts by DAb-seq analysis. At relapse, we confirmed the upregulated BCL2L1 in the predominant erythroid compartment in patient who had displayed an erythroid shift. Furthermore, we confirmed the upregulated MCL1 in the monocytic compartments of two patients with monocytic shifts. In one of these patients, scRNAseq additionally revealed a considerable presence of erythroid compartment upregulated with BCL2L1. Importantly, BCL2 was downregulated in all these compartments. One patient had displayed an erythroid shift during the nonresponsive stages of Dec+Ven, and through scRNAseq, we observed that the patient had a mixture of BCL2, MCL1, and BCL2L1-expressing cells after the first cycle of treatment.
In conclusion, transitions from stem-like toward more differentiated phenotypes (either monocytic or erythroid) were frequently observed in AML relapse following Dec+Ven therapy. These findings are consistent with the known dependency of these cells on non-BCL-2 anti-apoptotic proteins such as MCL-1 and BCL-xL. Hence, close monitoring of phenotypic alterations throughout the HMA+Ven treatment may potentially facilitate the precise identification of patients predisposed to relapse.
Keywords
acute myeloid leukemia, Venetoclax, computational biology, single-cell DNA-Antibody sequencing, single-cell RNA sequencing, multimodal analysis
Included in
Biomedical Informatics Commons, Hematology Commons, Oncology Commons, Translational Medical Research Commons