Resistance Mechanisms to Mutant IDH Inhibitors in Acute Myeloid Leukemia

Acute myeloid leukemia (AML) is an aggressive hematological malignancy characterized by the accumulation of immature myeloid stem and progenitor cells.In AML, around 10% of patients carry mutations in the isocitrate dehydrogenase 1 (IDH1) gene, which promote leukemic transformation through the production of the oncometabolite 2-hydroxyglutarate (R-2-HG). Ivosidenib (IVO) is an inhibitor of the mutant IDH1 enzyme approved for the treatment of IDH1-mutated AML. Treatment with IVO can induce terminal differentiation of leukemic blasts via suppression of R-2-HG. However, ivosidenib as a single agent has limited efficacy, highlighting the need to better understand the mechanisms of drug resistance. In Chapter 1, I describe how a genome-wide functional genomic screen led us to discover that CLEC5A-SYK signaling mediates IVO resistance by inducing STAT5-dependent expression of self-renewal genes. This discovery provides rationale for combining STAT5 inhibitors with IDH inhibitors for IDH-mutated AML, which demonstrated superior efficacy over single-agents in our pre-clinical studies. In Chapter 2, I characterized the varied responses of genetically distinct subclones of IDH-mutated AML to IDH inhibitors and other anti-leukemic agents using single-cell proteogenomic sequencing in both single patient-derived xenograft (PDX) and mixed-PDX models. This study highlights the utility of applying single-cell proteogenomic analysis in PDX models to gain insights into mechanisms of drug resistance and potential strategies to combat them. In Chapter 3, I describe a Bayesian statistical model that uses Gaussian process regression to remove droplet- and sample-specific technical noise in single-cell protein sequencing data. I demonstrate how this method improves data interpretability, uncovers true biological variation, and removes spurious findings. The final chapter is inspired by the technical difficulties in integrating a cell’s functional properties with single-cell sequencing readouts. This challenge stems from the fact that current single-cell assays for detecting genetic alterations or mRNA abundance ultimately kill the cell, thus eliminating the possibility of any functional interrogation. To this end, I describe the development of a technology that detects specific mRNA and converts this detection into a fluorescent signal within living cells using RNA-targeting CRISPR enzymes. Since the cells remain alive during the process, the fluorescently labeled cells can be isolated by FACS for functional characterization.

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