Abstract
Acute myeloid leukemia (AML) is an aggressive disease that is characterized by abnormal increase of immature myeloblasts in blood and bone marrow. The FLT3 receptor tyrosine kinase plays an integral role in hematopoiesis, and one third of AML diagnoses exhibit gain-of-function mutations in FLT3, with the juxtamembrane domain internal tandem duplication (ITD) and the kinase domain D835Y variants observed most frequently. Few FLT3 substrates or phosphorylation sites are known, which limits insight into FLT3's substrate preferences and makes assay design particularly challenging. We applied in vitro phosphorylation of a cell lysate digest (adaptation of the Kinase Assay Linked with Phosphoproteomics (KALIP) technique and similar methods) for high-throughput identification of substrates for three FLT3 variants (wild-type, ITD mutant, and D835Y mutant). Incorporation of identified substrate sequences as input into the KINATEST-ID substrate preference analysis and assay development pipeline facilitated the design of several peptide substrates that are phosphorylated efficiently by all three FLT3 kinase variants. These substrates could be used in assays to identify new FLT3 inhibitors that overcome resistant mutations to improve FLT3-positive AML treatment.
Highlights
Acute myeloid leukemia (AML) is an aggressive cancer with a diverse genetic landscape
Both internal tandem duplication (ITD) and tyrosine kinase domain (TKD) mutants can activate and dimerize with the wild type FLT3.7 The effects of these mutations on FLT3 signaling are still unclear, but one possibility is that mutant FLT3TKD and FLT3-ITD activate alternative signaling pathways, or activate standard FLT3 pathways aberrantly, compared to the WT
These findings prompted the use of a combinatorial approach to AML therapies to include FLT3 tyrosine kinase inhibitors (TKIs), which are frequently initially successful but often lead to FLT3 inhibitor resistance and subsequent disease relapse
Summary
Acute myeloid leukemia (AML) is an aggressive cancer with a diverse genetic landscape. The shared substrate sequences were extracted from the phosphoproteomics data outputs using data processing and analysis tools, the KinaMine and Commonality and Difference Finder and the Kinatest part 1.r script (Figure 2), described in the supplementary methods section, to generate PSMs of amino acid preference motifs from each dataset (Figure 3).
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