Characterization of Kinase Activity by Phosphoproteomics in Myeloid Cell Lines for Identification of Driving Oncogenic Pathways

<div> <div> <div> <p>Myelodysplastic syndromes (MDS) are heterogeneous clonal haematopoietic disorders caused by the sequential accumulation of genetic lesions in haematopoietic stem cells (HSC) where approximately 30% of MDS patients evolve towards secondary acute myeloid leukemia. The aim of this project was to build a bioinformatic pipeline to integrate phosphogenomic data with genetic information in order to characterize kinase activity of involved oncogenic pathways. Here, we present data on the ongoing phosphoproteome characterization and enrichment analysis of kinase-activity in five myeloid cell lines. K562, NB4, THP1, OCI-AML3 and MOLM-13 are myeloid cell lines with established driver oncogenes. They were cultured and analyzed in triplicates by reversed-phase nano liquid chromatography coupled to tandem-mass spectrometry (nanoLC-MS2). Kinase enrichment analysis was performed using R-package SetRank with kinase-substrate datasets from five different databases. 15’698, 14’087, 13’969, 13’993 and 14’201 unique phosphopeptides corresponding to 3’536, 3’363, 3’411, 3’410 and 3’403 unique phosphoproteins were identified, respectively. Kinase enrichment lead to the detection of 77 different kinases. Phenotypically related cell lines clustered together and unique kinase activity patterns emerged for each cell line. A signal from the driver kinase ABL1 was detectable from 2 different databases in K562 as well as additional downstream kinases of ABL1. We could not enrich for the driver kinase FLT3 in MOLM-13, probably due to lack of representation in the currently available substrate-kinase databases. However, downstream kinases of FLT3 were detected. We expect to further improve quantification and annotation by using heavy labeled cell lines (SILAC) as well as kinase motif analysis, respectively. </p> </div> </div> </div>