bioRxivCancer BiologyPreprint
Multi-omics analysis of AML cells treated with azacitidine reveals highly variable cell surface proteome remodeling
Kevin K Leung, Aaron Nguyen, Tao Shi, Lin Tang, Xiaochun Ni, Laure Escoubet, Kyle J MacBeth, Jorge DiMartino, James A Wells
Abstract
Myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML) are diseases of abnormal hematopoietic differentiation with aberrant epigenetic alterations. Azacitidine (AZA) is a DNA methyltransferase inhibitor (DNMTi) widely used to treat MDS and AML, yet the impact of AZA on the cell surface proteome has not been defined. To identify potential therapeutic targets for use in combination with AZA in AML patients, we investigated the effects of AZA treatment on four AML cell lines (KG1a, HL60, HNT34, and AML193), representing different stages of differentiation. The effect of AZA treatment on these cell lines was characterized at three levels: the DNA methylome (methylation array), the transcriptome (gene expression array), and the cell surface proteome (glycoprotein capture with SILAC labeling). Untreated AML cell lines showed substantial overlap in their methylomes, transcriptomes, and cell surface proteomes. AZA treatment globally reduced DNA methylation in all cell lines, but changes in the transcriptome and surface proteome were subtle and differed among the cell lines. Transcriptome analysis identified five commonly up-regulated coding genes upon AZA treatment in all four cell lines, TRPM4 being the only gene encoding a surface protein, and surface proteomics analysis found no commonly regulated proteins. Gene Set Enrichment Analysis (GSEA) of differentially-regulated RNA and surface proteins showed a decrease in metabolism pathways and an increase in immune defense response pathways. As such, AZA treatment in four AML cell lines had diverse effects at the individual gene and protein level, but converged to regulation of metabolism and immune response at the pathway level. Given the heterogeneous response of AZA in the four cell lines at the gene and protein level, we discuss potential therapeutic strategies for combinations with AZA.
- organism: human
- assay: DNA methylation
- assay: bulk RNA-seq
- assay: proteomics
- research focus: differential expression
- approach: statistical model
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