Glycoproteome remodeling in MLL-rearranged B-cell precursor acute lymphoblastic leukemia

Tiago Oliveira, Mingfeng Zhang, Eun Ji Joo, Hisham Abdel-Azim, Chun-Wei Chen, Lu Yang, Chih-Hsing Chou, Xi Qin, Jianjun Chen, Kathirvel Alagesan, Andreia Almeida, Francis Jacob, Nicolle H. Packer, Mark von Itzstein, Nora Heisterkamp*, Daniel Kolarich*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)
55 Downloads (Pure)

Abstract

B-cell precursor acute lymphoblastic leukemia (BCP-ALL) with mixed-lineage leukemia gene rearrangement (MLL-r) is a poor-prognosis subtype for which additional therapeutic targets are urgently needed. Currently no multi-omics data set for primary MLL r patient cells exists that integrates transcriptomics, proteomics and glycomics to gain an inclusive picture of theranostic targets.

Methods: We have integrated transcriptomics, proteomics and glycomics to i) obtain the first inclusive picture of primary patient BCP-ALL cells and identify molecular signatures that distinguish leukemic from normal precursor B-cells and ii) better understand the benefits and limitations of the applied technologies to deliver deep molecular sequence data across major cellular biopolymers.

Results: MLL-r cells feature an extensive remodeling of their glycocalyx, with increased levels of Core 2-type O-glycans and complex N-glycans as well as significant changes in sialylation and fucosylation. Notably, glycosaminoglycan remodeling from chondroitin sulfate to heparan sulfate was observed. A survival screen, to determine if glycan remodeling enzymes are redundant, identified MGAT1 and NGLY1, essential components of the N-glycosylation/degradation pathway, as highly relevant within this in vitro screening. OGT and OGA, unique enzymes that regulate intracellular O-GlcNAcylation, were also indispensable. Transcriptomics and proteomics further identified Fes and GALNT7-mediated glycosylation as possible therapeutic targets. While there is overall good correlation between transcriptomics and proteomics data, we demonstrate that a systematic combined multi-omics approach delivers important diagnostic information that is missed when applying a single omics technology.

Conclusions: Apart from confirming well-known MLL-r BCP-ALL glycoprotein markers, our integrated multi-omics workflow discovered previously unidentified diagnostic/therapeutic protein targets.

Original languageEnglish
Pages (from-to)9519-9537
Number of pages19
JournalTheranostics
Volume11
Issue number19
DOIs
Publication statusPublished - 2021

Bibliographical note

Copyright the Author(s) 2021. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Leukemia
  • Glycomics
  • Proteomics
  • Transcriptomics
  • multi-omics
  • Multi-omics

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