Oral Presentation 26th Annual Lorne Proteomics Symposium 2021

Multi-omics of B-cell precursor acute lymphoblastic leukemia cells with MLL rearrangement (MLL‑r) revealed a deep modification of their glycosylation machinery (#6)

Tiago Oliveira 1 , Eun J Joo 2 , Hisham Abdel-Azim 3 , Andreia Almeida 1 , Kathirvel Alagesan 1 , Mingfeng Zhang 2 , Francis Jacob 4 , Nicolle H Packer 1 5 6 , Mark von Itzstein 1 , Nora Heisterkamp 2 , Daniel Kolarich 1 6
  1. Institute for Glycomics - Griffith University, Southport, QLD, Australia
  2. Department of Systems Biology, Beckman Research Institute City of Hope, Monrovia, CA, USA
  3. Division of Hematology/Oncology and Bone Marrow Transplant, Children’s Hospital Los Angeles, Los Angeles, CA, USA
  4. Glyco-Oncology, Ovarian Cancer Research, Department of Biomedicine, University Hospital Basel and University of Basel, Basel, Switzerland
  5. Department of Chemistry and Biomolecular Sciences, Macquarie University, Sydney, NSW, Australia
  6. ARC Centre for Nanoscale BioPhotonics, Macquarie University and Griffith University, North Ryde and Gold Coast, NSW and QLD, Australia

Mixed-lineage Acute Leukemia (MLL) is one of the most high-risk forms of pediatric cancer. Although the long-term survival rates of pediatric acute lymphoblastic leukemia have increased over the past 40 years, the current chemotherapeutic treatment schemes often fail in MLL. The biological mechanisms resulting in drug resistance, however, are still not fully understood and there is an urgent need to identify novel diagnostic and therapeutical targets. We have established the first integrated multi‑omics investigation of primary patient MLL samples and control precursor B bone-marrow (BM) cells from healthy donors, mapping their proteome, transcriptome and glycome.

4-6 million cells from 3 normal BM and 2 MLL samples were used for analysis on our multi-omics platform. Porous‑Graphitised Carbon (PGC) nanoLC‑ESI-MS/MS was used for Glycomics analyses after the enzymatic and chemical release of N- and O-glycans, respectively. The proteome was explored using RP-LC-ESI-MS/MS analyses on an Orbitrap Fusion, performed after offline high-pH fractionation, in addition to RNA-seq analyses.

Overall, 4225 proteins were identified across the patient MLL and control BM cells, of which 216 were overexpressed in MLL (p<0.01, log2dif>2). Analyses of RNA-seq and proteomics data revealed significant correlations between gene and protein expression levels, with overexpression in MLL of important glycoprotein signalling receptors and extracellular matrix proteins as well as various transcription factors. Offline fractionation was the key to identify and quantify numerous important glycosyltransferases and other protein expression changes.

The O‑glycosylation initiating enzyme GALNT7 was specifically overexpressed in MLL cells, correlating with a significant increase in Core 2 type O-glycans. Core 2 O‑glycans account for (in average) 50% of the O-glycans found in MLL cells, whilst in Normal BM this percentage decreases to half. Core 1 O-glycans, however, experienced a significant decrease in MLL cells (63% in Normal BM to 37% in MLL), accompanied by an increase in GCNT1 and a decrease of ST6GALNAC1 transcript levels in MLL cells. Changes on N-glycans were less pronounced, with just a slight increase in complex type glycan levels in MLL cells, largely due to an increase in sialylated N‑glycans.

Our data shows that MLL cells undergo and extensive remodelling of the cell surface glycocalyx, in particular on the type of protein O-glycosylation. Next to confirming previous reports describing increased levels of a number of MLL glycoprotein markers such as FLT3, our integrated multi-omics workflow identified a number of hitherto not-reported diagnostic/therapeutic protein candidates that provide novel clues to understand MLL-r pathogenesis.