Unraveling the protein phosphorylation and glycosylation landscape of diffuse large B-Cell lymphoma using multilayer proteomics and integrative multiomics

Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma encountered clinically. Extensive genomics studies have enabled the stratification of DLBCL subtypes which exhibit significantly different clinical outcomes and responses to the most common treatment regimes. However, the functional consequences of these heterogeneous genetic aberrations on protein dynamics remain largely unknown. We applied multilayer proteomics and integrative multi-omics on DLBCL cell lines to investigate the underlying mechanisms of the disease.

Methods: 20 DLBCL cell lines were quantitatively profiled using our streamlined TMT-based pipeline, allowing for multiplexed proteomics, phospho- and glycoproteomics being analyzed from one consecutive sample preparation workflow. Data was analyzed on single layer level (e.g. differential expression and functional enrichment) and afterwards combined in an integrative approach using other layers of omics data (e.g. RNAseq and drug sensitivity) to identify interlayer-correlations.

Results: Our data clustered the cell lines into 4 subgroups showing distinct proteomic patterns of 772 proteins total. Two clusters showed significantly regulated proteins in B-cell receptor and NF-kappaB signalling pathways, respectively, in agreement with the well-established DLBCL genetic subtypes. Quantification of 18278 phospho-sites revealed distinct molecular regulations in the cell line clusters and allowed for activity-based prediction of upstream kinases and phosphatases, further stratifying the clusters. Quantification of 7800 glycoforms showed a distinct pattern compared to proteomics-based clustering, establishing three glycosylation-specific clusters exhibiting unique characteristics. The integrative multi-omics approach allowed us to identify additional pathways of interest in the respective clusters and provides further validation for our findings.

Conclusion: We established characteristic clusters of DLBCL cell lines with distinct biological and functional features. Integrated multi-omics analysis provides a valuable insight into the underlying mechanisms of different DLBCL subtypes and identifies potential targets for functional analysis guiding towards new treatment approaches, e.g. interfering with critical upstream enzymes of the respective subtypes. Soon, more DLBCL cell lines will be characterized using other mass spectrometry approaches and more in-depth integration is to be established.