The myeloma surface proteome (surfaceome) determines tumor interaction with the microenvironment and serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to define the myeloma surfaceome at baseline, in drug resistance, and in response to acute drug treatment. We provide a scoring system for surface antigens and identify CCR10 as a promising target in this disease expressed widely on malignant plasma cells. We engineer proof-of-principle chimeric antigen receptor (CAR) T-cells targeting CCR10 using its natural ligand CCL27. In myeloma models we identify proteins that could serve as markers of resistance to bortezomib and lenalidomide, including CD53, CD10, EVI2B, and CD33. We find that acute lenalidomide treatment increases activity of MUC1-targeting CAR-T cells through antigen upregulation. Finally, we develop a miniaturized surface proteomic protocol for profiling primary plasma cell samples with low inputs. These approaches and datasets may contribute to the biological, therapeutic, and diagnostic understanding of myeloma.
© 2022. The Author(s).

h4>ABSTRACT/h4> The myeloma cell surface proteome (“surfaceome”) not only determines tumor interaction with the microenvironment but serves as an emerging arena for therapeutic development. Here, we use glycoprotein capture proteomics to first define surface markers most-enriched on myeloma when compared to B-cell malignancy models, revealing unexpected biological signatures unique to malignant plasma cells. We next integrate our proteomic dataset with existing transcriptome databases, nominating CCR10 and TXNDC11 as possible monotherapeutic targets and CD48 as a promising co-target for increasing avidity of BCMA-directed cellular therapies. We further identify potential biomarkers of resistance to both proteasome inhibitors and lenalidomide including changes in CD53, EVI2B, CD10, and CD33. Comparison of short-term treatment with chronic resistance delineates large differences in surface proteome profile under each type of drug exposure. Finally, we develop a miniaturized version of the surface proteomics protocol and present the first surface proteomic profile of a primary myeloma patient plasma cell sample. Our dataset provides a unique resource to advance the biological, therapeutic, and diagnostic understanding of myeloma.

The surfaceome is critical because surface proteins provide a gateway for internal signals and transfer of molecules into cells, and surfaceome differences can influence therapy response. We have used a surfaceome analysis method, based on comparing RNA-seq data between normal and abnormal cells (Surfaceome DataBase Mining or Surfaceome DBM), to identify sets of upregulated cell surface protein mRNAs in an LMO2-mediated T-ALL mouse model and corroborated by protein detection using antibodies. In this model the leukemia initiating cells (LICs) comprise pre-leukaemic, differentiation inhibited thymocytes allowing us to provide a profile of the LIC surfaceome in which GPR56, CD53 and CD59a are co-expressed with CD25. Implementation of cell surface interaction assays demonstrates fluid interaction of surface proteins and CD25 is only internalized when co-localized with other proteins. The Surfaceome DBM approach to analyse cancer cell surfaceomes is a way to find targetable surface biomarkers for clinical conditions where RNA-seq data from normal and abnormal cell are available.