Abstract:
Multiple myeloma (MM) is a common hematological malignancy with poorly understood recurrence and relapse mechanisms. Notably, bortezomib resistance leading to relapse makes MM treatment significantly challenging. To clarify the drug resistance mechanism, we employed a quantitative proteomics approach to identify differentially expressed protein candidates implicated in bortezomib-resistant recurrent and relapsed MM (RRMM). Bone marrow aspirates from five patients newly diagnosed with MM (NDMM) were compared with those from five patients diagnosed with bortezomib-resistant RRMM using tandem mass tag-mass spectrometry (TMT-MS). Subcellular localization and functional classification of the differentially expressed proteins were determined by gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, and hierarchical clustering analyses. The top candidates identified were validated with parallel reaction monitoring (PRM) analysis using tissue samples from 11 NDMM and 8 RRMM patients, followed by comparison with the NCBI Gene Expression Omnibus (GEO) dataset of 10 MM patients and 10 healthy controls (accession no.: GSE80608). Thirty-four differentially expressed proteins in RRMM, including proteinase inhibitor 9 (SERPINB9), were identified by TMT-MS. Subsequent functional enrichment analyses of the identified protein candidates indicated their involvement in regulating cellular metabolism, apoptosis, programmed cell death, lymphocyte-mediated immunity, and defense response pathways in RRMM. The top protein candidate SERPINB9 was confirmed by PRM analysis and western blotting as well as by comparison with an NCBI GEO dataset. We elucidated the proteome landscape of bortezomib-resistant RRMM and identified SERPINB9 as a promising novel therapeutic target. Our results provide a resource for future studies on the mechanism of RRMM.