Proteomics and functional study reveal marginal zone B and B1 cell specific protein as a candidate marker of multiple myeloma

• Published in: International journal of oncology Vol. 57; no. 1; pp. 325 - 337
• Main Authors: Chanukuppa, Venkatesh, Paul, Debasish, Taunk, Khushman, Chatterjee, Tathagata, Sharma, Sanjeevan, Shirolkar, Amey, Islam, Sehbanul, Santra, Manas K, Rapole, Srikanth
• Format: Journal Article
• Language: English
• Published: Greece Spandidos Publications 01-07-2020; Spandidos Publications UK Ltd
• Subjects: Adaptor Proteins, Signal Transducing - analysis; Adaptor Proteins, Signal Transducing - metabolism; Aged; Anemia; Armed forces; Biomarkers, Tumor - analysis; Biomarkers, Tumor - metabolism; Biopsy; Blood; Bone marrow; Bone Marrow - pathology; Cell Line, Tumor; Comparative analysis; Computational Biology; Disease; Disease Progression; Down-Regulation; EDTA; Experiments; Female; Gene Expression Profiling; Hematology; Humans; Immunoglobulins; International economic relations; Kinases; Male; Middle Aged; Multiple myeloma; Multiple Myeloma - diagnosis; Multiple Myeloma - pathology; Pharmaceutical industry; Prognosis; Prostate cancer; Proteins; Proteomics; Scientific equipment industry; Up-Regulation; United States; Germany; India
• ISSN: 1019-6439; 1791-2423
• DOI: 10.3892/ijo.2020.5056

Multiple myeloma (MM) is a plasma cell‑associated cancer and accounts for 13% of all hematological malignancies, worldwide. MM still remains an incurable plasma cell malignancy with a poor prognosis due to a lack of suitable markers. Therefore, discovering novel markers and targets for diagnosis and therapeutics of MM is essential. The present study aims to identify markers associated with MM malignancy using patient‑derived MM mononuclear cells (MNCs). Label‑free quantitative proteomics analysis revealed a total of 192 differentially regulated proteins, in which 79 proteins were upregulated and 113 proteins were found to be downregulated in MM MNCs as compared to non‑hematological malignant samples. The identified differentially expressed candidate proteins were analyzed using various bioinformatics tools, including Ingenuity Pathway Analysis (IPA), Protein Analysis THrough Evolutionary Relationships (PANTHER), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and Database for Annotation, Visualization and Integrated Discovery (DAVID) to determine their biological context. Among the 192 candidate proteins, marginal zone B and B1 cell specific protein (MZB1) was investigated in detail using the RPMI-8226 cell line model of MM. The functional studies revealed that higher expression of MZB1 is associated with promoting the progression of MM pathogenesis and could be established as a potential target for MM in the future.