Impact of Genetic Polymorphisms in NF-ĸB2 and TRAF3 Genes on Response to Bortezomib-Based Therapy in Multiple Myeloma Patients

NF-κB2和TRAF3基因多态性对多发性骨髓瘤患者接受硼替佐米治疗反应的影响

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Abstract

BACKGROUND: Multiple myeloma (MM), being the second most common hematological malignancy, has garnered significant attention. The ubiquitin proteasomal pathway (UPP), crucial for normal cell function, plays a pivotal role in myeloma pathophysiology, especially with the advent of bortezomib (BTZ). Dysregulation of the UPP has implications ranging from developmental abnormalities to cancer. OBJECTIVES: This study aimed to delineate the clinical characteristics of newly diagnosed multiple myeloma patients and investigate the influence of single nucleotide polymorphisms (SNPs) in NF-ĸB2 and TRAF3 genes on the risk and treatment response to bortezomib-based chemotherapy. MATERIALS AND METHODS: Conducted at JIPMER, Pondicherry, this prospective study enrolled 184 participants, comprising cases and controls. DNA extraction from peripheral blood samples was followed by SNP analysis through Real-time Polymerase Chain Reaction. Patients were categorized into Good and Poor responders, and SNP associations with treatment response, response rates, and survival outcomes were assessed using chi-square and Kaplan-Meier analyses. RESULTS: The median age of participants was 55 years, with backache being the most prevalent symptom (66.3%). Hypercalcemia (22%), renal failure (8.7%), and bone fractures (45.7%) were also observed, alongside high prevalence of anemia. Notably, the frequency of the TRAF3 rs12147254 A allele was lower in cases compared to controls (31% vs. 49%, P-value=0.002). Poor responders exhibited higher frequencies of the GA+AA genotypes in TRAF3 rs12147254 (OR-3.882(1.629-9.251), P-value-0.002) and NFKB2 rs1056890 (OR-3.308(1.366-8.012), P-value-0.008) when compared to good responders. The GA+AA genotype in TRAF3 rs11160707 SNP correlated with improved progression-free survival. CONCLUSION: The study findings underscore a significant association between genetic polymorphisms and treatment response outcomes, suggesting their utility in prognostic determinations and clinical outcomes prediction in multiple myeloma patients.

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