The Disproportional Burden of Multiple Myeloma
Authors: Bikhet Mohamed , Olaniyan Halimat , Niu Wen , Tayeh Marwan , Vetrini Francesco , LePage Nichole 
Published: December 2024

Introduction:

Multiple myeloma (MM) is a plasma cell malignancy characterized by significant molecular heterogeneity, which impacts disease progression and treatment outcomes. This study explores the differences in MM mutations between Black and White individuals in the United States, focusing on the potential genetic and environmental factors contributing to the disparities in outcomes in these populations. Several studies have highlighted distinct genetic profiles in MM among racial groups, suggesting a higher prevalence of certain mutations in Black compared to White populations.

Up to 50% of MM patients have immunoglobulin heavy chain (IGH) gene (14q32) translocations with t(11:14) being the most common. The International Myeloma Working Group (IMWG) newly revised international staging system (R-ISS) requires the analysis of translocations t(4;14), t(14;16) and 17p deletion to stratify risk in MM patients. Patients with t(11;14) are considered standard risk, t(4;14) is intermediate risk, and t(14;16) is high risk. Target therapies exist for t(4;14), t(11;14) but do not currently exist for IGH-cMAF t(14;16) which is treated with high-dose chemotherapy. Understanding cytogenetic profiles of different populations will highlight the most common mutations to improve treatment and optimize personalized medicine.

Methods:

A retrospective cohort study was conducted at the Indiana University Health system investigating differences in multiple myeloma MM mutations between Black and White individuals. Data from medical records and Next Generation Sequencing (NGS) were analyzed. Primary outcomes included the prevalence of specific gene mutations on the NGS results, such as translocations and copy number variants (CNVs), and their frequencies were compared between racial groups. Descriptive statistics and chi-square tests were used for analysis, with a p-value of &lt;0.05 considered significant. The study was IRB-approved and patient confidentiality was maintained.

Results:

We analyzed 173 charts and NGS Multiple Myeloma Panels. 134 patients self-identified as White and 29 patients self-identified as Black or African American with a gender distribution of 94:79 (M:F), and an average age of 65 years old. Missense mutations, copy number variants (CNV), and translocations were the most common gene alterations.

The most common gene variant in White and Black patients was the CCND1-IGH t(11;14). CKS1B, RB1, and TP53 were also commonly indicated genes. CCNDR-IGH and IGH-MAFB translocations were seen in Black patients with a rate of 10% compared to 0% in White patients with p=0.00516.

Discussion:

Genetic profiles guide therapeutic decision-making, influencing eligibility for clinical trials and access to novel treatments tailored to specific molecular subtypes. Previous studies have found that regardless of race, patients with t(11;14) had an increased incidence of light-chain myeloma. Our results were congruent with IGH being the most common gene alteration. IGH-MAFB t(14;20), one of the two genes only detected in the Black patients in our study, is rare in MM but considered a high-risk association with poor prognosis.

Beyond genetic factors, socioeconomic disparities including access to healthcare and differential exposure to environmental risk factors also play crucial roles in shaping MM outcomes. Socioeconomic status further influences access to, timing of, and type of novel therapies and clinical trials available, impacting treatment efficacy and survival rates. Limited access to healthcare resources and disparities in health insurance coverage contribute to delayed diagnosis, suboptimal treatment adherence, and ultimately, poorer survival outcomes compared to their White counterparts.

Understanding these disparities is vital for developing targeted interventions and personalized treatment strategies aimed at improving outcomes in diverse MM patient populations. Integrating genetic screening with social determinants of health further personalized care and facilitate more equitable healthcare delivery and better outcomes for all MM patients.