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Bone Marrow Adipocytes May Offer Early Detection of MGUS Progression to Multiple Myeloma
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Key Takeaways
- BMAT changes may indicate progression from MGUS to MM, offering risk stratification opportunities for high-risk patients.
- AI-based histological analysis of bone marrow biopsies is a cost-effective tool for early detection and personalized treatment.
Increased bone marrow adiposity is associated with progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma.
Changes in bone marrow adipose tissue (BMAT) may serve as early indicators of progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM), according to published in Oncotarget. The researchers utilized artificial intelligence (AI)-based histological analysis of bone marrow biopsies, offering a more cost-effective, promising tool for early detection, risk stratification, and personalized treatment of patients with MGUS at high-risk for progression to MM.1
By identifying structural and functional changes within BMAT, there are opportunities for early identification of high-risk patients. Image Credit: © CHA - stock.adobe.com
MM is the second most common hematological malignancy characterized by the overproduction of mature, yet dysfunctional B lymphocytes, resulting in brittle bones, renal insufficiency, immune function suppression, and organ dysfunction. It is preceded by MGUS, a condition in which monoclonal proteins, abnormal proteins produced by plasma cells, are detected in the blood without clinical signs of organ damage. The risk of progression to MM remains stable at 1% per year, and patients with MGUS typically have no symptoms and do not need treatment.1-3
In the study, the authors identified that changes in BMAT provide risk stratification opportunities for MM, enabling the identification of high-risk patients and timely interventions. Various studies have found an association between increased bone marrow adiposity and risk of MGUS progression to MM, suggesting that bone marrow adipocytes (BMAds) may play a role in MM pathogenesis, as well as serve as a biomarker for progression.1
BMAds play an active role in the bone marrow microenvironment, influencing and modulating the function and behavior of hematopoietic and stromal cells, which impacts hematopoiesis regulation, bone health, and immune signaling. They are crucial for maintaining balance within the bone marrow and, when disrupted, can interfere with healthy immune functioning and normal blood cell production.1
Using AI-assisted histological analyses of unstained bone marrow biopsies, the researchers examined whether the composition of the BMAT is different in stable and progressing MGUS patients. Their analysis consisted of iliac crest bone biopsies from 41 patients with MGUS including 17 stable and 24 with known progression to MM within 10 years following biopsy collection.1
According to the data, there was no significant difference in the BMAT fraction within the bone marrow between the stable and progressing patients, suggesting that overall adipose tissue content was comparable. However, there was a notable decrease in BMAd density in patients who progressed to MM compared with those who did not. The researchers also observed increased BMAd size and roundness in progressing patients, which indicates that BMAds are subject to identifiable alterations during MM development.1
These findings highlight the potential of BMAds as critical players in the progression from MGUS to MM. By identifying structural and functional changes within BMAT, there are opportunities for early identification of high-risk patients to enable timely interventions and personalized treatment strategies. Additionally, utilizing an AI-based approach to characterize bone marrow biopsies is more cost-effective and efficient, allowing for faster, high-throughput analysis that may improve accessibility in clinical settings. Continued research into BMAT’s role could lead to novel strategies for managing MM, improving outcomes by intervening at the earliest stages of disease evolution.
