The Future of Risk Prediction and Monitoring in Multiple Myeloma

As multiple myeloma research evolves, new tools are emerging to better predict risk, monitor disease, and personalize treatments for each person. This area of research is working to identify less invasive methods  that could be sensitive to small traces of disease or even detect high-risk before other traditional methods.

Advancing detection techniques is crucial. It could help care teams identify who is at higher risk of progression, track response to therapy in real time, and reduce the need for invasive procedures. In this article, we summarize six novel approaches that could improve the way multiple myeloma is diagnosed, monitored, and managed in the future.

Circulating tumor cells improve risk prediction in newly diagnosed myeloma patients

Circulating tumor cells (CTCs) are cancer cells that are found in the bloodstream. Researchers are exploring how CTCs could be used as a biomarker to help predict outcomes for people with multiple myeloma. An analysis of 2,446 people newly diagnosed with myeloma showed that higher levels of CTCs could identify patients at a higher risk of cancer progression.  Higher CTC levels were linked to a shorter progression-free survival (PFS). The PFS ranged from 77 months in patients with very low levels (≤0.001%) to just 16 months in those with levels of1% or higher. High CTC levels were a sign of higher risk independent of other risk factors. For example, patients with low-risk cytogenetics and high CTC levels still had a higher risk of progression.  Importantly, this analysis included data from both clinical trials and real-world settings. It also included transplant-eligible and ineligible patients. 

 These findings suggest that measuring CTC could strengthen current risk models and support more individualized treatment decisions. More research is needed to understand the exact way to apply this marker in clinical practice.

While CTCs provide important clues about disease aggressiveness, researchers are also looking at genetic profiling tools to refine risk categories even further.

A new way to detect specific genes in plasma cells and identify high-risk myeloma 

A study of 139 patients with smoldering myeloma, newly diagnosed myeloma, and relapsed/refractory multiple myeloma evaluated the SKY92 gene-expression profile test alongside clinical and molecular markers. 

What is SKY92 and how is it different from other genetic tests? 

SKY92 is a gene-expression profiling (GEP) signature. It evaluates the activity of 92 specific genes in plasma cells. SKY92 was developed to identify high-risk multiple myeloma patients whose disease tends to progress faster and respond less favorably to standard therapies. Unlike traditional tests that focus on single genetic abnormalities, SKY92 provides a broader molecular risk assessment by capturing the overall biology of the disease. 

More people were classified as high-risk after being assessed with SKY92. This shows there were gaps in the previous risk stratification system that could be filled with this new method. In newly diagnosed myeloma patients, SKY92 could accurately predict cytogenetic abnormalities such as t(4;14), gain(1q), and del(17p). 

SKY92 compared with other tests to further confirm risk stratification

SKY92 high-risk status correlated with elevated serum BCMA. For instance, serum BCMA (B-cell maturation antigen) levels were significantly higher in newly diagnosed and relapsed/refractory myeloma compared to smoldering myeloma and people without myeloma. 

Combining SKY92 with the International Staging System (ISS) reclassified some patients initially labeled as low risk, improving the alignment of sBCMA with risk categories. These findings support the use of SKY92 as a tool to refine risk stratification and guide more personalized treatment approaches in multiple myeloma.

Beyond genetics, scientists are also exploring new imaging technologies that reveal how myeloma cells behave under treatment

MiROM: an imaging method that could offer real-time insight into myeloma treatment response

A study published in Nature Biomedical Engineering introduced MiROM, a new label-free imaging method developed at Helmholtz Munich that can assess how myeloma cells respond to treatment in real time.

What is MiROM and how does it work? 

MiROM works by using infrared light to trigger molecular vibrations in proteins, generating ultrasound signals that reveal structural changes such as protein misfolding and apoptosis (programmed cell death). These are key indicators of how well treatment is working. 

In laboratory tests, MiROM successfully detected misfolded protein structures in myeloma cells treated with doxorubicin compared to untreated cells. Unlike current methods that require large samples and are time-consuming, MiROM can rapidly analyze single cells without extensive preparation. 

A novelty imaging technique can help people with other diagnoses outside multiple myeloma

Beyond myeloma, the technology could be applied to other diseases involving protein misfolding, such as Alzheimer’s and Parkinson’s. For patients, MiROM holds potential for faster and more personalized treatment monitoring, drug screening, and possibly even at-home disease management once validated in larger clinical studies.

In addition to cell biology and imaging, advances in artificial intelligence are opening new doors for understanding immune system changes that influence myeloma progression.

AI-based immune profiling predicts smoldering myeloma progression

Artificial intelligence (AI) can help analyze large amounts of data in minutes, sometimes, even seconds. One study used AI tools to analyze the T-cells in people diagnosed with smoldering myeloma and found immune signatures that may predict progression to active myeloma. 

In a small group, the AI model achieved 75% accuracy in predicting progression. This result highlights the potential of immune profiling beyond traditional tumor-burden models like the Mayo 2/20/20 score. In the future, care could include immune-based biomarkers to better identify who is more likely to develop active myeloma and who may remain stable. This would allow for more personalized monitoring strategies.

3D Telomere Profiling Stratifies SMM Progression Risk

A study of 168 people with smoldering myeloma used three-dimensional telomere profiling to help predict who is likely to progress to multiple myeloma. Researchers used the TeloView platform which quantifies telomere dysfunction, a sign of genomic instability. Telomeres are part of chromosomes, and they protect them whenever a cell replicates its DNA. They are also an indicator of cell aging. If a telomere is shorter, it indicates the cell has aged. 

TeloView results matched the Mayo 20-2-20 score (53%) and more than 60% correlation with common cytogenetic abnormalities, suggesting it provides complementary biological information.

For patients, this means telomere profiling could help their care team identify high-risk SMM that may benefit from earlier treatment. It could also confirm stability in lower-risk SMM that can be monitored without therapy. Because TeloView can also be applied to blood samples as a liquid biopsy, it may support less invasive, repeatable follow-up over time. Discuss with your hematology team whether adding telomere profiling to current risk models could refine your individual monitoring and treatment plan.

Toward less invasive monitoring: blood-based MRD testing with 3D telomere profiling

A study introduced a new approach to minimal residual disease (MRD) monitoring in multiple myeloma. This also used the TeloView platform, which combines MRD cell enumeration with three-dimensional (3D) telomere profiling. 

In a small trial of 8 transplant-eligible patients, blood and bone marrow samples showed high concordance in most telomere parameters, suggesting that circulating plasma cells can reflect marrow disease biology. 

This method may overcome current MRD limitations, such as reliance on bone marrow biopsies and inability to capture disease heterogeneity. For patients, this could mean less bone marrow biopsies once the development of a blood-based assay becomes widely available. This could also allow more frequent monitoring and provide insight into which residual disease clones are more aggressive, helping clinicians predict relapse risk and refine treatment strategies.

Can MRI lesions predict myeloma progression?

In a large study of 746 people with smoldering myeloma at the University of Arkansas, the number of MRI focal lesions strongly correlated with progression to active myeloma. 

People with more than two lesions progressed at the highest rate (80.4%) compared with 28.7% of people without lesions. Having at least two lesions also shortened the time to progression, and higher gene-expression risk scores were linked to a greater number of lesions. Lesions were most commonly found in the spine and pelvis, but their presence did not impact overall survival.

Differences between MRI and PET scans revealed that using both imaging methods is necessary for a complete evaluation. This study shows that advanced imaging can provide valuable insight into individual risk of progression, helping care teams determine how closely to monitor and when to consider treatment.

Reshaping our understanding of how multiple myeloma is detected and monitored

Taken together, these studies highlight how technology is reshaping the understanding of multiple myeloma. From circulating tumor cells and SKY92 genetic profiling to MiROM imaging and AI-driven immune analysis, each method adds a layer of precision to risk prediction and disease monitoring. 

For people living with myeloma, the hope is that these tools will translate into earlier intervention, more tailored treatment strategies, and fewer burdensome procedures. While many of these approaches are still being validated in clinical trials, they point toward a future where care is increasingly personalized. 

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Sources: 

• Gene-expression-profiling plus integrated multidisciplinary approach to detect new-generation risk-adapted prognostic index in smoldering myeloma and multiple myeloma (GIMPI). 
• Immune profiling to identify a functionally high-risk smoldering multiple myeloma patient population. 
• MRI lesion burden as a predictor of progression and survival in smoldering multiple myeloma.
• Preliminary results of 3D telomeres profiling for myeloma MRD and evaluation of concordance between blood and marrow. 
• Three-dimensional telomere profiling predicts risk of progression in smoldering multiple myeloma
• New Imaging Method Tracks Multiple Myeloma Treatment Success