Researchers at Dana-Farber Cancer Institute and the Broad Institute have developed a new genomic risk score that could help identify which patients with early signs of multiple myeloma are likely to develop the full disease. Published in Nature Genetics, the study introduces the MM-like score, which evaluates the presence and accumulation of cancer-driving mutations to track disease progression.
The team analyzed whole-genome sequencing data from more than 1,000 individuals, including 218 with precursor conditions such as monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM). These early-stage conditions affect many more people than the approximately 32,000 diagnosed with multiple myeloma in the U.S. each year, but only a subset progress to active disease.
“Treating risk as simply ‘high’ or ‘low’ fails to capture the complexity of tumor timing and evolution,” said Jean-Baptiste Alberge, co-senior author of the study. “We saw an opportunity to redefine it through whole-genome sequencing.”
The MM-like score increases with the accumulation of specific mutations over time. In follow-up analyses of 47 tumor samples from 20 patients, rising scores were associated with progression to active disease, while stable scores often aligned with non-progressors.
“There has been an urgent need to identify genomic risk factors that predict disease progression in smoldering myeloma,” said Irene Ghobrial. “Our data provides a simple genomic score that can help predict progression and can improve on our clinical markers.”
Researchers also found that some key mutations may begin to accumulate decades before diagnosis, hinting at a much earlier origin for multiple myeloma than previously thought. Work is underway to adapt the score for use with liquid biopsies, which could make regular monitoring more practical in the clinic.
Publication Details
Alberge, JB., Dutta, A.K., Poletti, A. et al. Genomic landscape of multiple myeloma and its precursor conditions. Nat Genet (2025). https://doi.org/10.1038/s41588-025-02196-0
The team analyzed whole-genome sequencing data from more than 1,000 individuals, including 218 with precursor conditions such as monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM). These early-stage conditions affect many more people than the approximately 32,000 diagnosed with multiple myeloma in the U.S. each year, but only a subset progress to active disease.
“Treating risk as simply ‘high’ or ‘low’ fails to capture the complexity of tumor timing and evolution,” said Jean-Baptiste Alberge, co-senior author of the study. “We saw an opportunity to redefine it through whole-genome sequencing.”
The MM-like score increases with the accumulation of specific mutations over time. In follow-up analyses of 47 tumor samples from 20 patients, rising scores were associated with progression to active disease, while stable scores often aligned with non-progressors.
“There has been an urgent need to identify genomic risk factors that predict disease progression in smoldering myeloma,” said Irene Ghobrial. “Our data provides a simple genomic score that can help predict progression and can improve on our clinical markers.”
Researchers also found that some key mutations may begin to accumulate decades before diagnosis, hinting at a much earlier origin for multiple myeloma than previously thought. Work is underway to adapt the score for use with liquid biopsies, which could make regular monitoring more practical in the clinic.
Publication Details
Alberge, JB., Dutta, A.K., Poletti, A. et al. Genomic landscape of multiple myeloma and its precursor conditions. Nat Genet (2025). https://doi.org/10.1038/s41588-025-02196-0
