Molecular Prediction of Myeloma Initiation Molecular Prediction of Myeloma Initiation

总结

SUMMARY Multiple Myeloma (MM) is the second most common hematologic malignancy and is almost always preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering myeloma (SMM). Recent randomized trials have shown that early therapeutic intervention at the stage of SMM can improve progression- free and overall survival. This indicates that early detection and therapeutic intervention before symptomatic MM occurs may lead to improved survival and decreased morbidity from other complications such as bone fractures, renal failure and hospitalizations related to end-organ damage from myeloma. Early detection requires a comprehensive screening of the population at risk for developing MM. Known risk factors for developing MM include aging, race (Blacks), and familial history of hematologic malignancies. Our preliminary data of screening ~7,500 ethnically diverse individuals at risk of developing MM using a sensitive quantitative MALDI-TOF mass spectrometry has shown a prevalence rate of monoclonal protein in 45% in individuals of age >50y and having an early immune dysregulation that we termed Monoclonal Gammopathy of Indeterminate Potential (MGIP). MGUS was significantly more prevalent in Black participants and participants with familial hematologic malignancy (HM) history than in White participants with no family history of HM. To begin to delineate mechanisms by which these early MGIP clones progress to MGUS and further lead to MM, we plan to explore the host intrinsic (age, race, germline risk factors) and acquired (inflammation, antigenic activation) risk factors on the expanding clone and its environment that influence its behavior. We believe the next frontier in MM research is to understand how one develops myeloma and treat it early before end-organ damage. Identifying and preventing the development of the earliest stages of MM will lead to transformative approaches to treatment and serve as a paragon of cancer prevention. We hypothesize that defining risk as ancestry scores and genomic signatures, instead of defining risk by self-identified race, can improve risk prediction for MM. Similarly, instead of using chronological age as a risk factor for MM, we will test the hypothesis that the effective age of the bone marrow niche confers biological risk of developing MM. Together, we believe that these studies will help define the mechanistic underpinnings of the carcinogenic process linked to MM. This approach will allow the field to transition from a purely demographic definition of risk to a biological one.