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In The Clinic

Multiple Approaches to Myeloma

A native of Sweden, Ola Landgren, M.D., Ph.D., trained as a hematologist at the Karolinska Institute in Stockholm, where he also took advantage of the strong medical database resources in Scandinavia to study cancer at a population level. Initially intending to spend only two years at NCI, Landgren opted to remain as an Investigator in the Medical Oncology Branch of CCR because of the unique opportunities to take his observational findings back into the clinic and address his longstanding interest in multiple myeloma. His recent finding that multiple myeloma is consistently preceded by an asymptomatic precursor state—known by the acronym MGUS—has opened a unique window of opportunity for studying the progression of this fatal disease.

Multiple myeloma is a cancer that affects plasma cells in the bone marrow. These cells normally play a critical role in adaptive immunity by producing the antibodies that target infection and disease. In multiple myeloma, genetically aberrant plasma cells proliferate and produce excess antibody or antibody fragments, which show up clinically as M proteins (monoclonal gamma-globulins) in blood and sometimes urine.

In otherwise healthy individuals, normal plasma cells constitute less than five percent of the cells in healthy bone marrow. However, in multiple myeloma patients, abnormal plasma cells typically account for 10 percent or more of all cells. These cells can also circulate in the bloodstream and accumulate in bone marrow at sites far removed from the original source of the aberrant cells. Thisabnormal accumulation eventually results in damage to the bones and surrounding tissue, and the term “multiple myeloma” comes from the scattered bone lesions that are observed in later stages of the disease. Resulting damage eventually includes kidney failure, recurrent infections, abnormally high calcium levels in the blood, and anemia. At this time, it remains incurable.

Catching it Early

In cancer, early diagnosis is quite often the difference between life and death. Catching cancer before it starts, of course, is the best possible situation. However, in most cases, by the time patients come to our attention clinically, the cancer is well rooted in the body.

In the case of multiple myeloma, we know that there is a related condition called monoclonal gammopathy of unknown significance (MGUS). The name comes from the M proteins that are found in the serum in the absence of any disease pathology. In fact, MGUS is present in approximately three percent of the general population above the age of 50. There are no symptoms associated with MGUS—it is usually diagnosed when abnormal M-protein levels turn up during diagnostic tests performed for other reasons (see "The Doctor-Patient Relationship," page 32). We also know that for people with MGUS, the risk of developing multiple myeloma is significantly increased relative to the general population.

In cancer, early diagnosis is quite often the difference between life and death.

From the time I was working in Sweden, I have been fascinated by the existence of this precursor disease with a high risk of transformation. Using the unique population-based medical history databases that exist as part of universal health care in Scandinavia, we were able to identify over 4,000 MGUS patients and over 14,000 first-degree relatives of these patients. Equally important, we were also able to identify individuals and their relatives that were well matched to our patient population in important characteristics to serve as controls. In that study, which we published last year in the journal Blood, we found that MGUS is about three times as common in families as compared to controls, which indicated to us that susceptibility genes and/or shared environmental influences are involved in the disorder. We have since shown that the risk of these diseases varies in different populations.

In fact, although the link between MGUS and multiple myeloma has been known for some time, it has never been established whether MGUS is a required stage in the development of multiple myeloma or just one of many paths to the disease. From the beautiful work of John Shaughnessy’s laboratory at the University of Arkansas, we know, for example, that multiple myeloma is at least seven molecularly distinct disease subtypes and that some of these entities are relatively more indolent or aggressive. And we’ve done some preliminary work that indicates that, on average, African Americans have a better prognosis than Caucasians, which seems to be a reflection of the fact that they are more prone to the more indolent subtypes of multiple myeloma.

We were able to look at the relationship between MGUS and multiple myeloma longitudinally using an extraordinary NCI resource: the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial that has charted the cancer histories of over 77,000 participants since its inception in 1992. These individuals, who were all cancer-free at the beginning of the trial, had blood work done every year for up to six years and have been followed for up to 10 years. From this trial, we identified 71 individuals who developed multiple myeloma over the course of the study and went back to the freezer to examine each of their blood samples. In 100 percent of cases, we found MGUS abnormalities prior to the multiple myeloma diagnosis.

Tracking The Transformation

Although a simple finding, this unyielding relationship between multiple myeloma and MGUS has enormous implications. Suddenly, we have a population that we can hone in on and state with confidence that all cases of multiple myeloma will arise from it. Another key finding in our PLCO-based study is the fact that about 50 percent of the MGUS patients had a steady increase in M-protein levels prior to the development of multiple myeloma, while the other 50 percent had a stable M protein and yet they developed myeloma. Thus, a stable M-protein level over time is not a reliable marker to rule out multiple myeloma progression. There is no doubt we need better markers.

This unyielding relationship between multiple myeloma and MGUS has enormous implications.

We are taking several parallel approaches to address the need for better predictors of progression. For example, using stored blood samples of patients with MGUS and multiple myeloma, we are screening for biomarkers that signal progression. Also, newer imaging methods may give us insights into the course of the disease. We are currently developing a protocol that will take advantage of contrast agents to enhance imaging by positron emission tomography/ computed tomography (PET/CT) and magnetic resonance (MR). Using these techniques, we will study patients with MGUS and newly diagnosed multiple myeloma in order to establish better clinical markers of progression. In this study, we will correlate our imaging results with traditional skeletal surveys and with several molecular biomarkers.

We have also just opened the first natural history study of myeloma precursor disease here at the NIH Clinical Center and we are actively seeking patients for this important study. We are enrolling people with MGUS and smoldering multiple myeloma (SMM) and following them for up to five years. SMM is a high-risk precursor disease defined based on higher levels of M protein (>3 g/dL) or higher levels of plasma cells in the bone marrow (10 percent or more), or a combination. We will collect blood, bone marrow, and urine samples at multiple time points. The aim is to define molecular signatures for progressors versus non-progressors. At the moment, we don’t have any molecular markers that definitively distinguish between MGUS, SMM and multiple myeloma— the diagnoses are based on clinical criteria.

Of course, we want to be able to identify the patients with MGUS that will go on to develop multiple myeloma. If you are diagnosed at the age of 40 and you live to the age of 90, that’s 50 years of living with a one percent risk of transformation per year. For such an individual, the lifetime risk of developing multiple myeloma is 50 percent—essentially the same as flipping a coin. We need to identify the molecular signals that will allow us to predict individual risk scores with much greater accuracy.