MMRF Answer Fund: How CoMMpass data is helping define high-risk disease

Recent advances in multiple myeloma treatment have led to improvements in survival, but the success has not been uniform. Some patients enjoy many years in clinical remission; others relapse or die within 2 years. Why do some patients do poorly? The MMRF Answer Fund hopes to answer this critical question. The Answer Fund supports clinical research that uses genetic data collected from myeloma patients in the groundbreaking MMRF CoMMpass study to gain a better understanding of the genetic drivers of high-risk myeloma—that is, patients who do not enjoy long-term clinical remission.

One of the projects that the Answer Fund has supported is the research of Dr. Lawrence Boise, Dr. Benjamin Barwick, and their colleagues at the Winship Cancer Institute at Emory University in Atlanta, Georgia. The team analyzed genetic samples from 826 newly diagnosed myeloma patients from the CoMMpass study to identify any genetic factors that contribute to poor outcomes. The researchers found that a certain genetic abnormality—called chromosomal translocation (that is, when segments of two chromosomes switch positions)—occurs frequently in myeloma patients. Indeed, translocations between chromosomes 4 and 14—noted as t(4;14)—and others like t(11;14) are examples of common myeloma translocations.  

Based on Dr. Boise’s and Dr. Barwick’s research, a new, distinct translocation was identified in about 10% of patients and found to be associated with poor survival. This finding is significant, because this specific translocation—called t(IgL)—tends to occur in what had previously been considered a subset of patients who live longer than those considered high risk—this subset of patients is referred to as hyperdiploid (which means that their myeloma cells tend to have more chromosomes than normal cells). As revealed by this new finding, patients with t(IgL) represent a high-risk group.

Currently, testing for chromosomal hyperdiploidy is part of routine clinical evaluation, but testing for t(IgL) is not. In the absence of a test for this newly identified risk indicator, patients may have been determined to be at a lesser risk of poor outcomes (for example, relapse or death within 2 years) than they really were. The ability to identify patients with t(IgL) is important, because further research by the team at Winship showed that patients with t(IgL) do not benefit from treatment with immunomodulatory drugs (such as Revlimid).

Ultimately, these observations would not have been possible if not for the data collected from the large-scale CoMMpass study. These results open the door to the possibility of using t(IgL) as a marker of high-risk disease and poor prognosis. Research is ongoing into strategies for more quickly identifying patients with t(IgL) and for identifying treatments that these patients are more likely to respond to.

Additional Resources

Barwick BG, Neri P, Bahlis N, et al. Immunoglobulin lambda translocations identify poor outcome and IMiD Resistance in multiple myeloma and co-occur with hyperdiploidy. Blood. 2018;132: Abstract 405.

MMRF. Answer Fund.

MMRF. ASH 2018 Day 2 – CoMMpass oral presentations.