The Hematologist

September-October 2019, Volume 16, Issue 5

IgL Translocations for Risk Stratification in Multiple Myeloma

Ankit K. Dutta, PhD Postdoctoral Research Fellow, Department of Medical Oncology
Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
Elizabeth D. Lightbody, PhD Postdoctoral Research Fellow, Department of Medical Oncology
Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
Romanos Sklavenitis Pistofidis, MD Postdoctoral Fellow, Department of Medical Oncology
Dana-Farber Cancer Institute/Harvard Medical School, Boston, MA
Irene M. Ghobrial, MD Associate Professor of Medicine
Harvard Medical School; Dana Farber Cancer Institute, Boston, MA

Published on: August 06, 2019

Barwick BG, Neri P, Bahlis NJ, et al. Multiple myeloma immunoglobulin lambda translocations portend poor prognosis. Nat Commun. 2019;10:1911.

Multiple myeloma (MM) is a rare hematologic malignancy characterized by the clonal expansion of aberrant plasma cells within the bone marrow. MM is characterized by widespread intratumor heterogeneity and clonal evolution, which is believed to be the main confounder of durable clinical responses (CRs). This is especially so in the high-risk subset of patients with MM, who are defined by an overall survival (OS) of two years or less despite the use of novel treatments.1

Next-generation sequencing (NGS) analyses of MM and its precursor stages of monoclonal gammopathy of undetermined significance (MGUS) and smoldering MM (SMM), have led to a profound understanding of the underlying disease biology and clonal evolution patterns in MM.2-9 Currently, the consensus for the classification of newly diagnosed MM (NDMM) includes molecular cytogenetics to risk stratify patients into high-risk (deletion of chromosome 17p, t[14;16], and t[14;20]), intermediate-risk (t[4;14], deletion of chromosome 13, and hypodiploidy), and standard-risk (t[11;14], t[6;14], and hyperdiploidy) groups.10,11 Notably, due to the nature of clonal evolution, in which subclonal populations continually evolve under selective pressures, a patient may acquire abnormalities in a subclonal branch during the continuum of disease that was not initially present at diagnosis. Therefore, current classification methods at diagnosis may not identify true risk status with the same degree of accuracy as genetic-based biomarkers. Indeed, large cohorts of patients with NDMM are important for the statistical power needed to identify both frequent and rare genomic abnormalities. This recognition underlies the Multiple Myeloma Research Foundation’s (MMRF’s) Clinical Outcomes in Multiple Myeloma to Personal Assessment (CoMMpass) study (ClinicalTrials.gov identifier: NCT01454297), which aims to collect samples from more than 1,000 patients with NDMM (currently 1,154 patients from 90 sites worldwide) and track their clinical and genomic characteristics to establish molecular-based subgroups of MM to improve clinical outcomes for the patient population.

As part of the MMRF CoMMpass study, a recent investigation by Dr. Benjamin G. Barwick and colleagues revealed novel insight into a previously unrecognized genomic biomarker of high-risk MM, in which patients are characterized by translocation of the immunoglobulin λ (t[IgL]) light chain locus. Dr. Barwick’s team performed long-insert whole-genome sequencing analyses on a large cohort of patients with NDMM (n = 795). While they observed common translocations of the immunoglobulin heavy chain region with partner oncogenes, such as t(4;14), t(11;14), and t(14;16), they were not predictive of patient prognosis. Notably however, patients harboring t(IgL) accounted for approximately 10 percent of NDMM patients (n = 78/795) and were associated with poor progression-free survival (PFS), OS, and CR. While most IgL translocations occurred throughout the genome and were rare, IgL-MYC translocation was the most prevalent, accounting for 41 percent of patients (n= 32 of 78). Interestingly, IgL translocations were found to be subclonal and were associated with hyperdiploidy, which is remarkable as hyperdiploidy is a prognostic marker associated with standard risk. However, patients harboring t(IgL) were found to have significantly worse PFS and OS rates, independent of hyperdiploidy. Moreover, RNA sequencing was performed on a subset of patients (n = 629) to determine if t(IgL) patients show an underlying gene expression signature or associated with MM subtypes; however, no specific relationship was found. Patients with an IgL translocation were observed to have poor CR to immunomodulatory drug (IMiDs) treatment. To investigate the underlying mechanism, chromatin immunoprecipitation sequencing of Ikaros family zinc finger 1 (IKZF1), a lymphoid transcription factor in MM known to be degraded by the action of IMiDs, was performed on three MM cell lines: ARP-1 (expressing IgK), MM.1S (expressing IgL), and RPMI-8226 (expressing IgL and harboring t[IgL]). Indeed, IKZF1 was bound at high levels to enhancers in the IgL locus and not targeted for depletion by IMiD treatment, consequently conferring the poor CR reported. These data exemplify that infrequent genetic characteristics of MM can also be prognostic of patient survival and treatment outcomes.

Genomic studies continue to reinforce our understanding that MM is not one disease, but a collection of monoclonal gammopathies that share clinical symptoms. This study by Dr. Barwick and colleagues elegantly demonstrates how large patient cohort investigations can tease out critical infrequent genetic abnormalities. In this case, they demonstrated that translocation of the immunoglobulin gene does not merely enhance its partner gene expression, but impacts patient survival. This finding suggests that patients with MM may benefit from t(IgL) (mainly IgL-MYC) screening at diagnosis, as presenting standard-risk patients may actually be at higher risk with reduced CR to frontline IMiDs treatment such as lenalidomide. Continued efforts are underway to attain a comprehensive genomic understanding of MM, which will allow tumors to be diagnosed, risk stratified, and treated based on intrinsic genetic factors reflective of biological characteristics. Indeed, The MMRF has recently launched the Myeloma Developing Regimes Using Genomics (MyDRUG) master protocol clinical trial as a precision medicine initiative to determine approved and late-stage drugs in development that are untested in MM, which may be appropriate for high-risk patients with MM harboring actionable mutations.12 Additionally, it is important to not only gain an understanding of genetic characteristics, but also the role of noncoding, epigenetic, and tumor microenvironment changes that contribute to disease burden. Ultimately, a comprehensive understanding of MM will result in precision medicine approaches for early intervention and treatment strategies for what we strive to someday be a curable disease.

References

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  2. Bolli N, Avet-Loiseau H, Wedge DC, et al. Heterogeneity of genomic evolution and mutational profiles in multiple myeloma. Nat Commun. 2014;5:2997.
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  9. Zhao S, Choi M, Heuck C, et al. Serial exome analysis of disease progression in premalignant gammopathies. Leukemia. 2014;28:1548-1552.
  10. Mikhael JR, Dingli D, Roy V, et al. Management of newly diagnosed symptomatic multiple myeloma: updated Mayo Stratification of Myeloma and Risk-Adapted Therapy (mSMART) consensus guidelines 2013. Mayo Clin Proc. 2013;88:360-376.
  11. Fonseca R, Bergsagel PL, Drach J, et al. International Myeloma Working Group molecular classification of multiple myeloma: spotlight review. Leukemia. 2009;23:2210-2221.
  12. Auclair D, Lonial S, Anderson KC, et al. Precision medicine in multiple myeloma: are we there yet?. Exp Review of Prec Med and Drug Dev. 2019;4:51-53.

Conflict of Interests

Dr. Dutta, Dr. Lightbody, Dr. Sklavenitis-Pistofidis, and Dr. Ghobrial indicated no relevant conflicts of interest. back to top