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BioMed Research International
Volume 2014 (2014), Article ID 232546, 12 pages
http://dx.doi.org/10.1155/2014/232546
Review Article

Implications of Heterogeneity in Multiple Myeloma

1Department of Haematology-Oncology, National University Cancer Institute of Singapore, Singapore
2Cancer Science Institute of Singapore, National University of Singapore, Singapore
3National University Health System, NUHS Tower Block, Level 7, 1E Lower Kent Ridge Road, Singapore 119228

Received 27 March 2014; Accepted 2 May 2014; Published 2 July 2014

Academic Editor: Dong Soon Lee

Copyright © 2014 Sanjay de Mel et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Multiple myeloma is the second most common hematologic malignancy in the world. Despite improvement in outcome, the disease is still incurable for most patients. However, not all myeloma are the same. With the same treatment, some patients can have very long survival whereas others can have very short survival. This suggests that there is underlying heterogeneity in myeloma. Studies over the years have revealed multiple layers of heterogeneity. First, clinical parameters such as age and tumor burden could significantly affect outcome. At the genetic level, there are also significant heterogeneity ranging for chromosome numbers, genetic translocations, and genetic mutations. At the clonal level, there appears to be significant clonal heterogeneity with multiple clones coexisting in the same patient. At the cell differentiation level, there appears to be a hierarchy of clonally related cells that have different clonogenic potential and sensitivity to therapies. These levels of complexities present challenges in terms of treatment and prognostication as well as monitoring of treatment. However, if we can clearly delineate and dissect this heterogeneity, we may also be presented with unique opportunities for precision and personalized treatment of myeloma. Some proof of concepts of such approaches has been demonstrated.