Molecular Classification and Risk Stratification

Abstract

Studies over the past decade have greatly improved our understanding of the molecular basis of multiple myeloma and mechanisms of disease progression. Initial studies in myeloma, as with other hematological malignancies, depended solely on metaphase cytogenetics [1–5]. While this methodology was critical in the early studies of the disease, less than a third of the patients had bone marrow cytogenetic studies that were informative, primarily a reflection of the low proliferative state of the malignant plasma cells [6–8]. This was followed by the development of interphase FISH (fluorescent in situ hybridization), which did not depend on dividing cells for detection of abnormalities [9, 10]. With universal adoption of FISH studies, it became clear that nearly all patients with myeloma had genetic abnormalities that could be detected using FISH [11, 12]. Further refinement of the FISH techniques allowed simultaneous detection of the plasma cells, either by using markers for plasma cells or by performing FISH testing on sorted plasma cells, thus ensuring that the abnormality detected was unique to the plasma cells. Development of high-density oligonucleotide arrays allowed assessment of gene expression in tumor cells, and development of this technology provided an unprecedented look into the plasma cell biology, and better appreciation of the genetic heterogeneity that is the hallmark of this disease [13–18]. More recently, cutting edge genomic techniques including RNA sequencing, array CGH, SNP arrays, and whole genome sequencing have all been applied to myeloma allowing us to dissect the molecular complexity of this disease. A better appreciation of the heterogeneity uncovered by these assays have in turn led to several attempts at classifying the disease into groups that have implications on the disease outcome as well as best decisions regarding the best treatment approaches [19].