Blood, 1 March 2002, Vol. 99, No. 5, pp. 1504-1504
Defining the genetic chaos in myeloma
Progress in understanding the malignant transformations that
occur in multiple myeloma (MM) plasma cells has been slow, largely due
to the significant heterogeneity of genetic and signaling abnormalities, which include extensive chromosomal abnormalities, gene
mutations, and deregulated proliferative and apoptotic
pathways
indeed, a genetic chaos. Moreover, it remains a major
controversy to identify the clonal precursor(s) of the malignant plasma
cell. Current prognostic markers have been inadequate to accurately
define disease progression, therapeutic response, and clinical outcome.
Dr John Shaughnessy and colleagues (page 1745) are first off the block to assemble a high-density microarray of MM plasma cells and to demonstrate that the MM plasma cells are distinctly different than
normal plasma cells. In the work presented by Zhan and colleagues, purified plasma cells from 74 newly diagnosed patients and 31 healthy donors were examined for expression of 5 483 genes contained on the Affymetrix HuGeneFL GeneChip. Although the HuGeneFL GeneChip is
an early chip design that has been replaced by more extensive and
refined gene probe sets, the data presented provide a compelling new
definition of MM subgroups and identify a number of new genes as
potential therapeutic targets. Hierarchical clustering of plasma cell
gene expression demonstrated 4 distinct genetic subgroups. Using links
to clinical databases for the patients, the genetic profiles were
correlated with clinical outcomes. Many of the genes that distinguish
the malignant plasma cell from normal plasma cells were not surprising,
though these expectations solidify the validity of the results. The
most significant gene expression changes differentiating the MM1 (which
included the benign PC dyscrasia, MGUS) and MM4 subgroups code for
activities that implicate MM4 as having a more proliferative phenotype
and show close similarities with a variety of MM cell lines
(validating use of cell line models, at least for the MM4 subgroup).
Beyond the clustering of gene expression, Zhan and colleagues
identified gene expression spikes in subsets, which reflect the genetic
heterogeneity, some of which correlate with genes known to be
deregulated by chromosomal translocations. This first written report
provides a snapshot of genetic abnormalities that may contribute to the
malignant MM phenotype, and additional data presented at the
recent ASH meeting have been extended to nearly 150 patients.
We certainly anticipate that ongoing efforts to use gene profiling to
identify classes of genes may provide a new framework for studying the
biology of the disease, mechanisms for its progression, and potential
therapeutic targets. And not withstanding the power of gene profiling,
protein and signaling profiles will add important components to fully
understand and treat this malignancy.
Brian Van Ness
University of Minnesota
