Leukemia (2009), 1­12
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SPOTLIGHT REVIEW
International Myeloma Working Group molecular classification of multiple myeloma:
spotlight review
R Fonseca1, PL Bergsagel1, J Drach2, J. Shaughnessy3, N Gutierrez4, K Stewart1, G Morgan5, B Van Ness6, M Chesi1, S Minvielle7,
A Neri8, B Barlogie3, WM Kuehl9, P Liebisch10, F Davies5, S Chen-Kiang11, BGM Durie12, R Carrasco13, Orhan Sezer14, Tony
Reiman15, Linda Pilarski16 and H Avet-Loiseau7
1Department of Hematology­Oncology, Mayo Clinic, Scottsdale, AZ, USA; 2Clinical Division of Oncology, Department of
Medicine, University Hospital Vienna, Vienna, Austria; 3Department of MIRT, University of Arkansas for Medical Sciences, MIRT,
Little Rock, AR, USA; 4Department of Hematology, Hospital Universitario de Salamanca, CIC, Salamanca, Spain; 5Institute of
Cancer Research, Royal Marsden Hospital, Sutton, UK; 6Department of Genetics, Institute of Human Genetics, University of
Minnesota, Minneapolis, MN, USA; 7Universite´ de Nantes; Institut de Biologie, Laboratoire d'Hematologie, Nantes, France;
8Servizio di Ematologia, Istituto di Scienze Mediche, Universita di Milano, Ospedale Maggiore, IRCCS, Milan, Italy; 9The Genetics
Branch, National Cancer Institute, Bethesda, MD, USA; 10Department of Internal Medicine III, University of Ulm, Ulm, Germany;
11Department of Pathology, Columbia University, Weill-Cornell Medical College, New York, NY, USA; 12Cedars-Sinai Outpatient
Cancer Center at the Samuel Oschin Comprehensive Cancer Institute, Los Angeles, CA, USA; 13Department of Medical Oncology/
Hematologic Neoplasia, Dana-Farber Cancer Institute, Harvard University, Boston, MA, USA; 14Department of Hem/Onc,
Universitatsklinikum Charite, Berlin, Germany; 15Dalhousie University Department of Oncology, Saint John Regional Hospital,
Halifax, Nova Scotia, Canada and 16Cross Cancer Institute, University of Alberta, Alberta, Edmontoin, Canada
Myeloma is a malignant proliferation of monoclonal plasma
Introduction
cells. Although morphologically similar, several subtypes of the
disease have been identified at the genetic and molecular level.
This paper is a first attempt at creating an international
These genetic subtypes are associated with unique clinico-
pathological features and dissimilar outcome. At the top
consensus classification of multiple myeloma (MM). Undoubt-
hierarchical level, myeloma can be divided into hyperdiploid
edly this paper will present a working classification for MM, and
and non-hyperdiploid subtypes. The latter is mainly composed
will be updated as additional information becomes available
of cases harboring IgH translocations, generally associated
regarding the underlying biological and genetic composition of
with more aggressive clinical features and shorter survival.
the disease. The goals of this paper are: (i) to provide a
The three main IgH translocations in myeloma are the
biological classification of MM based on known genetic
t(11;14)(q13;q32), t(4;14)(p16;q32) and t(14;16)(q32;q23). Triso-
mies and a more indolent form of the disease characterize
subtypes with associated clinicopathological associations; (ii)
hyperdiploid myeloma. A number of genetic progression
to establish the prognostic value of known and new genetic
factors have been identified including deletions of chromo-
factors for MM outcome, including the information generated
somes 13 and 17 and abnormalities of chromosome 1 (1p
through genomic tools; (iii) and lastly, to provide a framework
deletion and 1q amplification). Other key drivers of cell survival
for evaluation of new markers capable of serving as predictive
and proliferation have also been identified such as nuclear
for efficacy of novel therapeutics.
factor- B-activating mutations and other deregulation factors
for the cyclin-dependent pathways regulators. Further under-
Multiple myeloma is a clonal late B-cell disorder in which
standing of the biological subtypes of the disease has come
malignant plasma cells (PCs) expand and accumulate in the
from the application of novel techniques such as gene
bone marrow, leading to cytopenias, bone resorption and the
expression profiling and array-based comparative genomic
production (in most cases) of the characteristic monoclonal
hybridization. The combination of data arising from these
protein.1 MM is a heterogeneous disease with some patients
studies and that previously elucidated through other mechan-
dying within a few weeks of diagnosis, whereas others live for
isms allows for most myeloma cases to be classified under one
SPOTLIGHT
of several genetic subtypes. This paper proposes a framework
longer than 10 years. The reason for this heterogeneity is
for the classification of myeloma subtypes and provides
compound and involves interaction between host factors and
recommendations for genetic testing. This group proposes
features intrinsic to disease biology. It is increasingly evident
that genetic testing needs to be incorporated into daily clinical
that the underlying genetic features of the tumor cells largely
practice and also as an essential component of all ongoing and
dictate the clinical heterogeneity of MM. The advent of
future clinical trials.
interphase molecular cytogenetics and genomics has unraveled
Leukemia advance online publication, 1 October 2009; doi:10.1038/
leu.2009.174
a complexity hereto underappreciated for MM oncogenomics.
Keywords: multiple myeloma; genetics; cytogenetics; molecular;
Throughout this paper we will review current knowledge
prognosis; gene expression profiling
regarding the effect those factors have in determining the
likelihood of a better or worse outcome for patients with new
diagnosis MM (prognosis). However, the validity of most
prognostic factors has been tested predominantly in the new
diagnosis setting, and little validation exists for the same factors
Correspondence: Dr R Fonseca, Department of Haematology­Oncol-
in the case of relapsed and refractory disease. Moreover, the
ogy, Mayo Clinic Arizona, Collaborative Research Building, 3-006,
value of different prognostic factors possibly changes with
13400 East Shea Boulevard, Scottsdale, AR, 85259-5494, USA.
advancing stages of the disease (that is, first relapse versus
E-mail: fonseca.rafael@mayo.edu
second and subsequent relapses). Biological factors that can
Members of the IMWG are listed in the appendix.
predict outcome at diagnosis possibly will have much lessened
Received 12 March 2009; revised 10 June 2009; accepted 23 June
2009
effect when tested in patients receiving third-line chemotherapy.
IMWG molecular classification of MM
R Fonseca et al
2
For instance, although it is generally accepted that patients
This prognostic classification is essential for better under-
entered into clinical trials for relapsed/refractory disease carry
standing the composition of patients entered into clinical trials,
the worst outcome, this is generally not true if one estimates
and also allows, albeit with the usual statistical limitations, cross
survival since the time of diagnosis. Patients with the most dire
comparison of different clinical trial populations. Indirectly, this
host factors, or the most aggressive biological variants of MM,
prognostic classification can also provide relevance to new
will not live for long enough to be enrolled in these types of
biological factors proposed as significant in disease patho-
clinical trials. Lastly, it is important to stress that different stages
genesis (but, as will be shown below, biological factors that are
of clonal evolution can be categorized as all being `new
considered crucial in the pathogenesis do not need to
diagnosis MM.' Some patients with new diagnosis MM may be a
necessarily have prognostic associations).
slow progressive evolution from monoclonal gammopathy of
Although undoubtedly a large fraction of disease hetero-
undetermined significance (MGUS) (for example, evolving
geneity can be determined by the genetic subtypes of MM,2,3 an
anemia over several months), whereas others may be associated
important component in determining outcome is related to host
with features of high clonal aggressiveness (for example, PC
features. The contribution of these factors will not be discussed
leukemia
or
extramedullary
plasmacytomas)
(Figure
1).
Although both can be clinically categorized as `new diagnosis
MM' they clearly present two different biological states of
evolution of the monoclonal PCs.
Primary genetic factors
Translocations, hyperdiploidy, etc.
The purpose of this proposed classification is not merely to
SPOTLIGHT
provide prognostic estimates; the ability to accurately prognos-
Progression factors
ticate is one of the several features to be discussed here. There
p53 deletion, NF-B
may be subgroups of the disease that have no known or
demonstrable prognostic associations, but are perceived at the
a
bc
biological level to be unique. These associations, though
MGUS
New diagnosis MM
supporting unique biology, should not be considered prerequi-
site for creation of a biological subtype of the disease.
Intramedullary
Extramedullary
Conversely, there may be biological factors or gene expression
disease
progression
signatures capable of discerning prognosis, which may not yet
Time from disease initiation
be explained by unified biological concepts, but have the ability
to discern patients with clearly dissimilar outcomes. In this
Figure 1 Relationship between clonal evolution of plasma cells and
paper, we will not attempt to discuss all available prognostic
time of diagnosis. The picture depicts the biology and genetic
heterogeneity of patients with a clinical diagnosis of `new diagnosis
models for MM, but rather focus on the prognostic implications
myeloma.' In some cases (a) the situation involves a slow progression
of the genetic derangements of MM and discuss the power of
from MGUS with gradual development of mild anemia, incipient
genomics to unravel the prognostic subcategories of the disease.
evidence of bone disease and slowly emerging need for treatment. In
There are many reasons why an accurate prognostic
some other individuals (b) myeloma presents with frank clinical
determination is paramount for clinical practice and research
features of aggressive disease (for example, bone lesions, anemia and
(Table 1). It allows the physician to engage in a more direct
other). Furthermore, in some individuals (c) the disease presents with
very aggressive features, including extramedullary disease, multiple
discussion with the patient regarding disease threat and
plasmacytomas and other complicating features. In these three
likelihood of survival. This risk stratification also allows for a
scenarios the clinical diagnosis is of `new diagnosis myeloma', yet
more rational selection and sequencing of therapy approaches.
the biological and genetic features are quiet different.
Table 1
FISH markers and association with outcome for patients with MM
Level
FISH tests
Testing
Validation
frequency
Minimal proposed testing (essential testing)
Established markers
t(4;14)(p16;q32)
Once
Validated by several studies
t(14;16)(q32;q23)
Once
17p13
May be repeated
Expanded panel
Markers with modest
Hyperdiploidy
Once
Weak effects when used
effects
alone. The first two may
portend a more favorable
outcome
t(11;14)(q13;q32)
Once
Chromosome 13
May be repeated
Other
Other translocations
Once
Rare events and not
routinely tested
Chromosome 1
1q amplification
May be repeated
Although conflicting studies
seem to predict outcome
1p deletion
aCGH derived
12p deletion
markers
5q amplification
May be repeated
Data not validated yet
Abbreviations: FISH, fluorescent in situ hybridization; MM, multiple myeloma.
Leukemia
IMWG molecular classification of MM
R Fonseca et al
3
here further, but some general considerations apply. For
Table 2
Emerging genetic tests: clinical and research recommen-
instance, genetics alone cannot fully explain outcome hetero-
dations
geneity and it is likely that host factors, such as performance
status, comorbidities (for example, renal function) and age, have
Level
FISH tests
Testing frequency
a predominant role in the prognosis determination in the
immediate period after diagnosis.2,3 It has been recently shown
Established
Minimal FISH panel (clinic)
Once (baseline)
markers
that, despite being enriched for higher-risk genetic subtypes,
GEP
May be repeated
younger patients live longer, presumptively as a consequence of
their ability to better tolerate treatment.4 With passage of time it
Suggested tests
aCGH/SNP
Once
is also likely that progression (also called secondary events) have
Predictive markers
Once
important roles in determining the fate of patients.
Serial GEP
Repeated
Abbreviations: FISH, fluorescent in situ hybridization; SNP, single
nucleotide polymorphism.
Classification of MM
Multiple myeloma is not one disease but rather many, with each
the prognostic significance of t(4;14)(p16;q32) may be amelio-
one of the subtypes largely defined by the specific genetic and
rated or eliminated in patients treated with bortezomib-
cytogenetic aberrations.2,3,5­7 These groups can now be
based combinations.13,14 It is also postulated that refinements
considered unique entities and unlikely to lose their classifica-
of classifications beyond those carried out merely by t(4;14)
tion status over time. Linked to these groups are others that may
(p16;q32) using other genomic tools gene expression profiling
depict only a small fraction of cases, and for whom there is no
(GEP) (Tables 3 and 4) or clinical parameters (for example,
known prognostic implications. These subgroups will be shown
b2-microglobulin) may modulate the prognostic significance of
in association with the larger ones, but highlighted as still under
the abnormality.6,15 These considerations will be discussed in
study and subject to further classification. As we have previously
greater detail under the t(4;14)(p16;q32) heading.
proposed, classifications can be proposed at three levels.
Predictive classification
Biological genetic classification
Accurate predictive classifications for MM do not yet exist and
This classification scheme is mostly driven by biology-based
will not be discussed in further detail in this paper. Although
considerations. Usually, the groups created will have unique
dissimilar outcomes can be associated with the utilization of
clinical and prognostic implications, but this is not a prerequi-
some of the aforementioned, a predictive factor should be able
site. Classic examples of this include the hyperdiploid versus
to discriminate with great accuracy the clinical benefit of a
non-hyperdiploid classification, specific chromosome transloca-
specific therapy intervention. The value of such factors should
tions, and so on.8­10 Assuming that no changes in the etiology of
be such that it allows selection and elimination of therapies for
the disease occur over time, similar proportion of patients with
subgroups of patients. For instance, if we had an effective
the different subtypes will be diagnosed in future years. Ethnicity
inhibitor of a cyclin D gene that only worked against a certain
or age may result in different prevalence of these primary
subtype of the disease (those expressing this cyclin D gene), the
genetic subtypes, but for the most part the distributions within
predictive marker would be clearly useful. The treatment would
one of those groups should remain similar. This classification
only be given to patients with this abnormality and not to those
can be considered as enduring, as the biological basis for its
without it, perhaps even if no other treatments were available.
classification will be more stable and less likely to evolve. The
Another situation may arise in which subsets of MM cases
subgroups will be defined primordially by a primary genetic
(coming from the many genetic subtypes) depend on a specific
abnormality that will be associated with a constellation of other
growth factor (for example, interleukin-6 or hepatocyte growth
genetic changes associated with clone progression and evolu-
factor) and for which a specific intervention may be beneficial
tion. The ultimate application of a predictive classification
(but not for cases without these abnormalities). Interestingly, the
would be on the basis of the development of targeted therapies
presence or lack of dependency on these growth factors could
SPOTLIGHT
against these primary genetic changes, such as is possible for
confer no specific prognostic associations and not be dictated by
bcr-abl inhibition of chronic myeloid leukemia cells with
the major biological or prognostic classification, and yet be a
imatinib. Such therapies do not yet exist for MM.
very useful predictive classifier.
Although most therapeutics available against MM target
specific vulnerabilities of the cells, most are not based on the
Prognostic classification
targeting of specific genetic markers of subsets of the disease, or
A prognostics classification incorporates classifiers capable of
targeting abnormal pathways in subsets of patients. When such
discriminating outcome of patients, and usually, albeit with
therapies become available the emergence of correct prediction
dissimilar penetrance, in groups of patients treated with multiple
will be paramount for proper selection of treatments. A classic
treatment modalities3,6,7 (Table 2). In addition, factors capable
example would be the use of endocrine-based therapies for
of serving as prognostic determinants will usually be associated
receptor-positive breast cancer or the use of trastuzomab against
with baseline clinicopathological features of disease aggressive-
HER-2-neu breast cancer. Some clinical trials in MM are
ness (such as high b2-microglobulin, high proliferation rates,
underway or have been completed using therapies that target
extramedullary disease, hypercalcemia, elevated lactate dehy-
specific pathways known to be activated by identifiable genetic
drogenase and so forth). As an example, the t(4;14)(p16;q32)
derangements. The first example was the phase 1 trial of TKI-
has always been associated with more aggressive disease at
258, an fibroblast growth factor 3 (FGFR3) inhibitor.16 If such
baseline, and in the series of patients treated with conven-
therapy would become of clinical use, then it would most likely
tional or high-dose chemotherapy, it discerns patients with
be indicated only for cases of t(4;14)(p16;q32) MM. The parallel
shortened survival.3,6,7,11,12 Recently it has been shown that
development of biomarkers capable of enriching groups of
Leukemia
IMWG molecular classification of MM
R Fonseca et al
4
Table 3
Comparison between TC and UAMS GEP-derived classification (major subtypes)
Group
TC
UAMS
Categories associated with a defined genetic lesion
Cyclin D translocation
11q13 CCND1 (15%)
CD-1
6p21 CCND3 (2%)
CD-2
12p13 CCND2 (o1%)
MMSET translocation
4p16 (15%)
MS
Three quarters express FGFR3
MAF translocation
16q23 C-maf (5%)
MF
Shared gene expression profile with
expression of ITGB7
20q11 MAFB (2%)
8q24 MAFA (o1%)
Hyperdiploid
D1 (30%)
HY
D1+D2 presumed to be progression
from D1
D1+D2 (8%)
RB deletion
None (2%)
SPOTLIGHT
Abbreviations: ITGB, integrin beta; RB, retinoblastoma; MAFA and MAFB, masculo aponeurotic fibrosarcoma, UAMS, University of Arkansas for
Medical Science.
Adapted from Chng et al.86
Table 4
Concordance between TC and UAMS GEP-derived
lines of treatment, it may be that predictive schemes may help in
classification
selecting the sequence of treatments to be administered, more
than providing data to make decisions about the use (or not) of a
Subtypes 4p16 MAF 6p21 11q13 D1 D1+D2 D2 None
All
specific therapy. For example, if a marker shows that certain
cases
subsets of patients have a likelihood of response to bortezomib
of only 15%, although those without the marker have a response
MS
68
68
MF
37
37
rate of 70%, should we withhold therapy for those in the former
CD-1
2
22
2
1
27
group if no other options exist? Probably not, and thus one may
CD-2
1
3
50
4
1
2
61
only want to use either bortezomib as the last option or as part of
HY
1
1
106
5
2
1
116
a combination that can elicit added value to early introduction
LB
1
1
8
8
39
1
58
of bortezomib. Furthermore, the predictive value will be specific
PR
6
2
4
10
9
13
3
47
to the treatments as used in the clinic, distinguishing the use of
All cases
74
40
7
78
130
23
57
5
414
single agents versus those same agents in combination.
Abbreviation: UAMS, University of Arkansas for Medical Science.
Clinically, it is well known that a patient who has failed an
Adapted from Chng et al.86
Immunomodulatory drug (IMiD) and who has also failed
treatment with bortezomib may respond to both when given
patients likely to have higher clinical benefit would be
in combination.
beneficial.
Currently available therapies for MM are not thought
to be targeted therapies and thus used in all suitable candidates.
Biological genetic classification
Yet only a fraction of cases exhibit responses to single
agents, suggesting that subgroups of MM may be more
Primary genetic events
or less responsive to specific therapies. The group from the
A biological classification of MM is unlikely to change
University of Arkansas has been developing assays, using
dramatically, given the current knowledge of disease patho-
GEP, to predict patients who are likely to derive benefit
genesis19 (Tables 3 and 4).
from bortezomib early in the course of therapy, and are able
to identify patterns associated with disease responsiveness
(after drug administration).17 In another example, our group
Hyperdiploid and nh-MM
has made the first observation that patients with relapsed and
Overall MM is broadly divided at the top level into two major
regractory (RR) MM with non-canonical nuclear factor kappa B
categories, hyperdiploid MM (h-MM) (harboring numerous
(NF-kB) activation seem to have heightened susceptibility to
chromosomal trisomies and a low prevalence of IgH transloca-
bortezomib treatment (before drug administration).18 Although
tions) and non-hyperdiploid MM (nh-MM) (encompassing
this observation is preliminary and needs validation, it also
hypodiploid, pseudodiploid and near tetraploid MM, and highly
suggests that the identification of patients likely to benefit from
enriched for IgH translocations).8,9,20 The dichotomy has been
bortezomib is possible. A minority of cases exhibits long-lasting
validated in multiple series and is observed when patients are
disease control and remission with minimal toxicity. The
studied through karyotypes, interphase fluorescent in situ
identification of this subset of the disease should be a top
hybridization (FISH) or other genomic tools. The ploidy
priority of ongoing research, given the long duration of clinical
categories are stable over time such that patients with h-MM
benefit for patients who still have many other treatment options
will usually remain hyperdiploid over the course of the
available in the future, including HDT and bortezomib.
disease.21 The dichotomy into hyperdiploidy has not been
Lastly, the difficulty in creating clinical applications of
documented by at least two groups at the stage of MGUS,
predictive factors in MM is likely to be challenging, unless the
indicating that two fundamentally different pathogenesis path-
observations are so absolute that they clearly show no or
ways exist for MM, h-MM and nh-MM.22,23 It should be noted
minimal likelihood of response to a specific treatment. Given
that although hyperdiploidy is mainly a feature of h-MM, and is
that many MM patients will commonly receive three or more
predominant in cases with multiple trisomies and no IgH
Leukemia
IMWG molecular classification of MM
R Fonseca et al
5
translocations, cases with primary IgH translocations and
chromosome 14 associated with the loss of FGFR3 expression
hyperdiploidy do exist (and are presumed to have an unfavor-
11. Of immediate clinical application was the observation that
able outcome). It is notable that the majority of the human MM
patients with t(4;14)(p16;q32) have short-remission duration
cell lines (HMCLs) belong to the nh-MM and just data emerging
after high-dose chemotherapy with stem cell support.6,12,33,34 In
regarding the description of h-MM cell lines.24
some series, the median time to relapse is as short as 8 months
The broad classification of the disease does not have major
after one high-dose therapy treatment, with patients becoming
implications at the clinical level. However, patients with h-MM
refractory to alkylators and steroids.6,12,33,34 Owing to this
have a tendency towards a more favorable outcome and more
unmet medical need, new treatments that specifically target the
commonly are elderly individuals, slightly more common
translocations have been developed. One such compound is
among males, and have a higher incidence of MM bone
TKI-258, a small molecule inhibitor of FGFR3 with in vitro and
disease. A recent genomic-based classification derived from
xenograft animal model activity against t(4;14)(p16;q32)
array based comparative genomic hybridization (aCGH) identi-
HMCLs.16,35 Studies are ongoing to evaluate the clinical worth
fied this dichotomy and further subclassified h-MM and nh-MM
of this compound. More recently, the prognostic value of the
as the major branches of the disease.10 In addition, albeit with a
translocation has been challenged in series of patients treated
small group of patients studied, the authors subdivided h-MM
with bortezomib.14 In one study of patients treated with
into those with chromosome 13 deletion and chromosome 1
bortezomib, melphalan and prednisone, the translocation did
abnormalities and those without them. Patients with h-MM and
not discriminate outcome among newly diagnosed cases,
chromosome 13 deletions had a reported shorter survival.10 In
although the numbers are still small to reach definitive
another larger series, the prognostic significance of chromosome
conclusions.14 Some of the clincopathological features asso-
13 among h-MM was not apparent. More recently, the French
ciated with the translocation include association with the use of
group IFM did show that most of the prognostic value of h-MM
IgA heavy chains, l-light chain usage and a very high
was related to the gain of chromosome 5.25 Within the h-MM,
prevalence of chromosome 13 abnormalities (deletions/monos-
GEP can identify four recurrent groups associated with an
omy).6,7,11,36,37 Although the t(4;14)(p16;q32) is also observed
NF-kB/anti-apoptosis signature, an interleukin-6/HGF signature,
in the premalignant stages of the disease, it seems to be less
a cancer testis antigen signature and `other'.26 This classification
common in patients with MGUS and present more frequently in
has been validated in three separate cohorts of patients, and in
patients with smoldering multiple myeloma (SMM).38,39
one tested it discriminates patients with a shorter survival.
t(14;16)(q32;q23), other maf translocations, and 16q
t(11;14)(q13;q32) and CCND3 translocations
abnormalities
Of all MM, 15% harbor t(11;14)(q13;q32), with consequent
Translocations involving maf genes have been described in
upregulation of cyclin D1. MM with t(11;14) is associated with
5­7% of all MM cases. These translocations arise from IgH
CD20 expression, lymphoplasmacytic morphology, hyposecre-
rearrangements involving a fragile site in chromosome 16. These
tory disease and l-light chain usage.27,28 The majority of all
translocations have also been associated with a higher
cases of IgM MM have been reported by one series to have
frequency of chromosome 13 deletion, IgA isotype, and in at
t(11;14)(q13;q32) and one half of all cases of light chain
least two series, a more aggressive clinical outcome associated
amyloidosis harbor this same translocation. The translocation
with C-maf translocations.7 There are minimal data regarding
can be observed in MGUS, in which it results in nuclear cyclin
the clinical implications of other maf translocations, but they
D1 expression, and yet patients may remain stable without
would be predicted to have similar clinical outcomes as those of
disease progression for decades. Although these clinicopatho-
C-maf.
logical features are not unique to t(11;14)(q13;q32) MM, the
entity seems unique, even when it is neutral with regard to
prognosis.6,29 In most series tested, t(11;14)(q13;q32) seem to be
Secondary genetic events
associated with a favorable outcome, but this effect is not strong
Tumor clone development is believed to be a consequence of a
enough to be statistically significant. The difficulty in establish-
multistep
process
that
accumulates
sequential
genetic
ing a favorable outcome for patients with t(11;14)(q13;q32) may
changes.19 It has not been well defined in MM what the specific
SPOTLIGHT
relate to heterogeneity within patients with this genetic
steps associated with disease progression are and what steps
aberration.
For
instance,
some
cases
of
MM
with
associate with the different cytogenetic subtypes. Some of the
t(11;14)(q13;q32) manifest with an aggressive phenotype such
genetic abnormalities that seem to reflect progression include
as plasma cell leukemia. The group from the University of
deletions at 17p13, chromosome 1 abnormalities (1p deletion
Arkansas for Medical Science (UAMS) has identified two distinct
and 1q amplification) and C-myc translocations. It is also likely
subsets of t(11;14)(q13;q32) with different outcomes reported
that some of the best prognostic markers will come from the
such that the global effect of t(11;14)(q13;q32) on prognosis
complete understanding of secondary (progression) events.
remains neutral.
Chromosome 13 deletion and monosomy
t(4;14)(p16;q32)
We have recently reexamined the role of chromosome 13 as a
Several
groups
have
shown
that
t(4;14)(p16;q32)
and
biological factor versus a surrogate marker of aggressive disease.
t(14;16)(q32;q23) are associated with poor survival, irrespective
The field of MM genetics was invigorated first by the observation
of the treatment modality.6,7 The t(4;14)(p16;q32) affects the
that cases with abnormal metaphase cytogenetics were asso-
most telomeric portion of chromosome 4 and is detectable only
ciated with a shortened survival, and later by the observation
by FISH or reverse transcriptase­PCR11,30­32. The consequence
that chromosome 13 deletions were also associated with a
of the translocation is increased expression of FGFR3 and
shorter survival.7,40­44 In the case of chromosome 13 abnorm-
multiple myelom SET domain (MMSET).31,32 The translocation
alities, they are detected in 50% of cases.45­48 Of all cases with
can be imbalanced with up to 25% losing the derivative
chromosome 13 abnormalities, 85% constitute monosomy,
Leukemia
IMWG molecular classification of MM
R Fonseca et al
6
whereas the remaining 15% are interstitial deletions.45­48 There
Although an initial search suggested that CKS1B might be the
is no known difference in effect for prognosis for deletions
responsible gene for this association, other studies have failed to
versus monosomy. The prognostic significance for chromosome
validate this notion.61 Two recent series have failed to confirm
13 likely emanates because of its close association with high-
the overriding negative prognostic association with chromo-
risk genetic features (for example, t(4;14)(p16;q32)).6,7,49,50
some 1 amplification detected by FISH.6,61 Although it is thus
Chromosome 13 deletion is not significant in discriminating
still unclear how chromosome 1 participates biologically in
prognosis for non-hyperdiploid patients50 and is not capable of
generating more aggressive clones, chromosome 1 abnormal-
distinguishing prognosis for hyperdiploid patients.51 Its prog-
ities continue to emerge as regions important in establishing the
nostic significance is thus now thought to be a surrogate of its
prognosis of patients.
association with nh-MM. Does that mean that chromosome 13
has no biological importance?50 More and more data suggest a
crucial role for chromosome 13 as prerequisite for clonal
NF-kB activation
expansion for tumors; nearly 90% of cases with t(4;14)(p16;q32)
We and others have recently shown that, through multiple
will harbor chromosome 13 deletion.45­48
primary genetic mechanisms, there is constitutive activation of
the NF-kB pathway in at least 50% of MM cases.18,62 This
Deletion of 17p13
activation is a consequence of inactivation of suppressors (by
either biallelic deletion of deletion/mutation combinations) or
The most important molecular cytogenetic factor for prognos-
by hyperactivity as a consequence of amplification or chromo-
SPOTLIGHT
tication is the deletion of 17p13 (the locus for the tumor-
some translocations. The summary of the effects of this (epistatic
suppressor gene, p53).6,7,52 In all series tested, 17p13 deletions
mutations) is readily detectable by gene expression profiling. All
confer a very negative effect on survival. We and others have
of these aberrations ultimately result in increased processing of
shown that patients with 17p13 deletions (mostly monoallelic)
substrate and consequent NFB nuclear hyperactivity. These
have an overall shorter survival, more aggressive disease, higher
genetic events have not been fully positioned in the process of
prevalence of extramedullary disease (such as plasmacytomas)
disease progression but likely are secondary genetic events as
and hypercalcemia.6,7,52 Deletions of 17p13 predict for a short
they transcend the primary genetic categories. One example of
duration of response after HDT and involvement of the central
prediction is our aforementioned recent observation of non-
nervous system.53,54 We have recently shown that extramedul-
canonical NF-kB activation in a subset of patients. We have
lary disease is likely a consequence of defective p53, as most
found that the likelihood of responsiveness to bortezomib and
cases of plasma cell leukemia (primary and secondary) have
sustainability of responses seem higher among patients who
abnormalities in the p53.55 In support of this we know that most,
have intrinsic activation of this pathway.18 In our study, those
if not all, HMCLs have p53 functional deficiency (M Kuehl,
with low level of TRAF3 gene expression had a much higher
personal communication). Our hypothesis is that PCs are indeed
likelihood of response to bortezomib (90%) as opposed to all
capable of surviving at extramedullary locations, but that they
others (30%).
will usually undergo apoptosis in the presence of an intact p53
response. In support of this hypothesis a confirmatory study
recently showed that p53 levels of gene expression are lower in
cases with monoallelic deletions and that introduction of p53
Ras mutation
back into the HMCLs induces apoptosis at high levels.56 Most
Other studies have shown an adverse outcome for patients with
studies have shown a negative effect on the prognosis for
K-ras mutations, but not with N-ras mutations.49,63­66 This is
patients with 17p13, something not even resolved by allogeneic
interesting as ras mutations cluster more among patients with
stem cell transplant.57 The overall complete remission (CR) rate
t(11;14)(q13;q32), and are likely important factors for disease
was 50%, with no differences between the genetic abnormalities
progression for this subtype.65,66
except for patients with del(17p13) who achieved less CR (7
versus 56%; P ¼ 0.001). For event-free survival, only age (hazard
ratio 2.8; P ¼ 0.01) and del(17p13) (hazard ratio: 2.05; P ¼ 0.03)
12p deletions
retained their negative prognostic value. It is worth commenting
In a recent single nucleotide polymorphism array study, the IFM
that chromosome 17 deletion is uncommon in MGUS.
did show that deletions of the short arm of chromosome 12
occurred in about 12% of the patients and was associated with
Chromosome 1 abnormalities
both a short event-free survival and short overall survival. The
size of the deletions was variable, but the minimal deleted
Chromosome 1 abnormalities have long been known to be
region was centered on the CD27 gene. Other studies have
highly prevalent in MM. The majority of these abnormalities
suggested that the low expression of CD27 was associated with
involve rearrangements located in the pericentromeric regions
a poor prognosis.
and frequently in the form of jumping translocations. Chromo-
some 1 abnormalities have been recently proposed as major
prognostic factors for MM.58 Regarding chromosome 1, it
should be noted that 1q gain and 1p loss are so closely related
p16 methylation and inactivation of p18
that it is hard to provide differentiation.8,10,59 We and others had
The issue is less clear for p16 methylation. Although some
previously reported that abnormalities of both the short and long
original studies had suggested negative associations with
arm of chromosome 1 were associated with shorter survival.8,60
prognosis,67­72 recent data on large data sets suggest that p16
In one study by Shaughnessy et al.58, they found and validated a
methylation is prognostically neutral.73 However, it has been
gene expression signature for high-risk disease. This signature is
recently found that a low transcription of the p16 gene measured
enriched disproportionately for genes located in chromosome 1.
by quantitative real-time PCR is associated with short survival,
This also builds on previous studies showing that chromosome 1
which suggests a possible impact of this gene in the MM
abnormalities are associated with an adverse outcome.
pathogenesis, but with limited prognostic value.74
Leukemia
IMWG molecular classification of MM
R Fonseca et al
7
miRNA
other musculoaponeurotic fibrosarcoma (MAF) variants. Other
Recent studies of microRNAs (miRNAs) show that they may also
prognostic markers exert effects across the major biological
be important in the pathogenesis of MM. Pichiorri et al.75 used
subtypes of MM. Some are well established, including the
miRNA microarrays and quantitative real-time PCR to profile
aforementioned effect of 17p13 in prognosis.6,7,52
miRNA expression in HMCLs (n ¼ 49), PCs from MM (n ¼ 16),
MGUS (n ¼ 6) and normal donors (n ¼ 6). They identified
expression of miR-21 (possibly blocking apoptosis in the early
Gene expression profiling
phases of clonal PC expansion), miR-106bB25 cluster, miR-
Using high-throughput genomic tools is likely to unravel novel
181a and b in MM and MGUS (otherwise not expressed in
means of predicting patient outcome. A major effort at the
normal PCs). Two sets of mir genes were found as upregulated in
University of Arkansas has identified a set of 70 genes (signature)
MM but not in MGUS, miR-32 and miR-17­92. In another study,
capable of predicting high-risk MM.58 The team further shows
ectopic expression of mir-21 made a cell line become
that a simplified list of 17 genes is capable of providing the
interleukin-6 independent.76 Functional in vitro and subsequent
same prognostic discrimination.58 This last model discriminates
xenograft experiments show that the postulated miRNA genes
with unprecedented ability `high-risk' disease. This high-risk
may have a significant role in the pathogenesis of MM through
profile was indeed enriched for genes located in chromosome 1.
the reduction of P300/CBP-associates factor (PCAF) (a positive
The IFM also demonstrated in an independent series of 250
p53 regulator), by downregulation of suppression of cytokine
patients that a set of 15 genes was able to identify the patients
signaling 1 (SOCS-1) and BCLZ like 11 (BIM).75
with the poorest prognosis. It is possible that reverse transcrip-
tase­PCR or immunohistochemistry-based strategies can be
used to derive clinically applicable prognostication models
16q abnormalities
for the disease. Other markers could include proliferation index
A recent paper using single nucleotide polymorphism arrays
by GEP, centrosome index by GEP and cancer testis anti-
lead to the conclusion that 16q abnormalities are also a
gens.5,51,80 It is important to note that there is minimal overlap
recurrent and important genetic aberration in MM (20% of
between the different proposed signatures. The ability of each
cases).77 The region 16q is unique in that it frequently harbors
one of these signatures to be used in different contexts of
both deletions, and leads to the postulation of WWOX as a
treatments and stages is still being validated. Furthermore, it is
putative tumor-suppressor gene in MM.77 One study reported a
conceivable that novel GEP derived signatures could be
40% loss of hetreozygocity (LOH) of 16q, including deletion of
developed in the future and that will better predict patient
the entire chromosome or the whole arm in 12 of 55 cases
outcomes. This will also be important and relevant with further
(22%), interstitial deletions in 7 of 55 cases (13%) and
developments of anti-MM therapies.
uniparental disomy (UPD) of the entire chromosome 16 or
16q in 4 of 55 cases (7%).78 These studies need confirmation.
aCGH prognostication
The availability of aCGH has provided new opportunities for the
Prognostic classifications
identification of new biomarkers capable of discerning prog-
nosis. Two aforementioned studies have identified recurrent
Prognosis by specific genetic aberrations
genetic aberrations associated with prognosis. A study by
Although it is now clear that much of the major prognostic
Carrasco et al.10 found that patients could be divided into four
variation of MM is dictated by primary genetic categories,
subgroups (the two major branches being h-MM and nh-MM).
secondary changes can also have a profound influence in
Furthermore the h-MM could be divided into cases with
outcome by providing clonal survival/proliferation advantages.
chromosome 13 deletions and 1 abnormality, and they had a
Some of the basic genetic categories have not resulted (yet) in
shorter survival. This study was small and needs confirmation. In
specific clinical outcome difference, yet define unique subtypes
another study, Avet-Loiseau et al. identified three recurrent
(for example, t(11;14)(q13;q32)).6,7 The clinical consequences
abnormalities as predictive of outcome, gain of 1q, loss of 12p
of secondary genetic changes tend not to be related to the
and gain of chromosome 5. Identification of biomarkers through
therapy administered. One possible way to define prognostic
aCGH is promising, as they can be easily converted to other
SPOTLIGHT
markers is that they associate with baseline features of
diagnostic tools such as FISH.25
aggressiveness (pathobiology) and they should exert their
influence if patients are not treated (natural history) (Table 1).
It is possible that these markers will also identify patients who
Diagnostic tests needed
are more likely to progress from the premalignant stages of the
disease. In general, the effect on overall outcome for validated
Summary and technical aspects
prognostic markers will be evident irrespective of treatment
We believe that a comprehensive cytogenetic evaluation
modality, even when the hazard ratios for their influence may
should be carried out in all cases at the time of diagnosis in
vary. As one example, we cite the negative implications for
both the clinical and research trials (Table 2). This paper has
outcome for the t(4;14)(p16;q32) as it identifies patients with
not focused as much on the technical aspects of detecting
shorter clinical benefit from standard and HDT (Table 1).
genetic aberrations and advantages or pitfalls of each tech-
Although it seems that some of the prognostic ability can be
nology, but rather on the importance of detecting each one of
challenged with novel agents, it is still too early to negate
these categories. We believe that clinical testing at this point
prognostication ability for t(4;14)(p16;q32) for patients receiv-
should include at a minimum interphase FISH in purified PCs
ing agents such as bortezomib.79 The same negative effect
or in combination with immunofluorescent detection of light
for prognosis is evident for the t(14;16)(q32;q23), as two
chain-restricted PC cytoplasmic immunoglobulin enhanced
series using conventional therapy (the Eastern Cooperative
FISH (cIg-FISH).81 It is imperative that all FISH testing in MM
Oncology Group) and HDT (UAMS) have shown the deleterious
incorporates one of these two strategies to improve on the rate of
effect on survival.3,7 Minimal data are available regarding the
abnormality detection. It is common for the cytogenetics portion
Leukemia
IMWG molecular classification of MM
R Fonseca et al
8
of a bone marrow aspirate draw to be the last tube collected.
profiling should be considered. The power of gene expression
Owing to this, hemodilution of the bone marrow aspirate will
profiling has already been exploited at some centers for the
result in a lower concentration of PCs and this will reduce the
selection of therapy for patients for different treatment algo-
yield even further. The two aforementioned methods are equally
rithms. The introduction of new predictive markers (such as
effective at selecting the cells to be studied and could be
those for bortezomib sensitivity) is also highly desirable for all
implemented more on the basis of laboratory experience.
future clinical trials.
Selection of cells has been more commonly used in Europe,
whereas cIg-FISH is now performed by at least two reference
laboratories in the United States.
Summary and consensus recommendations
International MM working genetic classification
Clinical testing
We recommend that the following working genetic classifica-
At a bare minimum, a FISH panel for MM should include testing
tion (Table 5) be adopted until further elucidation of the
for t(4;14)(p16;q32), t(14;16)(q32;q23) and ­17p13 (Table 2).
pathogenesis of other subtypes of MM is provided.
These three probes have been proposed by one group and have
If clinical testing for GEP existed, all (most) of these categories
been used by others in the stratification of cases into high- and
could be also identified. There is significant overlap between the
standard-risk disease.
translocations and cyclin d (TC) classification and the UAMS
The expansion of this panel to other probes may be desirable
molecular classification (Table 4), but there is excellent
SPOTLIGHT
as it provides a more comprehensive assessment of the disease
concordance for the MS and MF group corresponding to the
biology, clinical features and likely outcome. Among these are
4p16 and Maf groups, respectively, with 100% concordance.
those that identify 1q amplification, 1p deletions and others.
There is still good but imperfect concordance (88%) for the CD-
Those additional markers emanating from the aCGH analysis,
1 and CD-2 groups together corresponding to the 11q13 and
such as loss of 12p and gain of chromosome 5, could also be
6p21 groups. If one joins the TC D1 and D1 þ D2 groups, there
converted to FISH strategies(Table 2). Other markers include
is 96% concordance with the HY group. Significantly, overlap is
t(11;14)(q13;q32) (see below), hyperdiploidy and IgH transloca-
also seen between the D2 cases and LB from UAMS. As
tions, not otherwise specified. Although chromosome 13 alone
mentioned before, the PR group seems to encompass many of
is no longer considered a strong prognostic indicator, and hence
the other genetic subtypes that have acquired secondary genetic
could be abandoned, its use in combination with other variables
events.
(such as the b2-microglobulin or others) results in effective
segregation of cases into the high-risk category.
Testing recommendation
The t(11;14)(q13;q32) deserves special attention as it is
We recommend that at a minimum baseline genetic information
at a very high frequency in cases of light chain amyloidosis
should be obtained in all MM cases. Although many centers
(B35­50%)82,83 and almost universal in cases of IgM MM
continue to collect karyotypes as an important predictor of
(>90%).84 Detection of this translocation in a patient with
monoclonal IgM strongly supports the diagnosis of IgM
myeloma, as the clonal cells in patients with wladenstrom
macroglobulinemia (WM) almost never harbor IgH transloca-
Table 5
New proposed International Myeloma Working Group
tions.85 Patients with t(11;14)(q13;q32) MM can have lympho-
molecular cytogenetic classification
plasmacytic morphology, occasionally creating diagnostic
confusion and also have a higher rate of CD20 expression.28
Percentage
Clinical and laboratory features
The frequency of testing is not well defined (Tables 1 and 2).
of patients
It is now accepted that the major genetic subtypes of the
Hyperdiploid
45
More favorable, IgG-k, older
disease will not change over time. However, genetic progression
patients.
events are likely to arise with additional follow-up of cases
Non-hyperdiploid
40
Aggressive, IgA-l, younger
and repeat testing may be desirable. Two examples are testing
individuals
for ­17p13 and chromosome 1 amplification, and probably
Cyclin D
18
translocation
chromosome 13 too. The repeat testing for other markers is not
t(11;14)(q13;q32)
16
Upregulation of CCND1; favorable
defined yet. The utilization of FISH strategies for determina-
prognosis; bone lesions. Two
tion of minimal residual disease is not validated yet at the
subtypes by GEP
clinical level.
t(6;14q)(p21;32)
2
Probably same as CCND1
t(12;14)(p13;q32)
o1
Rare
MMSET
15
Clinical trial testing
translocation
t(4;14)(p16;q32)
15
Upregulation of MMSET;
The aforementioned testing should be considered in all ongoing
upregulation of FGFR3 in 75%
and future clinical trials(Tables 1 and 2). Trials that will be based
unfavorable prognosis with
on the targeting of specific genetic abnormalities need accurate
conventional therapy; bone lesions
determination of such subgroups and adequate clinical testing is
less frequent
needed. It should be considered mandatory that for demo-
MAF translocation
8
Aggressive
t(14;16)(q32;q23)
5
Confirmed as aggressive by at
graphic description of patients in future clinical trials, the table
least two series
describing the cohort contains descriptors of the genetic
t(14;20)(q32;q11)
2
One series shows more aggressive
subtypes of patients studied.
disease.
It is highly desirable to incorporate gene expression profiling
t(8;14)(q24;q32)
1
Unknown effect on outcome but
into the correlative science of ongoing clinical trials. Likewise,
presumed aggressive.
as new technology emerges, the incorporation of other high-
Unclassified (other)
15
Various subtypes and some with
overlap
throughput platforms such as aCGH and exon gene expression
Leukemia
IMWG molecular classification of MM
R Fonseca et al
9
outcome, further clarification using molecular cytogenetics is
unifying pathogenic event in multiple myeloma. Blood 2005;
warranted. This testing must be done with either cytoplasmic
106: 296­303.
immunoglobulin-enhanced FISH or FISH carried out on the
6 Avet-Loiseau H, Attal M, Moreau P, Charbonnel C, Garban F,
nuclei from purified PCs. Performing FISH in unsorted samples
Hulin C et al. Genetic abnormalities and survival in multiple
myeloma: the experience of the Intergroupe Francophone du
carries a significant risk of low sensitivity for detection of
Myelome. Blood 2007; 109: 3489­3495.
chromosome abnormalities. The minimum panel required for
7 Fonseca R, Blood E, Rue M, Harrington D, Oken MM, Kyle RA
prognostic
estimation
should
include
t(4;14)(p16;q32),
et al. Clinical and biologic implications of recurrent genomic
t(14;16)(q32;q23) and 17p13 deletions. A more comprehensive
aberrations in myeloma. Blood 2003; 101: 4569­4575.
panel should include testing for t(11;14)(q13;q32), chromosome
8 Debes-Marun C, Dewald G, Bryant S, Picken E, Santana-Da´vila S,
13 deletion, ploidy category and chromosome 1 abnormalities.
Gonza´lez-Paz N et al. Chromosome abnormalities clustering and
The utility of this information is both at the biological subtype
its implications for pathogenesis and prognosis in myeloma.
Leukemia 2003; 17: 427­436.
determination, as well as prognostic recommendations based on
9 Smadja NV, Fruchart C, Isnard F, Louvet C, Dutel JL, Cheron N
the minimal panel for testing. As new prognostic markers
et al. Chromosomal analysis in multiple myeloma: cytogenetic
emerge from ongoing aCGH studies, new markers may be
evidence of two different diseases. Leukemia 1998; 12: 960­969.
added to these screening panels.
10 Carrasco DR, Tonon G, Huang Y, Zhang Y, Sinha R, Feng B et al.
High-resolution genomic profiles define distinct clinico-patho-
genetic subgroups of multiple myeloma patients. Cancer Cell
GEP profiling: classification and prognosis
2006; 9: 313­325.
Our group also recognizes that the greatest prognostic ability for
11 Keats JJ, Reiman T, Maxwell CA, Taylor BJ, Larratt LM, Mant MJ
MM resides in the comprehensive analysis of GEP. At a
et al. In multiple myeloma, t(4;14)(p16;q32) is an adverse
minimum, all clinical trials should consider incorporation of
prognostic factor irrespective of FGFR3 expression. Blood 2003;
101: 1520­1529.
GEP into the correlative science studies to identify subgroups of
12 Gertz MA, Lacy MQ, Dispenzieri A, Greipp PR, Litzow MR,
high-risk disease. We also propose that methodology to include
Henderson KJ et al. Clinical implications of t(11;14)(q13;q32),
GEP into the clinical testing is urgently needed and methods for
t(4;14)(p16 3 q32) and -17p13 in myeloma patients treated with
implementation should be identified. Alternatively, conversion
high-dose therapy. Blood 2005; 106: 2837­2840.
of GEP signature profiles into other routine clinical diagnostic
13 Jagannath S, Richardson PG, Sonneveld P, Schuster MW, Irwin D,
tools is also likely to lead to rapid conversion of these prognostic
Stadtmauer EA et al. Bortezomib appears to overcome the poor
signatures into widely available clinical tests.
prognosis conferred by chromosome 13 deletion in phase 2 and 3
trials. Leukemia 2007; 21: 151­157.
14 San Miguel JF, Schlag R, Khuageva NK, Dimopoulos MA,
Shpilberg O, Kropff M et al. Bortezomib plus melphalan and
Conflict of interest
prednisone for initial treatment of multiple myeloma. N Engl J Med
2008; 359: 906­917.
R Fonseca is a consultant for Genzyme, Celgene, BMS, Otsuka,
15 Chng WJ, Kuehl WM, Bergsagel PL, Fonseca R. Translocation
Halozyme and Medtronic. His research was funded by
t(4;14) retains prognostic significance even in the setting of high-
Cylene and Proteolix. PL Bergsagel is on the advisory board of
risk molecular signature. [published erratum appears in Leukemia
Amgen, Genentech, Celgene. Hid research was funded by
2008; 22: 462] Leukemia 2008; 22: 459­461, e-pub ahead of print
Merck. B Van Ness serves on the IMF Scientific Advisory Board.
6 September 2007. No abstract available.
16 Trudel S, Li ZH, Wei E, Wiesmann M, Chang H, Chen C et al.
The rest of the authors declare no conflict of interest.
CHIR-258, a novel, multitargeted tyrosine kinase inhibitor for the
Shaughnessy's work was patented by Myelogix, Genzyme and
potential treatment of t(4;14) multiple myeloma. Blood 2005; 105:
Novartis. He is a scientific advisor to Myelogix, Genzyme,
2941­2948.
Novartis and Celgene. He receives royalties from Myelogix,
17 Shi J, Tricot GJ, Garg TK, Malaviarachchi PA, Szmania SM, Kellum
Genzyme, Novartis and Celgene, and is the owner of Myelogix.
RE et al. Bortezomib down-regulates the cell-surface expression of
Bart Barlogie's research was funded by NCI, Millennium,
HLA class I and enhances natural killer cell-mediated lysis of
Celgene and Novartis. He has received honoraria from
myeloma. Blood 2008; 111: 1309­1317.
18 Keats JJ, Fonseca R, Chesi M, Schop R, Baker A, Chng WJ
Millennium, Celgene and IMF. He is on the speakers Bureau
et
al.
Promiscuous
mutations
activate
the
noncanonical
of Millennium, Celgene and SWOG, and is a consultant for
NF-kappaB pathway in multiple myeloma. Cancer Cell 2007;
Celegene and Genzyme. He also has membership on an entity's
12: 131­144.
SPOTLIGHT
Board of Directors or advisory committees of IMF, MMRF
19 Kuehl WM, Bergsagel PL. Multiple myeloma: evolving genetic
and SWOG.
events and host interactions. Nature Rev Cancer 2002; 2:
175­187.
20 Fonseca R, Debes-Marun CS, Picken EB, Dewald GW, Bryant SC,
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SPOTLIGHT
Sammartino G et al. Multicolour spectral karyotyping identifies
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Appendix
Andrew Belch, Cross Cancer Institute, Alberta, Canada
Bill Bensinger, Fred Hutchinson Cancer Center, Seattle, WA,
Rafat Abonour, Indiana University School of Medicine,
USA
Indianapolis, IN, USA
Mario Boccadoro, University of Torino, Torino, Italy
Ray Alexanian, MD Anderson, Houston, TX, USA
Michele Cavo, Universita di Bologna, Bologna, Italy
Kenneth Anderson, DFCI, Boston, MA, USA
Wen Ming Chen, MM Research Center of Beijing, Beijing, China
Michael Attal, Purpan Hospital, Toulouse, France
Tony Child, Leeds General Hospital, Leeds, UK
Herve Avet-Loiseau, Institute de Biologie, Nantes, France
James Chim, Department of Medicine, Queen Mary Hospital,
Ashraf Badros, University of Maryland, Baltimore, MD, USA
Hong Kong
Leif Bergsagel, Mayo Clinic Scottsdale, Scottsdale, AZ, USA
Ray Comenzo, Tufts Medical Center, Boston, MA, USA
Joan Blade´, Hospital Clinica, Barcelona, Spain
John Crowley, Cancer Research and Biostatistics, Seattle, WA,
Bart Barlogie, MIRT UAMS Little Rock, AR, USA
USA
Regis Batille, Institute de Biologie, Nantes, France
William Dalton, H Lee Moffitt, Tampa, FL, USA
Meral Beksac, Ankara University, Ankara, Turkey
Faith Davies, Royal Marsden Hospital, London, England
Leukemia
IMWG molecular classification of MM
R Fonseca et al
12
Ca´rmino de Souza, Univeridade de Campinas, Caminas,
Maria Mateos, University of Salamanca, Salamanca, Spain
Brazil
Jayesh Mehta, Northwestern University, Chicago, IL, USA
Michel Delforge, University Hospital Gasthuisberg, Leuven,
GianPaolo Merlini, University of Pavia, Pavia, Italy
Belgium
Joseph Mikhael, Mayo Clinic Arizona, Scottsdale, AZ, USA
Meletios Dimopoulos, Alexandra Hospital, Athens, Greece
Philippe Moreau, University Hospital, Nantes, France
Angela Dispenzieri, Mayo Clinic, Rochester, MN, USA
Gareth Morgan, Royal Marsden Hospital, London, England
Brian GM Durie, Cedars-Sinai Outpatient Cancer Center, Los
Nikhil Munshi, Diane Farber Cancer Institute, Boston, MA,
Angeles, CA, USA
USA
Hermann Einsele, Universita¨tsklinik Wu¨rzburg, Wu¨rzburg,
Ruben Niesvizky, Weill Medical College of Cornell Uni-
Germany
versity, New York, NY, USA
Theirry Facon, Centre Hospitalier Regional Universitaire de
Yana Novis, Hospital Si´rioLibane^s, Bela Vista, Brazil
Lille, Lille, France
Amara Nouel, Hospital Rutz y Paez, Bolivar, Venezuela
Dorotea Fantl, Socieded Argentinade Hematolgia, Buenos
Robert Orlowski, MD Anderson Cancer Center, Houston, TX,
Aires, Argentina
USA
Jean-Paul Fermand, Hopitaux de Paris, Paris, France
Antonio Palumbo, Cathedra Ematologia, Torino, Italy
Rafael Fonseca, Mayo Clinic Arizona, Scottsdale, AZ, USA
Santiago Pavlovsky, Fundaleu, Buenos Aires, Argentina
Gosta Gahrton, Karolinska Institute for Medicine, Huddinge,
Linda Pilarski, University of Alberta, Alberta, Canada
Sweden
Raymond Powles, Leukaemia & Myeloma, Wimbledon,
SPOTLIGHT
Morie Gertz, Mayo Clinic, Rochester, MN, USA
England
John Gibson, Royal Prince Alfred Hospital, Sydney, Australia
S. Vincent Rajkumar, Mayo Clinic, Rochester, MN, USA
Sergio Giralt, MD Anderson Cancer Center, Houston, TX, USA
Donna Reece, Princess Margaret Hospital, Toronto, Canada
Hartmut Goldschmidt, University Hospital Heidelberg,
Tony Reiman, Cross Cancer Institute, Alberta, Canada
Heidelberg, Germany
Paul Richardson, Dana Farber Cancer Institute, Boston, MA,
Philip Greipp, Mayo Clinic, Rochester, MN, USA
USA
Roman Hajek, Brno University, Brno, Czech Republic
Angelina Rodriquez Morales, Bonco Metro Politano de
Izhar Hardan, Tel Aviv University, Tel Aviv, Israel
Sangre, Caracas, Venezuela
Jean-Luc Harousseau, Institute de Biologie, Nantes, France
Orhan Sezer, Department of Hem/Onc, Universitatsklinikum
Hiroyuki Hata, Kumamoto University Hospital, Kumamoto,
Charite, Berlin, Germany
Japan
John Shaughnessy, MIRT UAMS, Little Rock, AR, USA
Yutaka Hattori, Keio University School of Medicine, Tokyo,
Kazuyuki Shimizu, Nagoya City Midori General Hospital,
Japan
Nagoya, Japan
Joy Ho, Royal Prince Alfred Hospital, Sydney, Australia
David Siegel, Hackensack, Cancer Center, Hackensack, NJ,
Vania Hungria, Clinica San Germano, Sao Paolo, Brazil
USA
Shinsuke Ida, Nagoya City University Medical School,
Jesus San Miguel, University of Salamanca, Salamanca, Spain
Nagoya, Japan
Chaim Shustik, McGill University, Montreal, Canada
Peter Jacobs, Constantiaberg Medi-Clinic, Plumstead, South
Seema Singhal, Northwestern University, Chicago, IL,
Africa
USA
Sundar Jagannath, St Vincent's Comprehensive Cancer
Pieter Sonneveld, Erasmus MC, Rotterdam, The Netherlands
Center, New York, NY, USA
Andrew Spencer, The Alfred Hospital, Melbourne, Australia
Hou Jian, Shanghai Chang Zheng Hospital, Shanghai, China
Edward Stadtmauer, University of Pennsylvania, Philadelphia,
Douglas Joshua, Royal Prince Alfred Hospital, Sydney,
PA, USA
Australia
Keith Stewart, Mayo Clinic Arizona, Scottsdale, AZ, USA
Michio Kawano, Yamaguchi University, Ube, Japan
Patrizia Tosi, Italian Cooperative Group, Istituto di Ematologia
Nicolaus Kro¨ger, University Hospital Hamburg, Hamburg,
Seragnoli, Bologna, Italy
Germany
Guido Tricot, Huntsman Cancer Institute, Salt Lake City, UT, USA
Shaji Kumar, Department of Hematology, Mayo Clinic, MN,
Ingemar Turesson, Department of Hematology, Malmo
USA
University, Malmo, Sweden
Robert Kyle, Department of Laboratory Med. and Pathology,
Brian Van Ness, University of Minnesota, Minneapolis, MN,
Mayo Clinic, MN, USA
USA
Juan Lahuerta, Grupo Espanol di Mieloma, Hospital
Ivan Van Riet, Brussels Vrija University, Brussels, Belgium
Universitario, Madrid, Spain
Robert Vescio, Cedars-Sinai Cancer Center, Los Angeles, CA,
Jae Hoon Lee, Gachon University Gil Hospital, Incheon,
USA
Korea
David Vesole, Loyola University Chicago, IL, USA
Xavier LeLeu, Hospital Huriez, CHRU Lille, France
Anders Waage, University Hospital, Trondheim, Norway
Suzanne Lentzsch, University of Pittsburgh, Pittsburgh, PA,
NSMG
USA
Michael Wang, MD Anderson, Houston, TX, USA
Henk Lokhorst, University Medical CenterUtrecht, Utrecht,
Donna Weber, MD Anderson, Houston, TX, USA
The Netherlands
Jan Westin, Sahlgrenska University Hospital, Gothenburg,
Sagar Lonial, Emory University Medical School, Atlanta,
Sweden
GA, USA
Keith Wheatley, University of Birmingham, Birmingham, UK
Heinz Ludwig, Wilhelminenspital Der Stat Wien, Vienna,
Dina B Yehuda, Department of Hematology, Hadassah
Austria
University Hospital, Hadassah, Israel
Angelo Maiolino, Rua fonte da Saudade, Rio de Janeiro,
Jeffrey Zonder, SWOG, Department of Hem/Onc., Karmanos
Brazil
Cancer Institute, MI, USA
Leukemia

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