PURPOSE: Multiple myeloma (MM) is a clonal bone marrow disease characterized by the neoplastic transformation of differentiated postgerminal B cells. It is a heterogeneous disease both at the genetic level and in terms of clinical outcome. Immunoglobulin M (IgM) MM is a rare subtype of myeloma. Similar to Waldenström macroglobulinemia (WM), patients with MM experience IgM monoclonal gammopathy; however, both diseases are distinct in terms of treatment and clinical behavior. MATERIALS AND METHODS: To shed light on the presentation of IgM MM, its prognosis, and its gene expression profiling, we identified and characterized 21 patients with IgM MM from our database. RESULTS: One of these patients presented with a rare IgM monoclonal gammopathy of undetermined significance that progressed to smoldering myeloma. The median survival of the 21 patients was 4.9 years, which was comparable to a matched group of patients with non-IgM MM with similar myeloma prognostic factors (age, gender, albumin, creatinine, anemia, lactate dehydrogenase, β2-microglobulin, cytogenetics abnormalities), but much less than the median survival reported for patients with WM (9 years). We identified a cluster of genes that differ in their expression profile between MM and WM and found that the patients with IgM MM displayed a gene expression profile most similar to patients with non-IgM MM, confirming that IgM MM is a subtype of MM that should be differentiated from WM. CONCLUSION: Because the prognosis of IgM MM and WM differ significantly, an accurate diagnosis is essential. Our gene expression model can assist with the differential diagnosis in controversial cases.
PURPOSE:Multiple myeloma (MM) is a clonal bone marrow disease characterized by the neoplastic transformation of differentiated postgerminal B cells. It is a heterogeneous disease both at the genetic level and in terms of clinical outcome. Immunoglobulin M (IgM) MM is a rare subtype of myeloma. Similar to Waldenström macroglobulinemia (WM), patients with MM experience IgM monoclonal gammopathy; however, both diseases are distinct in terms of treatment and clinical behavior. MATERIALS AND METHODS: To shed light on the presentation of IgM MM, its prognosis, and its gene expression profiling, we identified and characterized 21 patients with IgM MM from our database. RESULTS: One of these patients presented with a rare IgM monoclonal gammopathy of undetermined significance that progressed to smoldering myeloma. The median survival of the 21 patients was 4.9 years, which was comparable to a matched group of patients with non-IgM MM with similar myeloma prognostic factors (age, gender, albumin, creatinine, anemia, lactate dehydrogenase, β2-microglobulin, cytogenetics abnormalities), but much less than the median survival reported for patients with WM (9 years). We identified a cluster of genes that differ in their expression profile between MM and WM and found that the patients with IgM MM displayed a gene expression profile most similar to patients with non-IgM MM, confirming that IgM MM is a subtype of MM that should be differentiated from WM. CONCLUSION: Because the prognosis of IgM MM and WM differ significantly, an accurate diagnosis is essential. Our gene expression model can assist with the differential diagnosis in controversial cases.
Multiple myeloma (MM) is considered a malignancy of postgerminal center long-lived
plasma cells. Although rare, T-cell–independent antigen stimulation can occur
in these patients, and when it does, it results in the production of immunoglobulin
M (IgM)–secreting short-lived plasma cells and lymphoplasmacytes. IgM MM is
an infrequent subtype of MM, with an estimated prevalence of 0.5%.[1] Because of its rarity and similarity
to Waldenström macroglobulinemia (WM), little is known about its clinical
characteristics, genetics, and prognosis compared with WM and other MM subtypes.The presence of serum monoclonal IgM and uncontrolled plasma cell proliferation is
associated with both IgM MM and WM. In most cases, it is not difficult to clinically
differentiate between these two diseases. WM is suspected in patients with
lymphadenopathy, hepatosplenomegaly, hyperviscosity syndrome, and the presence of a
monoclonal IgM in the serum.[2] A
panel of B-cell antigens (CD19, CD20, CD21, CD22, and CD24) is present on the WM
cells, whereas the CD23 antigen is usually absent.[3] The concentration of IgM varies widely in WM, and it
is not possible to define a concentration that reliably distinguishes WM from other
lymphoproliferative disorders.[4]
Alternatively, IgM MM is suspected in the presence of osteolytic lesions, bone pain,
monoclonal protein in blood or urine, or immune paresis, and it is confirmed with a
bone marrow biopsy along with the other established International Myeloma Working
Group (IMWG) criteria.[5] Patients
with IgM MM tend to have plasmacytic differentiation with high expression of CD138
and cytoplasmic immunoglobulin.[6]
However, when patients present with IgM monoclonal gammopathy, osteolytic lesions,
and lymphadenopathies or hepatosplenomegaly, untangling the MM-WM differential
diagnosis can be challenging.[5]One of the characteristics of MM is the rearrangement of its immunoglobulin heavy and
light chain genes. The high load of somatic hypermutations in the immunoglobulin
heavy chain (IgH) locus is consistent with its postgerminal
antigen-driven B-cell origin.[7]
There are five main translocation chromosomes in MM, which seem to be mediated
mostly by errors in the IgH switch recombination that occurs during B-cell
maturation in germinal centers.[8]
Those translocations are t(4;14), t(6;14), t(11;14), t(14;16), and t(14;20), and
they result in the overexpression of MMSET and
FGFR3,[9]
CCND3,[10]
CCND1,[9,11]
MAF,[12] and
MAFB, respectively.[13] Those aberrant chromosomal translocations are one of the
central molecular hallmarks of MM. Thus, translocations involving the 14q32 region,
for example, might represent clear-cut differences between MM and WM, and may be of
diagnostic value in difficult patients.[14]
MATERIALS AND METHODS
Patients
Twenty-one patients diagnosed with IgM MM between 1993 and 2013 were identified
in the University of Arkansas for Medical Sciences Myeloma Institute for
Research and Therapy (MIRT) patient database. Patient data collected for this
study included overall survival (OS), bone disease status (as defined by x-rays,
positron emission tomography [PET] scans, and magnetic resonance imaging scans),
gene expression profiles (GEPs), and laboratory values (hemoglobin, calcium, and
creatinine).To determine the potential impact of possessing the IgM MM subtype on the
prognosis of these patients, the survival of 21 patients with IgM MM was
retrospectively compared with a historical control group of 158 patients with WM
seen by MIRT[15] and a group of
84 patients with non-IgM MM matched by important prognostic clinical factors:
age,[16] albumin and
β2-microglobulin,[17] creatinine,[18] light chain type, serum lactate
dehydrogenase,[19] and
abnormal cytogenetics.[20] All
patients were treated around the same time at MIRT (Table 1).
Table 1
Baseline Characteristics of Patients With IgM MM and Non-IgM MM
Baseline Characteristics of Patients With IgM MM and Non-IgM MMA diagnosis of IgM MM was based on the morphologic and immunophenotypical
findings of biopsy specimens, the presence of a monoclonal IgM, and the presence
of typical clinical characteristics of MM (lytic bone lesions, hypercalcemia,
renal failure), using IMWG criteria.[5] In a similar fashion, the diagnosis of WM was based on the
morphologic and immunophenotypical findings of biopsy specimens, the presence of
a monoclonal IgM, and the presence of typical clinical characteristics of WM
(hepatosplenomegaly, lymphadenopathy). However, the presence of bone disease per
se was not exclusive to the MM diagnosis because verified patients with WM have
been described with pathologically confirmed bone involvement.[21-23]
Statistical Analysis
Survival curves were estimated using the Kaplan-Meier method and compared using
the log-rank test. Matching between IgM and non-IgM MM was performed using R
software[24] and the
MatchIT package[25] using
“to the nearest” method, with a 1 to 4 ratio without replacement,
taking into consideration the baseline characteristics listed in Table 1.Patients with IgM MM, non-IgM MM, and WM with available GEPs from MIRT were
compared. To find gene expressions that could best distinguish between WM and
non-IgM MM diagnoses, we selected the top 1,000 probe sets that maximized their
gene-specific ratio between these two groups to within-groups sums of squares on
the basis of the method by Dudoit et al.[26] Next, we performed unsupervised hierarchical clustering
on all samples, including patients with IgM MM using the top 1,000 probe
sets.For better illustration of the results, we reduced the dimensionality of the top
1,000 probe sets in WM and non-IgM MM groups to three dimensions using principal
component analysis[27] and
partial least squares.[28] Then,
a linear support vector machine model[29] was applied on the WM and non-IgM MM groups, and the
boundary plane was plotted. Next, the same transformation was applied to IgM MM
samples and added to the corresponding three-dimensional plot. The Database for
Annotation, Visualization, and Integrated Discovery (DAVID)[30] was used for the functional
enrichment analysis.
RESULTS
Patient Characteristics and Survival
Of the 21 confirmed patients with IgM MM, 13 presented at MIRT for initial
diagnosis, whereas eight were diagnosed and treated elsewhere before seeking
care at MIRT. Seven patients presented with each of stages I, II, and III of the
international staging system for plasma cell myeloma.[31] Osteolytic bone lesions and/or pathologic
fractures were evident by x-ray and computed tomography scan in 15 patients.
Either magnetic resonance imaging or PET scan detected active bone focal lesions
in three patients. Bone lesions were not observed in the remaining three
patients. There was no organomegaly evident in patients with an available
PET/computed tomography scan at baseline, and only one patient had evidence of
hilar and mediastinal lymphadenopathy along with calcified lung nodules.
Elevated creatinine levels (> 2.0 mg/dL) were evident in four patients at
the time of initial diagnosis. Disease characteristics of these patients and the
WM and non-IgM MM control groups are listed in Table 1.When the OS of the IgM MM group (4.9 years; 95% CI, 3.5 to ∞) was compared
with a matched group of 84 patients with non-IgM MM (7.9 years; 95% CI, 5.3 to
10.75), no statistically significant difference was observed (P
= .751; Fig 1). Both groups had lower OS
than the median OS of the historical group of 158 symptomatic patients with WM
(9.2 years).[15] As previously
reported, the median OS of the WM group remained largely unaffected, even when
the subgroup of patients with WM requiring treatment was analyzed (9.0
years).
Fig 1
Kaplan-Meier estimates of overall survival in immunoglobulin M (IgM)
multiple myeloma (MM; n = 21, red line) and a matched cohort of non-IgM
MM (n = 84, blue line). No statistical difference was found for overall
survival between these two groups, with a log-rank P
equal to .751.
Kaplan-Meier estimates of overall survival in immunoglobulin M (IgM)
multiple myeloma (MM; n = 21, red line) and a matched cohort of non-IgM
MM (n = 84, blue line). No statistical difference was found for overall
survival between these two groups, with a log-rank P
equal to .751.
Bone Marrow Karyotype, Fluorescence In Situ Hybridization, and DNA Flow
Cytometry
In our cohort, baseline bone marrow cytogenetic data were available for 19 of 21
patients. Six of 19 patients had abnormal cytogenetics at presentation. Two of
six patients had a t(11;14) translocation, one had t(14;16), and the other three
had complex karyotype with hypodiploidy.Only one patient who had interphase fluorescence in situ hybridization performed
on bone marrow aspirate at baseline demonstrated t(11;14) translocation
(CCND1/IgH) and a loss of chromosome 13; conventional cytogenetics for this
patient was reported as normal.Aneuploidy by DNA flow cytometry was evident in 13 of 21 patients (62%). This
fact is in accordance with the already published data stating the frequency of
aneuploidy in MM[32] and is in
striking antithesis with WM (aneuploidy was detected in 12 of 168 patients with
DNA flow cytometry; unpublished data; P < .001)
Gene Expression Profiling
Of 21 patients with IgM MM, 12 had available GEP data on initial diagnosis. One
patient had an upregulated CCND2.[33] In six of these patients (50%), cyclin D1 gene
expression was high. This is consistent with previously published
data.[34]To discover the features of gene expression that may be unique to IgM MM, we
performed an unsupervised hierarchical cluster analyses of GEP of CD138-positive
cells from the following samples: bone marrow aspirates of non-IgM MM and bone
marrow aspirates of WM. Next, we added in the GEP data from bone marrow
aspirates of the 21 patients with IgM MM.A comparative genomic analysis was performed on the patients with IgM MM, non-IgM
MM, and WM with available GEP data at initial diagnosis (12, 60, and 52
patients, respectively). We identified the best 1,000 probe sets (Data
Supplement) that distinguish between WM and non-IgM MM. Many of these probes are
for membrane proteins, such as CD19, CD20, CD22, CD24, CD138, components of the
major histocompatibility complex, and adherence junctions.Using support vector machine analysis alone[29] or together with principal component analysis[27] or partial least
squares,[28]
Figures 2 and 3 demonstrate that the majority of the IgM MM samples are on the
non-IgM MM side of the boundary, indicating that the GEP of IGM MM is more
closely related to non-IgM MM than it is to WM.
Fig 2
Complete-linkage clustering analysis of Euclidean distance. Unsupervised
hierarchical clustering was performed on all samples, including
Waldenström macroglobulinemia (WM; green), immunoglobulin M (IgM)
multiple myeloma (MM; red), and non-IgM MM (blue) gene expression
profiles, using the 1,000 probesets retrieved in the filtering step.
Fig 3
Analysis of gene expression profiles (GEPs). (A) Principal components
analysis of GEPs from immunoglobulin M (IgM) multiple myeloma (MM; red),
non-IgM MM (blue), and patients with Waldenström
macroglobulinemia (WM; green). (B) Partial least squares analysis of
GEPs from IgM MM, non-IgM MM, and WM patients. Both methods were used to
reduce the dimensionality of the top 1,000 probesets in WM and non-IgM
MM groups to three dimensions. The same transformation was applied to
IgM MM samples. Then, a linear support vector machine model was applied
to the WM non-IgM MM groups, and the boundary plane was plotted. This
method reflects the same results as the hierarchical clustering analysis
(Fig 2), in that the majority
of the IgM MM samples (red) are on the non-IgM MM side of the boundary,
indicating that the GEP of IGM MM is more closely related to non-IgM MM
subtypes than it is to WM.
Complete-linkage clustering analysis of Euclidean distance. Unsupervised
hierarchical clustering was performed on all samples, including
Waldenström macroglobulinemia (WM; green), immunoglobulin M (IgM)
multiple myeloma (MM; red), and non-IgM MM (blue) gene expression
profiles, using the 1,000 probesets retrieved in the filtering step.Analysis of gene expression profiles (GEPs). (A) Principal components
analysis of GEPs from immunoglobulin M (IgM) multiple myeloma (MM; red),
non-IgM MM (blue), and patients with Waldenström
macroglobulinemia (WM; green). (B) Partial least squares analysis of
GEPs from IgM MM, non-IgM MM, and WM patients. Both methods were used to
reduce the dimensionality of the top 1,000 probesets in WM and non-IgM
MM groups to three dimensions. The same transformation was applied to
IgM MM samples. Then, a linear support vector machine model was applied
to the WM non-IgM MM groups, and the boundary plane was plotted. This
method reflects the same results as the hierarchical clustering analysis
(Fig 2), in that the majority
of the IgM MM samples (red) are on the non-IgM MM side of the boundary,
indicating that the GEP of IGM MM is more closely related to non-IgM MM
subtypes than it is to WM.MM and WM are plasma cell–related disorders.WM and IgM myeloma present with elevated IgM levels. However, both
disorders are clearly distinct by expression of Myd88 in WM and in terms
of molecular profile, clinical presentation, treatment, and
prognosis.In the setting of elevated IgM levels, the presence of bone lytic
lesions, hypercalcemia, and renal failure points toward IgM myeloma,
whereas the presence of splenomegaly and lymphadenopathy points toward
WM.Our study demonstrates the difference between both diseases at the gene
expression profiling level and provides a useful tool when
differentiating both diseases is challenging.
DISCUSSION
IgM MM is a discrete clinical entity that should be distinguished from WM because
their prognoses and treatments differ greatly. Using one of the largest series of
patients with IgM MM ever published, we have shown that patients with IgM MM have a
clinical presentation, prognosis, and GEP similar to patients with non-IgM MM.Bone disease is associated with approximately 79% of newly diagnosed patients with MM
when observed with conventional radiologic techniques.[1] In our cohort of patients with IgM MM, bone disease
was evident in the majority of patients, especially when specialized radiologic
techniques were incorporated into the initial work-up.Organomegaly is one of the clinical findings that is usually associated with WM or
plasma cell leukemia.[35]
Avet-Loiseau et al[14] reported two
of eight patients with IgM MM with organomegaly; however, our results were
consistent with the findings of Schuster et al,[36] in that none of our patients presented with organomegaly or
plasma cell leukemia.To determine whether patients with IgM MM have a different prognosis than patients
with non-IgM MM, OS for these two groups was compared using the Kaplan-Meier
log-rank test. Patients with IgM MM displayed a median OS of 4.9 years, similar to
patients with non-IgM MM receiving similar treatments at our institution
(P < .05). Patients with WM treated at our institution
alternatively reported a longer median OS of 9 years.[15]Previous studies[16,37,38] have
estimated that approximately 14% to 17% of patients with monoclonal gammopathy of
undetermined significance (MGUS)–IgM type will develop a group of malignant
lymphoid disorders, including non-Hodgkin lymphomas, chronic lymphocytic leukemia,
and primary amyloidosis, within an average period of 4 years.The observation of MGUS progressing to IgM MM is rarely reported. In one of those
studies, Kyle et al[16] reported an
association between IgM MGUS and smoldering IgM MM in one patient of 213, and that
patient exhibited biclonal gammopathy (IgM 386 mg/dL plus IgA λ 2840 mg/dL).
Similarly, in our study, one of 21 patients presented with MGUS and progressed to
IgM MM.In general, genetic abnormalities are found in one third of patients with MM by
conventional cytogenetics.[39]
Approximately 31% of our patients had cytogenetic abnormalities, three of whom had a
t(11;14) or t(14;16) translocation, and both of these translocations are typically
found in patients with MM.[8]In concordance with the previous pathologic and clinical findings, GEPs for non-IgM
MM and patients with WM were separated into two distinct clusters. Using these two
groups as references, we added in the GEP data for patients with IgM MM. Clearly,
both GEP data for IgM MM and patients with non-IgM MM clustered together, indicating
that IgM MM is correctly classified as a subtype of MM, sharing the same genetic and
pathologic characteristics. Only two of the 12 IgM MM samples (IgM MM-2 and IgM
MM-6; Table 2) were located in the WM cluster
(Fig 2), whereas the remaining 10 IgM MM
samples were located in the non-IgM MM cluster.
Table 2
Predicted Probability of Group Membership for 12 IgM MM Patients Using SVM
Together With PCA or PLS, or by Itself
Predicted Probability of Group Membership for 12 IgM MM Patients Using SVM
Together With PCA or PLS, or by ItselfAlthough these two patients fulfilled the newest IMWG diagnostic criteria for
MM,[5] it should be noted
that both patients did not clinically resemble typical MM. Both patients had mild to
moderate plasma cell infiltration with absent or borderline immunoparesis and absent
bone focal lesions by any imaging technique. Furthermore, in one of these two
patients, renal insufficiency was due to light chain deposition disease without any
evidence of cast nephropathy. In the other patient, bone disease was due to profound
osteoporosis and associated pathologic fractures without any evidence of direct
plasma cell involvement in pathology or imaging.In conclusion, patients with IgM MM share clinical and genetic characteristics with
the other subtypes of MM and have distinct differences from WM clinically,
genetically, and in terms of prognosis. The IgM subtype of MM per se does not affect
prognosis. All MM subtypes are affected by the established prognostic factors of MM,
but the IgM subtype alone does not confer any additional prognostic indicator. In
view of the remarkable differences in both treatment and prognosis between IgM MM
and WM, an accurate diagnosis is essential and should be obtained with all available
clinical, pathologic, and genetic assays.
Authors: J Shaughnessy; A Gabrea; Y Qi; L Brents; F Zhan; E Tian; J Sawyer; B Barlogie; P L Bergsagel; M Kuehl Journal: Blood Date: 2001-07-01 Impact factor: 22.113
Authors: Philip R Greipp; Jesus San Miguel; Brian G M Durie; John J Crowley; Bart Barlogie; Joan Bladé; Mario Boccadoro; J Anthony Child; Herve Avet-Loiseau; Jean-Luc Harousseau; Robert A Kyle; Juan J Lahuerta; Heinz Ludwig; Gareth Morgan; Raymond Powles; Kazuyuki Shimizu; Chaim Shustik; Pieter Sonneveld; Patrizia Tosi; Ingemar Turesson; Jan Westin Journal: J Clin Oncol Date: 2005-04-04 Impact factor: 44.544
Authors: C Fernández de Larrea; R A Kyle; B G M Durie; H Ludwig; S Usmani; D H Vesole; R Hajek; J F San Miguel; O Sezer; P Sonneveld; S K Kumar; A Mahindra; R Comenzo; A Palumbo; A Mazumber; K C Anderson; P G Richardson; A Z Badros; J Caers; M Cavo; X LeLeu; M A Dimopoulos; C S Chim; R Schots; A Noeul; D Fantl; U-H Mellqvist; O Landgren; A Chanan-Khan; P Moreau; R Fonseca; G Merlini; J J Lahuerta; J Bladé; R Z Orlowski; J J Shah Journal: Leukemia Date: 2012-11-21 Impact factor: 11.528
Authors: R Khan; S Apewokin; M Grazziutti; S Yaccoby; J Epstein; F van Rhee; A Rosenthal; S Waheed; S Usmani; S Atrash; S Kumar; A Hoering; J Crowley; J D Shaughnessy; B Barlogie Journal: Leukemia Date: 2012-02-02 Impact factor: 11.528