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Prepublished online as a Blood First Edition Paper on September 26, 2002; DOI 10.1182/blood-2002-06-1737.
NEOPLASIA
From the Donna and Donald Lambert Laboratory of Myeloma
Genetics at the Myeloma Institute for Research and Therapy, University
of Arkansas for Medical Sciences, Little Rock, AR.
To identify genes linked to normal plasma cell (PC)
differentiation and to classify multiple myeloma (MM) with respect to the expression patterns of these genes, we analyzed global mRNA expression in CD19-enriched B cells (BCs) from 7 tonsils,
CD138-enriched PCs from 11 tonsils, 31 normal bone marrow samples, and
74 MM bone marrow samples using microarrays interrogating 6800 genes. Hierarchical clustering analyses with 3288 genes clearly
segregated the 4 cell types, and chi-square and Wilcoxin rank sum tests
(P < .0005) identified 359 and 500 previously defined
and novel genes that distinguish tonsil BCs from tonsil PCs (early
differentiation genes [EDGs]), and tonsil PCs from bone marrow PCs
(late differentiation genes [LDGs]), respectively. MM as a whole was
found to have dramatically variable expression of EDGs and
LDGs, and one-way analysis of variance (ANOVA) was used to identify the
most variable EDGs (vEDGs) and LDGs (v1LDG and v2LDG). Hierarchical
cluster analysis with these genes revealed that previously defined MM
gene expression subgroups (MM1-MM4) could be linked to one of the 3 normal cell types. Clustering with 30 vEDGs revealed that 13 of 18 MM4
cases clustered with tonsil BCs (P = .000 05), whereas
14 of 15 MM3 cases clustered with tonsil PCs when using 50 v1LDG
(P = .000 008), and 14 of 20 MM2 cases clustered with
bone marrow PCs when using 50 v2LDG
(P = .000 09). MM1 showed no significant linkage with
normal cell types studied. Thus, genes whose expression is linked to
distinct transitions in late-stage B-cell differentiation can be used
to classify MM.
(Blood. 2003;101:1128-1140) Although many of the steps in B-cell (BC)
development have been elucidated, the final stages of plasma cell (PC)
differentiation are not well understood. PCs generated during primary
humoral immune responses begin their differentiation in the light zones of the germinal centers of lymph nodes or in the red pulp of spleen and
have a life span of only a few days.1-3 During secondary humoral immune responses, long-lived PCs migrate from the secondary lymphoid tissues into the bone marrow or into the lamina propria of the
mucosa where they survive and secrete large amounts of immunoglobulin
for at least 3 weeks.4,5 Despite morphologic and
functional similarities, PCs isolated from different organs exhibit
distinct differences. For example, life spans of tonsil- and bone
marrow-derived PCs are different1,6,7 and differences in
somatic hypermutation of complementarity-determining regions (CDRs) of
IGV genes is evident.8,9 Although most of these observations have been derived from rodent models, accumulating evidence suggests that human PCs follow a similar progressive developmental process.10-17 Recent studies, using
alterations in the expression of a panel of CD markers and the
transcription factors BSAP and PRDI-BF1, showed
that human PCs follow a gradient of increasing maturity in the
direction of tonsil to peripheral blood to bone marrow.18
PC differentiation is marked by the loss or down-regulation of several
molecules including major histocompatibility complex (MHC) class II,
CD19, CD20, CD22, CD44, CD45, as well as transcription factors
CIITA19 and BSAP/Pax-5.20-23 On the other
hand, PCs turn on or up-regulate the transcription factors PRDI-BF1
(Blimp-1)24,25 and MUM1/IRF4,26 the rough
endoplasmic reticulum-associated antigen Vs38c, and cell-surface
molecules CD138 and CD38.27 Recently, XBP-1 has been
identified as the only transcription factor known to be required for
the terminal differentiation of PCs.28 For a comprehensive
examination of the molecular events in PC development, see Calame's
review.27
Multiple myeloma (MM) is a tumor of terminally differentiated PCs that
home to and expand in the bone marrow.29 Although MM
appears to originate in a postgerminal center cell, as suggested by the
presence of somatic hypermutation,30,31 much speculation exists concerning the exact cell in which this malignant transformation occurs. The hypoproliferative nature of MM, with labeling indexes in
the clonal PCs rarely exceeding 1%,32 has led to the
hypothesis that MM is a tumor arising from a transformed precursor cell
that proliferates and differentiates giving rise to the clonal
expansion of terminally differentiated PCs. Indeed, the bone marrow of
patients with multiple myeloma contains BC populations at different
stages of differentiation that are clonally related to the malignant PCs.33 Corradini and colleagues have shown that bone
marrow BCs, transcribing the MM PC-derived VDJ gene joined to
immunoglobulin M (IgM) sequence in IgG- and IgA-secreting MM, can
exist.34 Other investigations have shown that the
clonogenic cell in MM originates from a preswitched but somatically
mutated BC that lacks intraclonal variation.30,31
Detection of a high frequency of circulating BCs that share clonotypic
Ig heavy-chain VDJ rearrangements with MM PCs using single-cell in situ
reverse transcriptase-polymerase chain reaction (RT-PCR) has furthered
this hypothesis.35
Microarray analysis of global gene expression patterns has become a
powerful means of identifying clinical subgroups of hematopoietic neoplasms.36-42 Alizadeh et al used gene expression
profiling to identify distinct clinical entities of diffuse large
B-cell lymphoma (DLBCL) related to either pregerminal or postgerminal
center B cells with the pregerminal center-like group having a poorer
clinical course.37 The conclusions of these studies were
exquisitely dependent on the ability to put DLBCL gene expression in
the context of cells representing different stages of normal BC differentiation.
Here we show that comparative microarray profiling of CD19-enriched
tonsil BCs with CD138-enriched PCs from tonsil and bone marrow allowed
the identification of previously defined and novel genes differentially
expressed during late stage BC development. Hierarchical clustering of
MM and normal samples using these genes revealed that subsets of MM
could be linked to the 3 normal cell types studied. These MM clusters
were found to be consistent with previously defined unsupervised gene
expression defined subgroups, such that MM4, MM3, and MM2 have tonsil
BC-like, tonsil PC-like, or bone marrow PC-like expression features, respectively.
Cell isolation and analysis
Cytospin preparations were prepared following microbead enrichment and
cells fixed and stained using DiffQuick (Dade Diagnostics, Aguada,
Puerto Rico). Both CD19- and CD138-enriched cells were subjected to immunofluorescence microscopy for cytoplasmic
immunoglobulin light chain (cIg) expression. The analysis was performed
essentially as described.43 Briefly, cytospin preparations
of cells were fixed in 100% ethanol and stained with 100 µL of a
1:20 dilution of AMCA (7-amino-4-methylcourmarin-3-acitic acid)
conjugated goat anti-human-kappa immunoglobulin light chain (Vector
Laboratories, Burlingame, CA), washed 2 times in 1 × PBD (1 × PBS + 0.1% NP-40), then 100 µL of a 1:100 dilution of
fluorescein isothiocyanate (FITC)-conjugated goat anti-human-lambda
immunoglobulin light chain (Vector Laboratories) washed and stained
with propidium iodide at 0.1 µg/mL in 1 × PBS for 5 minutes,
washed in 1 × PBD, and antifade added (Molecular Probes, Eugene,
OR). Cells were visualized using an Olympus BX60 epifluorescence
microscope (Olympus, Melville, NY) equipped with appropriate filters.
Fluorescence-activated cell sorting (FACS) analysis was performed on
unpurified mononuclear cells and CD19-enriched or CD138-enriched cells
using FITC-labeled CD20, phycoerythrin (PE)-labeled CD38, FITC- or
PE + Texas Red-labeled CD45, PE- or PE + Cy5-labeled CD138, and isotype-matched control G1 antibodies (Beckman Coulter, Miami, FL). For detection of CD138 after CD138 microbead enrichment, we
employed an indirect detection strategy using an FITC-labeled rabbit
anti-mouse IgG antibody (Beckman Coulter). Cells were taken after
Ficoll Hypaque gradient or after microbead enrichment, washed in PBS,
and stained at 4°C with antibodies. After staining, cells were
resuspended in 1 × PBS and analyzed using an Epics XL-MCL flow
cytometry system (Beckman Coulter).
RNA purification and microarray hybridization and analysis
Gene expression data analysis Hierarchical clustering of average linkage clustering with the centered correlation metric was employed.44 A total of 3228 genes were scanned across 7 cases each of tonsil BCs, tonsil PCs, bone marrow PCs, and MM PCs. The 3228 genes were derived from 6800 by filtering out all control genes, all genes with absent absolute calls, and genes not fulfilling the test of Max-Min greater than 3.0 (3.0 being the natural log of the average difference call).Gene expression profiles of 7 CD19-enriched BCs were compared with
those from 11 CD138-enriched tonsil PC samples. The genes differentiating these 2 groups were defined as early differentiation genes (EDGs). Gene expression profiles of the same 11 tonsil PC samples
were compared with those of 31 CD138-enriched bone marrow PCs. The most
significantly differentially expressed genes in this comparison were
defined as late differentiation genes (LDGs). The first test applied
was a chi-square test ( To compare gene expression levels, the nonparametric Wilcoxin rank sum
(WRS) test (P < .0005) was applied to natural
log transformed average difference call (an Affymetrix algorithm-based
quantitative measure of gene expression). In this analysis, 496 and 646 discriminated between tonsil BCs and tonsil PCs and tonsil PCs and bone
marrow PCs, respectively. By combining the To classify MM with respect to EDGs and LDGs, 74 newly diagnosed cases of MM and the tonsil BC, tonsil PC, and bone marrow PC samples were tested for variance across the 359 EDGs and 500 LDGs using a one-way analysis of variance (ANOVA) test. The top 50 EDGs showing the most significant variance across all samples were defined as variable EDGs (vEDGs); likewise, the top 50 LDGs showing the most significant variance were defined as variable 1 LDGs (v1LDG). Subtracting the v1LDGs from the 500 LDGs and then applying one-way ANOVA to the remaining genes was used to identify variable 2 LDGs (v2LDG). Hierarchical clustering was applied to all samples using the vEDGs, v1LDGs, and v2LDGs. Of the 50 vEDGs, 20 were left out of the clustering analysis because these genes generally showed no variability across the MM sample group and thus could not be used to distinguish MM subgroups. These genes were filtered out by applying the Max-Min greater than 2.5 test.
Cell analysis of CD19-enriched tonsil BCs and CD138-enriched tonsil and bone marrow PCs FACS analysis of the tonsil preparations before CD19 microbead enrichment showed that approximately 70% of the cells had a CD20hi/CD38lo immunophenotype (Figure 1A). After anti-CD19 immunomagnetic bead enrichment, the CD20hi/CD38lo cells were enriched to 98% (Figure 1B) and were essentially void of CD138+ cells. A mean of 95% (SD 3%) of the cells in the 7 tonsil-derived CD19-enriched samples used for gene expression profiling had a CD20hi/CD38+/locell surface phenotype. Morphologic analysis (Figure 1B, top right) and FACS suggested that the CD19-enriched cells consisted of a combination of follicular mantle and subepithelial B lymphocytes (CD38lo, small cells) and germinal center centroblasts and centrocytes (CD38+, larger cells). Immunofluoresence staining for cIg light chain expression revealed that CD19-enriched fractions contained less than 5% cIg staining cells, indicating only a minor contamination with PCs (Figure 1B, bottom right).
FACS for the cells with a PC phenotype in the tonsil mononuclear
fractions revealed that CD38hi/CD45 CD38/CD45 and CD138/CD45 dual-color FACS analysis of the bone marrow
mononuclear cell samples from healthy donors revealed that between
0.5% and 2% of the population appeared to be PCs (Figure 1E). The
percentage of CD38hi/CD45 Comparative gene expression profiling of CD19- and CD138-enriched B-cell populations The expression patterns of approximately 6800 genes were determined for CD19-enriched tonsil BCs, CD138-enriched tonsil PCs, and bone marrow PCs using Affymetrix high-density oligonucleotide microarrays. The mean average difference call for a panel of CD markers and transcription factors known to change during PC development was compared across the 3 normal cell types (Table 1). Genes for CD45, CD20, CD79B, CD52, CD19, CD22, CD83, and CD72 showed high expression in tonsil BCs, intermediate levels in tonsil PCs, and low or absent expression in bone marrow PCs. CD21 showed no significant differences in the tonsil BC to tonsil PC comparison, but showed a significant reduction in bone marrow PCs. Conversely, CD138, CD38, and CD63 were absent or weakly expressed on tonsil BCs, with intermediate levels on tonsil PCs, and high in bone marrow PCs. To our knowledge, this is the first indication that CD63 may be differentially regulated during PC differentiation. CD27 showed significant up-regulation in the comparison of tonsil BCs to tonsil PCs; however, the tonsil and bone marrow PCs showed no significant differences.
Expression of the transcription factor IRF4 was significantly elevated in tonsil PCs compared with tonsil BCs and was higher in bone marrow PCs than in tonsil PCs. XBP1 showed a more than 4-fold increase in expression in the comparison of tonsil BCs to tonsil PCs, but no significant difference between tonsil and bone marrow PCs. On the other hand, CTIIA, STAT6, and BLK (a direct target of BSAP or PAX5,20-23) and the BCL2 homologue BCL2A1 were down-regulated in the tonsil BC to tonsil PC transition, whereas BCL6 was down-regulated in the tonsil PC to bone marrow PC transition. Although not present on the HuGeneFL GeneChip, recent studies using the U95Av2 GeneChip, have revealed that Blimp-1 (PRDM1) expression is significantly elevated in both tonsil and bone marrow PCs compared with tonsil BCs (our unpublished data, May 2002). Interestingly, whereas MYC showed significant down-regulation in the tonsil BC to tonsil PC transition, it was reactivated in bone marrow PCs to levels higher than those in the tonsil BCs. Whereas the chemokine receptors CXCR4 and CXCR5 showed down-regulation in the tonsil BC to tonsil PC transition, CXCR4, like MYC, was reactivated in bone marrow PCs. We next used
A total of 310 of 500 (62%) LDGs were up-regulated or turned on in the tonsil PC to bone marrow PC transition. This is in contrast to the EDG where a majority of the genes were turned off or down-regulated in the tonsil BC to tonsil PC transition. The 50 most significantly differentially expressed EDGs are listed in Table 3. Although 16 EDGs were transcription factors, only 5 LDGs belonged to this class. The BMI1 gene, which was an up-regulated EDG, was also an up-regulated LDG, indicating that the gene undergoes a progressive increase in expression during differentiation. BMI1 was the only up-regulated transcription factor. The genes MYBL1, MEF2B, and BCL6 were shut down in bone marrow PCs and the transcription elongation factor TCEA1 was also down-regulated. The largest class of LDGs (n = 16; 11 up-regulated and 5 down-regulated) coded for proteins involved in signaling. The LIM-containing protein with both nuclear and focal adhesion localization, FHL1; and the secreted protein, JAG1, a ligand for Notch, IGF1; and BMP6 were up-regulated. The dual-specific phosphatase DUSP5 and the chemokine receptor CCR2 represented genes with the most dramatically altered expression and were turned on to extremely high levels in bone marrow PCs while absent in tonsil PCs. Additional up-regulated LDGs included CAV1 and CAV2, plasma membrane proteins important in transportation of materials and organizing numerous signal transduction pathways.45 There were 4 adhesion molecules (SELPG, ITGA4, PECAM1, and EMP3) up-regulated in bone marrow PCs. As seen in the EDGs, no LDG adhesion genes were down-regulated. ARHH, which was down-regulated in tonsil PCs, also showed a significant decrease in bone marrow PCs compared with tonsil PCs. The lymphocyte-specific kinases SYK and LCK were shut off in bone marrow PCs. Consistent with a role in regulating longevity of bone marrow PCs, the antiapoptotic BCL2 was up-regulated and the proapoptotic BIK was down-regulated. A lymphoid-restricted, integral endoplasmic reticulum membrane protein LRMP (JAW1), was a down-regulated LDG, a finding consistent with previous studies showing down-regulation of this gene at the PC stage of BC development.46 Identification of genes with similar expression between MM and cells at different stages of B-cell development To provide a comprehensive assessment of the distinctions between the samples under study, we performed a hierarchical cluster analysis with 3288 genes on 7 tonsil BC, 7 tonsil PC, 7 bone marrow PC, and 7 MM PC samples (Figure 2). As expected, this analysis revealed a major division between the CD19-enriched tonsil BC samples and all the CD138-enriched PC samples, with the exception of one tonsil PC sample being clustered with tonsil BCs. The CD138-enriched PC branch was further subdivided into 2 distinct subbranches, one containing the tonsil and bone marrow PCs and the other containing the MM PCs. The tonsil and bone marrow PCs were separated on separate subbranches.
Although hierarchical clustering with 3288 genes distinguished MM from
the other normal tissues, we recognized that MM also exhibited a high
degree of variability in expression of EDGs and LDGs, with some MM
having tonsil BC- or tonsil PC-like patterns for these genes. Thus,
to determine the extent of this variability and to see if it could be
used to classify MM, a one-way ANOVA analysis of the EDGs and LDGs was
performed across the normal cell types and MM. The 50 most-variable EDG
(vEDGs) are listed in Table 4. This list
consists of 18 up-regulated and 32 down-regulated EDGs that exhibit
tonsil BC-like expression in all MM. The cyclin-dependent kinase 8 (CDK8), which was undetectable ("
Having identified tonsil PC-like MM genes in v1LDGs, we sought to
identify a subset of LDGs that had bone marrow PC-like expression in
MM. By subtracting the v1LDGs from the 500 LDGs we were able to
eliminate the genes with tonsil PC-like expression from the list of
LDGs. Applying one-way ANOVA to the remaining genes allowed the
identification of so-called variable 2 LDGs (v2LDGs). Unlike the vEDGs
and v1LDGs, whose expression in subsets of MM resembled that seen in
tonsil BCs and tonsil PCs, respectively, v2LDGs tended to show
similar expression levels between bone marrow PCs and subsets of MM
(Table 6). All v2LDGs showed variability
within MM and the variability could be dramatic. For example, whereas expression of the apoptosis-inducer BIK was absent in bone
marrow PCs, the expression ranged from negative to 4-plus in
MM. A large class of v2LDGs represented genes coding for enzymes
involved in metabolism with a majority involved in glucose metabolism. Metabolism genes were not a predominant class in vEDGs and v1LDGs.
Hierarchical cluster analysis with vEDGs, v1LDGs, and v2LDGs reveals relationships between gene expression-based and developmental stage-based groups of MM To identify whether the variability in gene expression seen in MM might be used to identify subgroups of disease, we performed hierarchical cluster analysis of 74 newly diagnosed MM cases, 7 tonsil BC, 7 tonsil PC, and 7 bone marrow PC samples using the vEDGs (Figure 3A). The cluster analysis created 2 major branches, one containing the tonsil BCs and one containing the tonsil PCs and bone marrow PCs intermingled. A total of 22 of the 74 MM cases clustered with the tonsil BCs. We have previously shown that the 74 MM cases used in this study could be separated into 4 distinct gene expression-defined subgroups (MM1 through MM4).42 An analysis of the 22 MM cases clustering with the tonsil BCs revealed that 13 of 18 MM4, 5 of 15 MM3, 1 of 21 MM2, and 3 of 20 MM1 cases (P = .000 05) made up this group (Table 7). An identical clustering approach was applied to the v1LDGs (Figure 3B). As expected, v1LDG clustering segregated bone marrow PCs and tonsil PCs into 2 major cluster branches. The tonsil BCs were tightly clustered together on a separate subbranch of the tonsil PC branch. A total of 29 MM cases were clustered with the tonsil PCs. Here, 3 of 18 MM4, 14 of 15 MM3, 4 of 21 MM2, and 8 of 20 MM1 clustered with the tonsil PCs (P = .000 008) (Table 7). Clustering with the v2LDGs again created 2 major branches segregating the bone marrow PCs from the tonsil BCs and PCs (Figure 3C). A subbranch on the bone marrow PC branch contained all bone marrow PC samples and 20 MM cases. Here, the gene expression subgroup distribution of the MM cases was 0 of 18 MM4, 0 of 15 MM3, 14 of 21 MM2, and 6 of 20 MM1 (P = .000 001; Table 7). Whereas all MM3 cases were able to be classified, 6 MM1, 5 MM2, and 3 MM4 cases did not cluster with any of the normal cell groups in 3 cluster analyses performed. A total of 3 MM1, 2 MM2, 4 MM3, and 1 MM4 cases could be clustered in 2 groups. With the exception of sample P241, which clustered with the bone marrow PCs and tonsil BCs, all cases clustering with 2 different normal cell types were always in adjacent, temporally appropriate, groups, such as tonsil PC and bone marrow PC. No samples were found to cluster with all 3 normal cell types. Thus, these data suggest that MM4, MM3, and MM2 subtypes have similarities to tonsil BCs, tonsil PCs, and bone marrow PCs, respectively. MM1 represented the only subgroup with no strong correlation with the normal cell counterparts tested here.
The cyclin B gene (CCNB1), which is expressed in
proliferating cells, was identified as a vEDG (Table 4). CCNB1
exhibited high average difference calls in tonsil BCs and the MM4
subgroup. CD19-enriched tonsil BCs and MM4 also exhibit elevated
expression of other proliferation-associated genes including
MKI67 and PCNA (Zhan et al42 and our
unpublished data, January 2002). In order to extend the
relationship between tonsil BCs and MM4, we compared the expression
patterns of a panel of proliferation-associated genes
(CCNB1, CKS1, CKS2, SNRPC,
EZH2, KNSL1, PRKDC, and
PRIM1) across all normal samples and the 4 MM subgroups
(Figure 4A). Kruskal-Wallis tests
revealed that expression differed across the samples
(P < 4.25 × 10
Additional evidence for a link between MM4 and tonsil BCs is supported
by the expression pattern of the transcription factor XBP1
(Figure 4B). XBP1 was identified as an EDG (Table 2)
but was not in the list of the 50 most significant vEDGs. A
Kruskal-Wallis test revealed significant differences across the groups
(P = 3.85 × 10
CD19-enriched BCs from human tonsil and CD138-enriched PCs from tonsil and bone marrow were used to compare the gene expression changes associated with late-stage BC differentiation. This global survey allowed the identification of previously defined and novel genes discriminating these cell types, which should aid in the elucidation of the genetic pathways involved in PC development. It is important to note that it is likely that many more novel genes remain to be discovered because only 6800 of the estimated 35000 human genes were investigated in this analysis. Although the CD19-enriched cells used in this study represented a heterogenous mixture of BCs, they appeared to represent an adequate cell population for identifying genes modulated as BCs progress to the tonsil PC stage of development, as genes known to change during this process showed significant variation in the comparison of these 2 groups. In addition, hierarchical clustering analysis with 3288 genes created 2 major branches containing either tonsil BC or PC samples. Furthermore, the 3 types of PC samples (tonsil PCs, bone marrow PCs, and MM PCs) could be further distinguished. Overall, the expression differences were consistent with the cells representing distinct stages of maturation in a direction of tonsil BCs to tonsil PCs to bone marrow PCs. Consistent with the terminal differentiation of PCs, many genes involved in cell-cycle control and DNA metabolism were found to be down-regulated in tonsil PCs. The downward modulation of the DNA ligase, LIG1, repair enzymes MSHC and RPA1, the checkpoint gene CDC20, and the cyclins CCNG2 and CCNF may have important consequences in inducing the quiescent state of PCs. The telomeric repeat binding protein, TERF2, which is one of 2 recently cloned mammalian telomere binding proteins, acts to protect telomere ends, prevent telomere end-to-end fusion, and may be important in maintaining genomic stability.47,48 It will be of interest to determine if TERF2 is down-regulated during the terminal differentiation of all cell types, and whether the lack of this gene product in tumors results in structural chromosome rearrangements, a common feature of MM. The CDC28 protein kinase 2 gene, CKS2, which binds to the catalytic subunit of the cyclin-dependent kinases and is essential for their biologic function, was the only cell-cycle gene in the LDGs being expressed in tonsil PCs, cells capable of modest proliferation,49 and extinguished in bone marrow PCs. Thus, shutting down CKS2 expression may be critical in ending the proliferative capacity of bone marrow PCs. Overall, the largest group of genes altered in these comparisons represented transcription factors. Surprisingly, 4 members of the ets family of transcription factors, ETS1, SPI1, SP1B, and ELF1, known to be expressed in the BC lineage,50 were shut down in tonsil PCs. ETS1 knock-out mice show massive increases in both splenic and peripheral blood PCs,51-53 supporting the notion that reduction of this protein is critical in PC differentiation. Given that multiple transcription factors appear to be modulated during PC differentiation, more extensive global expression profiling combined with sophisticated data mining tools may help elucidate the transcriptional networks driven by each of the various classes of transcription factors discovered in this study. MM PCs are derived from the bone marrow and are thought to represent a transformed counterpart of normal terminally differentiated bone marrow PCs. However, the dramatic differences in survival, which can range from several months to more than 10 years, suggest that MM may represent a constellation of several subtypes of disease that may reflect differences in the cell of origin. Using microarray profiling we previously demonstrated that MM can be classified into 4 distinct gene expression-based subgroups that exhibit differences in proliferation characteristics as well as clinical parameters associated with poor outcome.42 Variability in expression of the 359 EDGs and 500 LDGs in 74 newly diagnosed MM cases provided a means of classifying this malignancy, in that 3 of the 4 gene expression-defined subgroups had distinct similarities to the 3 normal cell populations studied, such that MM4, MM3, and MM2 have tonsil BC-like, tonsil PC-like, or bone marrow PC-like expression features, respectively. Most of the vEDGs used to classify MM4 as a tonsil BC-like subtype of disease belonged to a range of gene classes, including adhesion, transcription, signaling, and metabolism, with very few vEDGs being associated with cell proliferation. However, comparison of expression of a panel of proliferation genes across MM and normal cell types advanced the relationship between the MM4 group and tonsil BCs. In addition, the expression of XBP1, a transcription factor essential for PC differentiation, was significantly different across the 4 MM subgroups, with MM4 having the lowest level of the MM subgroups and thus being more similar to the tonsil BCs. A future question will be whether reduced XBP1 is a cause or effect in the apparent de-differentiated state of the MM4 subtype. It is of note that other transcription factors important in regulating PC development, for example, IRF4, BCL6, CIITA, STAT6, and PAX5, did not show the down-regulation seen with XBP1. Using the same type of analysis described in this study, we identified a panel of genes distinguishing 7 CD19-enriched peripheral blood BCs (kind gift from B. Klein) from the 7 CD19-enriched tonsil BCs. Hierarchical clustering with the most variable of these genes showed no link (P = .39) between the 4 MM subgroups and CD19-enriched peripheral blood BCs (our unpublished data, June 2002), suggesting that similarities between MM and normal BC development stages may be limited. It is important to note that MM1 was the only gene expression-defined subgroup lacking strong similarities to any of the normal cell types analyzed in our current study. It is possible that MM1 may be related to mucosal-derived PCs or peripheral blood PCs, which have recently been shown to represent a distinct type of PC.18 Although the distribution of MM2, MM3, and MM4 subgroups in the normal cell-defined clusters was significant, there were outliers. For example, the tonsil BC cluster consisted mainly of MM4 cases, but 5 MM3, 1 MM2, and 3 MM1 cases were also found in this cluster. In addition, 10 of 60 cases that could be clustered with normal cell types clustered with 2 different normal cell types depending on whether the genes used in the cluster analysis were VEDG, V1LDG, or V2LDG. Furthermore, 3 MM4, 5 MM2, and 6 MM1 cases could not be clustered with any of the normal cell types. These data demonstrate a lack of complete correlation between the class systems and that the possible plasticity seen suggests that outlier cases may have intermediate characteristics and may represent distinct clinical entities. It will be important to determine if our unsupervised gene expression-based or developmental stage-based classification system alone or in combination will represent a robust clinical stratification of MM. We anticipate that in the next year or two the clinical response data on this cohort of newly diagnosed MM cases treated with high-dose therapy and stem cell support will mature and allow us to answer this question.
We thank Eric Siegel for helpful discussions, Karin Tarte and Bernard Klein for helpful discussions and use of the peripheral blood BC samples, Dr David Parham and colleagues for providing tonsil samples, members of the Lambert Laboratory, Jena Derrick, Kelly McCastlain, John Smith, Yan Xiao, and Hongwei Xu, for technical assistance, and the clinical faculty of the MIRT for providing clinical MM samples.
Submitted June 12, 2002; accepted September 11, 2002.
Prepublished online as Blood First Edition Paper, September 26, 2002; DOI 10.1182/blood-2002-06-1737.
Supported through private funding and by grants CA55819 (B.B. and J.S.) and CA97513 (J.S.) from the National Cancer Institute, Bethesda, MD.
The publication costs of this article were defrayed in part by page charge payment. Therefore, and solely to indicate this fact, this article is hereby marked "advertisement" in accordance with 18 U.S.C. section 1734.
Reprints: John Shaughnessy Jr, Donna and Donald Lambert Laboratory of Myeloma Genetics, University of Arkansas for Medical Sciences, 4301 W Markham St, Slot 776, Little Rock, AR 72205; e-mail: shaughnessyjohn{at}uams.edu.
1. Koch G, Osmond DG, Julius MH, Benner R. The mechanism of thymus-dependent antibody formation in bone marrow. J Immunol. 1981;126:1447-1451[Abstract]. 2. Ho F, Lortan JE, MacLennan IC, Khan M. Distinct short-lived and long-lived antibody-producing cell populations. Eur J Immunol. 1986;16:1297-1301[Medline] [Order article via Infotrieve]. 3. Dilosa RM, Maeda K, Masuda A, Szakal AK, Tew JG. Germinal center B cells and antibody production in the bone marrow. J Immunol. 1991;146:4071-4077[Abstract]. 4. Benner R, Hijmans W, Haaijman JJ. The bone marrow: the major source of serum immunoglobulins, but still a neglected site of antibody formation. Clin Exp Immunol. 1981;46:1-8[Medline] [Order article via Infotrieve]. 5. Slifka MK, Matloubian M, Ahmed R. Bone marrow is a major site of long-term antibody production after acute viral infection. J Virol. 1995;69:1895-1902[Abstract]. 6. Slifka MK, Antia R, Whitmire JK, Ahmed R. Humoral immunity due to long-lived plasma cells. Immunity. 1998;8:363-372[CrossRef][Medline] [Order article via Infotrieve]. 7. Manz RA, Thiel A, Radbruch A. Lifetime of plasma cells in the bone marrow. Nature. 1997;388:133-134[CrossRef][Medline] [Order article via Infotrieve]. 8. Smith KG, Light A, Nossal GJ, Tarlinton DM. The extent of affinity maturation differs between the memory and antibody-forming cell compartments in the primary immune response. EMBO J. 1997;16:2996-3006[CrossRef][Medline] [Order article via Infotrieve].
9.
Takahashi Y, Dutta PR, Cerasoli DM, Kelsoe G.
In situ studies of the primary immune response to (4-hydroxy-3-nitrophenyl) acetyl. V. Affinity maturation develops in two stages of clonal selection.
J Exp Med.
1998;187:885-895 10. Medina F, Segundo C, Rodriguez C, Brieva JA. Regulatory role of CD95 ligation on human B cells induced in vivo capable of spontaneous and high-rate Ig secretion. Eur J Immunol. 1997;27:700-706[Medline] [Order article via Infotrieve].
11.
Merville P, Dechanet J, Desmouliere A, et al.
Bcl-2+ tonsillar plasma cells are rescued from apoptosis by bone marrow fibroblasts.
J Exp Med.
1996;183:227-236 12. Brieva JA, Roldan E, Rodriguez C, Navas G. Human tonsil, blood and bone marrow in vivo-induced B cells capable of spontaneous and high-rate immunoglobulin secretion in vitro: differences in the requirements for factors and for adherent and bone marrow stromal cells, as well as distinctive adhesion molecule expression. Eur J Immunol. 1994;24:362-366[Medline] [Order article via Infotrieve].
13.
Roldan E, Garcia-Pardo A, Brieva JA.
VLA-4fibronectin interaction is required for the terminal differentiation of human bone marrow cells capable of spontaneous and high rate immunoglobulin secretion.
J Exp Med.
1992;175:1739-1747
14.
Jego G, Robillard N, Puthier D, et al.
Reactive plasmacytoses are expansions of plasmablasts retaining the capacity to differentiate into plasma cells.
Blood.
1999;94:701-712
15.
Bhan AK, Nadler LM, Stashenko P, McCluskey RT, Schlossman SF.
Stages of B cell differentiation in human lymphoid tissue.
J Exp Med.
1981;154:737-749
16.
McMillan R, Longmire RL, Yelenosky R, Lang JE, Heath V, Craddock CG.
Immunoglobulin synthesis by human lymphoid tissues: normal bone marrow as a major site of IgG production.
J Immunol.
1972;109:1386-1394
17.
Stevens RH, Macy E, Morrow C, Saxon A.
Characterization of a circulating subpopulation of spontaneous antitetanus toxoid antibody producing B cells following in vivo booster immunization.
J Immunol.
1979;122:2498-2504 18. Medina F, Segundo C, Campos-Caro A, Gonzalez-Garcia I, Brieva JA. The heterogeneity shown by human plasma cells from tonsil, blood, and bone marrow reveals graded stages of increasing maturity, but local profiles of adhesion molecule expression. Blood. 2002;99:2154-2161[Medline] [Order article via Infotrieve].
19.
Silacci P, Mottet A, Steimle V, Reith W, Mach B.
Developmental extinction of major histocompatibility complex class II gene expression in plasmocytes is mediated by silencing of the transactivator gene CIITA.
J Exp Med.
1994;180:1329-1336 20. Morrison AM, Nutt SL, Thevenin C, Rolink A, Busslinger M. Loss- and gain-of-function mutations reveal an important role of BSAP (Pax-5) at the start and end of B cell differentiation. Semin Immunol. 1998;10:133-142[CrossRef][Medline] [Order article via Infotrieve]. 21. Nutt SL, Heavey B, Rolink AG, Busslinger M. Commitment to the B-lymphoid lineage depends on the transcription factor Pax5. Nature. 1999;401:556-562[CrossRef][Medline] [Order article via Infotrieve]. 22. Nutt SL, Eberhard D, Horcher M, Rolink AG, Busslinger M. Pax5 determines the identity of B cells from the beginning to the end of B-lymphopoiesis. Int Rev Immunol. 2001;20:65-82[Medline] [Order article via Infotrieve].
23.
Barberis A, Widenhorn K, Vitelli L, Busslinger M.
A novel B-cell lineage-specific transcription factor present at early but not late stages of differentiation.
Genes Dev.
1990;4:849-859 24. Turner CA Jr, Mack DH, Davis MM. Blimp-1, a novel zinc finger-containing protein that can drive the maturation of B lymphocytes into immunoglobulin-secreting cells. Cell. 1994;77:297-306[CrossRef][Medline] [Order article via Infotrieve].
25.
Angelin-Duclos C, Cattoretti G, Lin KI, Calame K.
Commitment of B lymphocytes to a plasma cell fate is associated with Blimp-1 expression in vivo.
J Immunol.
2000;165:5462-5471
26.
Eisenbeis CF, Singh H, Storb U.
Pip, a novel IRF family member, is a lymphoid-specific, PU.1dependent transcriptional activator.
Genes Dev.
1995;9:1377-1387 27. Calame KL. Plasma cells: finding new light at the end of B cell development. Nat Immunol. 2001;2:1103-1108[CrossRef][Medline] [Order article via Infotrieve]. 28. Reimold AM, Iwakoshi NN, Manis J, et al. Plasma cell differentiation requires the transcription factor XBP-1. Nature. 2001;412:300-307[CrossRef][Medline] [Order article via Infotrieve]. 29. Barlogie B, Shaughnessy J, Munshi N, Epstein J. Plasma cell myeloma. In: Beutler E,Lichtman M,Coller B,Kipps T, eds. William's Hematology. 6th ed. New York, NY: McGraw-Hill; 1999. 30. Bakkus MH, Van Riet I, Van Camp B, Thielemans K. Evidence that the clonogenic cell in multiple myeloma originates from a pre-switched but somatically mutated B cell. Br J Haematol. 1994;87:68-74[Medline] [Order article via Infotrieve]. 31. Vescio RA, Cao J, Hong CH, et al. Myeloma Ig heavy chain V region sequences reveal prior antigenic selection and marked somatic mutation but no intraclonal diversity. J Immunol. 1995;155:2487-2497[Abstract].
32.
Latreille J, Barlogie B, Dosik G, Johnston DA, Drewinko B, Alexanian R.
Cellular DNA content as a marker of human multiple myeloma.
Blood.
1980;55:403-408
33.
Billadeau D, Ahmann G, Greipp P, Van Ness B.
The bone marrow of multiple myeloma patients contains B cell populations at different stages of differentiation that are clonally related to the malignant plasma cell.
J Exp Med.
1993;178:1023-1031
34.
Corradini P, Boccadoro M, Voena C, Pileri A.
Evidence for a bone marrow B cell transcribing malignant plasma cell VDJ joined to C mu sequence in immunoglobulin (IgG)- and IgA-secreting multiple myelomas.
J Exp Med.
1993;178:1091-1096
35.
Szczepek AJ, Seeberger K, Wizniak J, Mant MJ, Belch AR, Pilarski LM.
A high frequency of circulating B cells share clonotypic Ig heavy-chain VDJ rearrangements with autologous bone marrow plasma cells in multiple myeloma, as measured by single-cell and in situ reverse transcriptase-polymerase chain reaction.
Blood.
1998;92:2844-2855
36.
Golub TR, Slonim DK, Tamayo P, et al.
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Science.
1999;286:531-537 37. Alizadeh AA, Eisen MB, Davis RE, et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 2000;403:503-511[CrossRef][Medline] [Order article via Infotrieve].
38.
Klein U, Tu Y, Stolovitzky GA, et al.
Gene expression profiling of B cell chronic lymphocytic leukemia reveals a homogeneous phenotype related to memory B cells.
J Exp Med.
2001;194:1625-1638
39.
Rosenwald A, Alizadeh AA, Widhopf G, et al.
Relation of gene expression phenotype to immunoglobulin mutation genotype in B cell chronic lymphocytic leukemia.
J Exp Med.
2001;194:1639-1647 40. Shipp MA, Ross KN, Tamayo P, et al. Diffuse large B-cell lymphoma outcome prediction by gene-expression profiling and supervised machine learning. Nat Med. 2002;8:68-74[CrossRef][Medline] [Order article via Infotrieve]. 41. Yeoh EJ, Ross ME, Shurtleff SA, et al. Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling. Cancer Cell. 2002;1:133-143[CrossRef][Medline] [Order article via Infotrieve].
42.
Zhan F, Hardin J, Kordsmeier B, et al.
Global gene expression profiling of multiple myeloma, monoclonal gammopathy of undetermined significance, and normal bone marrow plasma cells.
Blood.
2002;99:1745-1757
43.
Shaughnessy J, Tian E, Sawyer J, et al.
High incidence of chromosome 13 deletion in multiple myeloma detected by multiprobe interphase FISH.
Blood.
2000;96:1505-1511
44.
Eisen MB, Spellman PT, Brown PO, Botstein D.
Cluster analysis and display of genome-wide expression patterns.
Proc Natl Acad Sci U S A.
1998;95:14863-14868 45. Galbiati F, Razani B, Lisanti MP. Emerging themes in lipid rafts and caveolae. Cell. 2001;106:403-411[CrossRef][Medline] [Order article via Infotrieve].
46.
Behrens TW, Kearns GM, Rivard JJ, Bernstein HD, Yewdell JW, Staudt LM.
Carboxyl-terminal targeting and novel post-translational processing of JAW1, a lymphoid protein of the endoplasmic reticulum.
J Biol Chem.
1996;271:23528-23534
47.
Sze DM, Toellner KM, Garcia de Vinuesa C, Taylor DR, MacLennan IC.
Intrinsic constraint on plasmablast growth and extrinsic limits of plasma cell survival.
J Exp Med.
2000;192:813-821
48.
Garrett-Sinha LA, Dahl R, Rao S, Barton KP, Simon MC.
PU.1 exhibits partial functional redundancy with Spi-B, but not with Ets-1 or Elf-1.
Blood.
2001;97:2908-2912 49. Broccoli D, Smogorzewska A, Chong L, de Lange T. Human telomeres contain two distinct Myb-related proteins, TRF1 and TRF2. Nat Genet. 1997;17:231-235[CrossRef][Medline] [Order article via Infotrieve]. 50. van Steensel B, Smogorzewska A, de Lange T. TRF2 protects human telomeres from end-to-end fusions. Cell. 1998;92:401-413[CrossRef][Medline] [Order article via Infotrieve]. 51. Muthusamy N, Barton K, Leiden JM. Defective activation and survival of T cells lacking the Ets-1 transcription factor. Nature. 1995;377:639-642[CrossRef][Medline] [Order article via Infotrieve]. 52. Bories JC, Willerford DM, Grevin D, et al. Increased T-cell apoptosis and terminal B-cell differentiation induced by inactivation of the Ets-1 proto-oncogene. Nature. 1995;377:635-638[CrossRef][Medline] [Order article via Infotrieve]. 53. Barton K, Muthusamy N, Fischer C, et al. The Ets-1 transcription factor is required for the development of natural killer cells in mice. Immunity. 1998;9:555-563[CrossRef][Medline] [Order article via Infotrieve].
© 2003 by The American Society of Hematology.
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|
  A. M. Roccaro, A. Sacco, C. Chen, J. Runnels, X. Leleu, F. Azab, A. K. Azab, X. Jia, H. T. Ngo, M. R. Melhem, et al. microRNA expression in the biology, prognosis, and therapy of Waldenstrom macroglobulinemia Blood, April 30, 2009; 113(18): 4391 - 4402. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C.-M. Hogerkorp and C. A. K. Borrebaeck The Human CD77- B Cell Population Represents a Heterogeneous Subset of Cells Comprising Centroblasts, Centrocytes, and Plasmablasts, Prompting Phenotypical Revision J. Immunol., October 1, 2006; 177(7): 4341 - 4349. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Zhan, Y. Huang, S. Colla, J. P. Stewart, I. Hanamura, S. Gupta, J. Epstein, S. Yaccoby, J. Sawyer, B. Burington, et al. The molecular classification of multiple myeloma Blood, September 15, 2006; 108(6): 2020 - 2028. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 L. Nadav, B.-Z. Katz, S. Baron, N. Cohen, E. Naparstek, and B. Geiger The Generation and Regulation of Functional Diversity of Malignant Plasma Cells. Cancer Res., September 1, 2006; 66(17): 8608 - 8616. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. B. Baughn, M. Di Liberto, K. Wu, P. L. Toogood, T. Louie, R. Gottschalk, R. Niesvizky, H. Cho, S. Ely, M. A.S. Moore, et al. A novel orally active small molecule potently induces g1 arrest in primary myeloma cells and prevents tumor growth by specific inhibition of cyclin-dependent kinase 4/6. Cancer Res., August 1, 2006; 66(15): 7661 - 7667. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. H. Lee, M. Melchers, H. Wang, T. A. Torrey, R. Slota, C.-F. Qi, J. Y. Kim, P. Lugar, H. J. Kong, L. Farrington, et al. Regulation of the germinal center gene program by interferon (IFN) regulatory factor 8/IFN consensus sequence-binding protein J. Exp. Med., January 23, 2006; 203(1): 63 - 72. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Ely, M. Di Liberto, R. Niesvizky, L. B. Baughn, H. J. Cho, E. N. Hatada, D. M. Knowles, J. Lane, and S. Chen-Kiang Mutually Exclusive Cyclin-Dependent Kinase 4/Cyclin D1 and Cyclin-Dependent Kinase 6/Cyclin D2 Pairing Inactivates Retinoblastoma Protein and Promotes Cell Cycle Dysregulation in Multiple Myeloma Cancer Res., December 15, 2005; 65(24): 11345 - 11353. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Lotz, S. A. Mutallib, N. Oehlrich, U. Liewer, E. A. Ferreira, M. Moos, M. Hundemer, S. Schneider, S. Strand, C. Huber, et al. Targeting Positive Regulatory Domain I-Binding Factor 1 and X Box-Binding Protein 1 Transcription Factors by Multiple Myeloma-Reactive CTL J. Immunol., July 15, 2005; 175(2): 1301 - 1309. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. L. Bergsagel, W. M. Kuehl, F. Zhan, J. Sawyer, B. Barlogie, and J. Shaughnessy Jr Cyclin D dysregulation: an early and unifying pathogenic event in multiple myeloma Blood, July 1, 2005; 106(1): 296 - 303. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Moir, A. Malaspina, O. K. Pickeral, E. T. Donoghue, J. Vasquez, N. J. Miller, S. R. Krishnan, M. A. Planta, J. F. Turney, J. S. Justement, et al. Decreased Survival of B Cells of HIV-viremic Patients Mediated by Altered Expression of Receptors of the TNF Superfamily J. Exp. Med., September 6, 2004; 200(5): 587 - 600. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Fonseca, B. Barlogie, R. Bataille, C. Bastard, P. L. Bergsagel, M. Chesi, F. E. Davies, J. Drach, P. R. Greipp, I. R. Kirsch, et al. Genetics and Cytogenetics of Multiple Myeloma: A Workshop Report Cancer Res., February 15, 2004; 64(4): 1546 - 1558. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
U. Heider, I. Zavrski, C. Jakob, C. Fleissner, O. Sezer, A. C. W. Zannettino, B. Pan, A. N. Farrugia, G. J. Atkins, and L. B. To Identification and Clinical Relevance of Receptor Activator of Nuclear Factor {kappa}B Ligand Expression of Myeloma Cells Cancer Res., January 15, 2004; 64(2): 773 - 775. [Full Text] [PDF]
|
|
|
|
 |
|
 J.-L. Harousseau, J. Shaughnessy Jr., and P. Richardson Multiple Myeloma Hematology, January 1, 2004; 2004(1): 237 - 256. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Tian, F. Zhan, R. Walker, E. Rasmussen, Y. Ma, B. Barlogie, and J. D. Shaughnessy Jr. The Role of the Wnt-Signaling Antagonist DKK1 in the Development of Osteolytic Lesions in Multiple Myeloma N. Engl. J. Med., December 25, 2003; 349(26): 2483 - 2494. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
P. A. Croonquist, M. A. Linden, F. Zhao, and B. G. Van Ness Gene profiling of a myeloma cell line reveals similarities and unique signatures among IL-6 response, N-ras-activating mutations, and coculture with bone marrow stromal cells Blood, October 1, 2003; 102(7): 2581 - 2592. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Shaughnessy Jr Primer on Medical Genomics Part IX: Scientific and Clinical Applications of DNA Microarrays--Multiple Myeloma as a Disease Model Mayo Clin. Proc., September 1, 2003; 78(9): 1098 - 1109. [Abstract] [PDF]
|
|
|
|
|
|
K. Tarte, F. Zhan, J. De Vos, B. Klein, and J. Shaughnessy Jr Gene expression profiling of plasma cells and plasmablasts: toward a better understanding of the late stages of B-cell differentiation Blood, July 15, 2003; 102(2): 592 - 600. [Abstract] [Full Text] [PDF]
|
|
|
|
|
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K.-D. Wu, L. M. Orme, J. Shaughnessy Jr, J. Jacobson, B. Barlogie, and M. A. S. Moore Telomerase and telomere length in multiple myeloma: correlations with disease heterogeneity, cytogenetic status, and overall survival Blood, June 15, 2003; 101(12): 4982 - 4989. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. Shaughnessy, J. Jacobson, J. Sawyer, J. McCoy, A. Fassas, F. Zhan, K. Bumm, J. Epstein, E. Anaissie, S. Jagannath, et al. Continuous absence of metaphase-defined cytogenetic abnormalities, especially of chromosome 13 and hypodiploidy, ensures long-term survival in multiple myeloma treated with Total Therapy I: interpretation in the context of global gene expression Blood, May 15, 2003; 101(10): 3849 - 3856. [Abstract] [Full Text] [PDF]
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Top
Abstract
Introduction
2) of the absolute call
(an Affymetrix algorithm-based parameter of whether the gene is absent
or present). In each comparison, genes with 
cells
represented between 1% and 2% and
CD138hi/CD45
," absent
absolute call) in tonsil BCs, was up-regulated to a
"++++" level in both tonsil and bone marrow PCs, but was either
absent or at a "+" or "+ +" level in all MM cases,
representing one of the most dramatic examples of a vEDG. Of the 50 v1LDGs (Table 
