Price-Troska, Tammy

Abstract Cancer/testis antigens (CTAs), comprising the MAGE, CTAG, SSX and GAGE families, are expressed in different tumor types and restricted in normal tissues to germ cells of the testis. Many CTAs contain epitopes recognized by cytotoxic T cells and are potential targets for active immunotherapy. In MM, different CTAs have been shown to be expressed in cell lines and patient cells, and are associated with more proliferative and advance stage tumors. However, correlation with survival has never been reported. We undertook a global survey of CTA expression using gene expression profiling of CD138-enriched plasma-cell (PC) RNA in 15 normal, 101 MM, 22 MGUS and 24 SMM samples using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). 22 CTA genes were differentially expressed across the samples and unsupervised clustering using these genes clearly identifies a group of patients with high CTA expression. Most CTAs have significantly higher expression in MM as compared to SMM and especially MGUS, which has similar expression as normal PCs. As these antigens are not expressed in normal PCs, an upper limit of normal expression (ULN) was derived based on mean+3SD of expression in normal PCs for each CTA. A strict cut-off of normalized expression value greater than 2xULN was used to assign positive expression for each CTA genes. Using this method, the most commonly expressed CTAs are MAGE-A3 (73% of MM), MAGE-C1 (45%), MAGE-A6 (35%), SSX-1 (21%), GAGE-5 (18%) and NY-ESO-1 (14%). We then assigned patients with expression of more than 2 of these genes as having a CTA signature and correlated with clinical parameters. 45 patents (41 MM and 4 SMM) have the CTA signature. These patients have a significantly higher PCLI (median 0.2 v 0.7, p=0.0003). In fact, there is a significant correlation between the number of positive CTAs and PCLI (r=0.59, p<0.0001). Interestingly, there is no association between patients with a CTA signature and any of the recurrent genetic abnormalities (IgH translocations, chromosome 13 deletion and TC classes), yet MM patients with this signature have a significantly shorter survival (median 459 days vs not reached, log-rank p=0.017). A prognostic hierarchy exists amongst these CTAs. Only MAGE-A6, MAGE-A12, SSX-1 and SSX-5 expression has significant prognostic implications with the SSX family conferring the worse prognosis. Using a restricted panel of 3 CTAs (SSX-1, -5 and MAGE-A12), about 28% of MM patients expressing one or more of these genes can be identified with poor survival (median less than 1 year) that is independent of genetic subtypes. The genes differentially expressed between patients with and without the CTA signature are mainly involved in cell cycle regulation. Since the expression of this large set of CTAs appears to be under epigenetic control, we speculate that the same epigenetic processes that lead to dysregulation of the cell cycle also cause ectopic expression of CTA genes. As CTA expression is rare in MGUS, epigenetic processes may therefore also mediate transformation from MGUS to MM. These poor prognosis patients represent good candidates for novel therapies targeting the epigenetic machinery.

Abstract Hyperdiploid myeloma (H-MM) affects about 50% of MM. These patients exhibit significant karyotypic and clinical heterogeneity. In this study, we addressed possible biological heterogeneity within H-MM by gene expression profiling of CD138-enriched plasma-cell RNA from 53 H-MM patients using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). Analysis was performed using GeneSpring 7 (Agilent Technologies, Palo Alto, CA). Unsupervised hierarchical clustering performed using the top 100 most variable genes (generated by ANOVA) identifies 4 putative patient clusters. These clusters were reproduced using principal component analysis. Cluster 1 was characterized by high expression of a large group of cancer testis antigens and mitosis/proliferation related genes (TOP2A, NEK, ASPM, CENPA). Cluster 2 was characterized by high expression of genes involved in IL-6 and HGF signaling (MET, IL6R, SOCS3, SPINT1). Cluster 3 was characterized by high expression of genes involved in TNF/NF-KB signaling and anti-apoptosis (NFKB2, CFLAR, BIRC3, TNFAIP3, RRAS2). Cluster 4 was characterized by high expression of genes involve in angiogenesis (protocadherin, EDNRB). Unsupervised hierarchical clustering using the same set of genes in an independent cohort of H-MM patients (n=60) yielded the same 4 patient clusters over-expressing similar genes. The gene expression profile of these clusters were not driven by differences in trisomies (only about 25% of genes that define the clusters were located on the commonly trisomic chromosomes). Association between the 4 clusters and clinical parameters such as survival, chromosome 13 deletion (Δ13), presence of IgH translocations, PCLI, RAS mutation and p16 methylation was analyzed. Cluster 1 tumors were more proliferative (median PCLI 3.8, p<0.05). Cluster 2 was associated with presence of Δ13 (56%, p<0.05) although none of the genes that defined this cluster falls on chromosome 13. p16 methylation was also less common in cluster 2 (13%, p=0.06). Cluster 3 was associated with low PCLI (median 0.2, P<0.05). Most of the patients with p16 methylation also belonged to this cluster (67%, p=0.06). There was a complete absence of Δ13 in Cluster 4. Patients in the 4 clusters also had significantly different survival (log-rank p=0.002.). The difference in survival was independent of Δ13 since Δ13 has no impact on survival in this patient cohort. The molecular profiles of these subclasses may explain some of these associations. CTA expression is associated with proliferative tumors with poor prognosis. IL-6 is an important survival factor and HGF signaling has been associated with poor survival in MM which may explain the relative poor prognosis of this group. Cluster 3 may have better survival as it is associated with an anti-apoptotic signature rather than proliferative signature. In summary, gene expression profiling identified 4 sub-classes within H-MM (validated on an independent dataset and using different clustering techniques) with distinct clinical and biological associations. The gene signature associated with each sub-classes provide a molecular basis for the different clinical behaviour and further insights into deregulated pathways in H-MM.

Abstract Background: The inactivation of p53 by deletion of 17p13 is observed in 10% of multiple myeloma patients and is associated with shorter survival. In this study we were interested in assessing p53 function in the JMW myeloma cell line established from a patient with aggressive disease and circulating plasma cells. We characterized the plasma cells derived from the patient with the disease from the initial stage of procurement ofpatient tumor cells to permanence as a cell line. Results: At diagnosis, 95% of the cells had monosomy 17 and 4% of the cells had a FISH pattern consistent with interstitial deletion of p53 (17p13). However, we observed clonal evolution in that at 3 months from diagnosis, 70% of the patient cells exhibited a deletion of the p53 locus while 28% of the cells had a monosomy 17. This may be attributed to favored clonal expansion of the cells with the deletion of p53 (17p13). To resolve this issue we performed further interphase and metaphase FISH and found an unbalanced complex translocation resulting in LOH of 13q and 17p (der13 t(13;17)(q?;p?). In addition, we screened the remaining p53 gene for mutations by conformation-sensitive gel electrophoresis (CSGE). PCR fragments showing abnormal CSGE-banding patterns (in exons 5 and 8) were further characterized by DNA sequence analysis and we identified a G to A splice site mutation generating an alternate splice site 21 bp into exon 5. This mutation results in a mutant protein lacking amino acids 126–132 in the DNA binding domain of p53. We observed no differences in the expression level of p53 mRNA as determined by RT-PCR analysis. We determined the effect of the deletion on p53 protein expression and function. We examined the effect of DNA damage induced by UV radiation on p53 protein levels in JMW cells, using the myeloma cell line H929 (expressing wildtype p53) as a positive control for expression. The JMW cells were exposed to UV radiation (20 J/m2) and the cells were harvested for western blot analysis 5 hours after UV damage. An increase in the level of p53 protein was observed in JMW as well as the H929 cells following UV treatment. We then investigated the activation of p53 downstream targets. The CDK inhibitor p21WAF1/CIP1 is a well-characterized p53 target that mediates G1 cell cycle arrest. Thus, we examined the levels of p21 protein following UV treatment of JMW and H929 cells. Strikingly, JMW cells lacked p21 expression in untreated cells as well as UV exposed cells suggesting that the characterized deletion in the DNA binding domain is an inactivating mutation. Conclusion: Abrogation of p53 function was observed in the JMW cells. Further analysis of the p53 pathway in JMW and other myeloma cell lines will provide an in depth understanding of the role of p53 in disease progression. The study of the p53 pathway in myeloma is highly relevant, as we have shown it to be associated with relapsing and aggressive disease, particularly with extramedullary myeloma. Our studies suggest that malignant plasma cells have the ability to survive outside of the bone marrow microenvironment but a p53 dependent checkpoint results in cell death. In clones with p53 defects the cells survive and result in extramedullary disease, including plasma cell leukemia.

Abstract Hyperdiploid (>48 chromosomes) multiple myeloma (H-MM) and high hyperdiploid (>50 chromosomes) acute lymphoblastic leukemia (H-ALL) are characterized by aneuploidy and multiple recurrent trisomies (chromosome 3,5,7,9,11,15,19 for H-MM and chromosomes X,4,6,10,14,17,18,21 for H-ALL). Little is known about the oncogenic events, consequences of the trisomies and reasons for the different recurrent trisomies. In an attempt to answer these questions, we undertook a combined gene expression and network/pathway analysis approach. Gene expression data was generated using the Affymetrix U133A chip (Affymetrix, Santa Clara, Ca) for 53 H-MM and 37 non-hyperdiploid MM (NH-MM) cases using CD138-enriched plasma-cell RNA. Gene expression data using the same chip for ALL was obtained from previous published data (Ross ME et al Blood2004; 104: 3679–3687). Analysis was performed using Genespring 7 (Agilent Technologies, Palo Alto, CA). By comparing the median expression of all genes on each chromosome between H-MM/H-ALL and their non-hyperdiploid counterparts (NH-MM and NH-ALL) for the 23 chromosomes (excluding Y), one can clearly identify the commonly trisomic chromosomes in H-ALL and H-MM. However, the relationship of gene expression was highly variable for H-MM and NH-MM as compared to H-ALL and NH-ALL which tended to have expression ratios close to 1 for the non-trisomic chromosomes. Sixty-nine percent of the differentially expressed genes generated by ANOVA analysis (p<0.001) in H-ALL were on the commonly trisomic chromosomes and were upregulated whereas the corresponding figure in H-MM is 40%. These similarities and differences probably reflect both an overall gene dosage effect and the different complexities of the karyotypes of H-MM and H-ALL compared to NH-MM and NH-ALL respectively (MM karyotypes are more complex, hence difference between H and NH-MM is greater and less confined to the trisomic chromosomes). We next performed network analysis using a curated web-based software (MetaCore, GeneGo Inc, St Joseph, MI) using the 2 sets of differentially expressed genes. Majority of genes differentially expressed in H-MM are involved in mRNA translation/protein synthesis whereas the genes differentially expressed in H-ALL were mainly involved in signal transduction. Therefore the transcriptional program that characterize the difference between H and NH-MM/ALL seem to recapitulate normal cellular function: protein synthesis in the mature secretory plasma cells and signal transduction in response to cytokines in a differentiating early-B cell. However, due to the concurrent deregulation of many genes on these trisomic chromosomes, these and other cellular programs are deregulated resulting in malignant transformation. We also intersected the 2 lists of differentially expressed genes to find genes that are up- or downregulated in both H-MM and H-ALL relative to the NH tumors. Thirteen genes including interferon response genes (TNFSF10, MX1, ZNF185) and transcription factors like RUNX1 were upregulated, whereas 13 genes including a cancer testis antigen gene (MAGED4) were downregulated in both H-MM and H-ALL. These genes may point to common oncogenic mechanisms.

Abstract Introduction: The Multiple Myeloma Research Consortium (MMRC) has established a tissue bank for the deposition of bone marrow (BM) samples from patients with multiple myeloma (MM) to be mailed and processed under good laboratory practices (GLP). To date over 300 samples have been collected. The ability for multiple sites to utilize the same GLP protocols for isolation and storage of BM for batch testing can be cost prohibitive and can introduce derived variability. Currently, limited information is available on shipped BM aspirates in regards to cell viability, cell yield, cell purity, and subsequent RNA yield and quality. Materials and methods: To test these determinants we performed a pilot study on behalf of the MMRC where samples were drawn at Mayo Clinic Rochester (MCR) pooled and split into 2 equal aliquots. One-half of each sample was processed following the provided GLP compliant standard operating procedures (SOP’s), immediately after sample procurement, at MCR. The CD138+ cells were stored in TRIZOLTM and the RNA was isolated and analyzed in a single batch. The other half of the aspirate was sent overnight to Mayo Clinic Scottsdale (MCS) where they were processed using an identical protocol. At both locations samples were tested for the following quality determinants; cell yield, RNA yield and integrity, and viability using a 3 color flow cytometric method (CD45, CD38 and 7ADD). Cell counts were performed on the CD138+ fraction to determine plasma cell recovery and a slide based immunofluorescent assay used to determine purity. RNA recovery and integrity were assessed using the Agilent BioanalyzerTM. Lastly, gene expression profiles was compared to determine the “signature” emanating from the shipment of samples. Results: In aggregate, all quality determinants showed similar values when the two sets of samples were compared. Cell viability was similar in both sets of samples as was our ability to collect a highly enriched plasma cell population. The cell yield was very similar (r2=0.52) but slightly lower in the shipped samples (median 71% of locally processed, range 40–140%), probably due to some shipment-associated apoptosis with subsequent loss of cell surface CD138 antigen. The purity of the shipped samples was very similar to that of locally processed (median 94%). Subjective qualitative analysis of the RNA was similar between both groups (shipped yield being 80% of local) with no evidence of degradation in the shipped samples. Details regarding the shipment signatures using gene expression profiling will be presented at the meeting. Conclusion: Here we show that the shipment of samples is feasible with no appreciable loss in cell yield or quality of derived products. % APOPTOTIC+ DEAD PC YIELD PURITY (%) RNA Recovered MCR MCS MCR MCS MCR MCS MCR MCS 8.9 ND 15.2 6.8 93 90 11.4 12.8 6.2 ND 2 2.8 95 99 8 17.2 17.4 8 1.4 1.4 75 88 2.2 0 2.1 18.7 2.8 1.6 96 68 7.2 2 18.1 9.5 1.2 .8 100 94 3.4 .4 5 5.0 8.5 7.2 98 91 12.6 17.8 3.7 5.1 .4 .4 88 87 ND ND 19.5 10.3 1.6 1.2 88 79 .4 3.6 29.1 ND 9.2 1.2 100 56 30.2 1.4 5.6 ND 9.2 7.6 92 88 5.2 16.8 20.3 62.8 2.4 .8 84 61 4.6 0.2 4.6 3.7 10.4 2.4 100 94 29.4 8.4 26.5 13.5 5.8 2.8 ND 97 16.8 5.8 4.5 6.2 2.2 2 100 99 10 4.4 17.5 ND 19.2 12 ND ND 16.4 14

Abstract Chromosome 13 (Δ13) abnormalities are found in greater than 50% of patients with Multiple Myeloma (MM). MM is most commonly defined by chromosome 13 monosomy or 13q loss (85%). Interstitial deletions comprise the remaining 15%. Many studies have revealed that Δ13 in MM are associated with poor survival and reduced response to therapy. Genes mapping to chromosome 13 may be involved in pathogenesis and/or progression of the disease due to loss of function from gene mutation or from epigenetic effects such as haploinsufficiency. In this study, array-based comparative genomic hybridization coupled with microarray technology (aCGH) is used to detect gene copy number loss on chromosome 13 from nine MM patient samples. Whole genome long-oligo microarrays constructed by Agilent Technologies were used which contain 40,000 genes that span the human genome with an average spatial resolution of ~75 kb. Using genomic DNA isolated from MM patients with interstitial deletions on chromosome 13, DNA was amplified, labeled and hybridized with a differentially labeled normal DNA reference to determine gene/genomic copy number changes. Arrays were analyzed to search for the minimum region of loss based upon single copy loss for a series of nearby mapping transcripts. A common region of loss of 2.2 Mb, at 13q14.2 was detected. Additionally, we investigated the correlation between genomic copy number change and the expression level for MM patients in the13q region. From an independent gene expression data set whose expression measurements were conducted with Affymetrix HG-U133A v2 microarrays, data was selected that corresponded to the samples used for current aCGH. Expression values from MM samples were divided by the mean expression values from 12 normal bone marrow samples for each gene and the resulting values were treated as surrogate ratios between MM and normal samples. Probes from both microarrays were then aligned according to their chromosomal positions and merged if their chromosomal positions overlapped. Composite chromosomal maps were generated that displayed the expression levels and copy number changes. The maps were used to differentiate chromosomal regions in 13q where copy number changes and expression levels show high correlation and regions where such correlation was not observed. Although the number of probes sampled in the expression microarray was much smaller than those in aCGH microarray, a chromosomal region of great interest, that encompasses 13q14.2, arose naturally from this analysis. Although the mechanism by which loss of 13q effects tumorigenesis in MM could be a haploinsufficiency model, we are not ruling out the presence of a tumor suppressor gene in this region. We are evaluating candidate tumor suppressor genes in the region for loss of function by mutational analysis and hypermethylation studies.

Abstract Chromosome 13 deletion (Δ13) is one the most common genetic abnormalities observed in multiple myeloma (MM) and confers a poor prognosis. Studies to identify critical tumor suppressor genes in MM till date have lack adequate resolution, and the molecular phenotype associated with Δ13 has not been established. In this study we seek to establish a molecular profile for Δ13 and to finely map the minimal common region of deletion (CDR) on chromosome 13 by using gene expression profiling (GEP) and array comparative genomic hybridization (aCGH). GEP was performed on RNA from purified plasma cells of 72 newly diagnosed MM and 50 human myeloma cell lines (HMCLs) using the Affymetrix U133A chip and U133plus chip (Affymetrix, Santa Clara, CA) respectively. Patients were assigned TC classes which correlates with underlying genetic subtypes. In addition, aCGH was performed on 79 MM samples (36 with GEP data) and 50 myeloma cell lines (HMCLs; 48 with GEP data) using a platform utilizing 60-mer oligonucleotides (Human Genome CGH 44B Oligo Microarrays, Agilent Technologies), which have a resolution of about 70Kb. Raw data was extracted using the Feature Extraction 8.1 and visualized using CGH Analytics 3.2 (Agilent Technologies). To define a signature that reflects the biological consequences of Δ13 and not its close association with some genetic subtypes of MM (example, t(4;14) and t(14;16)), we selected a training cohort consisting of cases belonging to D1, D2, 11q13 and none TC class such that cases with and without Δ13 are balanced for ploidy and TC classes (n=28). A 152-gene Δ13 signature was identified. Its specificity was confirmed by leave-one-out cross validation using the K-nearest neighbor (KNN) class prediction algorithm (predictive accuracy of 100% in the training cohort). It was subsequently validated in a validation cohort that includes t(4;14) and t(14;16) that were not use to derive this gene signature, maintaining a high predictive accuracy (88%). This gene-set may therefore reflect core transcriptional consequences of Δ13 and is enriched for genes involved in the cell cycle and apoptosis. Using aCGH, 20 patients have Δ13 (mostly whole chromosome) all involving the 13q14–q21 region. Of the 32 HMCLs with Δ13 (whole chromosome or interstitial), 22 have mono-allelic loss of RB1 whereas 4 had bi-allelic loss. Besides RB1, bi-allelic loss of several other genes in the 13q14–q21 region (CYSLTR2, CDADC1, ITM2B, PCDH9) was also observed. As the CDR is large and contains a number of genes, we utilized a set of criteria (bi-allelic loss in HMCLs, within 13q14–q21 CDR, gene expression significantly correlated with copy number, and loss could explain molecular phenotype) to narrow down the potential candidates. Only RB1 and ITM2B fulfilled these criteria. Furthermore, RB protein levels correlated well with mRNA levels and DNA copy suggesting that even in absence of mutations resulting in bi-allelic loss, mono-allelic loss of RB1 could be tumorigenic through a haploinsufficiency mechanism.

Abstract Hyperdiploid MM (H-MM), characterized by recurrent trisomies constitute about 50% of MM, yet very little is known about its pathogenesis and oncogenic mechanisms. Studies in leukemia and solid tumors have shown gene dosage effect of aneuploidy on gene expression. To determine the possible gene dosage effect and deregulated cellular program in H-MM we undertook a gene expression study of CD138-enriched plasma-cell RNA from 53 hyperdiploid and 37 non-hyperdiploid MM (NH-MM) patients using the Affymetrix U133A chip (Affymetrix, Santa Clara, CA). Gene expression data was analyzed using GeneSpring 7 (Agilent Technologies, Palo Alto, CA). Genes differentially expressed between H-MM and NH-MM were obtained by t-test (p<0.01). The majority of the differentially expressed genes (57%) were under-expressed in H-MM. Genes located on the commonly trisomic chromosomes were mostly (but not always) over-expressed in H-MM and constitute 76% of over-expressed genes. Chromosome 1 contained the most differentially expressed genes (17%) followed by chromosome 12 (9%), and 19 (8%). To examine the relationship of gene copy number to gene expression, we examined the expression of genes on chromosomes 9 and 15 in subjects with 2 copies (15 normal control and 20 NH-MM) and 3 copies (12 H-MM) of each chromosome as detected by interphase FISH. We then derived a ratio of the mean expression of each gene on these chromosomes between patients with 3 copies and 2 copies of the chromosome. If a simple relationship exists between gene expression and gene copy number, one would expect the ratio of expression of most genes on these two chromosomes to be about 1.5 in H-MM compared to NH-MM. However, many genes have ratios either higher than 2 or lower than 0.5. Furthermore, when the heterogeneity of cells with underlying trisomies is taken into consideration by correcting the ratio for the number of cells with trisomies, the actual ratio is always lower than the expected ratio. When the expression of genes on a chromosome was compressed to a median value, this value was always higher in the trisomic chromosomes for H-MM compared to NH-MM. The data suggests that although gene dosage influence gene expression, the relationship is complex and some genes are more gene dosage dependent than others. Amongst the differentially expressed genes with known function, 33% are involved in mRNA translation/protein synthesis. Of note, 37 of the top 100 differentially expressed genes are involved in these processes. In particular, 60 ribosomal protein (RP) genes are significantly (p<0.05) upregulated in H-MM. This signature in H-MM is not associated with increase proliferation as measured by PCLI. This predominant signature suggests that deregulated protein synthesis may be important for the biology of H-MM. Many of these RPs are involved in the synthesis of product of oncogenic pathways (e.g. MYC, NF-KB pathways) and may mediate the growth and survival of tumor cells. It is therefore possible that these tumor cells may be sensitive to the disruption of mRNA translation/protein synthesis. Targeting the mTOR pathway with rapamycin may therefore be useful for treatment of H-MM.

Abstract Activation of NFkB has been noted in late B-cell malignancies, but no genetic basis for this activation has been shown except for rare mutations of the NFkB pathway in lymphoma and none have been described in MM. Bortezomib, highly tumoricidal in a subset of MM patients, inhibits NFkB suggesting it’s role as a therapeutic target. Here we show for the first time the critical importance of mutations that dysregulate this potential survival pathway in human myeloma cell lines (HMCL) and new diagnosis MM patients. We performed high-density oligonucleotide array CGH (Agilent 44k) on CD138+ selected MM cells from 68 patients and 42 unique HMCL. Initially we focused on small loci, bi-allelically deleted, as markers for inactivation of potential tumor suppressor genes. We next developed FISH probes for the identified loci to confirm the bi-allelic deletions seen by aCGH. We next sequenced all samples with monoallelic deletions, and additional unselected patients, and identified additional inactivating mutations. Multiple novel tumor suppressor genes (TSG) were identified and validated, whose loss of function (both in patients and HMCL) leads to activation of the non-canonical NFkB pathway including: TRAF2 (9q34), TRAF3 (14q32), BIRC2/BIRC3 (11q22) and CYLD (16q12). Functional studies showed that HMCL with deletion or mutations in these genes have markedly increased NFkB2 p52/p100 ratios relative to other HMCL (and for BIRC2/BIRC3 relative to an isogenic line that retains one copy of BIRC2/BIRC3), indicating genetic activation of the non-canonical NFkB pathway. Reintroduction of deleted TSG into HMCL inhibited cell growth and resulted in cell death (see data on abstract by J. Keats et al). We next focused our analysis (of combined aCGH and GEP data) on positive regulators of this pathway. Rare IgH translocations of NIK have recently been identified in MM. By aCGH we identified amplification and rearrangements of NIK. We identified dysregulated expression of TNF family receptors that activate the non-canonical pathway: CD40 (translocation), TACI (amplification) and LTBR. All of the HMCL with these mutations also showed increased NFkB2 p52/p100 ratios, consistent with activation of the non-canonical NFkB. These mutations correlate with a gene expression profile of NFkB activation that is detected in one half of patients. In summary, we have determined for the first time the genetic basis for constitutive NFkB activation - present in 19/42 HMCL, and we estimate in at least one quarter of newly diagnosed patients (approximately one half of those with evidence of NFkB activation by GEP). We propose a mechanism in which positive (TACI, CD40, LTBR) and negative regulators (TRAF2, TRAF3, BIRC2/BIRC3, CYLD) of the pathway converge on NIK to mediate the processing of NFKB2 p100 to p52. The preponderance of genetic evidence suggests that drugs that target the non-canonical NFkB pathway, will be most effective in treating the 50% of MM patients with NFkB activation.

Abstract Introduction: The analysis of what goes awry in a malignant cell has focused primarily on mutations of protein-encoding genes and their regulatory sequences. However, recent work on microRNA (miRNA) has shed light on the possible involvement of miRNA genes in human disease. miRNA are small “noncoding” or “non-messenger” RNAs of about 21–25 nucleotides in length that function as regulators of gene expression essentially by pairing to the mRNA of protein-coding genes to initiate mRNA degradation or repression of translation. We are interested in characterizing miRNA expression profiles in human myeloma cell lines (HMCLs) and myeloma patient samples. Multiple myeloma (MM) is a plasma cell tumor characterized by frequent chromosomal translocations. Materials and methods: The expression of miRNA in HMCLs, primary MM cells (hyperdiploid samples) and normal plasma cells was determined using human microRNA chips. The GenoExporerTM Human microRNA chips were developed by GenoSensor (Tempe, AZ) and the microarray contains 226 human microRNA sequences in addition to control sequences. The DNA oligo probes are synthesized and immobilized on the chips (1”x 3” standard glass microslide). The probes are designed based on the active mature miRNA sequences and some of their flanking sequences. Our analysis included seven myeloma patients (hyperdiploid MM), eight different HMCLs (MM1, 8226 with t(14;16); SKMM2, U266, INA-6 with t(11;14) and H929, KMS11, UTMC-2 with t(4;14)), and eight normal human plasma cells. The normal human plasma cells were collected at Mayo Clinic Rochester from bone samples of patients undergoing orthopedic surgery. For the assay 5–10 μg of total RNA per sample were used at a concentration of 1 μg/μL. The RNA is directly labeled with biotin and used as a target for the on-chip hybridization assays. A streptavidin-Alexa dye is used to stain the hybridized targets and the fluorescent signals are captured and analyzed. The gene signal intensities were normalized to tRNA signal intensity. Results: The primary MM cells and HMCLs displayed a distinctive miRNA expression profile compared with normal plasma cells. Using the GeneSpring 7 (Agilent Technologies, Palo Alto, CA) for gene expression analysis we have identified miRNA genes with significant variation in expression levels between tumor and normal samples including miR-125b, miR-133a, miR1, and miR-124a (p<0.01). Recently defined algorithms were used to identify putative targets for the miRNA genes of interest such as leukemia inhibitory factor (LIF) as targets of miR-125b and Stat3 and angiopoietin-1 precursor as targets of miR-124a (Lewis et al. 2003). Of note, miR-15 and miR-16, previously identified to be downregulated in CLL, were expressed at low levels in some MM patients and HMCLs, but not in the normal plasma cells. Further analysis will be carried out to validate the data from miRNA profiling using northern blot analysis or real-time RT-PCR to measure expression levels of miRNA genes and that of their target genes. Conclusion: Analysis of miRNA expression pattern (along with aCGH and gene expression profiling studies) will undoubtedly refine our understanding of the various genotypic subtypes of multiple myeloma.