Chang, Shi

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 Bortezomib and related proteasome inhibitors have profound pre-clinical and clinical activity in Multiple Myeloma (MM). However, the critical molecular target(s) modulated by proteosome inhibition remains unknown. The overall response rate to bortezomib in relapsed and refractory MM patients is consistently 35%–50%, suggesting specific molecular targets or resistance mechanisms are inherent in patients. None of the known effects of bortezomib has been shown to correlate with clinical responses in patients or to explain the unique sensitivity of MM (as opposed to other malignancies) to these reagents. Therefore, in this study, we have conducted a small interfering RNA (siRNA) screen of the druggable genome in human myeloma cells to identify genes that modulate sensitivity to bortezomib. KMS11 human myeloma cells were reverse transfected with 13,984 synthetic short interfering RNAs (siRNA) against each of 6992 druggable targets (2 siRNA/gene with a single-siRNA per well/384 well format). At 24 hours post transfection, bortezomib was added at IC10, 30, 60 and 90. Cell viability was measured by ATP-dependent luminescence assay 72 hours post drug treatment. The resulting data from primary screening was evaluated for multiple quality control metrics and found to exceed all expected performance parameters with >99% global transfection efficiency, <0.25 CV values across the dataset with minimal plate-to-plate and set-to-set variation observed. From analysis of the primary screening data, a core panel of 320 (4.6% of druggable targets in library) bortezomib sensitizers were identified. 187 (58%) of these were further confirmed in a secondary screening experiment by multiple (2 to 4) independent siRNA. Among these 187 genes (2.6% of the genes investigated), some known targets, such as proteasome subunits are evident. Other genes belonging to the same functional gene families (e.g. TNF receptor family, Ras family, kinases, oncogenes and transporter proteins) or functioning within the same network of signal transduction (e.g. NF-kB, Wnt and estrogen receptor pathways) are evident. Our primary screen also identified genes that attenuate bortezomib-induced cytotoxicity. Members in this group include genes implicated in the negative regulation of cell proliferation and survival, such as NF-kB inhibitors, JNK pathway activators, tumor suppressors, apoptosis inducers and phosphatases. These studies enable dissection of the molecular mechanism of bortezomib in myeloma cells and may serve to point to biomarkers for response prediction and novel chemotherapeutic combination therapies.

Abstract The oncogene c-maf is frequently over-expressed in multiple myeloma cell lines and patient samples and contributes to increased cellular proliferation in part by inducing cyclin D2 expression. Therefore, small molecules that inhibit c-maf and its targets could be useful chemical probes to better understand the role and regulation of this protein. We developed a high throughput chemical screen in NIH 3T3 cells stably over-expressing the promoter of the c-maf target cyclin D2 driving firefly luciferase. From a screen of 2400 off-patent drugs and chemicals, we identified 32 compounds that preferentially reduced cyclin D2 transactivation. Of these, 24 of the 32 hits belonged to the corticosteroid family of drugs. Indeed, the screen identified 24 of the 26 corticosteroids in the library. The most potent inhibitors were glucocorticoids such as dexamethasone. Mineralocorticoids such as fludrocortisone were weak hits, reflecting their weak glucocorticoid activity. The 24 glucocorticoids identified in this screen preferentially reduced cyclin D2 transactivation in the presence of c-maf. For example, the IC50 of dexamethasone was 11 ± 0.7 nM and >50 uM in NIH 3T3 cell with and without c-maf, respectively. Given the effects of glucocorticoids on c-maf in NIH 3T3 cells, we extended our investigation to multiple myeloma cell lines and demonstrated that nanomolar concentrations of the glucocorticoid dexamethasone reduced levels of c-maf protein and its target cyclin D2 within 6 hours of treatment. C-Maf was down regulated in isogenic MM1.S but not MM1.R cells respectively sensitive and resistant to dexamethasone. We also observed reductions in another c-maf target, beta integrin. Compared to cell lines RPMI 8226 and OCIMY5 that harbor the t(14;16) c-maf translocation, the concentration of dexamethasone required to reduce c-maf was approximately 50-fold lower in cell lines such as LP1 and OPM1 that lack the translocation but over-express c-maf. While dexamethasone reduced c-maf protein, no changes in levels of c-maf mRNA were detected. In both multiple myeloma and NIH3T3 cells, dexamethasone increased the ubiquitin-dependent destruction of c-maf. Finally, we linked glucocorticoids to c-maf ubiquitination by demonstrating that dexamethasone upregulated ubiquitin C mRNA at concentrations associated with the ubiquitination of c-maf. Moreover, ectopic expression of ubiquitin cDNA recapitulated the effects of dexamethasone and reduced levels of c-maf, suggesting that increased expression of ubiquitin C by dexamethasone is functionally important for dexamethasone’s effects on c-maf levels. Conclusion: a chemical biology screen identified glucocorticoids as c-maf dependent inhibitors of cyclin D2 transactivation. Glucocorticoids reduce c-maf by promoting its ubiquitination via the upregulation of ubiquitin C mRNA. This work provides new insights into the regulation of c-maf and has identified a novel mechanism by which glucocorticoids exert an anti-myeloma effect.

SummaryWe constructed a multiple myeloma (MM)‐specific gene panel for targeted sequencing and investigated 72 untreated high‐risk (del17p) MM patients. Mutations were identified in 78% of the patients. While the majority of studied genes were mutated at similar frequency to published literature, the prevalence of TP53 mutation was increased (28%) and no mutations were found in FAM46C. This study provides a comprehensive insight into the mutational landscape of del17p high‐risk MM. Additionally, our work demonstrates the practical use of a customized sequencing panel, as an easy, cheap and fast approach to characterize the mutational profile of MM.

Abstract Despite recent advances in targeted treatments for multiple myeloma, optimal molecular therapeutic targets have yet to be identified. To functionally identify critical molecular targets, we conducted a genome-scale lethality study in multiple myeloma cells using siRNAs. We validated the top 160 lethal hits with four siRNAs per gene in three multiple myeloma cell lines and two non-myeloma cell lines, cataloging a total of 57 potent multiple myeloma survival genes. We identified the Bcl2 family member MCL1 and several 26S proteasome subunits among the most important and selective multiple myeloma survival genes. These results provided biologic validation of our screening strategy. Other essential targets included genes involved in RNA splicing, ubiquitination, transcription, translation, and mitosis. Several of the multiple myeloma survival genes, especially MCL1, TNK2, CDK11, and WBSCR22, exhibited differential expression in primary plasma cells compared with other human primary somatic tissues. Overall, the most striking differential functional vulnerabilities between multiple myeloma and non–multiple myeloma cells were found to occur within the 20S proteasome subunits, MCL1, RRM1, USP8, and CKAP5. We propose that these genes should be investigated further as potential therapeutic targets in multiple myeloma. Cancer Res; 72(3); 757–68. ©2011 AACR.