ALBERT

Description: Introduction The current standard to investigate centrosome aberrations on a single cell level is labeling of known centrosomal as well as core centriolar proteins by immunofluorescence (IF) staining and subsequent manual quantification of centrosomes and centrioles. This approach is, however, very time-consuming and prone to inter-observer variations. In order to systematically evaluate centrosomal aberrations as potential predictors of malignancy, reliable high throughput analyses of IF images are required. To address this unmet need, we developed a semi-automated workflow using the highly versatile data analysis platform Konstanz Information Miner (KNIME) (Berthold et al., 2008). Input data U2OS-PLK4 cells (Konotop et al., Cancer Res. 2016) were induced for centrosomal amplification and immediately processed including IF staining against pericentrin and centrin and image acquisition using a Zeiss Cell Observer and 40× 1.3 NA Plan Apochromat objective. Per condition, 300 cells were observed and allocated manually to the phenotype classes - cells with normal centrosomes, cells with clustered amplified centrosomes and cells with declustered amplified centrosomes. The workflow settings were trained with 20% of the entire data. KNIME workflow and neural network for centrosome analysis Our KNIME workflow for centrosome analysis is composed of three main functional parts: (1) Input node groups, where image data is loaded and user-specific settings are pre-defined, (2) the Image Analysis metanode which carries out the central workflow functions and is outlined in the Figure and (3) the output node groups where all data is organized into results data tables and verification views are generated. Briefly, the Image Analysis metanode identifies nuclei, cells and centrosome areas (single or clustered centrosomes) based on thresholding and extracts various features of all objects. The centrosome detection is supposed to be highly sensitive to ensure a low number of false-negative detections. False-positive detections are filtered out or tagged as "uncertain" by a pre-defined set of rules, however, the thresholds used in these rules are adapted automatically based on features of "reference spots". These are identified centrosome candidates with a high likelihood to be true centrosomes. The workflow structure allows easy adjustment to changing parameters for a broad spectrum of user applications with a similar readout. To discriminate between cells with normal and amplified centrosomes we used a feed-forward neural network classifier that assigns the cells into these classes by evaluating relevant extracted feature parameters. The network is a multilayer perceptron (layer widths 70, 10, 10, 10, 2) with nonlinear sigmoid activation functions; the output layer carries a softmax activation and yields a probability distribution over the two classes "normal" and "clustered". The training was performed by maximizing the cross-entropy loss on a dataset of 554 manually-labelled samples, 154 of which were retained for validation. Comparison of manual and automated quantification As expected, centrosomal amplification increased upon TET-induction according to manual quantification (clustered 71% vs. 21%, declustered 7.4% vs. 0.3%). The KNIME workflow was used for feature extraction and to assign the cells into the phenotype class declustered in case of 〉2 spots per cell. It tagged 43/615 cells (7%) as uncertain and almost all of the remaining cells were labeled in agreement with the manual count (one false-positive and one false-negative). Subsequently, using the features exported from the KNIME workflow, a neural network was trained to discriminate between normal and clustered amplified centrosomes. The training loss converged to 95%, i.e. 381 of 400 training samples were correctly classified, and on the hitherto unseen validation samples the network correctly classified 88%, i.e. 135 of 154 were labeled in agreement with the manual method. The combined detection of centrosome amplification by the KNIME workflow and neural network was (TET-induced vs. control): clustered 79% vs. 21%, declustered 5.6% vs. 0.3%. Conclusions We present a reliable semi-automated workflow for high throughput analysis of IF images. This tool will be particularly useful for screens of centrosomal aberrations, but can also be easily adjusted for different experimental and infrastructural setups. Figure Disclosures Goldschmidt: Mundipharma: Research Funding; MSD: Research Funding; Amgen: Consultancy, Research Funding; Adaptive Biotechnology: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Dietmar-Hopp-Stiftung: Research Funding; John-Hopkins University: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; John-Hopkins University: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Chugai: Honoraria, Research Funding; Molecular Partners: Research Funding; Janssen: Consultancy, Research Funding. Schönland:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Medac: Other: Travel Grant. Krämer:Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Daiichi-Sankyo: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bayer: Research Funding; BMS: Research Funding.

Description: In patients with multiple myeloma (MM), risk stratification by chromosomal abnormalities may enable a more rational selection of therapeutic approaches. In the present study, we analyzed the prognostic value of 12 chromosomal abnormalities in a series of 354 MM patients treated within the HOVON-65/GMMG-HD4 trial. Because of the 2-arm design of the study, we were able to analyze the effect of a bortezomib-based treatment before and after autologous stem cell transplantation (arm B) compared with standard treatment without bortezomib (arm A). For allanalyzed chromosomal aberrations, progression-free survival (PFS) and overall survival (OS) were at least equal or superior in the bortezomib arm compared with the standard arm. Strikingly, patients with del(17p13) benefited the most from the bortezomib-containing treatment: the median PFS in arm A was 12.0 months and in arm B it was 26.2 months (P = .024); the 3 year-OS for arm A was 17% and for arm B it was 69% (P = .028). After multivariate analysis, del(17p13) was an independent predictor for PFS (P 〈 .0001) and OS (P 〈 .0001) in arm A, whereas no statistically significant effect on PFS (P = .28) or OS (P = .12) was seen in arm B. In conclusion, the adverse impact of del(17p13) on PFS and OS could be significantly reduced by bortezomib-based treatment, suggesting that long-term administration of bortezomib should be recommended for patients carrying del(17p13). This trial is registered at the International Standard Randomised Controlled Trial Number Register as ISRCTN64455289.

Description: Background: The selective HDAC6 inhibitor ACY-241, a tablet, is structurally related to ricolinostat (ACY-1215), the first agent in this class in the clinic.Ricolinostat, an oral liquid, demonstrated clinical efficacy in a Phase 2 combination with pomalidomide (Pom) and dexamethasone (Dex) in patients (pts) with relapsed or relapsed-and-refractory multiple myeloma (RRMM) without toxicities greater than those reported with Pom and Dex alone (Raje et al., EHA 2016, S813). Preclinical data demonstrate synergistic activity of ACY-241 with Pom and lenalidomide (Len) in induction of cell cycle arrest and apoptosis in MM cells as well as significant extension of survival in a mouse xenograft model (Niesvizky et al., Blood 2015, 126: 3040). We present updated data on safety and efficacy of the ACY-241/Pom/Dex combination in pts with relapsed or RRMM (ACE-MM-200, NCT02400242). Aims:Determine the safety, tolerability, and preliminary efficacy of ACY-241 monotherapy and combination with Pom and Dex and the recommended dose for further development. Methods:Based on clinical experience with ricolinostat and non-clinical pharmacokinetics (PK) of ACY-241, we designed a first-in-human phase 1a/1b clinical trial of a single-cycle of ACY-241 monotherapy followed by ACY-241 in combination with Pom (4mg) and low-dose Dex in pts with relapsed or RRMM. The starting dose of ACY-241 was chosen to give similar exposure to the therapeutic dose of ricolinostat (160 mg QD). The trial design was chosen to grant pts access to combination therapy with an active regimen while exploring the safety, PK, and pharmacodynamic profile of ACY-241 alone and in combination with Pom/Dex. The PK of Pom and Dex was also assessed. Pts with relapsed or RRMM previously treated with ≥ 2 cycles of Len and a proteasome inhibitor were eligible. Cohorts of 3 pts had ACY-241 PO QD as monotherapy (180, 360 and 480 mg) on days 1-21 of a 28 day cycle. If no DLT was noted in cycle 1 with ACY-241, pts continued to cycle 2 of combo therapy with ACY-241/Pom/Dex. Pharmacodynamic assessments were acetylated tubulin (HDAC6 marker) and acetylated histones (Class 1 HDAC marker) in peripheral blood mononuclear cells. Results: Since June 2015, 40 pts have enrolled (34 safety-evaluable, 6 had no dosing information in the database). Median age was 62 (34-84) years and median number of prior regimens was 3 (1-7). 90% of pts were refractory to last treatment. 83% were refractory to Len and 50% to both bortezomib and Len. 20% of pts had high risk cytogenetics. No monotherapy DLTs were observed at the highest dose explored (480 mg). Common toxicities in the monotherapy safety population (N=15) were all grade 1/2, except 1 pt with grade 3 anemia at the 480 mg dose level. Toxicities included nausea (4 pts, 27%), anemia (3 pts, 20%), dizziness, fatigue, leukopenia and thrombocytopenia (2 pts each, 13%). Doses of 180 mg and 360 mg were explored in combination; one DLT (grade 4 thrombocytopenia) occurred at 360 mg. Common toxicities in the combination therapy safety population (N=33) included neutropenia (13 pts, 40%), fatigue (9 pts, 27%), anemia, leukopenia (6 pts each, 18%), cough, insomnia, rash (4 pts each, 12%), and hyperglycemia (3 pts, 9%). Grade 3/4 toxicities included neutropenia (10 pts, 30%), leukopenia (3 pts, 9%) and anemia (2 pts, 6%). PK results showed a dose-linear increase in exposure with increasing dose, no accumulation and no drug-drug interaction with Pom and Dex. Selective increase in acetylated tubulin was seen at 180 mg with increasing levels of acetylated tubulin and histones at higher doses. Confirmed efficacy data (median follow-up 3.5 months) for combination treatment (N=22, all refractory to last treatment regimen) shows 1 VGPR, 10 PR, 2 MR and 8 SD and 1 PD. Median PFS and duration of response were not reached at time of the data cut. Given the safety profile, PK exposure (Cmax~6 µM) and PD profile, the 360 mg QD dose level was recommended for further clinical exploration of ACY-241 in combination with Pom/Dex. Summary/Conclusion:ACY-241 is well tolerated in combination with Pom/Dex with dose proportional increase in drug exposure. Early response data to combination treatment parallel those observed with ricolinostat/Pom/Dex and compare favorably to historic controls of Pom/Dex. Cohort expansion at 360 mg ACY-241 with Pom/Dex is ongoing to confirm the dose and schedule for a planned pivotal trial of Pom/Dex +/- ACY-241 and to explore selected biomarkers. Disclosures Richardson: Jazz Pharmaceuticals: Consultancy, Membership on an entity's Board of Directors or advisory committees. Nooka:Amgen: Consultancy; Spectrum: Consultancy; Novartis: Consultancy. Raab:Amgen: Consultancy, Research Funding; BMS: Consultancy; Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Consultancy, Research Funding. Shain:Takeda/Millennium: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Novartis: Speakers Bureau; Amgen/Onyx: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Signal Genetics: Research Funding. Matous:Celgene: Consultancy, Speakers Bureau; Takeda Pharmaceuticals International Co.: Speakers Bureau; Seattle Genetics: Research Funding, Speakers Bureau. Agarwal:Celgene: Speakers Bureau; Onyx: Speakers Bureau; Janssen: Speakers Bureau; Amgen: Consultancy; Millennium: Consultancy; AbbVie: Honoraria, Research Funding. Madan:Amgen: Speakers Bureau; Onyx: Speakers Bureau; Takeda: Speakers Bureau; Celgene: Speakers Bureau. Moreau:Novartis: Honoraria; Takeda: Honoraria; Janssen: Honoraria, Speakers Bureau; Celgene: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria. Mateos:Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria; Takeda: Honoraria. Facon:Acetylon Pharmaceuticals Inc: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Tamang:Acetylon Pharmaceutical Inc.: Employment. Jones:Acetylon Pharmaceuticals, Inc.: Employment, Equity Ownership. Markelewicz:Acetylon Pharmaceutical Inc.: Employment. Wheeler:Acetylon Pharmaceuticals Inc.: Employment. Trede:Acetylon Pharmaceutials Inc: Employment. Raje:Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Membership on an entity's Board of Directors or advisory committees; BMS: Consultancy, Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Research Funding; Eli Lilly: Research Funding. Terpos:Amgen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Genesis: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Novartis: Honoraria; BMS: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Other: Travel expenses, Research Funding; Takeda: Consultancy, Honoraria; Celgene: Honoraria. Bensinger:Amgen: Honoraria; Celgene: Honoraria; Acetylon Pharmaceuticals Inc.: Honoraria; Amgen: Consultancy; Celgene: Consultancy; Sanofi: Consultancy; Merck: Consultancy; Bristol-Meyers Squibb: Consultancy; Celgene: Speakers Bureau; Takeda: Speakers Bureau; Amgen: Speakers Bureau; Acetylon Pharmaceuticals Inc: Research Funding; Bristol-Meyers Squibb: Research Funding; Celgene: Research Funding; Karyopharm Therapeutics: Research Funding; Merck: Research Funding; Amgen: Research Funding; Sanofi: Research Funding; Takeda: Consultancy.

Description: Key Points The incidence of mutations within the MAPK pathway, the CRBN pathway, and TP53 is significantly increased in drug-refractory MM. Mutations in CRBN might contribute to IMiD resistance in drug-refractory MM.

Description: Multitargeted treatment approaches have been shown to be more effective than single agent therapy in multiple myeloma (MM). In addition, agents targeting not only the MM cells directly but also their microenvironment, like bone marrow stromal cells (BMSCs), endothelial cells, and osteoclasts (OCLs) causing enhancement of tumor cell growth, angiogenesis, and MM bone disease, respectively, are promising new treatment modalities for this still non-curable disease.Here we investigated the novel, orally available multi-kinase inhibitor BAY 73-4506, currently in phase I clinical trials, for its therapeutic effect in MM. BAY is a potent inhibitor of angiogenic (VEGFR 1-3, PDGFR-b), as well as oncogenic, kinases (cKIT, RET, FGFR, Raf). We first tested the ability of BAY to suppress MM cell proliferation and survival in a wide array of MM cell lines (MM.1S, RPMI 8226, NCI H929, OPM2, KMS11, KMS 18, INA6, U266, KMS12BM, S6B45), including those resistant to conventional chemotherapeutics (MM.1R, Dox40, LR5). Our data show that BAY is active in all cell lines tested in a low micromolar range equivalent to concentrations achieved in patient plasma during the first clinical trial in solid tumors. Importantly, BAY also overcomes the growth advantage conferred in a BMSC-MM, as well as an endothelial cell-MM, coculture system. BAY treatment abrogates MEK, ERK and AKT phosphorylation in a time and dose dependent manner, followed by induction of apoptosis, evidenced by Annexin staining and DNA fragmentation. Since VEGF signaling pathway is a potent inducer of angiogenesis and BAY targets VEGFR 1-3, we examined anti-angiogenic properties of BAY. This compound inhibits endothelial cell growth and endothelial cell tubuli formation in vitro at concentrations less than 1mM; moreover, BAY markedly inhibits the VEGF-induced cell migration on fibronectin. Activation of MAP kinase is a critical event during OCL differentiation, activation, and survival; BAY inhibits osteoclastogenesis, evidenced by blockade of M-CSF/RANKL-triggered differentiation of mononuclear cells to TRAP-positive osteoclasts, an important marker of osteoclastogenesis. Finally, combination treatment of BAY with dexamethasone shows synergistic effects on MM cell growth and survival. These in vitro experiments on the effects of BAY on MM tumor cells directly, in co-culture with endothelial or BMSCs, as well as on osteoclast differentiation, provides the basis for its evaluation in a murine model of human MM to confirm these promising in vitro effects of this novel multi-kinase inhibitor, finally leading to clinical evaluation to improve patient outcome.

Description: Background: In multiple myeloma (MM), deletion of chromosome (chr.) 13q and hypodiploidy are adverse prognostic factors. Prognostic evaluation is frequently based on interphase-fluorescence in-situ hybridization (FISH) with a single probe for chr. 13q14. Patients and methods: CD138-positive bone marrow cells from 97 patients with newly diagnosed MM (58 training group (TG) and 39 validation group (VG)) were enriched by magnetic-activated cell-sorting (median purity, 95%). Sorted cells were analyzed by interphase-FISH with probes for chr. 13q14, and additionally 9q34, 11q23, 19q13, t(11;14), and t(4;14). GEP was performed with Affymetrix U133A+B (TG) and HGU133-2.0plus (VG) microarrays. Nearest shrunken centroids classification (NSC) was applied to discriminate clones with FISH-detected del(13q14) vs. those without, using VSN-normalized gene expression values. Chromosomal localization of predictor genes was determined using the MapIt program, and functional relationship was established by Gene Ontology (GO) annotation and creation of GO-slims. Results: A deletion of chr. 13q14 was found in 27/58 patients (47%) of the training and in 21/39 (54%) of the validation group. Frequencies of trisomies were lower (9q: 48 vs. 74%; 11q: 41 vs. 74%; 19q: 44 vs. 84%) and of IgH translocations higher (48 vs. 16%) in patients with del(13q14). NSC resulted in a predictor for del(13q14) of 378 probe-sets with a cross-validated classification error rate of 22%; the VG is under statistical investigation. Of the predictor genes, 18% were localized on chr. 13 (distributed evenly from 13q12 to 13q33), followed by chr. 19, 11 and 3 (10/6/6%). In the 50 probe-sets with the highest scores, the most frequent localizations of the represented genes were chr. 19, 9, and 13 (12/8/6 of 50). In 8/8 incorrectly classified patients with del(13q14), at least 2 of 3 trisomies (9q, 11q, 19q) were present, hinting at hyperdiploidy. Only 1/5 incorrectly classified patients without del(13q14) harbored 3 trisomies. Biological functions (GO level 3) of predictor genes were related to protein and DNA metabolism (43%), cell growth/maintenance (27%), and cell communication (17%). The most frequent GO term for cellular component was ribosome (34%). Sixty-nine of 80 human ribosomal protein (RP) genes were represented in the predictor, and made up 33 of the top-50 probe-sets. RP genes were overexpressed in patients without del(13q14) compared to plasma cells from 7 normal donors. Expression levels of RPL12, RPLP2 and RPL13A (on chr. 9, 11 and 19) correlated with the respective chr. copy numbers. Conclusion: FISH-detected del(13q14) is associated with non-hyperdiploidy rather than defining an independent subentity of MM. Overexpression of RP-genes in malignancies has been linked to cell growth, disease progression and drug resistance. A possible pathogenetic role of the upregulation of virtually all ribosomal protein genes observed in del(13q)-negative/hyperdiploid MM clones has to be evaluated further.

Description: We have previously shown that the novel orally available small molecule inhibitor of PKC enzastaurin (Eli Lilly and Company) inhibits MM cell growth, survival and angiogenesis both in vitro and in vivo. To date, however, the downstream effects contributing to growth inhibition and cell death remain to be determined. Here, we performed global gene expression profiling on enzastaurin treated MM cells and identified 200 Genes to be differentially regulated with a 〉 2-fold cut off. Strikingly, two major groups of up-regulated probe sets were associated with either of two pathways - endoplasmatic reticulum (ER)-stress response or WNT-signaling. Importantly, MM cells, producing high levels of paraprotein, are highly susceptible to perturbation of ER function and protein folding. Moreover, PKC isoforms have been reported to directly regulate the canonical WNT pathway via phosphorylation of b-catenin (CAT), leading to its ubiquination and proteasomal degradation. Specifically, we fist evaluated the role of enzastaurin in mediating ER-stress in MM cells. The transcriptional up-regulation of genes involved in ER-stress (GADD153/CHOP, GADD34, ATF3), triggered by enzastaurin at 3h, was confirmed by western blot analysis, accompanied by induction of the molecular ER chaperone BiP/grp78, phosphorylation of eIF2a consistent with PERK activation, and up-regulation of p21. These events were preceded by an early (1h) increase of intracellular calcium levels, a hallmark of ER-stress, assessed by FLUO4 staining. These data suggest an important role of ER-stress response in the early growth inhibition of MM cells caused by enzastaurin. Second, we delineated effects of enzastaurin on WNT pathway in MM and other tumor cell lines. Upon enzastaurin treatment, CAT was dephosphorylated at Ser33, 37, 41 in a dose- and time-dependent manner in all cell lines tested (10 MM, 3 colon cancer, HeLa, as well as human embryonic kidney 293 cells). Consequently, accumulation of CAT occurred in both cytosolic and nuclear fractions of treated MM cells, associated with activated TOPflash LUC-reporter system, confirming nuclear transactivating activity. Specific inhibition of CAT by siRNA partially rescued HeLa, HEK 293, and MM cells from cell death induced by enzastaurin. Analysis of downstream target molecules revealed a CAT-dependent up-regulation of c-Jun, but not of c-Myc or Cyclin D1. c-Jun has been reported to stabilize p73, a pro-apoptotic p53-family member; CAT induction by enzastaurin led to p73 (but not p53) activation and was also abrogated by CAT-specific siRNA. In turn, specific knockdown of p73 by siRNA rescued cells from enzastaurin-induced apoptosis. Finally, ectopic overexpression of CAT in HeLa and MM cells induced c-Jun expression and p73 activation, followed by apoptotic cell death. Our studies therefore indicate that ER-stress response contributes to the immediate inhibition of proliferation by enzastaurin, followed by CAT accumulation leading to p73 activation, contributing to enzastaurin-mediated cell death. These findings provide a novel link between CAT and p53-family members. Moreover p73, which is only rarely mutated in human cancers, represents a novel therapeutic target in MM.

Description: Multiple myeloma (MM)-associated bone disease is caused by upregulation of osteoclast (OCL) activity and constitutive inhibition of osteoblast function. The extracellular signal-regulated kinase 1/2 (ERK1/2) MAP kinase pathway contributes to cytokine-induced OCL differentiation and maturation. We hypothesized that inhibition of ERK1/2 could prevent OCL differentiation and downregulate OCL function. Here we investigate the effects of AZD6244, which blocks the ERK1/2 MAPK pathway via direct inhibition of MEK1/2, on OCL in MM. Peripheral blood mononuclear cells (PBMC) from healthy donors (n=3) and MM patients (n=11) were harvested and stimulated with RANKL (50ng/ml) and M-CSF (25ng/ml) for 2 weeks to induce OCL formation, in the presence or absence of AZD6244. OCL characteristics were measured by flow cytometric analysis of anti-alphaVbeta3 integrin expression. AZD6244 inhibited OCL differentiation in a dose-dependent manner (n=11, median control: 77.4% at 0 uM; 77% at 0.02 uM; 54% at 0.2 uM; 53% at 2 uM; 38% at 5 uM; 29% at 10 uM). TRAP staining (tartrate-resistant acid phosphatase) was performed to identify OCL and to confirm activity. Importantly, AZD6244 inhibited OCL in a dose-dependent manner, as evidenced by a marked loss of TRAP+ cells. To assess bone resorption activity, OCL were cultured with dentine discs in the presence or absence of AZD6244, followed by the measurement of soluble collagen I fragments in the supernatant. AZD6244 inhibited bone resorption in a dose-dependent manner. We next asked whether AZD6244 affects mature OCL. Mature OCL were induced by cytokine stimulation for 2 weeks and then AZD6244 was added for 3 days, followed by flow cytometric analysis. AZD6244 had no effect on total number of alphaVbeta3 integrin-expressing mature OCL (n=6). Two major myeloma growth and survival factors produced by OCL, B-cell activation factor (BAFF) and a proliferation-inducing ligand (APRIL), were measured in OCL culture supernatants by ELISA. AZD6244 significantly inhibited secretion of BAFF and APRIL. In addition, macrophage inflammatory protein (MIP-1alpha), an important OCL differentiation factor and MM survival factor, was inhibited. These results indicate that AZD6244 inhibits OCL differentiation induced by M-CSF and RANKL, leading to reduced bone resorption activity. Moreover, AZD6244 downregulates MIP-1alpha and BAFF, APRIL secretion by OCL, which could inhibit MM cell survival in the bone marrow microenvironment. We have also demonstrated that AZD6244 inhibits proliferation and survival of human MM cell lines, either sensitive or resistant to conventional chemotherapy, as well as freshly isolated patient MM cells (Abstract #553572 and #553605, ASH 2006). In conclusion, the present study provides a preclinical rationale for the evaluation of AZD6244 (ARRY-142886) as a potential new therapy for patients with MM.

Description: Osteolytic bone disease in Multiple Myeloma (MM) is caused by enhanced osteoclast (OCLs) activation and inhibition of osteoblast function. Lenalidomide and bortezomib have shown promising anti-MM effects, and bortezomib has inhibitory effects on OCLs. However, the effect of lenalidomide on OCLs in MM and how bortezomib interferes with osteoclastogenesis is unknown. Here we investigated the effect of lenalidomide and bortezomib on human OCLs. Peripheral blood mononuclear cells (PBMC) from MM patients were stimulated with receptor activator of NFk-B ligand (RANKL) (50ng/ml) and M-CSF (25ng/ml) for two weeks to induce OCL formation, in the presence or absence of lenalidomide or bortezomib. OCLs were identified by flow cytometric analysis using anti-αVβ3 integrin. Lenalidomide and bortezomib inhibited OCL differentiation indicated by a decrease in αVβ3-integrin (lenalidomide at 0μM: median 69.3%; range 28.9 – 89.0%; at 2μM: median 50.4%; range 21.5 – 64.2%; at 10μM: median 39.2%; range 33.6 – 47.5%) (bortezomib at 0nM: median 69.3%; range 28.9 – 89.0%; at 2nM: median 35.0%; range 11.0 – 79.0%; at 5nM: median 11.5%; range 5.5 – 8.8%; p

Description: Multiple myeloma (MM) is proposed to consist of two main pathogenetic groups. While hyperdiploidy (HD) is characterized by multiple trisomies of odd-numbered chromosomes (i.e. 3, 5, 9, 11, 15, and 19), non-hyperdiploid MM (NHD) show frequently one of the several recurrent IgH-translocations. The aim was to compare HD versus NHD by gene expression profiling (GEP). CD138-positive multiple myeloma cells from 74 newly diagnosed MM patients (42 GEP training group (TG), 32 GEP validation group (VG)) were purified by autoMACS-sorting. Sorted cells were analyzed by interphase-FISH with probes specific for 6q21, 8p21, 9q34, 11q23, 13q14, 15q22, 17p13, 19q13 and translocations t(4;14) and t(11;14). HD and NHD were defined by using a copy number score (CS), which was calculated by subtracting the number of probes indicating losses from the number of probes detecting additional copies (CS 〉0: HD; CS ≤0: NHD). GEP was performed with Affymetrix DNA-microarrays. Nearest shrunken centroid classification (NSCC) was used to discriminate the different groups, using GCRMA-normalized gene expression values. The prediction error was estimated by means of nested cross-validation using 10 repetitions of 10-fold cross-validation within the training set and separately calculated by use of the NSCC classifier of the training set to predict the validation set. Goeman’s global test was used to check the influence of ribosomal protein expression between HD and NHD. In the TG, both HD and NHD were found in 21 patients. The VG comprised 13 patients with NHD and 19 patients with HD. NSCC resulted in a predictor for HD versus NHD of 81 probe sets with a cross-validated misclassification rate of 14.2% for the TG and 26.5% for the VG. Three of the top ten genes were ribosomal proteins, overexpressed in patients with HD. Goeman’s global test further showed that ribosomal proteins are overexpressed in HD (TG: p