Phase I Exploratory Study of IV Formulation of Panobinostat in Combination with Bortezomib in Relapsed/Refractory Multiple Myeloma Patients: Effect On Serum PTH and Gene Expression Profiling (GEP) Studies

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 4073-4073 ◽  
Author(s):  
Maurizio Zangari ◽  
Tamara Berno ◽  
Giampaolo Talamo ◽  
Xin Zhan ◽  
Wen Zhou ◽  
...  

Abstract Abstract 4073 Background: Inhibition of histone deacetylase (HDAC) provides a novel approach for cancer treatment. Bortezomib and panobinostat are active agents in multiple myeloma (MM) and have a synergistic antimyeloma effect when used in combination. Both compounds have also shown anabolic bone effect. Methods: We conducted a phase I exploratory study IV formulation of panobinostat in combination with bortezomib in relapsed/refractory MM patients who had failed at least one line of prior therapy. Patients were assigned to their dose levels in a classical 3+3 cohort design. Primary objective was to assess the toxicity of a fixed dose of bortezomib in combination with escalating doses of panobinostat to define the maximum tolerated dose (MTD). The secondary objective was to determine the osteoblastic response. Bortezomib was administered iv at the dose of 1 mg/m2 during cycles on days 1, 4, 8, and 11 of each 21 days cycle. Panobinostat was administered iv starting at cycle 2 on days 1 and 8 of the 21 day cycle, 5 mg/m2 n=1–3, 10 mg/m2 n=4–9, 15 mg/m2 n=10–12 (one screening failure). Patients with at least stable disease after the first 2 cycles (Phase I Portion of the Study) were allowed to continue to a maximum of 12 cycles. PTH was measured during the first two cycles, every 20 minutes starting one hour before infusion for a total of seven time points on days 1 and 4, and single pre dose on days 8 and 11 during cycles 1 and 2. Bone marrow (BM) aspiration and biopsies were collected at baseline, after the completion of second cycle and at the end of the study. H&E stained core biopsy slides were scanned using Scan Scope XT system. We developed classifier algorithms using Genie pattern recognition image analysis software to calculate Trabecular Volume (TV), Bone Volume (BV). RNA obtained from separate core biopsies at baseline and after second cycle was used to complete Gene Expression Profiling (GEP) studies. The paired t test was used to identify significantly gene changes. Results: Eleven patients with a median age of 58 years (range 44 to 70) were enrolled. 45% of patients received ≥ 3 previous lines of therapy. 45% was previously exposed to Bortezomib and 63% of patients failed prior autologous stem cell transplant. All eleven patients completed two cycles of therapy, 10 patients continued treatment, and three completed a total of 12 cycles. No MTD was reached with a 15 mg/m2IV Panobinostat dose. Using IMWG criteria after the second cycle of treatment we observed 1CR, 3 PR, 5 SD, 2 patients experienced PD. Best response during the entire treatment included 2 CR, 2 VGPR, 4 SD (≥ SD 72%). Common grade 3/4 AEs included: thrombocytopenia (36%), neutropenia (45%), leukopenia (54%), lymphopenia (18%), with no treatment-related mortality. The median baseline of Trabecular Volume/Hematopietic Area (TV/HA) was 27.6% (range 8.1–46%). Comparing the baseline to the end of study samples, an increment of TV/HA was noted in 6 of 9 available patients. The average TV/HA increment was 19.4% (range 9.9–38.3%). 72% of patients (n=8) showed changes in PTH level during treatment. Serial PTH samples significantly increased during treatment, from a mean of 39.4 pg/L (±22.3) at baseline, to a mean of 50.2 pg/L (±36.8) at day 4 cycle 2 (p=0.003). GEP from bone marrow baseline core biopsies were compared to post-treatment samples. A total of 3783 probe sets were found to be differentially expressed. 30% of genes were over-expressed and 70% were down regulated. Interestingly decorin, which function has been associated to antimyeloma effect of osteoblasts, and its down-stream target p21-activated kinase 4 (PAK4) were significantly increased in the post-treatment samples (p=0.04, p=0.03 respectively with 2.0 ratio) suggesting a bone anabolic and antimyeloma effect of these drugs in combination. Conclusions: The combination of IV Panobinostat and Bortezomib has predictable and manageable safety profile with significant antimyeloma activity as reflected by ≥ SD 72%, ≥ PR 36% including 18% CR. Changes in bone indices were observed by a computer assisted image analysis. Hormonal changes and genes studies also support an osteoblastic/anabolic effect of panobinostat in combination with bortezomib in relapsed/refractory MM patients. Disclosures: Zangari: Millennium, Onyx, Cephalon, Incyte: Research Funding, Speakers Bureau.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3497-3497
Author(s):  
Marc J. Braunstein ◽  
Daniel R. Carrasco ◽  
David Kahn ◽  
Kumar Sukhdeo ◽  
Alexei Protopopov ◽  
...  

Abstract In multiple myeloma (MM), bone marrow-derived endothelial progenitor cells (EPCs) contribute to tumor neoangiogenesis and their levels covary with tumor mass and prognosis. Recent X-chromosome inactivation studies in female patients showed that, similar to tumor cells, EPCs are clonally restricted in MM. Genomic profiling of MM using high-resolution array comparative genomic hybridization (aCGH) has been previously utilized to mine the genome and find clinical correlates in MM patients. In this study, clonotypic aspects of bone marrow-derived EPCs and MM cells were investigated using aCGH and expression profiling analysis. Confluent EPCs were outgrown from bone marrow aspirates by adherence to laminin. EPCs were >98% vWF/CD133/KDR+ and <1% CD38+. The laminin-nonadherent bone marrow fraction enriched for tumor cells was >50% CD38+. For aCGH and for gene expression profiling, genomic DNA and total RNA from EPCs and MM cells were hybridized to human oligonucleotide arrays (Agilent Technologies) and human cDNA microarrays (Affymetrix), respectively. High resolution aCGH with segmentation analysis showed that EPCs and MM cells in one of ten cases share identical patterns of chromosomal gains and losses, while another 5 cases shared multiple focal copy number alterations (CNAs) including gains and losses. The genomes of EPCs and MM cells additionally displayed exclusive CNAs, but these were far fewer in EPCs than in MM cells. In 3 patients, EPCs harbored a common 0.6Mb deletion at 1q21 not shared by MM cells. Pertinent genes in this region that could affect proliferation and tumor suppression include N2N, NBPF10, and TXNIP. Validation studies of aCGH findings by other methods are ongoing. Gene expression profiling showed decreased expression of 1q21 region genes (e.g., calgranulin C and lamin A/C). A genome-wide comparison of patients’ MM cells and EPCs, which is focused on their shared genetic characteristics, will be presented.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3123-3123
Author(s):  
Bart Barlogie ◽  
Emily Hansen ◽  
Sarah Waheed ◽  
Jameel Muzaffar ◽  
Monica Grazziutti ◽  
...  

Abstract Intra-tumoral heterogeneity (ITH) is increasingly viewed as the Achilles heel of treatment failure in malignant disease including multiple myeloma (MM). Most MM patients harbor focal lesions (FL) that are recognized on MRI long before bone destruction is detectable by conventional X-ray examination. Serial MRI examinations show that eventually 60% of patients will achieve resolution of FL (MRI-CR). However, this will lag behind the onset of a clinical CR by 18 to 24 months, thus attesting to the biological differences between FL and diffuse MM growth patterns. Consequently, we performed concurrent gene expression profiling (GEP) analyses of plasma cells (PC) from both random bone marrow (RBM) via iliac crest and FL. Our primary aims were to first compare the molecular profiles of FL vs. RBM, second to determine if ITH existed (as defined molecular subgroup and risk), and finally to investigate if the bone marrow micro-environment (ME) contained a biologically interesting signature. A total of 176 patients were available for this study with a breakdown of: TT3 (n=23), TT4 for low-risk (n=131) and TT5 for high-risk MM (n=22). Regarding the molecular analyses of PCs, GEP-based risk (GEP-70, GEP-5) and molecular subgroup correspondence were examined for commonalties and differences between RBM and FL. A “filtering” approach for ME genes was also developed and bone marrow biopsy (BMBx) GEP data derived from this method is under analysis. PC risk correspondence between FL and RBM was 86% for GEP70 and 88% for the GEP5 model. Additionally, 82% had a molecular subgroup concordance, however, they did differ among subgroups (p=0.020) by Fisher's Exact Test. A lower concordance was noted in the CD2, LB, and PR subgroups (67%, 69%, 73%, respectively). GEP70 and GEP5 risk concordance between RBM and FL samples by molecular subgroup was also examined. The overall correlation coefficients were 0.619 (GEP70) and 0.597 (GEP5). The best correspondence was noted for CD1, MF and PR subgroups especially for the GEP5 model. HY, LB and MS showed intermediate correlations, while CD2 fared worst with values of only 0.322 for GEP70 and 0.267 for GEP5 model. Figure 1 portrays these data in more detail for the GEP70 and GEP5 models. Good correlations were noted between RBM and FL based risk scores in case of molecular subgroup concordance (left panels) in both GEP5 and GEP70 risk models, whereas considerable scatter existed in case of subgroup discordance (right panels). The clinical implications in TT4 regarding RBM and FL derived risk and molecular subgroup information, viewed in the context of standard prognostic baseline variables are portrayed in Table 1. High B2M levels at both cut-points imparted inferior OS and PFS as did low hemoglobin. Although present in 42% of patients, cytogenetic abnormalities (CA) did not affect outcomes. FL-based GEP5-defined high-risk designation conferred poor OS and PFS. B2M>5.5mg/L and FL-derived GEP5 high-risk MM, pertaining to 29% and 11% of patients, survived the multivariate model for both OS and PFS. Next, in examining PC-GEP differences among RBM and FL sites, 199 gene probes were identified with a false discovery rate (FDR) of 1x10-6. Additionally, 55 of the 199 belong to four molecular networks of inter related genes associated with: lipid metabolism, cellular movement, growth and proliferation, and cell-to-cell interactions. Multivariate analysis identified the GEP5 high risk designation of focal lesion PCs to be significantly prognostic with a HR=3.73 (p=0.023).Table 1Cox regression analysis of variables linked to overall and progression-free survival in TT4.Overall SurvivalProgression-Free SurvivalVariablen/N (%)HR (95% CI)P-valueHR (95% CI)P-valueMultivariateB2M > 5.5 mg/L38/130 (29%)3.71 (1.49, 9.22)0.0053.84 (1.58, 9.31)0.003FL GEP5 High Risk14/130 (11%)3.68 (1.19, 11.41)0.0243.73 (1.20, 11.62)0.023HR- Hazard Ratio, 95% CI- 95% Confidence Interval, P-value from Wald Chi-Square Test in Cox RegressionNS2- Multivariate results not statistically significant at 0.05 level. All univariate p-values reported regardless of significance.Multivariate model uses stepwise selection with entry level 0.1 and variable remains if meets the 0.05 level.A multivariate p-value greater than 0.05 indicates variable forced into model with significant variables chosen using stepwise selection. Disclosures: No relevant conflicts of interest to declare.


2009 ◽  
Vol 15 (17) ◽  
pp. 5369-5378 ◽  
Author(s):  
Roberto Ria ◽  
Katia Todoerti ◽  
Simona Berardi ◽  
Addolorata Maria Luce Coluccia ◽  
Annunziata De Luisi ◽  
...  

Blood ◽  
2010 ◽  
Vol 116 (14) ◽  
pp. 2543-2553 ◽  
Author(s):  
Annemiek Broyl ◽  
Dirk Hose ◽  
Henk Lokhorst ◽  
Yvonne de Knegt ◽  
Justine Peeters ◽  
...  

Abstract To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6 corresponded to clusters described in the University of Arkansas for Medical Science (UAMS) classification, CD-1 (n = 13, 4.1%), CD-2 (n = 34, 1.6%), MF (n = 32, 1.0%), MS (n = 33, 1.3%), proliferation-associated genes (n = 15, 4.7%), and hyperdiploid (n = 77, 24.1%). Moreover, the UAMS low percentage of bone disease cluster was identified as a subcluster of the MF cluster (n = 15, 4.7%). One subgroup (n = 39, 12.2%) showed a myeloid signature. Three novel subgroups were defined, including a subgroup of 37 patients (11.6%) characterized by high expression of genes involved in the nuclear factor kappa light-chain-enhancer of activated B cells pathway, which include TNFAIP3 and CD40. Another subgroup of 22 patients (6.9%) was characterized by distinct overexpression of cancer testis antigens without overexpression of proliferation genes. The third novel cluster of 9 patients (2.8%) showed up-regulation of protein tyrosine phosphatases PRL-3 and PTPRZ1 as well as SOCS3. To conclude, in addition to 7 clusters described in the UAMS classification, we identified 3 novel subsets of multiple myeloma that may represent unique diagnostic entities.


2017 ◽  
Vol 60 (6) ◽  
pp. 326-334 ◽  
Author(s):  
Carla Martins Kaneto ◽  
Patrícia S. Pereira Lima ◽  
Karen Lima Prata ◽  
Jane Lima dos Santos ◽  
João Monteiro de Pina Neto ◽  
...  

2016 ◽  
Vol 6 (9) ◽  
pp. e471-e471 ◽  
Author(s):  
Y Jethava ◽  
A Mitchell ◽  
M Zangari ◽  
S Waheed ◽  
C Schinke ◽  
...  

BMC Genomics ◽  
2011 ◽  
Vol 12 (1) ◽  
pp. 461 ◽  
Author(s):  
Adriane Menssen ◽  
Thomas Häupl ◽  
Michael Sittinger ◽  
Bruno Delorme ◽  
Pierre Charbord ◽  
...  

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 73-73 ◽  
Author(s):  
Dirk Hose ◽  
Jean-Francois Rossi ◽  
Carina Ittrich ◽  
John deVos ◽  
Axel Benner ◽  
...  

Abstract AIM was to establish a new molecular classification of Multiple Myeloma (MM) based on changes in global gene expression attributable to cytogenetic aberrations detected by interphase FISH (iFISH) in order to (i) predict event free survival (EFS) and (ii) investigate differentially expressed genes as basis for a group specific and risk adapted therapy. PATIENTS AND METHODS. Bone marrow aspirates of 105 newly diagnosed MM-patients (65 trial (TG) / 40 independent validation group (VG)) and 7 normal donors (ND) were CD138-purified by magnetic activated cell sorting. RNA was in-vitro transcribed and hybridised to Affymetrix HG U133 A+B GeneChip (TG) and HG U133 2.0 plus arrays (VG). CCND1 and CCND2 expression was verified by real time RT-PCR. iFISH was performed on purified MM-cells using probes for chromosomes 11q23, 11q13, 13q14, 17p13 and the IgH-translocations t(4;14) and t(11;14). Expression data were normalised (Bioconductor package gcrma) and nearest shrunken centroids (NSC) applied to calculate and cross validate a predictor on 40 patients of the TG with a comprehensive iFISH panel available combined with CCND overexpression. Differentially expressed genes were identified using empirical Bayes statistics for pairwise comparison. RESULTS. Overexpression of a D-type cyclin (D1 or D2) was found in 61/65 patients with MM compared to ND. CCND3 overexpression only appeared concomitantly with CCND2 overexpression. Four groups could be distinguished: (1.1) CCND1 (11q13) overexpression and trisomy 11q13, (1.2) CCND1 overexpression and translocations involving 11q13 i.e. t(11;14), (2.1) CCND2 overexpression without 11q13+, t(11;14), t(4;14), (2.2) CCND2 overexpression with t(4;14) and FGFR3 upregulation. A predictor of 6 to 566 genes correctly classifies all 40 patients of the TG (estimated cross validated error rate 0%). An independent VG of 40 patients was used. Genes with highest scores in NSC are: (1.1) CCND1, ribosomal proteins (e.g. RPL 28, 29), GPX1, CCRL2, (1.2) CCND1, TGIF, and NCAM (non-overexpression), (2.1) CCND2, (2.2) FGFR3, WHSC1, CCND2, IRTA2, SELL, and MAGED4. Distribution of clinical parameters (i.e. β2M, Durie Salmon stages, ISS) was not significantly different between the groups. The distribution of del(13)(q14q14) was (1.1) 31.5%, (1.2) 37.5%, (2.1) 37.5% and (2.2) 100%. (p<0.01). I.e. HGF, DKK1, VCAM, CD163 are differentially expressed between all 4 groups and ND (adjusted p<0.001). The groups defined by the predictor show a significantly different EFS after autologous stem cell transplantation according to the GMMG-HD3 protocol (median: (1.1) 18 / (1.2) not reached (no event) / (2.1) 22 / (2.2) 6 months; log-rank-test: p=0.004). CONCLUSION. CCND1 or CCND2 overexpression is nearly ubiquitous in MM and attributable to defined cytogenetic aberrations. Gene expression and iFISH allow a molecular classification of MM which can be predicted by gene expression profiling alone. Groups in the classification show a distinctive pattern in gene expression as well as a different EFS interpretable as risk stratification and indicator of therapeutic targets.


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