In Silico Prediction of Novel Drug Combinations to Combat Bortezomib-Resistant Multiple Myeloma

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 1344-1344
Author(s):  
Holly A. F. Stessman ◽  
Tian Xia ◽  
Aatif Mansoor ◽  
Raamesh Deshpande ◽  
Linda B. Baughn ◽  
...  

Abstract Abstract 1344 Bortezomib/VELCADE® (Bz) is a proteasome inhibitor that has been used successfully in the treatment of multiple myeloma (MM) patients. However, acquired resistance to Bz is an emerging problem. Thus, there is a need for novel therapeutic combinations that enhance Bz sensitivity or re-sensitize Bz resistant MM cells to Bz. The Connectivity Map (CMAP; Broad Institute) database contains treatment-induced transcriptional signatures from 1,309 bioactive compounds in 4 human cancer cell lines. An input signature can be used to query the database for correlated drug signatures, a technique that has been used previously to identify drugs that combat chemoresistance in cancer (Wei, et al. Cancer Cell (2006) 10:331). In this study we used in silico bioinformatic screening of gene expression profiles from isogenic pairs of Bz sensitive and resistant mouse cell lines derived from the iMycCα/Bcl-xL mouse model of plasma cell malignancy to identify compounds that combat Bz resistance. We established Bz-induced kinetic gene expression profiles (GEPs) in 3 pairs of Bz sensitive and resistant mouse cell lines over the course of 24 hours. GEPs were collected in the absence of large-scale cell death. The 16 and 24 hour time points were averaged and compared between each Bz sensitive and resistant pair. Genes in the sensitive cell line with a fold change greater than 2, relative to the resistant line, were given the binary distinction of “up” or “down” depending on the direction of change. Genes that met these criteria were assembled into signatures, and then used as inputs for CMAP queries to identify compounds that induce similar transcriptional responses. In all pairs, treatment of the Bz sensitive line correlated with GEPs of drugs that target the proteasome, NF-κB, HSP90 and microtubules, as indicated by positive connectivity scores. However eight compounds, all classified as Topoisomerase (Topo) I and/or II inhibitors, were negatively correlated to our input signature. A negative connectivity score could have two interpretations: (1) this could indicate simply that Topos are upregulated by Bz treatment in Bz sensitive lines, which has been previously reported (Congdan, et al. Biochem. Pharmacol. (2008) 74: 883); or (2) this score could be interpreted as Topos are inhibited in Bz resistant cells upon Bz treatment. This led us to ask whether Topo inhibitors could target Bz resistant MM cells and re-sensitize them to Bz. Indeed, we found that multiple Topo inhibitors were significantly more active against Bz resistant cells as single agents and restored sensitivity to Bz when combined with Bz as a cocktail regimen. This work demonstrates the potential of this in silico bioinformatic approach for identifying novel therapeutic combinations that overcome Bz resistance in MM. Furthermore, it identifies Topo inhibitors – drugs that are already approved for clinical use – as agents that may have utility in combating Bz resistance in refractory MM patients. Disclosures: Stessman: Millennium: The Takeda Oncology Company: Research Funding. Van Ness:Millennium: The Takeda Oncology Company: Research Funding.

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2671-2671
Author(s):  
Yan Cheng ◽  
Fumou Sun ◽  
Huojun Cao ◽  
Dongzheng Gai ◽  
Bailu Peng ◽  
...  

Abstract Introduction The development of new treatments for high-risk multiple myeloma (HRMM) are needed. The PD-1/PD-L1 axis is one of the chief inhibitory immune checkpoints in antitumor immunity. Despite the success of PD-1 (PDCD1) / PD-L1 (CD274) blockade in some neoplasms, use of it as a monotherapy has failed to improve outcome in RRMM. We have previously demonstrated that the cell-cycle-regulated serine-threonine kinase, NEK2 is elevated in HRMM and that inhibition of NEK2 can overcome drug-resistance and prolong survival of xenografted MM cells. Here, we aimed to investigate the possible role of NEK2 in regulating the immune checkpoint response in MM and development of possible anti-PD1/PDL1 combination therapies. Methods Gene expression profiles and pathway enrichment analyses were conducted on oligonucleotide microarray gene expression profiles from over 1000 primary MM samples to evaluate the correlation of NEK2 and immune checkpoint expression levels. To elucidate the underlying mechanism, we used Nek2 -/- mice crossed with EμMyc mice to generate B cell tumor mouse model with NEK2 deficiency. RNA-sequencing analyses of premalignant B cells was compared between EμMyc/Nek2 WT and EμMyc/Nek2 -/- mice. The hub molecular regulators in the NEK2 correlated pathways were further determined by western blot using NEK2 overexpressing and knockdown cell lines and then verified by co-immunoprecipitation with a NEK2 antibody. Lastly, to establish its clinic significance, the efficacy of INH1 (small compound NEK2 inhibitor), (D)-PPA 1 (peptide-based PD-1/PD-L1 interaction inhibitor) or a PD-L1 (monoclonal antibody) was tested in bone marrow BM mononuclear cells from primary MM patients in-vitro as well as in MM xenografts. Tumor burden and T cell immune responses were monitored by M-spike and mass cytometry. Results Gene expression profiles demonstrated that CD274 expression was significantly higher in the non-proliferative hyperdiploid (HY) subtype of MM, representing between 25-35% of all MM. NEK2 was negatively correlated with CD274 gene expression across all 7 MM subtypes. Gene set enrichment analysis showed that the IFN-γ signaling pathway, which can induce CD274 expression, was significantly enriched in the HY subtype as well as premalignant B cells from EμMyc/Nek2 -/- mice. Elevated expression of EZH2, a histone methyltransferase gene, is also highly correlated wirth NEK2 levels in primary MM. We found that NEK2 inhibition increases CD274 expression as well as reduced EZH2 expression and H3K27me3 levels in MM cell lines. In contrarst, myeloma cells overexpressing NEK2 showed increased expression and activity of EZH2 and H3K27me3 levels. Thus, NEK2 appears to regulate CD274/PD-L1 expression through EZH2-mediated histone methylation. Next we demonstrated that NEK2 and EZH2 directly interact and that overexpression of NEK2 leads to increased methylation of the CD274/PD-L1 gene. We treated BM mononuclear cells from primary MM with PD-1/PD-L1 inhibitor with and without a NEK2 inhibitor. The combination was most effective at eliminating CD138 + myeloma cells while having no effects on T, B and myeloid cell populations. Conclusion Our study showed that expression of CD274/PD-L1 is suppressed in primary HRMM and that CD274/PD-L1 expression is negatively regulated by NEK2 via EZH2-mediated methylation. Inhibition of NEK2 sensitizes myeloma cells to PD-1/PD-L1 blockade, showing either a synergistic or an additive effect in MM cell cytotoxicity. Disclosures No relevant conflicts of interest to declare.


Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3393-3393
Author(s):  
Pieter Sonneveld ◽  
Eric Kamst ◽  
Yvonne de Knegt ◽  
Naomi Klarenbeek ◽  
Martijn Schoester

Abstract Multiple Myeloma (MM) is a disease of monoclonal plasma cells in the bone marrow which has a transient response to classic chemotherapy. At diagnosis, induction chemotherapy followed by high-dose melphalan (HDM) with stem cell support is used in most patients to achieve a clinical response. Because all patients will ultimately relapse, the treatment of melphalan-refractory disease represents a major clinical challenge and new agents are needed to overcome melphalan resistance. We have investigated the anti-myeloma efficacy of two new classes of targeted agents, i.e. proteasome inhibition and histone deacetylation inhibition alone or in combination in the melphalan sensitive MM1S and the Melphalan refractory MM1MEL2000 cell lines. The IC50 values of Bortezomib (B), Melphalan (M) and LAQ824 (L) in MM1S were 2.1 nM, 1.9 uM and 1.7 nM, respectively and in MM1MEL2000 3.9 nM, 50 uM and 4.0 nM. Using isobologram analysis a synergysm between B and L was observed in the sensitive, however not in the melphalan refractory cell line. These data indicate that B proteasome inhibition and histone deacetylation inhibition may be effective ways to overcome melphalan resistance. However, the previously reported synergism between these drugs does not seem to occur in melphalan resistant cells. The gene expression profiles of these cell lines were analysed using the Affymetrix U133plus 2.0 gene chip before and after treatment with melfaphalan or the proteasome inhibitor B or the histone deacetylation inhibitor L or the combination of B and L. Genes that were highly expressed in the melphalan refractory derivate cell line MM1MEL2000 as compared with wild-type MM1S included GP M6B, ADAM23 and HTPAP. Following melphalan exposure, TMF1, a CEBp glucocorticoid interaction factor, WHSC1L1, a MMSET homologue with EGF like domain and several transcription factors had highly increased expression as compared to MM1S. With exposure to B combined with L, increased expression in MM1MEL2000 over MM1S was observed for GTP exchange factor TIAM1 which interacts with RAS and JNK, and the lymphoid enhancer factor, a notch transcription factor. It is concluded that Bortezomib and the histone deacetylase inhibitor LAQ824 are effective agents to overcome melphalan resistance in multiple myeloma. However, the combination fails to show the synergism observed in melphalan sensitive cells. Gene analysis sofar does not provide a clear explanation for this lack of synergism. A comprehensive summary of the observed shifts of gene expression profiles in melphalan resistant cells following exposure to these agents, will be presented.


Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3061-3061
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Martha Q. Lacy ◽  
Jessica L. Haug ◽  
Angela Dispenzieri ◽  
...  

Introduction: High-risk multiple myeloma can be defined by the presence of specific cytogenetic abnormalities (structural) or by characteristic changes in bone marrow and peripheral blood biomarkers (functional). While both entities are characterized by therapeutic resistance, frequent disease relapses, and adverse survival outcomes, the underlying molecular mechanisms remain incompletely understood. Methods: We performed gene expression profiling (GEP) using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from 137 patients diagnosed with multiple myeloma between 2004 and 2012. All patients underwent Fluorescence In-situ Hybridization (FISH) evaluation, plasma cell labeling, International Staging System (ISS) risk stratification, and GEP prior to initiating treatment with novel agents. The presence of del(17p), t(4;14), t(14;16), and t(14;20) on FISH, a plasma cell labeling index (PCLI) > 2%, and ISS stage III were considered high-risk abnormalities: FISH-HR (n = 15, structural high-risk, at least one high-risk FISH lesion), PCLI-HR (n = 20; functional high-risk, PCLI > 2%), and ISS-HR (n = 12; functional high-risk, ISS stage III). For each HR group we sampled standard risk (SR) controls in a 4:1 ratio. After data quality control and normalization, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple comparisons using a false discovery rate-based approach for genome-wide experiments (q-value). We employed PANTHER pathway analysis for the differentially expressed genes in each HR group. We implemented a simple gene expression score (GES) by calculating the sum of quartiles of the normalized gene expression values for genes differentially expressed in more than one HR group (GES = ΣUP(quartile - 1) + ΣDN(4 - quartile)) and externally validated its prognostic significance (UAMS TT2 / TT3, GSE24080). Survival outcomes were analyzed using the methods described by Kaplan, Meier, and Cox. Computation and visualization were performed in R. Results: Median age at diagnosis was 63 years (32 - 87), 53% of the patients were male. High-risk disease was associated with inferior overall survival, regardless of the used definition (left Kaplan-Meier plots): FISH-HR (HR 4.3, 95% CI 1.9 - 9.8, p < 0.001), PCLI-HR (HR 2.7, 95% CI 1.4 - 5.3, p = 0.004), and ISS-HR (HR 2.8, 95% CI 1.2 - 6.5, p = 0.015). There were 59 (FISH-HR), 424 (ISS-HR), and 507 (PCLI-HR) differentially expressed genes (q < 0.050 for all genes, volcano plots). PCLI-HR and FISH-HR demonstrated a predominance of transcriptional up-regulation while ISS-HR had a balanced gene expression profile with a similar number of genes being up- and down-regulated. The involved cellular pathways were different across the HR groups except for anti-apoptotic signaling (bar graphs). All HR groups had distinct gene expression profiles with no complete overlap between all HR groups. There were 71 genes with overlap between two HR groups (69 up-regulated, 2 down-regulated, Venn diagrams). The median GES was 97 (18 - 206, higher numbers indicating higher expression of up-regulated and lower numbers of down-regulated high-risk genes) in 559 patients treated on UAMS TT2 / TT3 (GSE24080). Tertiles of the GES were associated with event-free survival (HR 1.4, 95% CI 1.2 - 1.6, p < 0.001) and remained independently prognostic after adjusting for age, sex, and ISS stage (HR 1.3, 95% CI 1.1 - 1.5, p < 0.001). Conclusions: High-risk multiple myeloma remains associated with inferior overall survival, regardless of the used definition (structural or functional). The subtypes of high-risk disease have distinct gene expression profiles and involve different cellular pathways, providing important clues to the underlying biology. A 71 gene signature derived from the different high-risk subtypes was of prognostic significance in a clinical trial population after adjusting for known prognostic factors. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Stewart:Takeda: Consultancy; Seattle Genetics: Consultancy; Roche: Consultancy; Ono: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.


2019 ◽  
Vol 9 (24) ◽  
pp. 5552 ◽  
Author(s):  
Gabriella Casalino ◽  
Mauro Coluccia ◽  
Maria L. Pati ◽  
Alessandra Pannunzio ◽  
Angelo Vacca ◽  
...  

Microarray data are a kind of numerical non-negative data used to collect gene expression profiles. Since the number of genes in DNA is huge, they are usually high dimensional, therefore they require dimensionality reduction and clustering techniques to extract useful information. In this paper we use NMF, non-negative matrix factorization, to analyze microarray data, and also develop “intelligent” results visualization with the aim to facilitate the analysis of the domain experts. For this purpose, a case study based on the analysis of the gene expression profiles (GEPs), representative of the human multiple myeloma diseases, was investigated in 40 human myeloma cell lines (HMCLs). The aim of the experiments was to study the genes involved in arachidonic acid metabolism in order to detect gene patterns that possibly could be connected to the different gene expression profiles of multiple myeloma. NMF results have been verified by western blotting analysis in six HMCLs of proteins expressed by some of the most abundantly expressed genes. The experiments showed the effectiveness of NMF in intelligently analyzing microarray data.


Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e58809 ◽  
Author(s):  
Yingxiang Li ◽  
Xujun Wang ◽  
Haiyang Zheng ◽  
Chengyang Wang ◽  
Stéphane Minvielle ◽  
...  

2015 ◽  
Vol 11 (1) ◽  
pp. 86-96 ◽  
Author(s):  
Aakash Chavan Ravindranath ◽  
Nolen Perualila-Tan ◽  
Adetayo Kasim ◽  
Georgios Drakakis ◽  
Sonia Liggi ◽  
...  

Integrating gene expression profiles with certain proteins can improve our understanding of the fundamental mechanisms in protein–ligand binding.


2021 ◽  
Vol 10 ◽  
Author(s):  
Heather Fairfield ◽  
Samantha Costa ◽  
Carolyne Falank ◽  
Mariah Farrell ◽  
Connor S. Murphy ◽  
...  

Within the bone marrow microenvironment, mesenchymal stromal cells (MSCs) are an essential precursor to bone marrow adipocytes and osteoblasts. The balance between this progenitor pool and mature cells (adipocytes and osteoblasts) is often skewed by disease and aging. In multiple myeloma (MM), a cancer of the plasma cell that predominantly grows within the bone marrow, as well as other cancers, MSCs, preadipocytes, and adipocytes have been shown to directly support tumor cell survival and proliferation. Increasing evidence supports the idea that MM-associated MSCs are distinct from healthy MSCs, and their gene expression profiles may be predictive of myeloma patient outcomes. Here we directly investigate how MM cells affect the differentiation capacity and gene expression profiles of preadipocytes and bone marrow MSCs. Our studies reveal that MM.1S cells cause a marked decrease in lipid accumulation in differentiating 3T3-L1 cells. Also, MM.1S cells or MM.1S-conditioned media altered gene expression profiles of both 3T3-L1 and mouse bone marrow MSCs. 3T3-L1 cells exposed to MM.1S cells before adipogenic differentiation displayed gene expression changes leading to significantly altered pathways involved in steroid biosynthesis, the cell cycle, and metabolism (oxidative phosphorylation and glycolysis) after adipogenesis. MM.1S cells induced a marked increase in 3T3-L1 expression of MM-supportive genes including Il-6 and Cxcl12 (SDF1), which was confirmed in mouse MSCs by qRT-PCR, suggesting a forward-feedback mechanism. In vitro experiments revealed that indirect MM exposure prior to differentiation drives a senescent-like phenotype in differentiating MSCs, and this trend was confirmed in MM-associated MSCs compared to MSCs from normal donors. In direct co-culture, human mesenchymal stem cells (hMSCs) exposed to MM.1S, RPMI-8226, and OPM-2 prior to and during differentiation, exhibited different levels of lipid accumulation as well as secreted cytokines. Combined, our results suggest that MM cells can inhibit adipogenic differentiation while stimulating expression of the senescence associated secretory phenotype (SASP) and other pro-myeloma molecules. This study provides insight into a novel way in which MM cells manipulate their microenvironment by altering the expression of supportive cytokines and skewing the cellular diversity of the marrow.


2006 ◽  
Vol 2 ◽  
pp. S552-S552
Author(s):  
Boe-Hyun Kim ◽  
Jae-Il Kim ◽  
Eun-Kyoung Choi ◽  
Richard I. Carp ◽  
Yong-Sun Kim

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