scholarly journals Intelligent Microarray Data Analysis through Non-negative Matrix Factorization to Study Human Multiple Myeloma Cell Lines

2019 ◽  
Vol 9 (24) ◽  
pp. 5552 ◽  
Author(s):  
Gabriella Casalino ◽  
Mauro Coluccia ◽  
Maria L. Pati ◽  
Alessandra Pannunzio ◽  
Angelo Vacca ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Lines ◽  
Microarray Data ◽  
Matrix Factorization ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Myeloma Cell ◽  
Human Multiple Myeloma ◽  
Non Negative Matrix Factorization

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.

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 ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Lines ◽  
In Silico ◽  
Research Funding ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Mouse Cell ◽  
Resistant Mouse ◽  
Novel Therapeutic

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.

scholarly journals NEK2 Inhibition Enhances the Efficacy of PD-1/PD-L1 Blockade in Multiple Myeloma

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2671-2671
Author(s):  
Yan Cheng ◽  
Fumou Sun ◽  
Huojun Cao ◽  
Dongzheng Gai ◽  
Bailu Peng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
B Cells ◽  
Cell Lines ◽  
Immune Checkpoint ◽  
Mononuclear Cells ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Myeloma Cells

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.

A Trangenic Mouse Model of Plasma Cell Malignancy Shows Cytogenetic and Gene Expression Profiles Similar to Human Multiple Myeloma.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 619-619
Author(s):  
Kristin Boylan ◽  
Mary A. Kvitrud ◽  
Brian G. Van Ness
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Plasma Cell ◽  
Plasma Cells ◽  
Chromosomal Abnormalities ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rt Pcr ◽  
Mouse Tumors ◽  
Human Multiple Myeloma

Abstract Multiple myeloma is an incurable plasma cell malignancy for which existing animal models are limited. Human plasma cell tumors are genetically diverse, with no single chromosomal abnormality defining the disease, however, dysregulation of the genes c-myc and bcl-xl are both commonly observed. We have previously shown that targeted expression of c-myc and bcl-xl transgenes in mouse plasma cells produces malignancy which displays features of human myeloma such as localization of tumor cells to the bone marrow and lytic bone lesions. Tumors are also present at extramedullary sites (Cheung et al., J. Clin. Invest.113: 1763, 2004). Tumors rapidly develop (median 16 weeks) in 100% of mice, and can be adoptively transferred to syngeneic controls using as few as 1 million tumor cells to produce tumors in as few as 10 days. Adoptive transfer of similar cell numbers from younger double transgenic mice, without evidence of malignancy, results in increased tumor latency (>8 weeks) or the absence of tumor formation, suggesting that an accumulation of genetic changes is required for tumor development. In order to understand the specific genetic alterations required for tumor progression and for localization of tumors to the bone marrow vs extramedullary sites, we have undertaken a detailed analysis of plasma cell tumors in myc/bcl-xl mice and have begun to compare them with human multiple myeloma. Analysis of cell surface markers shows the majority of tumors have a plasmablast phenotype, expressing CD138+, B220+, CD38+, and CD19+. This result is confirmed by RT-PCR for B cell and plasma cell specific markers Pax5, Xbp1 and Blimp1, which can be detected in tumor samples. In addition, transcripts for Mip1α, EZH2, and Dusp6, genes shown to be upregulated in human myeloma, can also be detected in the mouse myc/bcl-xl tumors. Spectral karyotype analysis of metaphase chromosomes from primary tumor cell cultures demonstrates that a variety of chromosomal abnormalities are present in mouse tumors, including trisomies and translocations, similar to what is observed in human myeloma. The most frequently aberrant chromosomes are 12 and 16, followed by chromosomes 1 and 4. Interestingly, two common sites for translocations were identified; 12F which corresponds to the mouse immunoglobulin heavy chain locus, and 4D, which corresponds to a genomic region containing genes for plasma cell tumor susceptibility (Bliskovsky et al., PNAS100:14982, 2003). Further characterization of these translocations are being done to identify the precise breakpoints involved, and analysis of gene expression by RT-PCR and microarray analysis will be correlated to specific chromosomal abnormalities. Additionally, global gene expression profiles from myc/bcl-xl tumor cell cultures have been compared to existing profiles of human myeloma (Zhan et al., Blood99: 1745, 2002). Our preliminary comparison of gene expression profiles from myc/bcl-xl tumors to human myeloma tumors with high myc expression show the mouse tumors are more similar to human tumors than to normal plasma cells. These data suggest the myc/bcl-xl mouse tumors are similar to a subset of human myelomas, and will provide insight into the specific genes and pathways underlying human disease.

Melphalan Resistance in Multiple Myeloma Can Be Overcome by Proteasome Inhibition or Histone Deacetylation: Lack of Syngergism of the Combination.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3393-3393
Author(s):  
Pieter Sonneveld ◽  
Eric Kamst ◽  
Yvonne de Knegt ◽  
Naomi Klarenbeek ◽  
Martijn Schoester
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Line ◽  
Cell Lines ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Proteasome Inhibition ◽  
Histone Deacetylation ◽  
Interaction Factor ◽  
Resistant Cells

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.

scholarly journals SC-JNMF: Single-cell clustering integrating multiple quantification methods based on joint non-negative matrix factorization

2020 ◽  
Author(s):  
Mikio Shiga ◽  
Shigeto Seno ◽  
Makoto Onizuka ◽  
Hideo Matsuda
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Matrix Factorization ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Clustering Methods ◽  
Clustering Method ◽  
Multiple Gene ◽  
Cell Clustering ◽  
Non Negative Matrix Factorization

AbstractUnsupervised cell clustering is important in discovering cell diversity and subpopulations. Single-cell clustering using gene expression profiles is known to show different results depending on the method of expression quantification; nevertheless, most single-cell clustering methods do not consider the method.In this article, we propose a robust and highly accurate clustering method using joint non-negative matrix factorization (joint NMF) based on multiple gene expression profiles quantified using different methods. Matrix factorization is an excellent method for dimension reduction and feature extraction of data. In particular, NMF approximates the data matrix as the product of two matrices in which all factors are non-negative. Our joint NMF can extract common factors among multiple gene expression profiles by applying each NMF to them under the constraint that one of the factorized matrices is shared among the multiple NMFs. The joint NMF determines more robust and accurate cell clustering results by leveraging multiple quantification methods compared to the conventional clustering methods, which uses only a single quantification method. In conclusion, our study showed that our clustering method using multiple gene expression profiles is more accurate than other popular methods.

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