Integrative high-resolution microarray analysis of human myeloma cell lines reveals deregulated miRNA expression associated with allelic imbalances and gene expression profiles

2009 ◽  
Vol 48 (6) ◽  
pp. 521-531 ◽  
Author(s):  
Marta Lionetti ◽  
Luca Agnelli ◽  
Laura Mosca ◽  
Sonia Fabris ◽  
Adrian Andronache ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Resolution ◽  
Cell Lines ◽  
Microarray Analysis ◽  
Mirna Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Myeloma Cell ◽  
Human Myeloma Cell

Integrative Genomic Approach Identifies Deregulated MicroRNAs in Human Myeloma Cell Lines.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1684-1684
Author(s):  
Marta Lionetti ◽  
Luca Agnelli ◽  
Laura Mosca ◽  
Katia Todoerti ◽  
Domenica Ronchetti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Lines ◽  
Mirna Expression ◽  
Mirna Gene ◽  
Myeloma Cell ◽  
Host Gene ◽  
Expression Levels ◽  
Mirna Genes ◽  
Genome Wide ◽  
Human Myeloma Cell

Abstract The recent discovery of microRNAs (miRNAs), small noncoding RNAs involved in the regulation of cell cycle, survival, and differentiation programmes, has added a further level of complexity to normal and cancer cell biology. Loss or amplification of miRNA genes by broad cytogenetic abnormalities or minute molecular aberrations has been observed in a variety of human malignancies, with the consequent altered expression of these regulatory genes. Additionally, approximately one third of miRNAs are located within the intronic regions of coding transcription units, and recent evidence indicates that the expression of these miRNAs largely coincides with the transcription of the corresponding host genes. To date, no evidence of deregulated miRNA expression has been reported in multiple myeloma (MM). To provide insights into miRNA biology in MM, we performed an integrative analysis of genome-wide, gene expression and miRNA expression profilings in a panel of 16 human myeloma cell lines (HMCLs). Global miRNA and mRNA expression data were generated on Agilent miRNA microarrays (representing 470 human mature miRNAs) and GeneChip® HG-U133A arrays, respectively, and both quantile-normalized. Genome-wide profiling data were generated on GeneChip® Human Mapping 250K NspI arrays and copy number (CN) values were inferred using the circulary binary segmentation (DNAcopy R Bioconductor package). To measure the correlation between the expression levels of each miRNA and the corresponding CN value or host gene expression, conventional non-parametric analyses were performed (Kendall’s tau and Wilcoxon rank-sum tests). As regards miRNA gene CN, the most frequent alteration identified was represented by gain/amplification (for all miRNA genes investigated, an increased CN was present in at least 3 HMCLs, with an average frequency of 58%), followed by loss (5%) and biallelic deletion (0.3%). Our analysis revealed that 14 different miRNA transcripts (miR-15a, miR-19a, miR-21, miR-22, miR-30d, miR-99b, miR-130b, miR-132, miR-140, miR-185, miR-339, miR-491, miR-503, miR-768-3p) had concordant levels with the inferred CN value of the corresponding miRNA gene. Notably, the identified miRNAs mapped to different genomic regions, some of which are involved in recurrent CN alterations in MM, such as 8q24, 19q13.33, or chromosome arms 13q, 16q, 17p, 17q, 22q, and for some of the miRNAs a role in other types of cancer has already been suggested. As regards intragenic miRNAs, 187 miRNA/host gene pairs were obtained after localizing miRNAs within the absolute 5′ and 3′ regions of genes represented on the HG-U133A arrays; 25 of these showed a significant correlation between miRNA and mRNA levels. Among the most correlated miRNA/hostgene pairs we identified miR-152/COPZ2, miR-342-3p/EVL, miR-335/MEST, miR-25 and miR-106b/MCM7. For some of the identified pairs, miRNA expression levels were validated by means of Q-RT-PCR. In conclusion, we showed that miRNA expression in HMCLs could be affected by the presence of genomic lesions or may correlate with host-gene modulation, suggesting a possible role in the molecular pathogenesis of MM. Our integrative approach represents the basis for further investigations, also in primary tumors, aimed at functionally characterizing specific miRNAs in MM.

Identification and Characterization of Cancer Stem Cells in Multiple Myeloma.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 512-512
Author(s):  
Daniel Sze ◽  
Yen S. Loh ◽  
Suilin Mo ◽  
Warren Kaplan ◽  
Ross D. Brown ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
Cancer Cells ◽  
Cell Lines ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Fold Increase ◽  
Myeloma Cell ◽  
Hoechst 33342 ◽  
Myeloma Cells

Abstract There is increasing evidence that the Cancer Stem Cell (CSC), a small percentage of cancer cells that have the characteristic to self-renew, proliferate, differentiate and replenish the bulk of the tumor, may be the leading cause of cancer relapse after chemotherapy. A distinct subpopulation within cancer cells known as the side population (SP), distinguished via Hoechst 33342 staining, has been repeatedly reported to be enriched with cells possessing CSC characteristics. In this study, we first examine if SP can be identified in four established myeloma cell lines. Hoechst-33342 stained cells were analyzed through FACS LSRII using a blue and red dual-wavelength analysis after UV excitation to detect the important red-blue differential dye emission feature of the SP cells. An average of 26.5% of SP cells was found in RPMI8226, 21.4% in KMS-11, 5.4% in U266 and 10.1% in OPM-2 within the viable cells compartment in four separate experiments. In addition, 4.9% of SP cells were also identified in the plasma cell leukemia cell line ARH77. SP and non-SP cells of RPMI8226 and KMS-11 were then sorted and respective RNAs were extracted, amplified and labeled for subsequent Affymetrix microarray scanning. The gene-expression profiles of SP and non-SP cells from RPMI8226 and KMS-11 were compared before selecting statistically significant genes of interest. Two genes were found to be highly upregulated in SP cells. The first one was the Receptor for Hyaluronan-Mediated Motility (RHAMM) gene of 29.0 and 3.9 fold increase in RPMI8226 and KMS-11 respectively. Increased expression of RHAMM has been previously reported to correlate with human B cell malignancies. The second upregulated gene was the human inhibitor of apoptosis protein-family gene, Apollon, of 4.4 and 3.2 fold increase in RPMI8226 and KMS-11 respectively. Another gene - interferon gamma receptor 1 (IFNGR1) gene was found to be down-regulated in SP cells, of 4.3 and 1.2 fold decrease in RPMI8226 and KMS-11 that may provide an explanation of their escape from immune response via T cells. We then examine if SP cells that represent putative CSC exist in primary myeloma cells. Seven myeloma patients’ bone marrow samples were investigated and 0.1 to 5.2 %, of an average of 1.4% of SP cells were identified in the CD38++ plasma cells compartments in 6 out of 7 bone marrow samples. This study reports the existence of SP in both myeloma cell lines and primary myeloma cases. Further studies will be required to confirm the protein expression of selected genes selected from the gene-expression profiles of SP versus non-SP from myeloma cells for the insights into the characteristic and tumorigenicity of CSC in myeloma.

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.

scholarly journals Comprehensive analysis of the gene expression profiles in human gastric cancer cell lines

Oncogene ◽  
2002 ◽  
Vol 21 (42) ◽  
pp. 6549-6556 ◽  
Author(s):  
Jiafu Ji ◽  
Xin Chen ◽  
Suet Yi Leung ◽  
Jen-Tsan A Chi ◽  
Kent Man Chu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Cell Lines ◽  
Cancer Cell ◽  
Gastric Cancer Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Comprehensive Analysis ◽  
Human Gastric Cancer ◽  
Gastric Cancer Cell Lines

scholarly journals Gene Expression Profiles at Moxibustioned Site (ST36): A Microarray Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hai-Yan Yin ◽  
Yong Tang ◽  
Sheng-Feng Lu ◽  
Ling Luo ◽  
Jia-Ping Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Expression Profiles ◽  
Alternative Therapy ◽  
Gene Expression Profiles ◽  
Biological Processes ◽  
Physiological Conditions ◽  
Pathological Conditions ◽  
Molecular Events ◽  
Zusanli Acupoint

As a major alternative therapy in Traditional Chinese Medicine, it has been demonstrated that moxibustion could generate a series of molecular events in blood, spleen, and brain, and so forth. However, what would happen at the moxibustioned site remained unclear. To answer this question, we performed a microarray analysis with skin tissue taken from the moxibustioned site also Zusanli acupoint (ST36) where 15-minute moxibustion stimulation was administrated. The results exhibited 145 upregulated and 72 downregulated genes which responded immediately under physiological conditions, and 255 upregulated and 243 downregulated genes under pathological conditions. Interestingly, most of the pathways and biological processes of the differentially expressed genes (DEGs) under pathological conditions get involved in immunity, while those under physiological conditions are involved in metabolism.

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