Characterization of Oncogene Dysregulation in Multiple Myeloma by Combined FISH and DNA Microarray Analyses.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4844-4844
Author(s):  
Antonino Neri ◽  
Sonia Fabris ◽  
Luca Agnelli ◽  
Michela Mattioli ◽  
Luca Baldini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Dna Microarray ◽  
Plasma Cell ◽  
Target Genes ◽  
Expression Profiles ◽  
Molecular Cytogenetic ◽  
Igh Locus ◽  
Microarray Analyses

Abstract Chromosomal translocations involving the immunoglobulin heavy chain (IGH@) locus and variuos partner loci are frequently associated with multiple myeloma (MM). We investigated the expression profiles of FGFR3/MMSET, CCND1, CCND3, MAF and MAFB genes, respectively involved in t(4;14)(p16.3;q32), t(11;14)(q13;q32), t(6;14)(p21;q32), t(14;16)(q32;q23) and t(14;20)(q32;q12), in purified plasma cell populations from 39 MMs and six plasma cell leukemias (PCL) using DNA microarray analysis, and compared the results with the presence of translocations as assessed by dual-color FISH or RT-PCR. The t(4;14) was found in six MMs, t(11;14) in 9 MMs and 1 PCL, t(6;14) in one MM, t(14;16) in 2 MMs and 1 PCL, and t(14;20) in one PCL. The translocations were associated with the spiked expression of target genes in all cases. Furthermore, gene expression profiling allowed the identification of putative translocations dysregulating CCND1 (1 MM and 1 PCL) and MAFB (1 MM and 1 PCL) without any apparent involvement of immunoglobulin loci. Notably, all of the translocations were mutually exclusive. Markedly increased levels of MMSET expression were found in one MM showing associated FGFR3 and MMSET signals on an unidentified chromosome. Our data suggest the importance of using combined molecular cytogenetic and gene expression approaches to detect genetic aberrations in MM.

A Local Versus Centralized Processing Comparison of Plasma Cell Isolation, Viability, and RNA Integrity.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3413-3413
Author(s):  
Gregory J. Ahmann ◽  
Kimberly J. Henderson ◽  
Tammy L. Price-Troska ◽  
Michael M. Timm ◽  
Rempel Rachel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Viability ◽  
Plasma Cell ◽  
Mayo Clinic ◽  
Expression Profiles ◽  
Tissue Bank ◽  
Cell Yield ◽  
Color Flow ◽  
Cell Counts

Abstract Introduction: The Multiple Myeloma Research Consortium (MMRC) has established a tissue bank for the deposition of bone marrow (BM) samples from patients with multiple myeloma (MM) to be mailed and processed under good laboratory practices (GLP). To date over 300 samples have been collected. The ability for multiple sites to utilize the same GLP protocols for isolation and storage of BM for batch testing can be cost prohibitive and can introduce derived variability. Currently, limited information is available on shipped BM aspirates in regards to cell viability, cell yield, cell purity, and subsequent RNA yield and quality. Materials and methods: To test these determinants we performed a pilot study on behalf of the MMRC where samples were drawn at Mayo Clinic Rochester (MCR) pooled and split into 2 equal aliquots. One-half of each sample was processed following the provided GLP compliant standard operating procedures (SOP’s), immediately after sample procurement, at MCR. The CD138+ cells were stored in TRIZOLTM and the RNA was isolated and analyzed in a single batch. The other half of the aspirate was sent overnight to Mayo Clinic Scottsdale (MCS) where they were processed using an identical protocol. At both locations samples were tested for the following quality determinants; cell yield, RNA yield and integrity, and viability using a 3 color flow cytometric method (CD45, CD38 and 7ADD). Cell counts were performed on the CD138+ fraction to determine plasma cell recovery and a slide based immunofluorescent assay used to determine purity. RNA recovery and integrity were assessed using the Agilent BioanalyzerTM. Lastly, gene expression profiles was compared to determine the “signature” emanating from the shipment of samples. Results: In aggregate, all quality determinants showed similar values when the two sets of samples were compared. Cell viability was similar in both sets of samples as was our ability to collect a highly enriched plasma cell population. The cell yield was very similar (r2=0.52) but slightly lower in the shipped samples (median 71% of locally processed, range 40–140%), probably due to some shipment-associated apoptosis with subsequent loss of cell surface CD138 antigen. The purity of the shipped samples was very similar to that of locally processed (median 94%). Subjective qualitative analysis of the RNA was similar between both groups (shipped yield being 80% of local) with no evidence of degradation in the shipped samples. Details regarding the shipment signatures using gene expression profiling will be presented at the meeting. Conclusion: Here we show that the shipment of samples is feasible with no appreciable loss in cell yield or quality of derived products. % APOPTOTIC+ DEAD PC YIELD PURITY (%) RNA Recovered MCR MCS MCR MCS MCR MCS MCR MCS 8.9 ND 15.2 6.8 93 90 11.4 12.8 6.2 ND 2 2.8 95 99 8 17.2 17.4 8 1.4 1.4 75 88 2.2 0 2.1 18.7 2.8 1.6 96 68 7.2 2 18.1 9.5 1.2 .8 100 94 3.4 .4 5 5.0 8.5 7.2 98 91 12.6 17.8 3.7 5.1 .4 .4 88 87 ND ND 19.5 10.3 1.6 1.2 88 79 .4 3.6 29.1 ND 9.2 1.2 100 56 30.2 1.4 5.6 ND 9.2 7.6 92 88 5.2 16.8 20.3 62.8 2.4 .8 84 61 4.6 0.2 4.6 3.7 10.4 2.4 100 94 29.4 8.4 26.5 13.5 5.8 2.8 ND 97 16.8 5.8 4.5 6.2 2.2 2 100 99 10 4.4 17.5 ND 19.2 12 ND ND 16.4 14

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.

Interleukin-6–dependent gene expression profiles in multiple myeloma INA-6 cells reveal a Bcl-2 family–independent survival pathway closely associated with Stat3 activation

Blood ◽  
2004 ◽  
Vol 103 (1) ◽  
pp. 242-251 ◽  
Author(s):  
Katja Brocke-Heidrich ◽  
Antje K. Kretzschmar ◽  
Gabriele Pfeifer ◽  
Christian Henze ◽  
Dennis Löffler ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Multiple Myeloma ◽  
Interleukin 6 ◽  
Target Genes ◽  
B Lymphocyte ◽  
Expression Profiles ◽  
B Cell Lymphoma ◽  
Myeloma Cells ◽  
Survival Pathway

Abstract Interleukin 6 (IL-6) is a growth and survival factor for multiple myeloma cells. As we report here, the IL-6–dependent human myeloma cell line INA-6 responds with a remarkably rapid and complete apoptosis to cytokine withdrawal. Among the antiapoptotic members of the B-cell lymphoma-2 (Bcl-2) family of apoptosis regulators, only myeloid cell factor-1 (Mcl-1) was slightly induced by IL-6. Overexpression studies demonstrated, however, that IL-6 does not exert its survival effect primarily through this pathway. The IL-6 signal transduction pathways required for survival and the target genes controlled by them were analyzed by using mutated receptor chimeras. The activation of signal transducer and activator of transcription 3 (Stat3) turned out to be obligatory for the survival of INA-6 cells. The same held true for survival and growth of XG-1 myeloma cells. Gene expression profiling of INA-6 cells by using oligonucleotide microarrays revealed many novel IL-6 target genes, among them several genes coding for transcriptional regulators involved in B-lymphocyte differentiation as well as for growth factors and receptors potentially implicated in autocrine or paracrine growth control. Regulation of most IL-6 target genes required the activation of Stat3, underscoring its central role for IL-6 signal transduction. Taken together, our data provide evidence for the existence of an as yet unknown Stat3-dependent survival pathway in myeloma cells.

Gene Expression Profiling of Plasma Cell Dyscrasias: The Role of IGH Translocations in the Heterogeneity of Multiple Myeloma.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4845-4845
Author(s):  
Antonino Neri ◽  
Michela Mattioli ◽  
Luca Agnelli ◽  
Sonia Fabris ◽  
Luca Baldini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Plasma Cell ◽  
Plasma Cells ◽  
Germ Line ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Plasma Cell Dyscrasia ◽  
Transcriptional Level ◽  
Plasma Cell Dyscrasias

Abstract Multiple Myeloma (MM) is the most common form of plasma cell dyscrasia, characterized by a marked heterogeneity of genetic lesions and clinical course. It may develop from a premalignant condition (monoclonal gammopathy ofundetermined significance, MGUS) or progress from intra-medullary to extra-medullaryforms (plasma cell leukemia, PCL). To provide insights into the molecular characterization of plasma cell dyscrasias and to investigate the contribution of specific genetic lesions to the biological and clinical heterogeneity of MM, we analyzed the gene expression profiles of plasma cells isolated from 7 MGUS, 39 MM and 6 PCL patients by means of DNA microarrays. MMs resulted highly heterogeneous at transcriptional level, whereas the differential expression of genes mainly involved in DNA metabolism and proliferation distinguished MGUS from PCLs and the majority of MM cases. The clustering of MM patients was mainly driven by the presence of the most recurrent translocations involving the immunoglobulin heavy-chain locus. Distinct signatures have been found to be associated with different lesions: the overexpression of CCND2 and genes involved in cell adhesion pathways was observed in cases with deregulated MAF and MAFB, whereas genes upregulated in cases with the t(4;14) showed apoptosis related functions. In addition, we identified a set of cancer germ-line antigens specifically expressed in a sub-group of MM patients characterized by an aggressive clinical evolution, a finding that could have implications for patient classification and immunotherapy.

Characterization of oncogene dysregulation in multiple myeloma by combined FISH and DNA microarray analyses

2005 ◽  
Vol 42 (2) ◽  
pp. 117-127 ◽  
Author(s):  
Sonia Fabris ◽  
Luca Agnelli ◽  
Michela Mattioli ◽  
Luca Baldini ◽  
Domenica Ronchetti ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Dna Microarray ◽  
Microarray Analyses

Characterization of Gene Expression Profiles of Plasma Cells in Patients with Multiple Myeloma.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 5082-5082
Author(s):  
Manoela M. Ortega ◽  
Anderson F. Cunha ◽  
Dulcineia M. Alberquerque ◽  
Adriana S.S Duarte ◽  
Carmino De Souza ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Molecular Mechanisms ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Global Analysis ◽  
Gene Expression Profiles ◽  
Accurate Method ◽  
Gold Standard Method

Abstract Background: The molecular mechanisms involved in multiple myeloma (MM) are still not completely elucidated. Recently, the serial analysis of gene expression (SAGE) method has allowed the global analysis of genes expressed in a determined cell or tissue. To the best of our knowledge, no studies in plasma cells of MM have already been performed using the SAGE method. Aims and Methods: Thus, we have characterized, by SAGE, purified plasma cells from a newly diagnosed MM patient and purified normal plasma cells (PN), differentiated from bone marrow B cells of a healthy individual, obtained by magnetic sorting in a column, using the CD-138 antibody macs microbeads. The functional classification of genes was performed according to the Gene Ontology Consortium. Results: After automatic sequencing, a total of 84 965 tags from SAGE MM and 77 080 tags from SAGE PN were generated, representing 24 601 and 25 527 unique tags, respectively. In the comparison of both profiles, 476 differentially expressed transcripts were identified (P< 0.01; fold ≥ 5), including 30% that may represent novel transcripts. The expression of 16 arbitrarily selected genes was further investigated by real-time polymerase chain reaction (qPCR), which was considered the gold standard method for the quantification of gene expression, in the SAGE MM sample, with the purpose of validating the results obtained by the SAGE method. These same genes were also analyzed in purified plasma cell samples of another 13 MM patients, with the purpose of verifying whether the results obtained by the SAGE method were reproducible in MM disease. Similar expression was detected by both methods in almost all analyzed genes (CD19, CD40, FCER2, RNAse1, CCND1, DUSP1, FOSB, IGHG3, IGKC, VFOS and VJUN). Five genes (EEF1D, IL6-ST, PRDM2, B2M and XBP1) had contrasting expression, measured by both methods used in study. In samples of the patients of the MM group, all genes presented equal expressions to the validation results. We have also found in this study, a cluster of genes involved with growth, differentiation and cell cycle, anti apoptosis, cytokine and cytokine receptors, proteasomes, ubiquitines and chemokines, transcriptional and translational genes and finally, genes related to apoptosis, survival and drug resistance. Some of these genes have been previously observed related with MM; however, expressions of genes not related with this disease (to our knowledge), such as PRDM2, TOB1, ERG-1, ZNF630, SNF1LK, S100A, LATS2 and IER3 genes were identified, as well as abnormal and non-identified genes Conclusion: Together, our results indicate that SAGE is an accurate method for: 1) the characterization of the total gene expression in plasma cells, although the measurement of the expression of specific genes by qPCR is recommendable, 2) the identification of the abnormal expression of genes involved in cell proliferation, differentiation and apoptosis and, therefore, seems to substantially contribute to elucidate the pathology of the disease.

scholarly journals Generation of polyclonal plasmablasts from peripheral blood B cells: a normal counterpart of malignant plasmablasts

Blood ◽  
2002 ◽  
Vol 100 (4) ◽  
pp. 1113-1122 ◽  
Author(s):  
Karin Tarte ◽  
John De Vos ◽  
Thomas Thykjaer ◽  
Fenghuang Zhan ◽  
Geneviève Fiol ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Differentiation ◽  
B Cells ◽  
Plasma Cell ◽  
Peripheral Blood ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Homogeneous Population ◽  
Normal Plasma

A new way to identify tumor-specific genes is to compare gene expression profiles between malignant cells and their autologous normal counterparts. In patients with multiple myeloma, a major plasma cell disorder, normal plasma cells are not easily attainable in vivo. We report here that in vitro differentiation of peripheral blood B lymphocytes, purified from healthy donors and from patients with multiple myeloma, makes it possible to obtain a homogeneous population of normal plasmablastic cells. These cells were identified by their morphology, phenotype, production of polyclonal immunoglobulins, and expression of major transcription factors involved in B-cell differentiation. Oligonucleotide microarray analysis shows that these polyclonal plasmablastic cells have a gene expression pattern close to that of normal bone marrow–derived plasma cells. Detailed analysis of genes statistically differentially expressed between normal and tumor plasma cells allows the identification of myeloma-specific genes, including oncogenes and genes coding for tumor antigens. These data should help to disclose the molecular mechanisms of myeloma pathogenesis and to define new therapeutic targets in this still fatal malignancy. In addition, the comparison of gene expression between plasmablastic cells and B cells provides a new and powerful tool to identify genes specifically involved in normal plasma cell differentiation.

Characterization of Oncogene Dysregulation in Multiple Myeloma by Combined FISH and RT-PCR Analyses.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 5056-5056
Author(s):  
Shenxian Qian
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Target Genes ◽  
Expression Profiles ◽  
Youden Index ◽  
Rt Pcr ◽  
Chi Square ◽  
Pcr Product ◽  
Fish Samples ◽  
Chi Square Test

Abstract Chromosomal translocations involving the immunoglobulin heavy chain (IGH) locus and various partner loci frequently are associated with multiple myeloma (MM). We investigated the expression profiles of the FGFR3/MMSET, CCND1, CCND3, MAF genes, which are involved in t(4;14)(p16.3;q32), t(11;14)(q13;q32), t(6;14)(p21;q32), and t(14;16)(q32;q23), respectively. The analysis was performed by RT-PCR from purified plasma cell populations from 57 MMs and we compared the results with the presence of translocations as assessed by dual-color FISH. A t(4;14) was found in 11MMs, t(11;14) in 9 MMs, t(6;14) in 5 MM, and t(14;16) in 4 MMs. In all cases, the translocations were associated with the spiked expression of target genes. Furthermore, gene expression profiling enabled the identification of putative translocations causing dysregulation of CCND1 (1 MM) and MAF (1 MM) without any apparent involvement of immunoglobulin loci. Notably, all of the translocations were mutually exclusive. IGH-MMSET hybrid transcripts were found in 10 of the 57 (17.7%) MM samples. There was complete concordance between the findings of RT-PCR and FISH analyses of the MM samples, with 19.2% (11/57) t(4; 14) detected by FISH. Samples were separated further into three major groups based on the size of the RT-PCR product. The 1064bp, 438bp, and 275bp of IGH-MMSET were found in 7, 2, and in 1 sample, respectively. We then screened all 57 MM samples for the expression of FGFR3 using RT-PCR, with primers amplifying the 283bp fragments. Specific transcripts were detected in 11 (19.2%) samples that validate the t(4; 14) from cytogenetic studies. In the remaining 46 MM patients without t(4; 14), and 10 normal bone marrow controls, the FGFR3 amplified transcript was barely detectable. Only one patient sample without t(4; 14) revealed detectable levels of FGFR3 expression. Thus, RT-PCR assay for FGFR3 expression can detect all cases with evident or cryptic t(4; 14) translocation (P< 0.01). Using the primers corresponding to 7–10 exon in 11 cases of MM patients with overexpression of FGFR3, we directly sequenced the FGFR3 cDNA fragments amplified by PCR. Polymorphism (GGC>GGT) was detected in nine of the 11 patients. This polymorphism was tightly associated with higher expression of FGFR3. No FGFR3 mutations were found in the remaining 2 MM patients with overexpression of FGFR3. Our data indicate that RT-PCR is a sensitive and reliable method for the detection of FGFR3 and IGH-MMSET. Translocation t(4; 14) in MM detected by FISH can be validated by RT-PCR method. We examined our result by the Chi-Square test and revealed 90% sensitivity and 100% specificity. The Youden Index remains 0.9. This rapid and reliable detection of FGFR3 and IGH-MMSET overexpression may have practical clinical utility in the analysis and monitoring of the disease in MM patients with t(4; 14). Our data suggest the importance of using combined molecular cytogenetic and gene expression approaches to detect genetic aberrations in MM.

scholarly journals Time Dependent Gene Expression Changes in the Liver of Mice Treated with Benzene

2008 ◽  
Vol 3 ◽  
pp. BMI.S590 ◽  
Author(s):  
Han-Jin Park ◽  
Jung Hwa Oh ◽  
Seokjoo Yoon ◽  
S.V.S. Rana
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
General Purpose ◽  
Time Dependent ◽  
Expression Data ◽  
Benzene Exposure ◽  
Microarray Analyses ◽  
First Time ◽  
Affymetrix Gene Chip

Benzene is used as a general purpose solvent. Benzene metabolism starts from phenol and ends with p-benzoquinone and o-benzoquinone. Liver injury inducted by benzene still remains a toxicologic problem. Tumor related genes and immune responsive genes have been studied in patients suffering from benzene exposure. However, gene expression profiles and pathways related to its hepatotoxicity are not known. This study reports the results obtained in the liver of BALB/C mice (SLC, Inc., Japan) administered 0.05 ml/100 g body weight of 2% benzene for six days. Serum, ALT, AST and ALP were determined using automated analyzer (Fuji., Japan). Histopathological observations were made to support gene expression data. c-DNA microarray analyses were performed using Affymetrix Gene-chip system. After six days of benzene exposure, twenty five genes were down regulated whereas nineteen genes were up-regulated. These gene expression changes were found to be related to pathways of biotransformation, detoxification, apoptosis, oxidative stress and cell cycle. It has been shown for the first time that genes corresponding to circadian rhythms are affected by benzene. Results suggest that gene expression profile might serve as potential biomarkers of hepatotoxicity during benzene exposure.

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