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.

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.

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.

scholarly journals Gene Expression Profiles of Tumor Biology Provide a Novel Approach to Prognosis and May Guide the Selection of Therapeutic Targets in Multiple Myeloma

2009 ◽  
Vol 27 (25) ◽  
pp. 4197-4203 ◽  
Author(s):  
Ariel Anguiano ◽  
Sascha A. Tuchman ◽  
Chaitanya Acharya ◽  
Kelly Salter ◽  
Cristina Gasparetto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Tumor Biology ◽  
Gene Expression Profiles ◽  
Staging System ◽  
Gene Signature ◽  
Molecular Defects

PurposeMonoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) comprise heterogeneous disorders with incompletely understood molecular defects and variable clinical features. We performed gene expression profiling (GEP) with microarray data to better dissect the molecular phenotypes and prognoses of these diseases.MethodsUsing gene expression and clinical data from 877 patients ranging from normal plasma cells (NPC) to relapsed MM (RMM), we applied gene expression signatures reflecting deregulation of oncogenic pathways and tumor microenvironment to highlight molecular changes that occur as NPCs transition to MM, create a high-risk MGUS gene signature, and subgroup International Staging System (ISS) stages into more prognostically accurate clusters of patients.ResultsMyc upregulation and increasing chromosomal instability (CIN) characterized the evolution from NPC to RMM (P < .0001 for both). Studies of MGUS revealed that some samples shared biologic features with RMM, which comprised the basis for a high-risk MGUS signature. Regarding MM, we subclassified ISS stages into clusters based on shared features of tumor biology. These clusters differentiated themselves based on predictions for prognosis (eg, in ISS stage I, one cluster was characterized by increased CIN and a poor prognosis).ConclusionGEP provides insight into the molecular defects underlying plasma cell dyscrasias that may explain their clinical heterogeneity. GEP also may also refine current prognostic and therapeutic models for MGUS and MM.

scholarly journals Modulation of the Immune Response by Deferasirox in Myelodysplastic Syndrome Patients

2021 ◽  
Vol 14 (1) ◽  
pp. 41
Author(s):  
Hana Votavova ◽  
Zuzana Urbanova ◽  
David Kundrat ◽  
Michaela Dostalova Merkerova ◽  
Martin Vostry ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Blood Cell ◽  
Myelodysplastic Syndrome ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Adaptive Immune Response ◽  
Gene Expression Profiles ◽  
Iron Chelator ◽  
Multiple Cancer

Deferasirox (DFX) is an oral iron chelator used to reduce iron overload (IO) caused by frequent blood cell transfusions in anemic myelodysplastic syndrome (MDS) patients. To study the molecular mechanisms by which DFX improves outcome in MDS, we analyzed the global gene expression in untreated MDS patients and those who were given DFX treatment. The gene expression profiles of bone marrow CD34+ cells were assessed by whole-genome microarrays. Initially, differentially expressed genes (DEGs) were determined between patients with normal ferritin levels and those with IO to address the effect of excessive iron on cellular pathways. These DEGs were annotated to Gene Ontology terms associated with cell cycle, apoptosis, adaptive immune response and protein folding and were enriched in cancer-related pathways. The deregulation of multiple cancer pathways in iron-overloaded patients suggests that IO is a cofactor favoring the progression of MDS. The DEGs between patients with IO and those treated with DFX were involved predominantly in biological processes related to the immune response and inflammation. These data indicate DFX modulates the immune response mainly via neutrophil-related genes. Suppression of negative regulators of blood cell differentiation essential for cell maturation and upregulation of heme metabolism observed in DFX-treated patients may contribute to the hematopoietic improvement.

Characterization of gene expression profiles at low and very low doses of ionizing radiation

DNA Repair ◽  
2013 ◽  
Vol 12 (7) ◽  
pp. 508-517 ◽  
Author(s):  
Ingrid Nosel ◽  
Aurélie Vaurijoux ◽  
Joan-Francesc Barquinero ◽  
Gaetan Gruel
Keyword(s):  
Gene Expression ◽  
Ionizing Radiation ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Low Doses

scholarly journals Classify Hyperdiploidy Status of Multiple Myeloma Patients Using Gene Expression Profiles

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

scholarly journals 909 Differentiation subgroups within LKB1-deficient lung cancer influence both the immune exclusion phenotype and cellular composition of the immune microenvironment

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A954-A955
Author(s):  
Jacob Kaufman ◽  
Doug Cress ◽  
Theresa Boyle ◽  
David Carbone ◽  
Neal Ready ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Lung Adenocarcinoma ◽  
Plasma Cells ◽  
Immune Cell ◽  
Expression Profiles ◽  
Neuroendocrine Differentiation ◽  
Gene Expression Profiles ◽  
Immune Microenvironment ◽  
Immune Exclusion

BackgroundLKB1 (STK11) is a commonly disrupted tumor suppressor in NSCLC. Its loss promotes an immune exclusion phenotype with evidence of low expression of interferon stimulated genes (ISG) and decreased microenvironment immune infiltration.1 2 Clinically, LKB1 loss induces primary immunotherapy resistance.3 LKB1 is a master regulator of a complex downstream kinase network and has pleiotropic effects on cell biology. Understanding the heterogeneous phenotypes associated with LKB1 loss and their influence on tumor-immune biology will help define and overcome mechanisms of immunotherapy resistance within this subset of lung cancer.MethodsWe applied multi-omic analyses across multiple lung adenocarcinoma datasets2 4–6 (>1000 tumors) to define transcriptional and genetic features enriched in LKB1-deficient lung cancer. Top scoring phenotypes exhibited heterogeneity across LKB1-loss tumors, and were further interrogated to determine association with increased or decreased markers of immune activity. Further, immune cell-types were estimated by Cibersort to identify effects of LKB1 loss on the immune microenvironment. Key conclusions were confirmed by blinded pathology review.ResultsWe show that LKB1 loss significantly affects differentiation patterns, with enrichment of ASCL1-expressing tumors with putative neuroendocrine differentiation. LKB1-deficient neuroendocrine tumors had lower expression of Interferon Stimulated Genes (ISG), MHC1 and MHC2 components, and immune infiltration compared to LKB1-WT and non-neuroendocrine LKB1-deficient tumors (figure 1).The abundances of 22 immune cell types assessed by Cibersort were compared between LKB1-deficient and LKB1-WT tumors. We observe skewing of immune microenvironmental composition by LKB1 loss, with lower abundance of dendritic cells, monocytes, and macrophages, and increased levels of neutrophils and plasma cells (table 1). These trends were most pronounced among tumors with neuroendocrine differentiation, and were concordant across three independent datasets. In a confirmatory subset of 20 tumors, plasma cell abundance was assessed by a blinded pathologist. Pathologist assessment was 100% concordant with Cibersort prediction, and association with LKB1 loss was confirmed (P=0.001).Abstract 909 Figure 1Immune-associated Gene Expression Profiles Affected by Neuroendocrine Differentiation within LKB1-Deficient Lung Adenocarcinomas. Gene expression profiles corresponding to five immune-associated phenotypes are shown with bars indicating average GEP scores for tumors grouped according to LKB1 and neuroendocrine status as indicated. P-values represent results from Student’s T-test between groups as indicated.Abstract 909 Table 1LKB1 Loss Affects Composition of Immune Microenvironment. Values indicate log10 P-values comparing LKB1-loss to LKB1-WT tumors. Positive (red) indicates increased abundance in LKB1 loss. Negative (blue) indicates decreased abundance.ConclusionsWe conclude that tumor differentiation patterns strongly influence the immune microenvironment and immune exclusion characteristics of LKB1-deficient tumors. Neuroendocrine differentiation is associated with the strongest immune exclusion characteristics and should be evaluated clinically for evidence of immunotherapy resistance. A novel observation of increased plasma cell abundance is observed across multiple datasets and confirmed by pathology. Causal mechanisms linking differentiation status to immune activity is not well understood, and the functional role of plasma cells in the immune biology of LKB1-deficient tumors is undefined. These questions warrant further study to inform precision immuno-oncology treatments for these patients.AcknowledgementsThis work was funded by SITC AZ Immunotherapy in Lung Cancer grant (SPS256666) and DOD Lung Cancer Research Program Concept Award (LC180633).ReferencesSkoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5:860–77.Schabath MB, Welsh EA, Fulp WJ, et al. Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma. Oncogene 2016;35:3209–16.Skoulidis F, Goldberg ME, Greenawalt DM, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery 2018;8:822-835.Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511:543–50.Chitale D, Gong Y, Taylor BS, et al. An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 2009;28:2773–83.Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 2008;14:822–7.

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