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1.
Br J Cancer ; 118(8): 1062-1073, 2018 04.
Article in English | MEDLINE | ID: mdl-29500406

ABSTRACT

BACKGROUND: Multiple myeloma (MM) is the second most common hematologic malignancy. Aberrant epigenetic modifications have been reported in MM and could be promising therapeutic targets. As response rates are overall limited but deep responses occur, it is important to identify those patients who could indeed benefit from epigenetic-targeted therapy. METHODS: Since HDACi and DNMTi combination have potential therapeutic value in MM, we aimed to build a GEP-based score that could be useful to design future epigenetic-targeted combination trials. In addition, we investigated the changes in GEP upon HDACi/DNMTi treatment. RESULTS: We report a new gene expression-based score to predict MM cell sensitivity to the combination of DNMTi/HDACi. A high Combo score in MM patients identified a group with a worse overall survival but a higher sensitivity of their MM cells to DNMTi/HDACi therapy compared to a low Combo score. In addition, treatment with DNMTi/HDACi downregulated IRF4 and MYC expression and appeared to induce a mature BMPC plasma cell gene expression profile in myeloma cell lines. CONCLUSION: In conclusion, we developed a score for the prediction of primary MM cell sensitivity to DNMTi/HDACi and found that this combination could be beneficial in high-risk patients by targeting proliferation and inducing maturation.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Cellular Reprogramming/drug effects , Epigenesis, Genetic/drug effects , Histone Deacetylase Inhibitors/administration & dosage , Multiple Myeloma/drug therapy , Plasma Cells/drug effects , Animals , Cell Differentiation/drug effects , Cell Differentiation/genetics , Cellular Reprogramming/genetics , Gene Expression Profiling , Gene Expression Regulation, Neoplastic/drug effects , Humans , Mice , Mice, Inbred C57BL , Microarray Analysis , Molecular Targeted Therapy/methods , Multiple Myeloma/genetics , Multiple Myeloma/pathology , Plasma Cells/physiology , Research Design , Transcriptome , Tumor Cells, Cultured
2.
Cytometry B Clin Cytom ; 94(3): 484-492, 2018 05.
Article in English | MEDLINE | ID: mdl-28865180

ABSTRACT

BACKGROUND: Multiple myeloma (MM) is an incurable disease characterized by clonal plasma cell (PC) proliferation within the bone marrow (BM). Next-generation flow cytometry has become the reference tool to follow minimal residual disease (MRD). We developed a new simpler and cheaper flow cytometry method to analyze bone marrow samples in patients with MM. METHODS: To identify and characterize abnormal PCs, we designed a simple panel composed of anti-CD38, antikappa, and antilambda light chain antibodies, combined with two antibody pools with the same fluorophore (anti-CD19 and anti-CD27 for the negative pool and anti-CD56, anti-CD117, and anti-CD200 antibodies for the positive pool). We also developed dedicated software for the automated identification of malignant PCs and MRD assessment. We then compared PC identification with our simple antibody panel and with the larger antibody panel routinely used at Montpellier University Hospital Center in 52 patients with MM (M-CHU cohort). RESULTS: Results for total PC detection (r2  = 0.9965; P < 0.001; n = 52) and malignant PC detection (r2  = 0.9486; P < 0.001; n = 38) obtained with the two panels were significantly correlated. Moreover, comparison of the results obtained by automated detection with our software and by manual gating analysis in 80 BM samples (38 from the M-CHU cohort and 42 patients from another MM cohort) showed strong correlation for both total and malignant PC selection (respectively, r2  = 0.936; P < 0.001 and r2  = 0.9505; P < 0.001). CONCLUSIONS: Our simple and automated strategy for MRD assessment in MM could help increasing reproducibility and productivity without compromising sensitivity and specificity, while decreasing the test cost. © 2017 International Clinical Cytometry Society.


Subject(s)
Multiple Myeloma/pathology , Plasma Cells/pathology , Antibodies/metabolism , Antigens, CD/metabolism , Bone Marrow/metabolism , Bone Marrow/pathology , Cohort Studies , Flow Cytometry/methods , Humans , Multiple Myeloma/metabolism , Neoplasm, Residual/metabolism , Neoplasm, Residual/pathology , Plasma Cells/metabolism , Reproducibility of Results
3.
Front Neurol ; 6: 181, 2015.
Article in English | MEDLINE | ID: mdl-26379616

ABSTRACT

Brain inflammation is one of the hallmarks of Alzheimer disease (AD) and a current trend is that inflammatory mediators, particularly cytokines and chemokines, may represent valuable biomarkers for early screening and diagnosis of the disease. Various studies have reported differences in serum level of cytokines, chemokines, and growth factors in patients with mild cognitive impairment or AD. However, data were often inconsistent and the exact function of inflammation in neurodegeneration is still a matter of debate. In the present work, we measured the expression of 120 biomarkers (corresponding to cytokines, chemokines, growth factors, and related signaling proteins) in the serum of 49 patients with the following diagnosis distribution: 15 controls, 14 AD, and 20 MCI. In addition, we performed the same analysis in the cerebrospinal fluid (CSF) of 20 of these patients (10 AD and 10 controls). Among the biomarkers tested, none showed significant changes in the serum, but 13 were significantly modified in the CSF of AD patients. Interestingly, all of these biomarkers were implicated in neurogenesis or neural stem cells migration and differentiation. In the second part of the study, 10 of these putative biomarkers (plus 4 additional) were quantified using quantitative multiplex ELISA methods in the CSF and the serum of an enlarged cohort composed of 31 AD and 24 control patients. Our results confirm the potential diagnosis interest of previously published blood biomarkers, and proposes new ones (such as IL-8 and TNFR-I). Further studies will be needed to validate these biomarkers which could be used alone, combined, or in association with the classical amyloid and tau biomarkers.

4.
Oncotarget ; 6(8): 6431-47, 2015 Mar 20.
Article in English | MEDLINE | ID: mdl-25669983

ABSTRACT

Resistance to chemotherapy is a major limitation of cancer treatments with several molecular mechanisms involved, in particular altered local drug metabolism and detoxification process. The role of drug metabolism and clearance system has not been satisfactorily investigated in Multiple Myeloma (MM), a malignant plasma cell cancer for which a majority of patients escapes treatment. The expression of 350 genes encoding for uptake carriers, xenobiotic receptors, phase I and II Drug Metabolizing Enzymes (DMEs) and efflux transporters was interrogated in MM cells (MMCs) of newly-diagnosed patients in relation to their event free survival. MMCs of patients with a favourable outcome have an increased expression of genes coding for xenobiotic receptors (RXRα, LXR, CAR and FXR) and accordingly of their gene targets, influx transporters and phase I/II DMEs. On the contrary, MMCs of patients with unfavourable outcome displayed a global down regulation of genes coding for xenobiotic receptors and the downstream detoxification genes but had a high expression of genes coding for ARNT and Nrf2 pathways and ABC transporters. Altogether, these data suggests ARNT and Nrf2 pathways could be involved in MM primary resistance and that targeting RXRα, PXR, LXR and FXR through agonists could open new perspectives to alleviate or reverse MM drug resistance.


Subject(s)
Antineoplastic Agents/pharmacokinetics , Carrier Proteins/metabolism , Multiple Myeloma/metabolism , Drug Resistance, Multiple , Humans , Prognosis
5.
PLoS Comput Biol ; 11(1): e1004077, 2015 Jan.
Article in English | MEDLINE | ID: mdl-25633866

ABSTRACT

DNA microarrays have considerably helped to improve the understanding of biological processes and diseases. Large amounts of publicly available microarray data are accumulating, but are poorly exploited due to a lack of easy-to-use bioinformatics resources. The aim of this study is to build a free and convenient data-mining web site (www.genomicscape.com). GenomicScape allows mining dataset from various microarray platforms, identifying genes differentially expressed between populations, clustering populations, visualizing expression profiles of large sets of genes, and exporting results and figures. We show how easily GenomicScape makes it possible to construct a molecular atlas of the B cell differentiation using publicly available transcriptome data of naïve B cells, centroblasts, centrocytes, memory B cells, preplasmablasts, plasmablasts, early plasma cells and bone marrow plasma cells. Genes overexpressed in each population and the pathways encoded by these genes are provided as well as how the populations cluster together. All the analyses, tables and figures can be easily done and exported using GenomicScape and this B cell to plasma cell atlas is freely available online. Beyond this B cell to plasma cell atlas, the molecular characteristics of any biological process can be easily and freely investigated by uploading the corresponding transcriptome files into GenomicScape.


Subject(s)
B-Lymphocytes/cytology , Cell Differentiation/physiology , Genomics/methods , Internet , Plasma Cells/cytology , Software , Cluster Analysis , Data Mining , Databases, Genetic , Gene Expression Profiling , Humans , Principal Component Analysis
6.
Oncotarget ; 5(9): 2487-98, 2014 May 15.
Article in English | MEDLINE | ID: mdl-24809299

ABSTRACT

DNA repair is critical to resolve extrinsic or intrinsic DNA damage to ensure regulated gene transcription and DNA replication. These pathways control repair of double strand breaks, interstrand crosslinks, and nucleotide lesions occurring on single strands. Distinct DNA repair pathways are highly inter-linked for the fast and optimal DNA repair. A deregulation of DNA repair pathways may maintain and promote genetic instability and drug resistance to genotoxic agents in tumor cells by specific mechanisms that tolerate or rapidly bypass lesions to drive proliferation and abrogate cell death. Multiple Myeloma (MM) is a plasma cell disorder characterized by genetic instability and poor outcome for some patients, in which the compendium of DNA repair pathways has as yet not been assessed for a disease-specific prognostic relevance. We design a DNA repair risk score based on the expression of genes coding for proteins involved in DNA repair in MM cells. From a consensus list of 84 DNA repair genes, 17 had a bad prognostic value and 5 a good prognostic value for both event-free and overall survival of previously-untreated MM patients. The prognostic information provided by these 22 prognostic genes was summed within a global DNA repair score (DRScore) to take into account the tight linkage of repair pathways. DRscore was strongly predictive for both patients' event free and overall survivals. Also, DRscore has the potential to identify MM patients whose tumor cells are dependent on specific DNA repair pathways to design treatments that induce synthetic lethality by exploiting addiction to deregulated DNA repair pathways.


Subject(s)
Biomarkers, Tumor/analysis , Computational Biology , DNA Repair Enzymes/genetics , DNA Repair/genetics , Multiple Myeloma/genetics , Multiple Myeloma/mortality , Aged , DNA Damage/genetics , Female , Humans , Male , Multiple Myeloma/therapy , Predictive Value of Tests , Signal Transduction , Survival Rate
7.
Gut ; 63(9): 1490-500, 2014 Sep.
Article in English | MEDLINE | ID: mdl-24153249

ABSTRACT

OBJECTIVE: Adult primary human hepatocytes (PHHs) support the complete infection cycle of natural HCV from patients' sera. The molecular details underlying sera infectivity towards these cells remain largely unknown. Therefore, we sought to gain a deeper comprehension of these features in the most physiologically relevant culture system. DESIGN: Using kinetic experiments, we defined the optimal conditions to infect PHH and explored the link between cell organisation and permissivity. Based on their infectivity, about 120 sera were classified in three groups. Concentration of 52 analytes was measured in 79 selected sera using multiplexed immunobead-based analyte profiling. RESULTS: PHH permissivity towards HCV infection negatively correlated with cell polarisation and formation of functional bile canaliculi. PHH supported HCV replication for at least 2 weeks with de novo virus production. Depending on their reactivity, sera could be classified in three groups of high, intermediate or low infectivity toward PHH. Infectivity could not be predicted based on the donors' clinical characteristics, viral load or genotype. Interestingly, highly infectious sera displayed a specific cytokine profile with low levels of most of the 52 tested analytes. Among them, 24 cytokines/growth factors could impact hepatocyte biology and infection efficiency. CONCLUSIONS: We identified critical factors leading to efficient PHH infection by HCV sera in vitro. Overall, we showed that this cellular model provides a useful tool for studying the mechanism of HCV infection in its natural host cell, selecting highly infectious isolates, and determining the potency of drugs towards various HCV strains.


Subject(s)
Hepacivirus/pathogenicity , Hepatocytes/virology , Adult , Biomarkers/metabolism , Cell Culture Techniques/methods , Cell Line , Cells, Cultured , Cytokines/metabolism , Hepacivirus/metabolism , Hepatocytes/physiology , Humans , Kinetics , Models, Immunological , Real-Time Polymerase Chain Reaction , Reverse Transcriptase Polymerase Chain Reaction , Serum/virology
8.
Cell Cycle ; 12(17): 2760-73, 2013 Sep 01.
Article in English | MEDLINE | ID: mdl-23966156

ABSTRACT

Every day, cells are faced with thousands of DNA lesions, which have to be repaired to preserve cell survival and function. DNA repair is more or less accurate and could result in genomic instability and cancer. We review here the current knowledge of the links between molecular features, treatment, and DNA repair in multiple myeloma (MM), a disease characterized by the accumulation of malignant plasma cells producing a monoclonal immunoglobulin. Genetic instability and abnormalities are two hallmarks of MM cells and aberrant DNA repair pathways are involved in disease onset, primary translocations in MM cells, and MM progression. Two major drugs currently used to treat MM, the alkylating agent Melphalan and the proteasome inhibitor Bortezomib act directly on DNA repair pathways, which are involved in response to treatment and resistance. A better knowledge of DNA repair pathways in MM could help to target them, thus improving disease treatment.


Subject(s)
Carcinogenesis/genetics , Carcinogenesis/pathology , DNA Repair/genetics , Molecular Targeted Therapy , Multiple Myeloma/genetics , Multiple Myeloma/therapy , Drug Resistance, Neoplasm/genetics , Humans , Models, Biological
9.
PLoS One ; 8(6): e66574, 2013.
Article in English | MEDLINE | ID: mdl-23805239

ABSTRACT

Diffuse gliomas are incurable brain tumors divided in 3 WHO grades (II; III; IV) based on histological criteria. Grade II/III gliomas are clinically very heterogeneous and their prognosis somewhat unpredictable, preventing definition of appropriate treatment. On a cohort of 65 grade II/III glioma patients, a QPCR-based approach allowed selection of a biologically relevant gene list from which a gene signature significantly correlated to overall survival was extracted. This signature clustered the training cohort into two classes of low and high risk of progression and death, and similarly clustered two external independent test cohorts of 104 and 73 grade II/III patients. A 22-gene class predictor of the training clusters optimally distinguished poor from good prognosis patients (median survival of 13-20 months versus over 6 years) in the validation cohorts. This classification was stronger at predicting outcome than the WHO grade II/III classification (P≤2.8E-10 versus 0.018). When compared to other prognosis factors (histological subtype and genetic abnormalities) in a multivariate analysis, the 22-gene predictor remained significantly associated with overall survival. Early prediction of high risk patients (3% of WHO grade II), and low risk patients (29% of WHO grade III) in clinical routine will allow the development of more appropriate follow-up and treatments.


Subject(s)
Brain Neoplasms , Gene Expression Regulation, Neoplastic , Glioma , Adult , Brain Neoplasms/classification , Brain Neoplasms/genetics , Brain Neoplasms/metabolism , Brain Neoplasms/mortality , Case-Control Studies , Disease-Free Survival , Female , Gene Expression Profiling/methods , Glioma/classification , Glioma/genetics , Glioma/metabolism , Glioma/mortality , Humans , Male , Neoplasm Grading , Predictive Value of Tests , Survival Rate
10.
PLoS One ; 8(4): e62752, 2013.
Article in English | MEDLINE | ID: mdl-23646139

ABSTRACT

High throughput DNA microarray has made it possible to outline genes whose expression in malignant plasma cells is associated with short overall survival of patients with Multiple Myeloma (MM). A further step is to elucidate the mechanisms encoded by these genes yielding to drug resistance and/or patients' short survival. We focus here on the biological role of the DEP (for Disheveled, EGL-10, Pleckstrin) domain contained protein 1A (DEPDC1A), a poorly known protein encoded by DEPDC1A gene, whose high expression in malignant plasma cells is associated with short survival of patients. Using conditional lentiviral vector delivery of DEPDC1A shRNA, we report that DEPDC1A knockdown delayed the growth of human myeloma cell lines (HMCLs), with a block in G2 phase of the cell cycle, p53 phosphorylation and stabilization, and p21(Cip1) accumulation. DEPDC1A knockdown also resulted in increased expression of mature plasma cell markers, including CXCR4, IL6-R and CD38. Thus DEPDC1A could contribute to the plasmablast features of MMCs found in some patients with adverse prognosis, blocking the differentiation of malignant plasma cells and promoting cell cycle.


Subject(s)
Multiple Myeloma/genetics , Multiple Myeloma/metabolism , Neoplasm Proteins/genetics , Neoplasm Proteins/metabolism , Apoptosis/genetics , Bone Marrow Cells/metabolism , Bone Marrow Cells/pathology , Cell Cycle/genetics , Cell Differentiation/genetics , Cell Line, Tumor , Cell Proliferation , Cluster Analysis , Cyclin-Dependent Kinase Inhibitor p21/metabolism , GTPase-Activating Proteins , Gene Expression Profiling , Gene Expression Regulation, Neoplastic , Gene Knockdown Techniques , Humans , Multiple Myeloma/mortality , Mutation , Phosphorylation , Plasma Cells/metabolism , Plasma Cells/pathology , Prognosis , Protein Stability , RNA Interference , Signal Transduction , Tumor Suppressor Protein p53/genetics
11.
Blood ; 121(22): 4493-503, 2013 May 30.
Article in English | MEDLINE | ID: mdl-23603913

ABSTRACT

Although functionally competent cytotoxic, T cells are frequently observed in malignant diseases, they possess little ability to react against tumor cells. This phenomenon is particularly apparent in multiple myeloma. We here demonstrate that cytotoxic T cells reacted against myeloma antigens when presented by autologous dendritic cells, but not by myeloma cells. We further show by gene expression profiling and flow cytometry that, similar to many other malignant tumors, freshly isolated myeloma cells expressed several carcinoembryonic antigen-related cell adhesion molecules (CEACAMs) at varying proportions. Binding and crosslinking of CEACAM-6 by cytotoxic T cells inhibited their activation and resulted in T-cell unresponsiveness. Blocking of CEACAM-6 on the surface of myeloma cells by specific monoclonal antibodies or CEACAM-6 gene knock down by short interfering RNA restored T-cell reactivity against malignant plasma cells. These findings suggest that CEACAM-6 plays an important role in the regulation of CD8+ T-cell responses against multiple myeloma; therefore, therapeutic targeting of CEACAM-6 may be a promising strategy to improve myeloma immunotherapy.


Subject(s)
Antigens, CD/immunology , CD8-Positive T-Lymphocytes/immunology , Cell Adhesion Molecules/immunology , Multiple Myeloma/immunology , T-Lymphocytes, Cytotoxic/immunology , Antigens, CD/genetics , Antigens, CD/metabolism , CD8-Positive T-Lymphocytes/metabolism , CD8-Positive T-Lymphocytes/pathology , Cell Adhesion Molecules/genetics , Cell Adhesion Molecules/metabolism , Coculture Techniques , Cytotoxicity, Immunologic/genetics , Cytotoxicity, Immunologic/immunology , GPI-Linked Proteins/genetics , GPI-Linked Proteins/immunology , GPI-Linked Proteins/metabolism , Humans , Immunotherapy/methods , MCF-7 Cells , Multiple Myeloma/pathology , Multiple Myeloma/therapy , Plasma Cells/immunology , Plasma Cells/metabolism , Plasma Cells/pathology , RNA, Small Interfering/genetics , Signal Transduction/immunology , T-Lymphocytes, Cytotoxic/metabolism , Tumor Cells, Cultured , U937 Cells
12.
Bioinformatics ; 29(9): 1149-57, 2013 May 01.
Article in English | MEDLINE | ID: mdl-23493321

ABSTRACT

MOTIVATION: Despite huge prognostic promises, gene expression-based survival assessment is rarely used in clinical routine. Main reasons include difficulties in performing and reporting analyses and restriction in most methods to one high-risk group with the vast majority of patients being unassessed. The present study aims at limiting these difficulties by (i) mathematically defining the number of risk groups without any a priori assumption; (ii) computing the risk of an independent cohort by considering each patient as a new patient incorporated to the validation cohort and (iii) providing an open-access Web site to freely compute risk for every new patient. RESULTS: Using the gene expression profiles of 551 patients with multiple myeloma, 602 with breast-cancer and 460 with glioma, we developed a model combining running log-rank tests under controlled chi-square conditions and multiple testing corrections to build a risk score and a classification algorithm using simultaneous global and between-group log-rank chi-square maximization. For each cancer entity, we provide a statistically significant three-group risk prediction model, which is corroborated with publicly available validation cohorts. CONCLUSION: In constraining between-group significances, the risk score compares favorably with previous risk classifications. AVAILABILITY: Risk assessment is freely available on the Web at https://gliserv.montp.inserm.fr/PrognoWeb/ for personal or test data files. Web site implementation in Perl, R and Apache.


Subject(s)
Gene Expression Profiling , Models, Statistical , Neoplasms/mortality , Algorithms , Breast Neoplasms/genetics , Breast Neoplasms/metabolism , Breast Neoplasms/mortality , Female , Glioma/genetics , Glioma/metabolism , Glioma/mortality , Humans , Multiple Myeloma/genetics , Multiple Myeloma/metabolism , Multiple Myeloma/mortality , Prognosis , Risk Assessment , Survival Analysis
13.
Mol Cancer Ther ; 11(12): 2685-92, 2012 Dec.
Article in English | MEDLINE | ID: mdl-23087257

ABSTRACT

Multiple myeloma is a plasma cell cancer with poor survival, characterized by the clonal expansion of multiple myeloma cells (MMC), primarily in the bone marrow. Novel compounds are currently tested in this disease, but partial or minor patients' responses are observed for most compounds used as a single agent. The design of predictors for drug efficacy could be most useful to better understand basic mechanisms targeted by these drugs and design clinical trials. In the current study, we report the building of a DNA methylation score (DM score) predicting the efficacy of decitabine, an inhibitor of DNA methyltransferase (DNMT), targeting methylation-regulated gene expression. DM score was built by identifying 47 genes regulated by decitabine in human myeloma cell lines and the expression of which in primary MMCs of previously untreated patients is predictive for overall survival. A high DM score predicts patients' poor survival, and, of major interest, high sensitivity of primary MMCs or human myeloma cell lines to decitabine in vitro. Thus, DM score could be useful to design novel treatments with DMNT inhibitor in multiple myeloma and has highlighted 47 genes, the gene products of which could be important for multiple myeloma disease development.


Subject(s)
DNA Methylation/drug effects , DNA Modification Methylases/antagonists & inhibitors , Gene Expression Profiling/methods , Multiple Myeloma/drug therapy , Multiple Myeloma/genetics , Antimetabolites, Antineoplastic/pharmacology , Azacitidine/analogs & derivatives , Azacitidine/pharmacology , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Cell Line, Tumor , Decitabine , Gene Expression Regulation, Neoplastic/drug effects , Humans , Multiple Myeloma/metabolism , Predictive Value of Tests , Prognosis
14.
PLoS One ; 7(7): e42161, 2012.
Article in English | MEDLINE | ID: mdl-22860071

ABSTRACT

Gene expression-based scores used to predict risk in cancer frequently include genes coding for DNA replication, repair or recombination. Using two independent cohorts of 206 and 345 previously-untreated patients with Multiple Myeloma (MM), we identified 50 cell cycle-unrelated genes overexpressed in multiple myeloma cells (MMCs) compared to normal human proliferating plasmablasts and non-proliferating bone marrow plasma cells and which have prognostic value for overall survival. Thirty-seven of these 50 myeloma genes (74%) were enriched in genes overexpressed in one of 3 normal human stem cell populations--pluripotent (18), hematopoietic (10) or mesenchymal stem cells (9)--and only three genes were enriched in one of 5 populations of differentiated cells (memory B lymphocytes, T lymphocytes, polymorphonuclear cells, monocytes, osteoclasts). These 37 genes shared by MMCs and adult or pluripotent stem cells were used to build a stem cell score ((SC)score), which proved to be strongly prognostic in the 2 independent cohorts of patients compared to other gene expression-based risk scores or usual clinical scores using multivariate Cox analysis. This finding highlights cell cycle-unrelated prognostic genes shared by myeloma cells and normal stem cells, whose products might be important for normal and malignant stem cell biology.


Subject(s)
Adult Stem Cells/metabolism , Cell Cycle/genetics , Gene Expression Profiling , Multiple Myeloma/pathology , Pluripotent Stem Cells/metabolism , Adult Stem Cells/immunology , Humans , Immunologic Memory , Multiple Myeloma/genetics , Multiple Myeloma/immunology , Pluripotent Stem Cells/immunology , Prognosis
15.
Blood ; 120(5): 1087-94, 2012 Aug 02.
Article in English | MEDLINE | ID: mdl-22705595

ABSTRACT

Annexin A2 (ANXA2) promotes myeloma cell growth, reduces apoptosis in myeloma cell lines, and increases osteoclast formation. ANXA2 has been described in small cohorts of samples as expressed by myeloma cells and cells of the BM microenvironment. To investigate its clinical role, we assessed 1148 samples including independent cohorts of 332 and 701 CD138-purified myeloma cell samples from previously untreated patients together with clinical prognostic factors, chromosomal aberrations, and gene expression-based high-risk scores, along with expression of ANXA2 in whole BM samples, stromal cells, osteoblasts, osteoclasts, and BM sera. ANXA2 is expressed in all normal and malignant plasma cell samples. Higher ANXA2 expression in myeloma cells is associated with significantly inferior event-free and overall survival independently of conventional prognostic factors and is associated with gene expression-determined high risk and high proliferation. Within the BM, all cell populations, including osteoblasts, osteoclasts, and stromal cells, express ANXA2. ANXA2 expression is increased significantly in myelomatous versus normal BM serum. ANXA2 exemplifies an interesting class of targetable bone-remodeling factors expressed by normal and malignant plasma cells and the BM microenvironment that have a significant impact on survival of myeloma patients.


Subject(s)
Annexin A2/physiology , Multiple Myeloma/diagnosis , Annexin A2/genetics , Annexin A2/metabolism , Biomarkers, Tumor/genetics , Biomarkers, Tumor/metabolism , Biomarkers, Tumor/physiology , Bone Diseases/diagnosis , Bone Diseases/genetics , Case-Control Studies , Cell Line, Tumor , Cell Proliferation , Gene Expression Regulation, Neoplastic , Genetic Association Studies , Humans , Multiple Myeloma/genetics , Multiple Myeloma/mortality , Prognosis , Receptors, Peptide/genetics , Receptors, Peptide/metabolism , Risk Factors , Survival Analysis , Tumor Microenvironment/genetics , Validation Studies as Topic
16.
Haematologica ; 97(4): 622-30, 2012 Apr.
Article in English | MEDLINE | ID: mdl-22102711

ABSTRACT

BACKGROUND: Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. DESIGN AND METHODS: Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. RESULTS: In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, P<0.001) using the training cohort of 206 patients. The spike band score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. CONCLUSIONS: We present a new approach to identify spike genes and their relationship to patients' survival.


Subject(s)
Gene Expression Profiling , Multiple Myeloma/diagnosis , Multiple Myeloma/genetics , Translocation, Genetic , Cluster Analysis , DNA Copy Number Variations , Gene Expression Regulation, Neoplastic , Gene Regulatory Networks , Humans , Multiple Myeloma/mortality , Prognosis
17.
Clin Cancer Res ; 17(23): 7240-7, 2011 Dec 01.
Article in English | MEDLINE | ID: mdl-21986844

ABSTRACT

PURPOSE: Multiple myeloma is an incurable malignant plasma cell disease characterized by survival ranging from several months to more than 15 years. Assessment of risk and underlying molecular heterogeneity can be excellently done by gene expression profiling (GEP), but its way into clinical routine is hampered by the lack of an appropriate reporting tool and the integration with other prognostic factors into a single "meta" risk stratification. EXPERIMENTAL DESIGN: The GEP-report (GEP-R) was built as an open-source software developed in R for gene expression reporting in clinical practice using Affymetrix microarrays. GEP-R processes new samples by applying a documentation-by-value strategy to the raw data to be able to assign thresholds and grouping algorithms defined on a reference cohort of 262 patients with multiple myeloma. Furthermore, we integrated expression-based and conventional prognostic factors within one risk stratification (HM-metascore). RESULTS: The GEP-R comprises (i) quality control, (ii) sample identity control, (iii) biologic classification, (iv) risk stratification, and (v) assessment of target genes. The resulting HM-metascore is defined as the sum over the weighted factors gene expression-based risk-assessment (UAMS-, IFM-score), proliferation, International Staging System (ISS) stage, t(4;14), and expression of prognostic target genes (AURKA, IGF1R) for which clinical grade inhibitors exist. The HM-score delineates three significantly different groups of 13.1%, 72.1%, and 14.7% of patients with a 6-year survival rate of 89.3%, 60.6%, and 18.6%, respectively. CONCLUSION: GEP reporting allows prospective assessment of risk and target gene expression and integration of current prognostic factors in clinical routine, being customizable about novel parameters or other cancer entities.


Subject(s)
Algorithms , Gene Expression Profiling , Multiple Myeloma/genetics , Software , Chromosome Aberrations , Data Interpretation, Statistical , Gene Expression Regulation, Neoplastic , Humans , Microarray Analysis , Multiple Myeloma/mortality , Multiple Myeloma/pathology , Oligonucleotide Array Sequence Analysis , Prognosis
18.
J Immunol ; 187(8): 3931-41, 2011 Oct 15.
Article in English | MEDLINE | ID: mdl-21918187

ABSTRACT

The early steps of differentiation of human B cells into plasma cells are poorly known. We report a transitional population of CD20(low/-)CD38(-) preplasmablasts along differentiation of human memory B cells into plasma cells in vitro. Preplasmablasts lack documented B cell or plasma cell (CD20, CD38, and CD138) markers, express CD30 and IL-6R, and secrete Igs at a weaker level than do plasmablasts or plasma cells. These preplasmablasts further differentiate into CD20(-)CD38(high)CD138(-) plasmablasts and then CD20(-)CD38(high)CD138(+) plasma cells. Preplasmablasts were fully characterized in terms of whole genome transcriptome profiling and phenotype. Preplasmablasts coexpress B and plasma cell transcription factors, but at a reduced level compared with B cells, plasmablasts, or plasma cells. They express the unspliced form of XBP1 mRNA mainly, whereas plasmablasts and plasma cells express essentially the spliced form. An in vivo counterpart (CD19(+)CD20(low/-)CD38(-)IL-6R(+) cells) of in vitro-generated preplasmablasts could be detected in human lymph nodes (0.06% of CD19(+) cells) and tonsils (0.05% of CD19(+) cells). An open access "B to Plasma Cell Atlas," which makes it possible to interrogate gene expression in the process of B cell to plasma cell differentiation, is provided. Taken together, our findings show the existence of a transitional preplasmablast population using an in vitro model of plasma cell generation and of its in vivo counterpart in various lymphoid tissues.


Subject(s)
B-Lymphocytes/cytology , Cell Differentiation/immunology , Plasma Cells/cytology , B-Lymphocytes/immunology , Enzyme-Linked Immunosorbent Assay , Humans , Immunophenotyping , Oligonucleotide Array Sequence Analysis , Plasma Cells/immunology , Reverse Transcriptase Polymerase Chain Reaction
19.
Exp Hematol ; 39(5): 546-557.e8, 2011 May.
Article in English | MEDLINE | ID: mdl-21316416

ABSTRACT

OBJECTIVE: The ADAM (a disintegrin and metalloproteinases) and the related ADAMTS (a disintegrin and metalloproteinases with thrombospondin) motifs metalloproteinases are membrane-anchored and secreted proteins exhibiting key roles in mediating cell adhesion, proteolytic shedding, and cell signaling. Dysregulation of these proteins has been observed in some pathologic states, including cancers. Their contribution to multiple myeloma, a plasma-cell neoplasia strongly dependent on bone marrow environment, has been poorly characterized. MATERIALS AND METHODS: We analyzed the expression of genes encoding for these proteins and their inhibitors (tissue inhibitor of metalloproteinases [TIMP], reversion-inducing cysteine-rich protein with kazal motifs) in normal B-cell differentiation, primary malignant plasma cells, human myeloma cell lines, and various bone marrow environment cells. The prognostic value of the expression of these genes was analyzed in two independent series of newly diagnosed patients. RESULTS: ADAM28 and ADAMTS6 were overexpressed in normal memory B cells, ADAM10 and ADAM19 in plasmablasts, and TIMP1 and TIMP2 in normal bone marrow plasma cells. ADAMTS9 was aberrantly expressed by primary malignant plasma cells and ADAM23 expression was associated with a bad prognosis, its expression being spiked in some primary myeloma cell samples. Bone marrow environment cells displayed distinct expression profiles for genes encoding for ADAMs and their inhibitors. They expressed ADAMTSs genes at a low level, with the exception of bone marrow stromal cells. CONCLUSIONS: This study provides an overview of expression data related to ADAMs and ADAMTSs genes potentially involved in myeloma pathogenesis.


Subject(s)
ADAM Proteins/genetics , Bone Marrow Cells/metabolism , Gene Expression Profiling , Multiple Myeloma/genetics , Plasma Cells/metabolism , Bone Marrow Cells/enzymology , Cell Line , Humans , Multiple Myeloma/enzymology , Plasma Cells/cytology , Plasma Cells/enzymology , Plasma Cells/pathology
20.
Haematologica ; 96(1): 87-95, 2011 Jan.
Article in English | MEDLINE | ID: mdl-20884712

ABSTRACT

BACKGROUND: Proliferation of malignant plasma cells is a strong adverse prognostic factor in multiple myeloma and simultaneously targetable by available (e.g. tubulin polymerase inhibitors) and upcoming (e.g. aurora kinase inhibitors) compounds. DESIGN AND METHODS: We assessed proliferation using gene expression-based indices in 757 samples including independent cohorts of 298 and 345 samples of CD138-purified myeloma cells from previously untreated patients undergoing high-dose chemotherapy, together with clinical prognostic factors, chromosomal aberrations, and gene expression-based high-risk scores. RESULTS: In the two cohorts, 43.3% and 39.4% of the myeloma cell samples showed a proliferation index above the median plus three standard deviations of normal bone marrow plasma cells. Malignant plasma cells of patients in advanced stages or those harboring disease progression-associated gain of 1q21 or deletion of 13q14.3 showed significantly higher proliferation indices; patients with gain of chromosome 9, 15 or 19 (hyperdiploid samples) had significantly lower proliferation indices. Proliferation correlated with the presence of chromosomal aberrations in metaphase cytogenetics. It was significantly predictive for event-free and overall survival in both cohorts, allowed highly predictive risk stratification (e.g. event-free survival 12.7 versus 26.2 versus 40.6 months, P < 0.001) of patients, and was largely independent of clinical prognostic factors, e.g. serum ß2-microglobulin, International Staging System stage, associated high-risk chromosomal aberrations, e.g. translocation t(4;14), and gene expression-based high-risk scores. CONCLUSIONS: Proliferation assessed by gene expression profiling, being independent of serum-ß2-microglobulin, International Staging System stage, t(4;14), and gene expression-based risk scores, is a central prognostic factor in multiple myeloma. Surrogating a biological targetable variable, gene expression-based assessment of proliferation allows selection of patients for risk-adapted anti-proliferative treatment on the background of conventional and gene expression-based risk factors.


Subject(s)
Biomarkers, Tumor/genetics , Cell Proliferation , Chromosome Aberrations , Multiple Myeloma/pathology , Multiple Myeloma/therapy , Plasma Cells/pathology , Biomarkers, Tumor/metabolism , Blotting, Western , Cohort Studies , Gene Expression Profiling , Humans , In Situ Hybridization, Fluorescence , Multiple Myeloma/genetics , Oligonucleotide Array Sequence Analysis , Precision Medicine , Prognosis , RNA, Messenger/genetics , Reverse Transcriptase Polymerase Chain Reaction , Tumor Cells, Cultured
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