DNMTi/HDACi combined epigenetic targeted treatment induces reprogramming of myeloma cells in the direction of normal plasma cells.

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.

GenomicScape: an easy-to-use web tool for gene expression data analysis. Application to investigate the molecular events in the differentiation of B cells into plasma cells.

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.

Tumor cells in multiple myeloma patients inhibit myeloma-reactive T cells through carcinoembryonic antigen-related cell adhesion molecule-6.

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.

In vitro infection of primary human hepatocytes by HCV-positive sera: insights on a highly relevant model.

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.

Modeling risk stratification in human cancer.

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.

Clinical and prognostic role of annexin A2 in multiple myeloma.

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.

Osteoclast-gene expression profiling reveals osteoclast-derived CCR2 chemokines promoting myeloma cell migration.

Multiple myeloma is characterized by the clonal expansion of malignant plasma cells (multiple myeloma cells [MMCs]), in the bone marrow. Osteolytic bone lesions are detected in 80% of patients because of increased osteoclastic bone resorption and reduced osteoblastic bone formation. MMCs are found closely associated with sites of increased bone resorption. Osteoclasts strongly support MMC survival in vitro. To further elucidate the mechanisms involved in osteoclast/MMC interaction, we have identified 552 genes overexpressed in osteoclasts compared with other bone marrow cell subpopulations. Osteoclasts express specifically genes coding for 4 CCR2-targeting chemokines and genes coding for MMC growth factors. An anti-CCR2 monoclonal antibody blocked osteoclast chemoattractant activity for MMC, and CCR2 chemokines are also MMC growth factors, promoting mitogen-activated protein kinase activation in MMC. An anti-insulin growth factor-1 receptor monoclonal antibody completely blocked the osteoclast-induced survival of MMC suppressing both osteoclast and MMC survival. Specific a proliferation-inducing ligand or IL-6 inhibitors partially blocked osteoclast-induced MMC survival. These data may explain why newly diagnosed patients whose MMC express high levels of CCR2 present numerous bone lesions. This study displays additional mechanisms involved in osteoclast/MMC interaction and suggests using CCR2 and/or insulin growth factor-1 targeting strategies to block this interaction and prevent drug resistance.

Characterization of a transitional preplasmablast population in the process of human B cell to plasma cell differentiation.

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.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma.

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.

The role of IGF-1 as a major growth factor for myeloma cell lines and the prognostic relevance of the expression of its receptor.

A plethora of myeloma growth factors (MGFs) has been identified, but their relative importance and cooperation have not been determined. We investigated 5 MGFs (interleukin-6 [IL-6], insulin-like growth factor type 1 [IGF-1], hepatocyte growth factor [HGF], HB-epidermal growth factor [HB-EGF], and a proliferation-inducing ligand [APRIL]) in serum-free cultures of human myeloma cell lines (HMCLs). In CD45(-) HMCLs, an autocrine IGF-1 loop promoted autonomous survival whereas CD45(+) HMCLs could not survive without addition of MGFs, mainly IGF-1 and IL-6. IGF-1 was the major one: its activity was abrogated by an IGF-1R inhibitor only, whereas IL-6, HGF, or HB-EGF activity was inhibited by both IGF-1R- and receptor-specific inhibition. APRIL activity was inhibited by its specific inhibitor only. Of the investigated MGFs and their receptors, only expressions of IGF-1R and IL-6R in multiple myeloma cells (MMCs) of patients delineate a group with adverse prognosis. This is mainly explained by a strong association of IGF-1R and IL-6R expression and t(4;14) translocation, but IGF-1R expression without t(4;14) can also have a poor prognosis. Thus, IGF-1-targeted therapy, eventually in combination with anti-IL-6 therapy, could be promising in a subset of patients with MMCs expressing IGF-1R.

Induction of angiogenesis by normal and malignant plasma cells.

Abundant bone marrow angiogenesis is present in almost all myeloma patients requiring therapy and correlated to treatment response and survival. We assessed the expression of 402 angiogenesis-associated genes by Affymetrix DNA microarrays in 466 samples, including CD138-purified myeloma cells (MMCs) from 300 previously untreated patients, in vivo microcirculation by dynamic contrast-enhanced magnetic resonance imaging, and in vitro angiogenesis (AngioKit-assay). Normal bone marrow plasma cells (BMPCs) express a median of 39 proangiogenic (eg, VEGFA, ADM, IGF-1) and 28 antiangiogenic genes (eg, TIMP1, TIMP2). Supernatants of BMPCs unlike those of memory B cells induce angiogenesis in vitro. MMCs do not show a significantly higher median number of expressed proangiogenic (45) or antiangiogenic (31) genes, but 97% of MMC samples aberrantly express at least one of the angiogenic factors HGF, IL-15, ANG, APRIL, CTGF, or TGFA. Supernatants of MMCs and human myeloma cell lines induce significantly higher in vitro angiogenesis compared with BMPCs. In conclusion, BMPCs express a surplus of proangiogenic over antiangiogenic genes transmitting to the ability to induce in vitro angiogenesis. Aberrant expression of proangiogenic and down-regulation of antiangiogenic genes by MMCs further increases the angiogenic stimulus, together leading to bone marrow angiogenesis at various degrees in all myeloma patients.

Inhibition of aurora kinases for tailored risk-adapted treatment of multiple myeloma.

Genetic instability and cellular proliferation have been associated with aurora kinase expression in several cancer entities, including multiple myeloma. Therefore, the expression of aurora-A, -B, and -C was determined by Affymetrix DNA microarrays in 784 samples including 2 independent sets of 233 and 345 CD138-purified myeloma cells from previously untreated patients. Chromosomal aberrations were assessed by comprehensive interphase fluorescence in situ hybridization and proliferation of primary myeloma cells by propidium iodine staining. We found aurora-A and -B to be expressed at varying frequencies in primary myeloma cells of different patient cohorts, but aurora-C in testis cell samples only. Myeloma cell samples with detectable versus absent aurora-A expression show a significantly higher proliferation rate, but neither a higher absolute number of chromosomal aberrations (aneuploidy), nor of subclonal aberrations (chromosomal instability). The clinical aurora kinase inhibitor VX680 induced apoptosis in 20 of 20 myeloma cell lines and 5 of 5 primary myeloma cell samples. Presence of aurora-A expression delineates significantly inferior event-free and overall survival in 2 independent cohorts of patients undergoing high-dose chemotherapy, independent from conventional prognostic factors. Using gene expression profiling, aurora kinase inhibitors as a promising therapeutic option in myeloma can be tailoredly given to patients expressing aurora-A, who in turn have an adverse prognosis.

A high-risk signature for patients with multiple myeloma established from the molecular classification of human myeloma cell lines.

BACKGROUND: Multiple myeloma is a plasma-cell tumor with heterogeneity in molecular abnormalities and treatment response. DESIGN AND METHODS: We have assessed whether human myeloma cell lines have kept patients' heterogeneity using Affymetrix gene expression profiling of 40 human myeloma cell lines obtained with or without IL6 addition and could provide a signature for stratification of patient risk. RESULTS: Human myeloma cell lines, especially those derived in the presence of IL6, displayed a heterogeneity that overlaps that of the patients with multiple myeloma. Human myeloma cell lines segregated into 6 groups marked by overexpression of MAF, MMSET, CCND1, FRZB with or without overexpression of cancer testis antigens (CTA). Cell lines of CTA/MAF and MAF groups have a translocation involving C-MAF or MAFB, cell lines of groups CCND1-1 and CCND1-2like have a t(11;14) and cell lines of group MMSET have a t(4;14). The CTA/FRZB group comprises cell lines that had no or no recurrent 14q32 translocation. Expression of 248 genes accounted for human myeloma cell line molecular heterogeneity. Human myeloma cell line heterogeneity genes comprise genes with prognostic value for survival of patients making it possible to build a powerful prognostic score involving a total of 13 genes. CONCLUSIONS: Human myeloma cell lines derived in the presence of IL6 recapitulate the molecular diversity of multiple myeloma that made it possible to design, using human myeloma cell line heterogeneity genes, a high-risk signature for patients at diagnosis. We propose this classification to be used when addressing the physiopathology of multiple myeloma with human myeloma cell lines.

Proliferation is a central independent prognostic factor and target for personalized and risk-adapted treatment in multiple myeloma.

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.

Gene expression profiling and real-time PCR analyses identify novel potential cancer-testis antigens in multiple myeloma.

Cancer-testis (CT) Ags are attractive targets for immunotherapeutic strategies since they are aberrantly expressed in malignant cells and not, or in limited number, in somatic tissues, except germ cells. To identify novel CT genes in multiple myeloma, we used Affymetrix HG-U133 gene expression profiles of 5 testis, 64 primary multiple myeloma cells (MMC), and 24 normal tissue samples. A 5-filter method was developed to keep known CT genes while deleting non-CT genes. Starting from 44,928 probe sets, including probe sets for 18 previously described CT genes, we have obtained 82 genes expressed in MMC and testis and not detected in more than 6 normal tissue samples. This list includes 14 of the 18 known CT genes and 68 novel putative CT genes. Real-time RT-PCR was performed for 34 genes in 12 normal tissue samples, 5 MMC samples, and one sample of five pooled testes. It has validated the CT status of 23 of 34 genes (67%). We found one novel "testis-restricted" gene (TEX14, expression in testis and tumor only), eight "tissue-restricted" (mRNA detected in one or two nongametogenic tissues), and seven "differentially expressed" (mRNA detected in three to six nongametogenic tissues) CT genes. Further studies are warranted to determine the immunogenicity of these novel CT Ag candidates.

Growth factors in multiple myeloma: a comprehensive analysis of their expression in tumor cells and bone marrow environment using Affymetrix microarrays.

BACKGROUND: Multiple myeloma (MM) is characterized by a strong dependence of the tumor cells on their microenvironment, which produces growth factors supporting survival and proliferation of myeloma cells (MMC). In the past few years, many myeloma growth factors (MGF) have been described in the literature. However, their relative importance and the nature of the cells producing MGF remain unidentified for many of them. METHODS: We have analysed the expression of 51 MGF and 36 MGF receptors (MGFR) using Affymetrix microarrays throughout normal plasma cell differentiation, in MMC and in cells from the bone marrow (BM) microenvironment (CD14, CD3, polymorphonuclear neutrophils, stromal cells and osteoclasts). RESULTS: 4/51 MGF and 9/36 MGF-receptors genes were significantly overexpressed in plasmablasts (PPC) and BM plasma cell (BMPC) compared to B cells whereas 11 MGF and 11 MGFR genes were overexpressed in BMPC compared to PPC. 3 MGF genes (AREG, NRG3, Wnt5A) and none of the receptors were significantly overexpressed in MMC versus BMPC. Furthermore, 3/51 MGF genes were overexpressed in MMC compared to the the BM microenvironment whereas 22/51 MGF genes were overexpressed in one environment subpopulation compared to MMC. CONCLUSIONS: Two major messages arise from this analysis 1) The majority of MGF genes is expressed by the bone marrow environment. 2) Several MGF and their receptors are overexpressed throughout normal plasma cell differentiation. This study provides an extensive and comparative analysis of MGF expression in plasma cell differentiation and in MM and gives new insights in the understanding of intercellular communication signals in MM.

Gene expression of anti- and pro-apoptotic proteins in malignant and normal plasma cells.

The survival of malignant plasma cells is a key event in disease occurrence, progression and chemoresistance. Using DNA-microarrays, we analysed the expression of genes coding for 58 proteins linked with extrinsic and intrinsic apoptotic pathways, caspases and inhibitor of apoptosis proteins. We considered six memory B cells (MBC), seven plasmablasts (PPC), seven bone marrow plasma cells (BMPC) and purified myeloma cells (MMC) from 92 newly-diagnosed patients. Forty out of the 58 probe sets enabled the separation of MBC, PPC and BMPC in three homogeneous clusters, characterized by an elevated expression of TNFRSF10A, TNFRSF10B, BCL2A1, CASP8, CASP9 and PMAIP1 genes for MBC, of FAS, FADD, AIFM1, BIRC5, CASP CASP2, CASP3 and CASP6 for PPC and of BCL2, MCL1, BID, BIRC3 and XIAP for BMPC. Thus, B cell differentiation was associated with change of expression of pro-apoptotic and anti-apoptotic genes. Regarding MMC, the major finding was TRAIL upregulation that might be counteracted by a high osteoprotegerin production by BM stromal cells and a decreased expression of FAS, APAF1 and BNIP3 compared to normal BMPC. Out of the 40 genes, CASP2 and BIRC5 expression in MMC had adverse prognosis in two independent series of previously-untreated patients.

Expression of genes encoding for proteins involved in heparan sulphate and chondroitin sulphate chain synthesis and modification in normal and malignant plasma cells.

Syndecan-1 is a proteoglycan that concentrates heparin-binding factors on the surface of multiple myeloma cells, and probably plays a major role in multiple myeloma biology. As heparan sulphate and chondroitin sulphate are the bioactive components of syndecan-1, we analysed the signature of genes encoding 100 proteins involved in synthesis of these chains, i.e. from precursor uptake to post-translational modifications, using Affymetrix microarrays. The expression of enzymes required for heparan sulphate and chondroitin sulphate biosynthesis was shown to increase in parallel with syndecan-1 expression, throughout the differentiation of memory B cells into plasmablasts and normal bone marrow plasma cells. Sixteen genes were significantly different between normal and malignant plasma cells, nine of these genes -EXT2, CHSY3, CSGALNACT1, HS3ST2, HS2ST1, CHST11, CSGALNACT2, HPSE, SULF2 - encode proteins involved in glycosaminoglycan chain synthesis or modifications. Kaplan-Meier analysis was performed in two independent series of patients: B4GALT7, CSGALNACT1, HS2ST1 were associated with a good prognosis whereas EXT1 was linked to a bad prognosis. This study provides an overall picture of the major genes encoding for proteins involved in heparan sulphate and chondroitin sulphate synthesis and modifications that can be implicated in normal and malignant plasma cells.

Transcriptome of retrovirally transduced CD8+ lymphocytes: influence of cell activation, transgene integration, and selection process.

A suicide gene introduced by retroviral means can allow in vivo control of alloreactivity mediated by donor gene-modified T cells (GMTC) after allogeneic hematopoietic stem cell transplantation. The present study establishes the transcriptomic profile of GMTC prepared according to the GMTC production process used in our clinical trial (activation/selection methods, CD3/NeoR), which was previously demonstrated to induce phenotypical and functional alterations. This transcriptomic profile was compared with that of GMTC prepared by a novel process (CD3-CD28/DeltaNGFR-MACS) that limits alterations. Using a human pan-genomic microarray and GeneSpring software, we determined the gene expression profiles of CD8+ T cells from four healthy donors before and after the different steps required for gene modification. This analysis revealed that the gene expression pattern of GMTC is affected mainly by the activation step. Specific analysis of GMTC production processes showed that DeltaNGFR-MACS selection combined with CD3-CD28 activation limits the aberrant expression of genes involved in immunological functions and apoptotic pathways. Furthermore, our results indicate a limited risk of oncogenesis associated with retroviral-mediated gene transfer in CD8+ cells, a lower perturbation of the cell cycle regulation pathway after CD3-CD28 activation than after CD3 activation, and no significant involvement of the DeltaNGFR transduction signaling pathway when DeltaNGFR is used for selection. Moreover, genes that might be targeted to limit T cell functional alterations after ex vivo manipulation and culture were identified. These findings should be relevant to further adoptive T cell immunotherapy trials using ex vivo-expanded, gene-modified or unmodified T cells.

A new method for class prediction based on signed-rank algorithms applied to Affymetrix microarray experiments.

BACKGROUND: The huge amount of data generated by DNA chips is a powerful basis to classify various pathologies. However, constant evolution of microarray technology makes it difficult to mix data from different chip types for class prediction of limited sample populations. Affymetrix(R) technology provides both a quantitative fluorescence signal and a decision (detection call: absent or present) based on signed-rank algorithms applied to several hybridization repeats of each gene, with a per-chip normalization. We developed a new prediction method for class belonging based on the detection call only from recent Affymetrix chip type. Biological data were obtained by hybridization on U133A, U133B and U133Plus 2.0 microarrays of purified normal B cells and cells from three independent groups of multiple myeloma (MM) patients. RESULTS: After a call-based data reduction step to filter out non class-discriminative probe sets, the gene list obtained was reduced to a predictor with correction for multiple testing by iterative deletion of probe sets that sequentially improve inter-class comparisons and their significance. The error rate of the method was determined using leave-one-out and 5-fold cross-validation. It was successfully applied to (i) determine a sex predictor with the normal donor group classifying gender with no error in all patient groups except for male MM samples with a Y chromosome deletion, (ii) predict the immunoglobulin light and heavy chains expressed by the malignant myeloma clones of the validation group and (iii) predict sex, light and heavy chain nature for every new patient. Finally, this method was shown powerful when compared to the popular classification method Prediction Analysis of Microarray (PAM). CONCLUSION: This normalization-free method is routinely used for quality control and correction of collection errors in patient reports to clinicians. It can be easily extended to multiple class prediction suitable with clinical groups, and looks particularly promising through international cooperative projects like the "Microarray Quality Control project of US FDA" MAQC as a predictive classifier for diagnostic, prognostic and response to treatment. Finally, it can be used as a powerful tool to mine published data generated on Affymetrix systems and more generally classify samples with binary feature values.