45 research outputs found

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

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    <p>Abstract</p> <p>Background</p> <p>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.</p> <p>Methods</p> <p>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).</p> <p>Results</p> <p>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.</p> <p>Conclusions</p> <p>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.</p

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

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    <p>Abstract</p> <p>Background</p> <p>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<sup>® </sup>technology provides both a quantitative fluorescence signal and a decision (<it>detection call</it>: 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.</p> <p>Results</p> <p>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).</p> <p>Conclusion</p> <p>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.</p

    Transcriptional Silencing of the Wnt-Antagonist DKK1 by Promoter Methylation Is Associated with Enhanced Wnt Signaling in Advanced Multiple Myeloma

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    The Wnt/β-catenin pathway plays a crucial role in the pathogenesis of various human cancers. In multiple myeloma (MM), aberrant auto-and/or paracrine activation of canonical Wnt signaling promotes proliferation and dissemination, while overexpression of the Wnt inhibitor Dickkopf1 (DKK1) by MM cells contributes to osteolytic bone disease by inhibiting osteoblast differentiation. Since DKK1 itself is a target of TCF/β-catenin mediated transcription, these findings suggest that DKK1 is part of a negative feedback loop in MM and may act as a tumor suppressor. In line with this hypothesis, we show here that DKK1 expression is low or undetectable in a subset of patients with advanced MM as well as in MM cell lines. This absence of DKK1 is correlated with enhanced Wnt pathway activation, evidenced by nuclear accumulation of β-catenin, which in turn can be antagonized by restoring DKK1 expression. Analysis of the DKK1 promoter revealed CpG island methylation in several MM cell lines as well as in MM cells from patients with advanced MM. Moreover, demethylation of the DKK1 promoter restores DKK1 expression, which results in inhibition of β-catenin/TCF-mediated gene transcription in MM lines. Taken together, our data identify aberrant methylation of the DKK1 promoter as a cause of DKK1 silencing in advanced stage MM, which may play an important role in the progression of MM by unleashing Wnt signaling

    Hepatocyte Growth Factor Increases Osteopontin Expression in Human Osteoblasts through PI3K, Akt, c-Src, and AP-1 Signaling Pathway

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    BACKGROUND: Hepatocyte growth factor (HGF) has been demonstrated to stimulate osteoblast proliferation and participated bone remodeling. Osteopontin (OPN) is a secreted phosphoglycoprotein that belongs to the SIBLING family and is present during bone mineralization. However, the effects of HGF on OPN expression in human osteoblasts are large unknown. METHODOLOGY/PRINCIPAL FINDINGS: Here we found that HGF induced OPN expression in human osteoblasts dose-dependently. HGF-mediated OPN production was attenuated by c-Met inhibitor and siRNA. Pretreatment of osteoblasts with PI3K inhibitor (Ly294002), Akt inhibitor, c-Src inhibitor (PP2), or AP-1 inhibitor (curcumin) blocked the potentiating action of HGF. Stimulation of osteoblasts with HGF enhanced PI3K, Akt, and c-Src activation. In addition, incubation of cells with HGF also increased c-Jun phosphorylation, AP-1-luciferase activity, and c-Jun binding to the AP-1 element on the OPN promoter. HGF-mediated AP-1-luciferase activity and c-Jun binding to the AP-1 element was reduced by c-Met inhibitor, Ly294002, Akt inhibitor, and PP2. CONCLUSIONS/SIGNIFICANCE: Our results suggest that the interaction between HGF and c-Met increases OPN expression in human osteoblasts via the PI3K, Akt, c-Src, c-Jun, and AP-1 signaling pathway

    CXCL12 and [N33A]CXCL12 in 5637 and HeLa Cells: Regulating HER1 Phosphorylation via Calmodulin/Calcineurin

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    In the human neoplastic cell lines 5637 and HeLa, recombinant CXCL12 elicited, as expected, downstream signals via both G-protein-dependent and β-arrestin-dependent pathways responsible for inducing a rapid and a late wave, respectively, of ERK1/2 phosphorylation. In contrast, the structural variant [N33A]CXCL12 triggered no β-arrestin-dependent phosphorylation of ERK1/2, and signaled via G protein-dependent pathways alone. Both CXCL12 and [N33A]CXCL12, however, generated signals that transinhibited HER1 phosphorylation via intracellular pathways. 1) Prestimulation of CXCR4/HER1-positive 5637 or HeLa cells with CXCL12 modified the HB-EGF-dependent activation of HER1 by delaying the peak phosphorylation of tyrosine 1068 or 1173. 2) Prestimulation with the synthetic variant [N33A]CXCL12, while preserving CXCR4-related chemotaxis and CXCR4 internalization, abolished HER1 phosphorylation. 3) In cells knockdown of β-arrestin 2, CXCL12 induced a full inhibition of HER1 like [N33A]CXCL12 in non-silenced cells. 4) HER1 phosphorylation was restored as usual by inhibiting PCK, calmodulin or calcineurin, whereas the inhibition of CaMKII had no discernable effect. We conclude that both recombinant CXCL12 and its structural variant [N33A]CXCL12 may transinhibit HER1 via G-proteins/calmodulin/calcineurin, but [N33A]CXCL12 does not activate β-arrestin-dependent ERK1/2 phosphorylation and retains a stronger inhibitory effect. Therefore, we demonstrated that CXCL12 may influence the magnitude and the persistence of signaling downstream of HER1 in turn involved in the proliferative potential of numerous epithelial cancer. In addition, we recognized that [N33A]CXCL12 activates preferentially G-protein-dependent pathways and is an inhibitor of HER1

    APRIL is overexpressed in cancer: link with tumor progression

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    <p>Abstract</p> <p>Background</p> <p>BAFF and APRIL share two receptors – TACI and BCMA – and BAFF binds to a third receptor, BAFF-R. Increased expression of BAFF and APRIL is noted in hematological malignancies. BAFF and APRIL are essential for the survival of normal and malignant B lymphocytes, and altered expression of BAFF or APRIL or of their receptors (BCMA, TACI, or BAFF-R) have been reported in various B-cell malignancies including B-cell non-Hodgkin's lymphoma, chronic lymphocytic leukemia, Hodgkin's lymphoma, multiple myeloma, and Waldenstrom's macroglobulinemia.</p> <p>Methods</p> <p>We compared the expression of <it>BAFF, APRIL, TACI and BAFF-R </it>gene expression in 40 human tumor types – brain, epithelial, lymphoid, germ cells – to that of their normal tissue counterparts using publicly available gene expression data, including the Oncomine Cancer Microarray database.</p> <p>Results</p> <p>We found significant overexpression of <it>TACI </it>in multiple myeloma and thyroid carcinoma and an association between TACI expression and prognosis in lymphoma. Furthermore, <it>BAFF and APRIL </it>are overexpressed in many cancers and we show that <it>APRIL </it>expression is associated with tumor progression. We also found overexpression of at least one proteoglycan with heparan sulfate chains (HS), which are coreceptors for APRIL and TACI, in tumors where APRIL is either overexpressed or is a prognostic factor. APRIL could induce survival or proliferation directly through HS proteoglycans.</p> <p>Conclusion</p> <p>Taken together, these data suggest that APRIL is a potential prognostic factor for a large array of malignancies.</p
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