17 research outputs found
Transcriptional Silencing of the Wnt-Antagonist DKK1 by Promoter Methylation Is Associated with Enhanced Wnt Signaling in Advanced Multiple Myeloma
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
Regularization and grouping -omics data by GCA method: A transcriptomic case.
The paper presents the application of Grade Correspondence Analysis (GCA) and Grade Correspondence Cluster Analysis (GCCA) for ordering and grouping -omics datasets, using transcriptomic data as an example. Based on gene expression data describing 256 patients with Multiple Myeloma it was shown that the GCA method could be used to find regularities in the analyzed collections and to create characteristic gene expression profiles for individual groups of patients. GCA iteratively permutes rows and columns to maximize the tau-Kendall or rho-Spearman coefficients, which makes it possible to arrange rows and columns in such a way that the most similar ones remain in each other's neighbourhood. In this way, the GCA algorithm highlights regularities in the data matrix. The ranked data can then be grouped using the GCCA method, and after that aggregated in clusters, providing a representation that is easier to analyze-especially in the case of large sets of gene expression profiles. Regularization of transcriptomic data, which is presented in this manuscript, has enabled division of the data set into column clusters (representing genes) and row clusters (representing patients). Subsequently, rows were aggregated (based on medians) to visualise the gene expression profiles for patients with Multiple Myeloma in each collection. The presented analysis became the starting point for characterisation of differentiated genes and biochemical processes in which they are involved. GCA analysis may provide an alternative analytical method to support differentiation and analysis of gene expression profiles characterising individual groups of patients
Aberrant Wnt signaling in multiple myeloma: molecular mechanisms and targeting options
Aberrant activation of Wnt/β-catenin signaling plays a central role in the pathogenesis of a wide variety of malignancies and is typically caused by mutations in core Wnt pathway components driving constitutive, ligand-independent signaling. In multiple myelomas (MMs), however, these pathway intrinsic mutations are rare despite the fact that most tumors display aberrant Wnt pathway activity. Recent studies indicate that this activation is caused by genetic and epigenetic lesions of Wnt regulatory components, sensitizing MM cells to autocrine Wnt ligands and paracrine Wnts emanating from the bone marrow niche. These include deletion of the tumor suppressor CYLD, promotor methylation of the Wnt antagonists WIF1, DKK1, DKK3, and sFRP1, sFRP2, sFRP4, sFRP5, as well as overexpression of the co-transcriptional activator BCL9 and the R-spondin receptor LGR4. Furthermore, Wnt activity in MM is strongly promoted by interaction of both Wnts and R-spondins with syndecan-1 (CD138) on the MM cell-surface. Functionally, aberrant canonical Wnt signaling plays a dual role in the pathogenesis of MM: (I) it mediates proliferation, migration, and drug resistance of MM cells; (II) MM cells secrete Wnt antagonists that contribute to the development of osteolytic lesions by impairing osteoblast differentiation. As discussed in this review, these insights into the causes and consequences of aberrant Wnt signaling in MM will help to guide the development of targeting strategies. Importantly, since Wnt signaling in MM cells is largely ligand dependent, it can be targeted by drugs/antibodies that act upstream in the pathway, interfering with Wnt secretion, sequestering Wnts, or blocking Wnt (co)receptors
Caffeic Acid Targets AMPK Signaling and Regulates Tricarboxylic Acid Cycle Anaplerosis while Metformin Downregulates HIF-1α-Induced Glycolytic Enzymes in Human Cervical Squamous Cell Carcinoma Lines
The small molecules, natural antioxidant Caffeic Acid (trans-3,4-Dihydroxycinnamic acid CA) and anti-diabetic drug Metformin (Met), activate 5′-adenosine monophosphate-activated protein kinase (AMPK) and interfere with metabolic reprogramming in human cervical squamous carcinoma cells. Here, to gain more insight into the ability of CA, Met and the combination of both compounds to impair aerobic glycolysis (the “Warburg effect”) and disrupt bioenergetics of cancer cells, we employed the cervical tumor cell lines C-4I and HTB-35/SiHa. In epithelial C-4I cells derived from solid tumors, CA alleviated glutamine anaplerosis by downregulation of Glutaminase (GLS) and Malic Enzyme 1 (ME1), which resulted in the reduction of NADPH levels. CA treatment of the cells altered tricarboxylic acid (TCA) cycle supplementation with pyruvate via Pyruvate Dehydrogenase Complex (PDH), increased ROS formation and enhanced cell death. Additionally, CA and CA/Met evoked intracellular energetic stress, which was followed by activation of AMPK and the impairment of unsaturated FA de novo synthesis. In invasive HTB-35 cells, Met inhibited Hypoxia-inducible Factor 1 (HIF-1α) and suppressed the expression of the proteins involved in the “Warburg effect”, such as glucose transporters (GLUT1, GLUT3) and regulatory enzymes of glycolytic pathway Hexokinase 2 (HK2), 6-Phosphofructo-2-Kinase/Fructose-2,6-Biphosphatase 4 (PFKFB4), Pyruvate Kinase (PKM) and Lactate Dehydrogenase A (LDH). Met suppressed the expression of c-Myc, BAX and cyclin-D1 (CCND1) and evoked apoptosis in HTB-35 cells. In conclusion, both small molecules CA and Met are capable of disrupting energy homeostasis, regulating oxidative metabolism/glycolysis in cervical tumor cells in regard to specific metabolic phenotype of the cells. CA and Met may provide a promising approach in the prevention of cervical cancer progression
Transcriptional Silencing of the Wnt-Antagonist Dickkopf-1 (DKK1) by Promoter Methylation Unleashes Aberrant Wnt Signaling In Advanced Multiple Myeloma
Analysis of <i>DKK1</i> promoter methylation in MM bone marrow samples.
<p>Methylation specific PCR of the CpG island of the <i>DKK1</i> promoter region in the bone marrow samples of twelve patients with multiple myeloma (P1–P12), HT-29 and DLD-1 colon cell lines were used as unmethylated (U_DNA) and methylated (M_DNA) control respectively. DNA bands in lanes labeled with U and M indicate PCR products amplified with primers recognizing unmethylated and methylated promoter sequences respectively.</p
Loss of CYLD expression unleashes Wnt signaling in multiple myeloma and is associated with aggressive disease
DKK1 expression represses Wnt pathway activation in MM.
<p>(A) MM cell lines OPM-1 and UM-1 were transduced with either the LZRS-pBMN-IRES-eGFP (control) or the LZRS-pBMN-DKK1-IRES-eGFP (DKK1) virus. Conditioned medium of sorted, transduced cells was harvested and immunoblotted using a goat polyclonal antibody against DKK1. Representative immunoblot confirms the expression of DKK1 in the conditioned medium of LZRS-pBMN-DKK1-IRES-eGFP transduced cells. β-actin is shown as internal control for equal cell number. (B) Cytoplasmic and nuclear proteins were prepared from the LZRS-pBMN-IRES-eGFP (control) or the LZRS-pBMN-DKK1-IRES-eGFP (DKK1) MM cells, stimulated for 24h with Wnt3a conditioned medium (+). As a control, L-cells conditioned medium was applied (−).To assess β-catenin accumulation, nuclear and cytoplasmic cells lysate was immunoblotted by using a monoclonal anti-β-catenin antibody. The bottom part of the blot was stained with β-tubulin and Histone H2B as controls for cytoplasmic and nuclear proteins, respectively. (C) LZRS-pBMN-IRES-eGFP (control) or the LZRS-pBMN-DKK1-IRES-eGFP (DKK1) cells were transfected with TOPFLASH reporter and renilla contruct. 24 hours upon transfection cells were treated with L-cells conditioned medium (−) or Wnt3a conditioned medium (+).The relative light units value of LZRS-pBMN-IRES-eGFP cells treated with L-cells conditioned medium was normalized to 1. The mean ± SD of representative experiment performed in triplicate is shown. * indicates p value<0.05 *** indicates p value<0.001. by student's t test.</p
<i>DKK1</i> promoter methylation in MM cell lines.
<p>(A) Total RNA was isolated and RT–PCR analyses were performed with the specific primers indicated. Complementary DNA from prostate cancer cell line (PC-3) was used as positive control (PC) for DKK1 expression. The β-actin expression was used as a loading control. (B) Schematic representation of the promoter area analyzed for <i>DKK1</i>, containing a CpG island. White arrows indicate the positions of primers used for bisulfite sequencing, and black arrows indicate the positions of primers used for methylation specific PCR. Each of the CpG dinucleotides is presented as open circle. (C) <i>Upper panel</i>. Representation of bisulfite genomic sequencing results of 5 clones of the <i>DKK1</i> promoter region in HT-29 and DLD-1 colon cell lines used as unmethylated (U_DNA) and methylated (M_DNA) control, respectively. The amplified 326 bp product corresponds to the <i>DKK1</i> promoter region from −193 to +122. In total, 18 CpG dinucleotides (CpGs) within the CpG island were analyzed and are represented as open and closed circles, which indicate unmethylated and methylated CpG sites, respectively. <i>Lower panel</i>. Electropherograms of bisulfite modified DNA from <i>DKK1</i> CpG island in HT-29 (U_DNA) and DLD-1 (M_DNA) cells. (D) Methylation specific PCR of the CpG island of the <i>DKK1</i> promoter region in MM cell lines. DNA bands in lanes labeled with U indicate PCR products amplified with primers recognizing unmethylated promoter sequences, whereas DNA bands in lanes labeled with M represent amplified products with primers designed for the methylated template. (E) Bisulfite sequencing analysis of the the <i>DKK1</i> promoter region in multiple myeloma cell lines, open circles indicating unmethylated CpG sites, and closed circles representing methylated CpG sites. Percentages indicate the fraction of methylated CpG dinucleotides of the total CpG sites analyzed.</p