RUNX3 Mediates Suppression of Tumor Growth and Metastasis of Human CCRCC by Regulating Cyclin Related Proteins and TIMP-1

Here we presented that the expression of RUNX3 was significantly decreased in 75 cases of clear cell renal cell carcinoma (CCRCC) tissues (p<0.05). Enforced RUNX3 expression mediated 786-O cells to exhibit inhibition of growth, G1 cell-cycle arrest and metastasis in vitro, and to lost tumorigenicity in nude mouse model in vivo. RUNX3-induced growth suppression was found partially to regulate various proteins, including inhibition of cyclinD1, cyclinE, cdk2, cdk4 and p-Rb, but increase of p27Kip1, Rb and TIMP-1. Therefore, RUNX3 had the function of inhibiting the proliferative and metastatic abilities of CCRCC cells by regulating cyclins and TIMP1

Table3_In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis.XLSX

Background: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mechanisms of ESRD and OS.Methods and results: Download microarray data for ESRD and OS from the Gene Expression Omnibus (GEO) database. Weighted correlation network analysis (WGCNA) was used to identify co-expression modules associated with ESRD and OS. Random Forest (RF) and Lasso Regression were performed to identify candidate genes, and consensus clustering for hierarchical analysis. In addition, miRNAs shared in ESRD and OS were identified by differential analysis and their target genes were predicted by Tragetscan. Finally, we constructed a common miRNAs-mRNAs network with candidate genes and shared miRNAs. By WGCNA, two important modules of ESRD and one important module of OS were identified, and the functions of three major clusters were identified, including ribosome, RAS pathway, and MAPK pathway. Eight gene signatures obtained by using RF and Lasso machine learning methods with area under curve (AUC) values greater than 0.7 in ESRD and in OS confirmed their diagnostic performance. Consensus clustering successfully stratified ESRD patients, and C1 patients with more severe ESRD phenotype and OS phenotype were defined as “OS-prone group”.Conclusion: Our work identifies biological processes and underlying mechanisms shared by ESRD and OS, and identifies new candidate genes that can be used as biomarkers or potential therapeutic targets, revealing molecular alterations in susceptibility to OS in ESRD patients.</p

Table2_In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis.XLSX

Background: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mechanisms of ESRD and OS.Methods and results: Download microarray data for ESRD and OS from the Gene Expression Omnibus (GEO) database. Weighted correlation network analysis (WGCNA) was used to identify co-expression modules associated with ESRD and OS. Random Forest (RF) and Lasso Regression were performed to identify candidate genes, and consensus clustering for hierarchical analysis. In addition, miRNAs shared in ESRD and OS were identified by differential analysis and their target genes were predicted by Tragetscan. Finally, we constructed a common miRNAs-mRNAs network with candidate genes and shared miRNAs. By WGCNA, two important modules of ESRD and one important module of OS were identified, and the functions of three major clusters were identified, including ribosome, RAS pathway, and MAPK pathway. Eight gene signatures obtained by using RF and Lasso machine learning methods with area under curve (AUC) values greater than 0.7 in ESRD and in OS confirmed their diagnostic performance. Consensus clustering successfully stratified ESRD patients, and C1 patients with more severe ESRD phenotype and OS phenotype were defined as “OS-prone group”.Conclusion: Our work identifies biological processes and underlying mechanisms shared by ESRD and OS, and identifies new candidate genes that can be used as biomarkers or potential therapeutic targets, revealing molecular alterations in susceptibility to OS in ESRD patients.</p

Table1_In-depth exploration of the shared genetic signature and molecular mechanisms between end-stage renal disease and osteoporosis.XLSX

Background: Osteoporosis (OS) and fractures are common in patients with end-stage renal disease (ESRD) and maintenance dialysis patients. However, diagnosing osteoporosis in this population is challenging. The aim of this research is to explore the common genetic profile and potential molecular mechanisms of ESRD and OS.Methods and results: Download microarray data for ESRD and OS from the Gene Expression Omnibus (GEO) database. Weighted correlation network analysis (WGCNA) was used to identify co-expression modules associated with ESRD and OS. Random Forest (RF) and Lasso Regression were performed to identify candidate genes, and consensus clustering for hierarchical analysis. In addition, miRNAs shared in ESRD and OS were identified by differential analysis and their target genes were predicted by Tragetscan. Finally, we constructed a common miRNAs-mRNAs network with candidate genes and shared miRNAs. By WGCNA, two important modules of ESRD and one important module of OS were identified, and the functions of three major clusters were identified, including ribosome, RAS pathway, and MAPK pathway. Eight gene signatures obtained by using RF and Lasso machine learning methods with area under curve (AUC) values greater than 0.7 in ESRD and in OS confirmed their diagnostic performance. Consensus clustering successfully stratified ESRD patients, and C1 patients with more severe ESRD phenotype and OS phenotype were defined as “OS-prone group”.Conclusion: Our work identifies biological processes and underlying mechanisms shared by ESRD and OS, and identifies new candidate genes that can be used as biomarkers or potential therapeutic targets, revealing molecular alterations in susceptibility to OS in ESRD patients.</p

Serum Response Factor Accelerates the High Glucose-Induced Epithelial-to-Mesenchymal Transition (EMT) via Snail Signaling in Human Peritoneal Mesothelial Cells

<div><p>Background</p><p>Epithelial-to-Mesenchymal Transition (EMT) induced by glucose in human peritoneal mesothelial cells (HPMCs) is a major cause of peritoneal membrane (PM) fibrosis and dysfunction.</p><p>Methods</p><p>To investigate serum response factor (SRF) impacts on EMT-derived fibrosis in PM, we isolated HPMCs from the effluents of patients with end-stage renal disease (ESRD) to analyze alterations during peritoneal dialysis (PD) and observe the response of PM to SRF in a rat model.</p><p>Results</p><p>Our results demonstrated the activation and translocation of SRF into the nuclei of HPMCs under extensive periods of PD. Accordingly, HPMCs lost their epithelial morphology with a decrease in E-cadherin expression and an increase in α-smooth muscle actin (α-SMA) expression, implying a transition in phenotype. PD with 4.25% glucose solution significantly induced SRF up-regulation and increased peritoneal thickness. In immortal HPMCs, high glucose (HG, 60 mmol/L) stimulated SRF overexpression in transformed fibroblastic HPMCs. SRF-siRNA preserved HPMC morphology, while transfection of SRF plasmid into HPMCs caused the opposite effects. Evidence from electrophoretic mobility shift, chromatin immunoprecipitation and reporter assays further supported that SRF transcriptionally regulated Snail, a potent inducer of EMT, by directly binding to its promoter.</p><p>Conclusions</p><p>Our data suggested that activation of SRF/Snail pathway might contribute to the progressive PM fibrosis during PD.</p></div

RUNX3 protein expression in CCRCC tissues and the matched noncancerous counterparts.

<p>a and b. Representative immunohistochemical photographs were taken at different magnifications in CCRCC tumor tissues and their matched noncancerous counterparts (×100 a1, ×200 a2, ×400 a3 and negative control a4 for noncancerous tissues; ×100 b1, ×200 b2, ×400 b3 and negative control b4 for tumor tissues). c. Expression protein levels of Runx3 in six CCRCC and the matched adjacent noncancerous tissues. d.Expression mRNA levels of RUNX3 in the CCRCC-derived cell lines and human kidney proximal tubular cell lines by real time RT-PCR. 18S was used as an internal control. ^*<i>P</i> <0.05 vs HKC cells. e. Expression protein levels of RUNX3 in the CCRCC-derived cell lines and human kidney proximal tubular cell lines by Western Blot. Tubulin was used as an internal control.</p

Overexpression of SRF by a SRF plasmid enhances HPMC EMT <i>in vitro</i>.

<p>(a) Western blot analysis of SRF in HPMCs transfected with a SRF plasmid or control plasmid. (b) Fluorescence microscopy showed the location and expression of the EMT markers E-cadherin, α-SMA and SRF in HPMCs transfected with a SRF plasmid or control plasmid. Magnification is 100×. (c) Real-time PCR showing mRNA of SRF, E-cadherin and α-SMA in HPMCs transfected with a SRF plasmid or control plasmid (*P<0.05 vs. control).</p

HPMC EMT induced by HG <i>in vitro</i> results in increased SRF expression, while knockdown of SRF by SRF-siRNA reverses HPMC EMT <i>in vitro</i>.

<p>(a) Morphological changes in HPMCs induced by HG stimulation for 96 h compared to the control. Magnification is 200×. (b) Fluorescence microscopy showed the altered location and expression of SRF and EMT markers E-cadherin and α-SMA in HPMCs induced by 0 h, 96 h and 7 d of treatment. Magnification is 200×. (c1) Western blot analysis showing the induction of SRF, p-SRF and EMT marker proteins E-cadherin and α-SMA expression by HG at 0 h, 24 h, 48 h, 72 h, 96 h, and 7 d in immortal HPMCs. (c2) Western blot analysis of SRF in HPMCs which were exposed with HG for 96 h and then transfected with SRF-siRNA or control vector. (d1-3) Induction of E-cadherin, α-SMA and SRF mRNA expression at 0 h, 24 h, 48 h, 72 h, 96 h, and 7 d in immortal HPMCs. Bars in A represent the fold induction over untreated cells and are depicted as the mean +/− S.E. of three independent experiments conducted in duplicate(*P<0.05 vs. control HPMCs). (e) Real-time PCR showing mRNA of SRF, E-cadherin and α-SMA in HPMCs transfected with SRF-siRNA or control vector (*P<0.05 vs. HG-HPMCs-control). (f) Fluorescence microscopy showed the location and expression of the EMT markers E-cadherin, α-SMA and SRF in HG-induced SRF-siRNA-treated HPMCs and control cells. Magnification, 200×.</p

Inhibition of SRF by CCG-1423 ameliorates PD-induced PM fibrosis <i>in vivo</i>.

<p>(a) Rats received a daily instillation of PD fluid or saline for 6 weeks. After that period, samples were prepared and analyzed as described in the Concise <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0108593#s2" target="_blank">Methods</a> section. (a1) As measured by HE staining, saline exposure resulted in little change in PM. (a2) Exposure to 4.25% PD fluid resulted in an increase in the thickness of the PM. (a3). CCG-1423 treatment significantly reduced HG-PD effects. The histogram showed the thickness for HE staining in the submesothelial compact zone (mean±SE, n = 8). Magnification is 200×. (b) Staining of the EMT markers E-cadherin, α-SMA and SRF in peritoneal samples by immunohistochemistry reveals that PD fluid exposure induces the EMT process, while CCG-1423 treatment significantly ameliorated EMT-derived fibrosis. Magnification is 200×.</p

Target genes regulated by RUNX3.

<p>a. The expression of cyclin D1, cyclin E, cdk2, cdk4, p-Rb, Rb, p27, MMP2, MMP9, TIMP-1 and TIMP-2 proteins were evaluated in 786-O-Ctrl and 786-O-RUNX3 cells by Western blot. b. The expression of cyclin D1, cyclin E, cdk2, cdk4, p-Rb, Rb, p27, MMP2, MMP9, TIMP-1 and TIMP-2 proteins were evaluated in HKC-Ctrl and HKC-siRUNX3 by Western blot. All examined gene expression levels quantitatively analyzed and expressed as the ratios over β-actin.</p