Cadherin-11 blockade reduces inflammation-driven fibrotic remodeling and improves outcomes after myocardial infarction

Schroer, Alison K.; Bersi, Matthew R.; Clark, Catherine L.; Zhang, Qinkun; Sanders, Lehanna H.; Hatzopoulos, Antonis K.; Force, Thomas; Majka, Susan M.; Lal, Hind; Merryman, W. David

doi:10.1172/jci.insight.131545

Cited by 39 publications

(36 citation statements)

References 52 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…CDH11 was identified to participate in multiple BPs including bone formation, cellular signal transduction, tumor invasion, and metastasis (Lee et al, 2007;Li et al, 2012;Langhe et al, 2016;Madarampalli et al, 2019;Yuan et al, 2019a), and also play important roles in developmental and pathogenic mechanisms of heart valve (Zhou et al, 2013;Bowler et al, 2018). A recent study found that CDH11 contributed to inflammation-driven fibrotic remodeling after myocardial infarction (Schroer et al, 2019), which indicated that the increased CDH11 might be involved in the development of HF through inflammatory response. Besides, lncRNA NONRATT027756 was predicted to trans-regulate HCN4 by means of miRNA sequestration.…”

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis and Co-Expression Network of mRNAs and lncRNAs in Pressure Overload-Induced Heart Failure

Chen

Xue

et al. 2019

Front. Genet.

View full text Add to dashboard Cite

Aim: Heart failure (HF) is the end stage of various cardiovascular diseases. However, the precise regulation of gene expression profiles and functional mechanisms of long non-coding RNAs (lncRNAs) in HF remain to be elucidated. The present study aimed to identify the differentially expressed profiles and interaction of messenger RNAs (mRNAs) and lncRNAs in pressure overload-induced HF.Methods: Male Sprague-Dawley rats were randomly divided into the HF group and the sham-operated group. HF was induced by the transverse aortic constriction (TAC) surgery. The cardiac expression profiles of mRNAs and lncRNAs in HF were investigated using the microarray. Bioinformatics analyses and co-expression network construction were performed from the RNA sequencing data.Results: The expression profiles of mRNAs and lncRNAs showed significant differences between HF and controls. A total of 147 mRNAs and 162 lncRNAs were identified to be differentially expressed with a fold change of >2 in HF. The relative expression levels of several selected mRNAs and lncRNAs were validated by quantitative PCR. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that diverse pathways were involved in the molecular mechanisms of cardiac hypertrophy and HF including immune response, smooth muscle contraction, ion transmembrane transport. The mRNA-lncRNA and transcription factors (TFs)-lncRNA co-expression networks were constructed and several genes and TFs were identified as key regulators in the pathogenesis of HF. Further functional prediction showed that the lncRNA NONRATT013999 was predicted to cis-regulate mRNA CDH11, and NONRATT027756 was predicted to trans-regulate HCN4.Conclusion: This study revealed specific expression regulation and potential functions of mRNAs and lncRNAs in pressure overload-induced HF. These results will provide new insights into the underlying mechanisms and potential therapeutic targets for HF.

show abstract

Section: Discussionmentioning

confidence: 99%

Comprehensive Analysis and Co-Expression Network of mRNAs and lncRNAs in Pressure Overload-Induced Heart Failure

Chen

Xue

et al. 2019

Front. Genet.

View full text Add to dashboard Cite

show abstract

“…Krishnan et al [133], Hu et al [134], Martins et al [135], Prieto-Sánchez et al [136], Sugulle et al [137], Zhao et al [138], Siddiqui et al [139], Han et al [140], Lappas et al [141], Wang et al [142], Artunc-Ulkumen et al [143], Blois et al [144], Vacínová et al [145] and Vilmi-Kerälä et al [146] demonstrated that the expression of CREBRF (CREB3 regulatory factor), STRA6, EGFR (epidermal growth factor receptor), MFSD2A, GDF15, PAK1, VCAM1, IGFBP2, IGFBP7, PRKCA (protein kinase C alpha), ADAMTS9, LGALS1, BIN1, TIMP1 and are associated with progression of GDM. Aquila et al, [147],Chen et al [148], Xie et al [149], Zhang et al [150], Aspit et al [151], Akadam-Teker et al [152], Jiang et al [153], Cetinkaya et al [154], Grond-Ginsbach et al [155], Dong et al [156], Chardon et al [157], Chen et al [158], Yamada et al [159], Hu et al [160], Bobik and Kalinina [161], Schwanekamp et al [162], Liu et al [163], Schroer et al [164], Raza et al [165], Yang et al [166], Azuaje et al [167], Durbin et al [168], Chowdhury et al [169], Wang et al [170], Li et al [171], Lv et al [172], Bertoli-Avella et al [173], Grossman et al [174], Andenæs et al [175] and Chen et al [176] demonstrated that HES1, SPIN1, TBX3, EVA1A, CAP2, BMP1, HSPB8, RDX (radixin), COL5A1, LIMS2, PARVA (parvin alpha), EGFLAM (EGF like, fibronectin type III and laminin G domains), NEXN (nexilin F-actin binding protein), TNFRSF14, TGFBI (transforming growth factor beta induced), HAVCR2, CDH11, COL4A1, COL4A2, COL5A2, SHROOM3, HYAL2, PDLIM3, ETS2, PLSCR4, TGFB3, COL6A2 and LTBP2 could induce cardiovascular diseases, but these genes might be essential for progression of GDM. Flamant et al [177], Wan et al [178], Zhang et al [179], Vallvé et al [180], Heximer and Husain [181], Selvarajah et al [182], Jain et al [183], Sun et al [184], Satomi-Kobayashi et al [185], Jiang et al [186], Waghulde et al [187] and Dahal et al [188] reported that DDR1, CAST (calpastatin), KYNU (kynureninas...…”

Section: Discussionmentioning

confidence: 99%

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Vastrad¹,

Vastrad²,

Tengli

2021

Preprint

View full text Add to dashboard Cite

Gestational diabetes mellitus (GDM) is one of the metabolic diseases during pregnancy. The identification of the central molecular mechanisms liable for the disease pathogenesis might lead to the advancement of new therapeutic options. The current investigation aimed to identify central differentially expressed genes (DEGs) in GDM. The transcription profiling by array data (E-MTAB-6418) was obtained from the ArrayExpress database. The DEGs between GDM samples and non GDM samples were analyzed with limma package. Gene ontology (GO) and REACTOME enrichment analysis were performed using ToppGene. Then we constructed the protein-protein interaction (PPI) network of DEGs by the Search Tool for the Retrieval of Interacting Genes database (STRING) and module analysis was performed. Subsequently, we constructed the miRNA-hub gene network and TF-hub gene regulatory network by the miRNet database and NetworkAnalyst database. The validation of hub genes was performed through receiver operating characteristic curve (ROC). Finally, the candidate small molecules as potential drugs to treat GDM were predicted by using molecular docking. Through transcription profiling by array data, a total of 869 DEGs were detected including 439 up regulated and 430 down regulated genes. Biological process analysis of GO enrichment analysis showed these DEGs were mainly enriched in reproduction, nuclear outer membrane-endoplasmic reticulum membrane network, identical protein binding, cell adhesion, supramolecular complex and signaling receptor binding. Signaling pathway enrichment analysis indicated that these DEGs played a vital in cell surface interactions at the vascular wall and extracellular matrix organization. Ten genes, HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA in the center of the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were associated with GDM, according to ROC analysis. Finally, the most significant small molecules were predicted based on molecular docking. Our results indicated that HSP90AA1, EGFR, RPS13, RBX1, PAK1, FYN, ABL1, SMAD3, STAT3, and PRKCA could be the potential novel biomarkers for GDM diagnosis, prognosis and the promising therapeutic targets. The current might be essential to understanding the molecular mechanism of GDM initiation and development.

show abstract

“…It suggests that CDH11 plays an important part in solving tissue rupture and promoting myocardial remodeling. CDH11 may serve as a potential therapeutic target, so targeting CDH11 may reduce early inflammation and tissue breakdown mediated by neutrophil and macrophage, later collagen deposition mediated by myofibroblast and inflammation and fibrotic remodeling after MI 83 .…”

Section: Other Diseases and Cdh11mentioning

confidence: 99%

Research progress in the role and mechanism of Cadherin-11 in different diseases

Chen¹,

Xiang²,

Yu³

et al. 2021

J. Cancer

View full text Add to dashboard Cite

Cadherin is an important cell-cell adhesion molecule, which mediates intercellular adhesion through calcium dependent affinity interaction. Cadherin-11 (CDH11, OB-cadherin) is a member of cadherin family, and its gene is situated on chromosome 16q22.1. Increasing lines of researches have proved that CDH11 plays important roles in the occurrence and development of a lot of diseases, such as tumors, arthritis and so on. CDH11 often leads to promoter methylation inactivation, which can induce cancer cell apoptosis, suppress cell motility and invasion, and can inhibit cancer through Wnt/β-catenin, AKT/Rho A and NF-κB signaling pathways. This review focused on the current knowledge of CDH11, including its function and mechanism in different diseases. In this article, we aimed to have a more comprehensive and in-depth understanding of CDH11 and to provide new ideas for the treatment of some diseases.

show abstract

Cadherin-11 blockade reduces inflammation-driven fibrotic remodeling and improves outcomes after myocardial infarction

Cited by 39 publications

References 52 publications

Comprehensive Analysis and Co-Expression Network of mRNAs and lncRNAs in Pressure Overload-Induced Heart Failure

Comprehensive Analysis and Co-Expression Network of mRNAs and lncRNAs in Pressure Overload-Induced Heart Failure

Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus

Research progress in the role and mechanism of Cadherin-11 in different diseases

Contact Info

Product

Resources

About