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A proteomic approach to differentiate histologically classified stable and unstable plaques from human carotid arteries.

ABSTRACT: By using proteomics we isolated and identified proteins that were expressed/retained in stable and unstable human carotid artery atherosclerotic plaques.The criteria for plaque instability were the presence of a thin fibrous cap or fissured cap covering the foamy or necrotic core, and the presence of overt, hemorrhagic, ulcerated or thrombotic plaques. Proteins were extracted from finely minced endarterectomy specimens (19 stable and 29 unstable plaques) and separated by two-dimensional gel electrophoresis. Coomassie Blue-stained gels were analysed using PD-Quest software.A total of 57 distinct spots corresponding to 33 different proteins were identified by matrix assisted laser desorption/ionization mass spectrometry using the NCBI database. Most of the spots were present in both types of extracts, although significantly (p<0.05) differing in abundance between them. Compared to stable plaque, unstable ones showed reduced abundance of: protective enzymes SOD3 and GST, small heat shock proteins HSP27 and HSP20, annexin A10, and Rho GDI. In unstable plaques the more abundant proteins were: ferritin light subunit, SOD 2 and fibrinogen fragment D. For fibrinogen fragment D, the increased levels in unstable versus stable plaques was confirmed by Western blot analysis.Since many of the differentially expressed proteins are known to have a functional role in inflammation and oxidative stress, we speculate that they may be involved in events relating to plaque stability.

SUBMITTER: Lepedda AJ

PROVIDER: S-EPMC2659534 | biostudies-other | 2009 Mar

REPOSITORIES: biostudies-other

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A proteomic approach to differentiate histologically classified stable and unstable plaques from human carotid arteries.

Lepedda Antonio J AJ Cigliano Antonio A Cherchi Gian Mario GM Spirito Rita R Maggioni Marco M Carta Franco F Turrini Franco F Edelstein Celina C Scanu Angelo M AM Formato Marilena M

Atherosclerosis 20080712 1

<h4>Objectives</h4>By using proteomics we isolated and identified proteins that were expressed/retained in stable and unstable human carotid artery atherosclerotic plaques.<h4>Methods</h4>The criteria for plaque instability were the presence of a thin fibrous cap or fissured cap covering the foamy or necrotic core, and the presence of overt, hemorrhagic, ulcerated or thrombotic plaques. Proteins were extracted from finely minced endarterectomy specimens (19 stable and 29 unstable plaques) and se ...[more]

PMID: 18715566

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Project description:Atherosclerosis is a chronic inflammatory disease with high prevalence and mortality. The rupture of atherosclerotic plaque is the main reason for the clinical events caused by atherosclerosis. Making clear the transcriptomic and proteomic profiles between the stabe and unstable atherosclerotic plaques is crucial to prevent the clinical manifestations. In the present study, 5 stable and 5 unstable human carotid atherosclerotic plaques were obtained by carotid endarterectomy. The samples were used for the whole transcriptome sequencing (RNA-Seq) by the Next-Generation Sequencing using the Illumina HiSeq, and for proteome analysis by HPLC-MS/MS. The lncRNA-targeted genes and circRNA-originated genes were identified by analyzing their location and sequence. Gene Ontology and KEGG enrichment was carried out to analyze the functions of differentially expressed RNAs and proteins. The protein-protein interactions (PPI) network was constructed by the online tool STRING. The consistency of transcriptome and proteome were analyzed, and the lncRNA/circRNA-miRNA-mRNA interactions were predicted. As a result, 202 mRNAs, 488 lncRNAs, 91 circRNAs, and 293 proteins were identified to be differentially expressed between stable and unstable atherosclerotic plaques. The 488 lncRNAs might target 381 protein-coding genes by cis-acting mechanisms. Sequence analysis indicated the 91 differentially expressed circRNAs were originated from 97 protein-coding genes. These differentially expressed RNAs and proteins were mainly enriched in the terms of the cellular response to stress or stimulus, the regulation of gene transcription, the immune response, the nervous system functions, the hematologic activities, and the endocrine system. These results were consistent with the previous reported data in the dataset GSE41571. Further analysis identified CD5L, S100A12, CKB (target gene of lncRNA MSTRG.11455.17), CEMIP (target gene of lncRNA MSTRG.12845), and SH3GLB1 (originated gene of hsacirc_000411) to be critical genes in regulating the stability of atherosclerotic plaques. Our results provided a comprehensive transcriptomic and proteomic knowledge on the stability of atherosclerotic plaques.

Project description:ObjectiveThis study identified underlying genetic molecules associated with histologically unstable carotid atherosclerotic plaques through bioinformatics analysis that may be potential biomarkers and therapeutic targets.MethodsThree transcriptome datasets (GSE41571, GSE120521 and E-MTAB-2055) and one non-coding RNA dataset (GSE111794) that met histological grouping criteria of unstable plaque were downloaded. The common differentially expressed genes (co-DEGs) of unstable plaques identified from three mRNA datasets were annotated by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG). A protein-protein interaction (PPI) network was constructed to present the interaction between co-DEGs and screen out hub genes. MiRNet database and GSE111794 dataset were used to identify the miRNAs targeting hub genes. Associated transcription factors (TFs) and drugs were also predicted. These predicted results were used to construct miRNA/TFs-hub gene and drug-hub gene regulatory networks.ResultsA total of 105 co-DEGs were identified, including 42 up-regulated genes and 63 down-regulated genes, which were mainly enriched in collagen-containing extracellular matrix, focal adhesion, actin filament bundle, chemokine signaling pathway and regulates of actin cytoskeleton. Ten hub genes (up-regulated: HCK, C1QC, CD14, FCER1G, LCP1 and RAC2; down-regulated: TPM1, MYH10, PLS3 and FMOD) were screened. HCK and RAC2 were involved in chemokine signaling pathway, MYH10 and RAC2 were involved in regulation of actin cytoskeleton. We also predicted 12 miRNAs, top5 TFs and 25 drugs targeting hub genes. In the miRNA/TF-hub gene regulatory network, PLS3 was the most connected hub genes and was targeted by six miRNAs and all five screened TFs. In the drug-hub gene regulatory network, HCK was targeted by 20 drugs including 10 inhibitors.ConclusionsWe screened 10 hub genes and predicted miRNAs and TFs targeting them. These molecules may play a crucial role in the progression of histologically unstable carotid plaques and serve as potential biomarkers and therapeutic targets.

Project description:BACKGROUND:Several models have been developed to predict asymptomatic carotid stenosis (ACS), however these models did not pay much attention to people with lower level of stenosis (<50% or carotid plaques, especially instable carotid plaques) who might benefit from early interventions. Here, we developed a new model to predict unstable carotid plaques through systematic screening in population with high risk of stroke. METHODS:Community residents who participated the China National Stroke Screening and Prevention Project (CNSSPP) were screened for their stroke risks. A total of 2841 individuals with high risk of stroke were enrolled in this study, 266 (9.4%) of them were found unstable carotid plaques. A total of 19 risk factors were included in this study. Subjects were randomly distributed into Derivation Set group or Validation Set group. According to their carotid ultrasonography records, subjects in derivation set group were further categorized into unstable plaque group or stable plaque group. RESULTS:174 cases and 1720 cases from Derivation Set group were categorized into unstable plaque group and stable plaque group respectively. The independent risk factors for carotid unstable plaque were: male (OR 1.966, 95%CI 1.406-2.749), older age (50-59, OR 6.012, 95%CI 1.410-25.629; 60-69, OR 13.915, 95%CI 3.381-57.267;≥70, OR 31.267, 95%CI 7.472-130.83), married(OR 1.780, 95%CI 1.186-2.672), LDL-C(OR 2.015, 95%CI 1.443-2.814), and HDL-C(OR 2.130, 95%CI 1.360-3.338). A predictive scoring system was generated, ranging from 0 to 10. The cut-off value of this predictive scoring system is 6.5. The AUC value for derivation and validation set group were 0.738 and 0.737 respectively. CONCLUSIONS:For those individuals with high risk of stroke, we developed a new model which could identify those who have a higher chance to have unstable carotid plaques. When an individual's predictive model score exceeds 6.5, the probability of having carotid unstable plaques is high, and carotid ultrasonography should be conducted accordingly. This model could be helpful in the primary prevention of stroke.

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A proteomic approach to differentiate histologically classified stable and unstable plaques from human carotid arteries.

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A proteomic approach to differentiate histologically classified stable and unstable plaques from human carotid arteries.

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