Identification of Neuropeptides as Potential Crosstalks Linking Down Syndrome and Periodontitis Revealed by Transcriptomic Analyses

Background. This bioinformatics study was aimed to investigate the relationship between periodontitis (PD) and Down Syndrome (DS) regarding potential crosstalk genes, related neuropeptides, and biological processes. Methods. Data for PD (GSE23586, GSE10334 and GSE16134) and DS (GSE35665) were downloaded from NCBI Gene Expression Omnibus (GEO). Following normalization and merging of PD data, differential expression analysis was performed ( p value < 0.05 and ∣ log FC ∣ ≥ 0.5 ). The common deregulated genes between PD and DS were considered as crosstalk genes. The significantly differentially expressed genes were used to construct the coexpression network and to further identify coexpression gene modules. To acquire the significant modules, the significant expression level of genes in the module was used to analyze the enrichment of genes in each module. Neuropeptides were assessed from NeuroPedia database. Neuropeptide genes and crosstalk genes were merged and mapped into PPI network, and the correlation coefficient (Spearman) was determined for the crosstalk genes. Results. 138 crosstalk genes were predicted. According to the functional enrichment analysis, these genes significantly regulated different biological processes and pathways. In enrichment analysis, the significant module of DS was pink module, and turquoise module was significant in PD. Four common crosstalk genes were acquired, i.e., CD19, FCRL5, FCRLA, and HLA-DOB. In the complex network, INS and IGF2 interacted with CASP3 and TP53, which commonly regulated the MAPK signaling pathway. Moreover, the results showed that TP53 interacted with IGF2 and INS inducing the dysregulation of PI3K-Akt signaling pathway. UBL was positively correlated with crosstalk genes in both diseases. LEP was revealed to be both a neuropeptide and crosstalk gene and was positively correlated with other crosstalk genes. Conclusion. Different crosstalk genes, related neuropeptides, and biological pathways and processes were revealed between PD and DS, which can serve as a theoretical basis for future research.

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Identification of Candidate Genetic Markers and a Novel 4-genes Diagnostic Model in Osteoarthritis through Integrating Multiple Microarray Data

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207323666200428120310 ◽

2020 ◽

Vol 23 (8) ◽

pp. 805-813

Author(s):

Ai Jiang ◽

Peng Xu ◽

Zhenda Zhao ◽

Qizhao Tan ◽

Shang Sun ◽

...

Keyword(s):

Signaling Pathway ◽

Microarray Data ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Functional Enrichment ◽

Joint Disease ◽

Support Vector ◽

Diagnostic Model ◽

Data Sets

Background: Osteoarthritis (OA) is a joint disease that leads to a high disability rate and a low quality of life. With the development of modern molecular biology techniques, some key genes and diagnostic markers have been reported. However, the etiology and pathogenesis of OA are still unknown. Objective: To develop a gene signature in OA. Method: In this study, five microarray data sets were integrated to conduct a comprehensive network and pathway analysis of the biological functions of OA related genes, which can provide valuable information and further explore the etiology and pathogenesis of OA. Results and Discussion: Differential expression analysis identified 180 genes with significantly expressed expression in OA. Functional enrichment analysis showed that the up-regulated genes were associated with rheumatoid arthritis (p < 0.01). Down-regulated genes regulate the biological processes of negative regulation of kinase activity and some signaling pathways such as MAPK signaling pathway (p < 0.001) and IL-17 signaling pathway (p < 0.001). In addition, the OA specific protein-protein interaction (PPI) network was constructed based on the differentially expressed genes. The analysis of network topological attributes showed that differentially upregulated VEGFA, MYC, ATF3 and JUN genes were hub genes of the network, which may influence the occurrence and development of OA through regulating cell cycle or apoptosis, and were potential biomarkers of OA. Finally, the support vector machine (SVM) method was used to establish the diagnosis model of OA, which not only had excellent predictive power in internal and external data sets (AUC > 0.9), but also had high predictive performance in different chip platforms (AUC > 0.9) and also had effective ability in blood samples (AUC > 0.8). Conclusion: The 4-genes diagnostic model may be of great help to the early diagnosis and prediction of OA.

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Weighted Gene Correlation Network Analysis Identifies Specific Functional Modules and Genes in Esophageal Cancer

Journal of Oncology ◽

10.1155/2021/8223263 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Wei Xu ◽

Jian Xu ◽

Zhiqiang Wang ◽

Yuequan Jiang

Keyword(s):

Esophageal Cancer ◽

Network Analysis ◽

Cell Cycle Progression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Future Research ◽

Hub Genes ◽

Pathological Staging

Objective. Esophageal cancer (ESCA) is one of the most aggressive malignancies globally with an undesirable five-year survival rate. Here, this study was conducted for determining specific functional genes linked with ESCA initiation and progression. Methods. Gene expression profiling of ESCA was curated from TCGA (containing 160 ESCA and 11 nontumor specimens) and GSE38129 (30 paired ESCA and nontumor tissues) datasets. Differential expression analysis was conducted between ESCA and nontumor tissues with adjusted p value <0.05 and |log2fold-change|>1. Weighted gene coexpression network analysis (WGCNA) was conducted for determining the ESCA-specific coexpression modules and genes. Thereafter, ESCA-specific differentially expressed genes (DEGs) were intersected. Functional enrichment analysis was then presented with clusterProfiler package. Protein-protein interaction was conducted, and hub genes were determined. Association of hub genes with pathological staging was evaluated, and survival analysis was presented among ESCA patients. Results. This study determined 91 ESCA-specific DEGs following intersection of DEGs and ESCA-specific genes in TCGA and GSE38129 datasets. They were remarkably linked to cell cycle progression and carcinogenic pathways like the p53 signaling pathway, cellular senescence, and apoptosis. Ten ESCA-specific hub genes were determined, containing ASPM, BUB1B, CCNA2, CDC20, CDK1, DLGAP5, KIF11, KIF20 A, TOP2A, and TPX2. They were prominently associated with pathological staging. Among them, KIF11 upregulation was in relation to undesirable prognosis of ESCA patients. Conclusion. Collectively, we determined ESCA-specific coexpression modules and hub genes, which offered the foundation for future research concerning the mechanistic basis of ESCA.

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Integrated lncRNA and mRNA Transcriptome Analyses in the Ovary of Cynoglossus semilaevis Reveal Genes and Pathways Potentially Involved in Reproduction

Frontiers in Genetics ◽

10.3389/fgene.2021.671729 ◽

2021 ◽

Vol 12 ◽

Author(s):

Yani Dong ◽

Likang Lyu ◽

Daiqiang Zhang ◽

Jing Li ◽

Haishen Wen ◽

...

Keyword(s):

Signaling Pathways ◽

Target Genes ◽

Enrichment Analysis ◽

Mapk Signaling ◽

Cynoglossus Semilaevis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Biological Processes ◽

Tongue Sole ◽

Oocyte Meiosis

Long non-coding RNAs (lncRNAs) have been reported to be involved in multiple biological processes. However, the roles of lncRNAs in the reproduction of half-smooth tongue sole (Cynoglossus semilaevis) are unclear, especially in the molecular regulatory mechanism driving ovarian development and ovulation. Thus, to explore the mRNA and lncRNA mechanisms regulating reproduction, we collected tongue sole ovaries in three stages for RNA sequencing. In stage IV vs. V, we identified 312 differentially expressed (DE) mRNAs and 58 DE lncRNAs. In stage V vs. VI, we identified 1,059 DE mRNAs and 187 DE lncRNAs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DE mRNAs were enriched in ECM-receptor interaction, oocyte meiosis and steroid hormone biosynthesis pathways. Furthermore, we carried out gene set enrichment analysis (GSEA) to identify potential reproduction related-pathways additionally, such as fatty metabolism and retinol metabolism. Based on enrichment analysis, DE mRNAs with a potential role in reproduction were selected and classified into six categories, including signal transduction, cell growth and death, immune response, metabolism, transport and catabolism, and cell junction. The interactions of DE lncRNAs and mRNAs were predicted according to antisense, cis-, and trans-regulatory mechanisms. We constructed a competing endogenous RNA (ceRNA) network. Several lncRNAs were predicted to regulate genes related to reproduction including cyp17a1, cyp19a1, mmp14, pgr, and hsd17b1. The functional enrichment analysis of these target genes of lncRNAs revealed that they were involved in several signaling pathways, such as the TGF-beta, Wnt signaling, and MAPK signaling pathways and reproduction related-pathways such as the progesterone-mediated oocyte maturation, oocyte meiosis, and GnRH signaling pathway. RT-qPCR analysis showed that two lncRNAs (XR_522278.2 and XR_522171.2) were mainly expressed in the ovary. Dual-fluorescence in situ hybridization experiments showed that both XR_522278.2 and XR_522171.2 colocalized with their target genes cyp17a1 and cyp19a1, respectively, in the follicular cell layer. The results further demonstrated that lncRNAs might be involved in the biological processes by modulating gene expression. Taken together, this study provides lncRNA profiles in the ovary of tongue sole and further insight into the role of lncRNA involvement in regulating reproduction in tongue sole.

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Identification of key genes and biological processes contributing to colitis associated dysplasia in ulcerative colitis

PeerJ ◽

10.7717/peerj.11321 ◽

2021 ◽

Vol 9 ◽

pp. e11321

Author(s):

Di Zhang ◽

Pengguang Yan ◽

Taotao Han ◽

Xiaoyun Cheng ◽

Jingnan Li

Keyword(s):

Ulcerative Colitis ◽

Mitochondrial Dysfunction ◽

Single Gene ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Cell Junction ◽

Biological Processes ◽

Hub Genes ◽

Key Genes

Background Ulcerative colitis-associated colorectal cancer (UC-CRC) is a life-threatening complication of ulcerative colitis (UC). The mechanisms underlying UC-CRC remain to be elucidated. The purpose of this study was to explore the key genes and biological processes contributing to colitis-associated dysplasia (CAD) or carcinogenesis in UC via database mining, thus offering opportunities for early prediction and intervention of UC-CRC. Methods Microarray datasets (GSE47908 and GSE87466) were downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) between groups of GSE47908 were identified using the “limma” R package. Weighted gene co-expression network analysis (WGCNA) based on DEGs between the CAD and control groups was conducted subsequently. Functional enrichment analysis was performed, and hub genes of selected modules were identified using the “clusterProfiler” R package. Single-gene gene set enrichment analysis (GSEA) was conducted to predict significant biological processes and pathways associated with the specified gene. Results Six functional modules were identified based on 4929 DEGs. Green and blue modules were selected because of their consistent correlation with UC and CAD, and the highest correlation coefficient with the progress of UC-associated carcinogenesis. Functional enrichment analysis revealed that genes of these two modules were significantly enriched in biological processes, including mitochondrial dysfunction, cell-cell junction, and immune responses. However, GSEA based on differential expression analysis between sporadic colorectal cancer (CRC) and normal controls from The Cancer Genome Atlas (TCGA) indicated that mitochondrial dysfunction may not be the major carcinogenic mechanism underlying sporadic CRC. Thirteen hub genes (SLC25A3, ACO2, AIFM1, ATP5A1, DLD, TFE3, UQCRC1, ADIPOR2, SLC35D1, TOR1AIP1, PRR5L, ATOX1, and DTX3) were identified. Their expression trends were validated in UC patients of GSE87466, and their potential carcinogenic effects in UC were supported by their known functions and other relevant studies reported in the literature. Single-gene GSEA indicated that biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to angiogenesis and immune response were positively correlated with the upregulation of TFE3, whereas those related to mitochondrial function and energy metabolism were negatively correlated with the upregulation of TFE3. Conclusions Using WGCNA, this study found two gene modules that were significantly correlated with CAD, of which 13 hub genes were identified as the potential key genes. The critical biological processes in which the genes of these two modules were significantly enriched include mitochondrial dysfunction, cell-cell junction, and immune responses. TFE3, a transcription factor related to mitochondrial function and cancers, may play a central role in UC-associated carcinogenesis.

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The Role of Circular RNA CDR1as/ciRS-7 in Regulating Tumor Microenvironment: A Pan-Cancer Analysis

Biomolecules ◽

10.3390/biom9090429 ◽

2019 ◽

Vol 9 (9) ◽

pp. 429 ◽

Cited By ~ 24

Author(s):

Zou ◽

Zheng ◽

Deng ◽

Yang ◽

Xie ◽

...

Keyword(s):

Tumor Microenvironment ◽

Signaling Pathway ◽

Malignant Tumors ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Circular Rna ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Receptor Interaction

Circular RNA CDR1as/ciRS-7 functions as an oncogenic regulator in various cancers. However, there has been a lack of systematic and comprehensive analysis to further elucidate its underlying role in cancer. In the current study, we firstly performed a bioinformatics analysis of CDR1as among 868 cancer samples by using RNA-seq datasets of the MiOncoCirc database. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), CIBERSORT, Estimating the Proportion of Immune and Cancer cells (EPIC), and the MAlignant Tumors using Expression data (ESTIMATE) algorithm were applied to investigate the underlying functions and pathways. Functional enrichment analysis suggested that CDR1as has roles associated with angiogenesis, extracellular matrix (ECM) organization, integrin binding, and collagen binding. Moreover, pathway analysis indicated that it may regulate the TGF-β signaling pathway and ECM-receptor interaction. Therefore, we used CIBERSORT, EPIC, and the ESTIMATE algorithm to investigate the association between CDR1as expression and the tumor microenvironment. Our data strongly suggest that CDR1as may play a specific role in immune and stromal cell infiltration in tumor tissue, especially those of CD8+ T cells, activated NK cells, M2 macrophages, cancer-associated fibroblasts (CAFs) and endothelial cells. Generally, systematic and comprehensive analyses of CDR1as were conducted to shed light on its underlying pro-cancerous mechanism. CDR1as regulates the TGF-β signaling pathway and ECM-receptor interaction to serve as a mediator in alteration of the tumor microenvironment.

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Identification of PKP 2/3 as potential biomarkers of ovarian cancer based on bioinformatics and experiments

Cancer Cell International ◽

10.1186/s12935-020-01602-3 ◽

2020 ◽

Vol 20 (1) ◽

Author(s):

Lingling Gao ◽

Xiao Li ◽

Qian Guo ◽

Xin Nie ◽

Yingying Hao ◽

...

Keyword(s):

Ovarian Cancer ◽

Signaling Pathway ◽

Poor Prognosis ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Biological Behavior ◽

Cell Junction ◽

Immune Infiltration ◽

Potential Biomarker

Abstract Background Plakophilins (PKPs) are widely involved in gene transcription, translation, and signal transduction, playing a crucial role in tumorigenesis and progression. However, the function and potential mechanism of PKP1/2/3 in ovarian cancer (OC) remains unclear. It’s of great value to explore the expression and prognostic values of PKP1/2/3 and their potential mechanisms, immune infiltration in OC. Methods The expression levels, prognostic values and genetic variations of PKP1/2/3 in OC were explored by various bioinformatics tools and databases, and PKP2/3 were selected for further analyzing their regulation network and immune infiltration. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways (KEGG) enrichment were also conducted. Finally, the expression and prognosis of PKP2 were validated by immunohistochemistry. Results The expression level and prognosis of PKP1 showed little significance in ovarian cancer, and the expression of PKP2/3 mRNA and protein were upregulated in OC, showing significant correlations with poor prognosis of OC. Functional enrichment analysis showed that PKP2/3 and their correlated genes were significantly enriched in adaptive immune response, cytokine receptor activity, organization of cell–cell junction and extracellular matrix; KEGG analysis showed that PKP2/3 and their significantly correlated genes were involved in signaling pathways including cytokine-mediated signaling pathway, receptor signaling pathway and pathways in cancer. Moreover, PKP2/3 were correlated with lymphocytes and immunomodulators. We confirmed that high expression of PKP2 was significantly associated with advanced stage, poor differentiation and poor prognosis of OC patients. Conclusion Members of plakophilins family showed various degrees of abnormal expressions and prognostic values in ovarian cancer. PKP2/3 played crucial roles in tumorigenesis, aggressiveness, malignant biological behavior and immune infiltration of OC, and can be regarded as potential biomarker for early diagnosis and prognosis evaluation in OC.

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Transcriptomics in Toxicogenomics, Part II: Preprocessing and Differential Expression Analysis for High Quality Data

Nanomaterials ◽

10.3390/nano10050903 ◽

2020 ◽

Vol 10 (5) ◽

pp. 903 ◽

Cited By ~ 2

Author(s):

Antonio Federico ◽

Angela Serra ◽

My Kieu Ha ◽

Pekka Kohonen ◽

Jang-Sik Choi ◽

...

Keyword(s):

Rna Sequencing ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Data Preprocessing ◽

Functional Enrichment Analysis ◽

Toxicity Assessment ◽

Functional Enrichment ◽

Quality Data ◽

Chemical Toxicity ◽

Transcriptomics Data

Preprocessing of transcriptomics data plays a pivotal role in the development of toxicogenomics-driven tools for chemical toxicity assessment. The generation and exploitation of large volumes of molecular profiles, following an appropriate experimental design, allows the employment of toxicogenomics (TGx) approaches for a thorough characterisation of the mechanism of action (MOA) of different compounds. To date, a plethora of data preprocessing methodologies have been suggested. However, in most cases, building the optimal analytical workflow is not straightforward. A careful selection of the right tools must be carried out, since it will affect the downstream analyses and modelling approaches. Transcriptomics data preprocessing spans across multiple steps such as quality check, filtering, normalization, batch effect detection and correction. Currently, there is a lack of standard guidelines for data preprocessing in the TGx field. Defining the optimal tools and procedures to be employed in the transcriptomics data preprocessing will lead to the generation of homogeneous and unbiased data, allowing the development of more reliable, robust and accurate predictive models. In this review, we outline methods for the preprocessing of three main transcriptomic technologies including microarray, bulk RNA-Sequencing (RNA-Seq), and single cell RNA-Sequencing (scRNA-Seq). Moreover, we discuss the most common methods for the identification of differentially expressed genes and to perform a functional enrichment analysis. This review is the second part of a three-article series on Transcriptomics in Toxicogenomics.

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Differential co-expression network analysis for identification of functional modules in HIV infection and tubercolosis-HIV co-infection

Journal of Biological Research - Bollettino della Società Italiana di Biologia Sperimentale ◽

10.4081/jbr.2016.5950 ◽

2016 ◽

Vol 89 (2) ◽

Cited By ~ 1

Author(s):

Mohit Jha ◽

Anvita Gupta ◽

Sudha Singh ◽

Khushhali Menaria Pandey

Keyword(s):

Network Analysis ◽

Hiv Infection ◽

Enrichment Analysis ◽

Gene Interaction ◽

Gene Clusters ◽

Functional Enrichment Analysis ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

Specific Gene ◽

Diagnostic Strategies

Co-infection with tuberculosis (TB) is the preeminent cause of demise in human immunodeficiency virus (HIV) infected individuals. However, diagnosis of TB, particularly in the presence of an HIV co-infection, can be limiting owing to the high inaccuracy associated with conventional diagnostic strategies. Here we determine dysregulated pathways in TB-HIV co-infection and HIV infection utilizing coexpression networks. Primarily, we utilized preservation statistics to identify gene modules that exhibit a weak conservation of network topology within HIV infected and TB-HIV co-infected networks. Raw data was downloaded from Gene Expression Omnibus (GSE50834) and duly pre-processed. Co-expression networks for each condition (HIV infected and TB-HIV co-infected) were constructed independently. Preservation of HIV infected network edges was evaluated with respect to TB-HIV co-infected and vice versa using weighted correlation network analysis. Two out of the 22 modules were identified as exhibiting weak preservation in both conditions. Functional enrichment analysis identified that weakly preserved modules were pertinent to the condition under study. For instance, weakly preserved TBHIV co-infected module T1 enriched for genes associated with mitochondrion exhibited the highest fraction of gene interaction pairs exclusive to TB-HIV co-infection. Concisely, we illustrated the application of using preservation statistics to detect modules functionally linked with dysregulated pathways in disease, as exemplified by the mitochondrion module T1. Our analyses discovered gene clusters that are non-randomly linked with the disease. Highly specific gene pairs pointed to interactions between known markers of disease and favoured identification of possible markers that are likely to be associated with the disease.

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Functional Enrichment Analysis by David in Transgenic MYCN Zebrafish Model

Blood ◽

10.1182/blood.v120.21.5114.5114 ◽

2012 ◽

Vol 120 (21) ◽

pp. 5114-5114

Author(s):

Li-Jing Shen ◽

Fang-Yuan Chen ◽

Lan-Fang Cao ◽

Yong Zhang ◽

Hua Zhong

Keyword(s):

Cell Cycle ◽

Signaling Pathways ◽

Microarray Analysis ◽

Conflicts Of Interest ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Mapk Signaling ◽

Functional Enrichment ◽

Tgfβ Signaling ◽

Apoptosis Pathway

Abstract Abstract 5114 Introduction The MYCN oncogene encodes a basic helix-loop-helix/leucine zipper (bHLH/LZ) transcription factor that is frequently overexpressed in hematologic malignancies neoplasms (including acute leukemia, T-cell lymphoma, and so on). MYCN acts as a poor prognostic marker to promote an aggressive phenotype. However, the mechanisms of action and pathways affected by MYCN are still largely unclear. Methods We induced murine MYCN gene overexpression in embryonic zebrafish through heat-shock promoter and established stable germline Tg(MYCN:HSE:EGFP) zebrafish. RNA was extracted at 3 days post fertilization from wild type (WT) and transgenic zebrafish F1 generation (TG) embryo hematopoietic cells, collected by the flow cytometer, for microarray analysis. The samples were processed and subsequently analyzed in triplicate on Zebrafish Oligo Microarrays (Agilent Technologies), containing 43, 554 sets of probe, at the Advanced Throughput Inc. The microarrays were scanned in an Agilent DNA Microarray Scanner and the images were processed using Feature Extraction software. A False Discovery Rate≤0. 05 for overall interactions effect and P<0. 001 between comparisons were used to determine differentially expressed genes (DEG). Ingenuity Pathway Analysis and DAVID performed the functional analysis of DEG. Results Microarray analysis revealed 626 (342 genes up-regulated and 284 genes down-regulated) DEG that showed >2-fold change in TG comparing with that of WT. Using functional enrichment analysis by DAVID, several signaling pathways were regulated in TG samples (Table 1). MAPK signaling pathway was high activated through FGF, PDGF, BDNF and CACN high expression, promoting up-regulated of Ras and MKP, enhancing phosphorylation and leading to increase of cells proliferation. TGFβ signaling was inhibited by up-regulation of IFN Ã and Smad 6/7, which negative control of TGFβR and Smad 2/3. Further, we found that MYCN enhances the expression of skp2, via decreased p21 and increased CDK2, promoting cell cycle progression (Fig. 1). In addition, overexpression of MYCN weakened the function of mismatch repair, base excision repair, while increased apoptosis pathway mediated by p53 (up-regulated Bid gene). Meanwhile, Glycolysis/gluconeogenesis pathway was significantly up-regulated in TG fish. Conclusions Overexpression of MYCN induced up-regulation of cell proliferation and Glycolysis/gluconeogenesis pathway (as the Warburg effect in rapidly proliferating tumors), attenuation of repair function, all of which are phenomena associated with proliferation and malignancies transformation of blood cell feature. We found that MYCN down-regulates p27kip1, p57kip2 and p21cip1 through up-regulate Skp2, thus up-regulates CDK2, CycA, CycB, CycD and CycE. All above changes shortened the time taken to progress through the cell cycle. Increased MARK signaling and decreased TGFβ signaling pathways also contributed to promote cell cycle. (Red star marks the up-regulated genes). Disclosures: No relevant conflicts of interest to declare.

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Identification of novel genes and pathways in carotid atheroma using integrated bioinformatic methods

Scientific Reports ◽

10.1038/srep18764 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 10

Author(s):

Wenqing Nai ◽

Diane Threapleton ◽

Jingbo Lu ◽

Kewei Zhang ◽

Hongyuan Wu ◽

...

Keyword(s):

Signaling Pathway ◽

Transforming Growth Factor ◽

Interaction Network ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Transforming Growth Factor Β ◽

Functional Enrichment ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Atheromatous Plaques

Abstract Atherosclerosis is the primary cause of cardiovascular events and its molecular mechanism urgently needs to be clarified. In our study, atheromatous plaques (ATH) and macroscopically intact tissue (MIT) sampled from 32 patients were compared and an integrated series of bioinformatic microarray analyses were used to identify altered genes and pathways. Our work showed 816 genes were differentially expressed between ATH and MIT, including 443 that were up-regulated and 373 that were down-regulated in ATH tissues. GO functional-enrichment analysis for differentially expressed genes (DEGs) indicated that genes related to the “immune response” and “muscle contraction” were altered in ATHs. KEGG pathway-enrichment analysis showed that up-regulated DEGs were significantly enriched in the “FcεRI-mediated signaling pathway”, while down-regulated genes were significantly enriched in the “transforming growth factor-β signaling pathway”. Protein-protein interaction network and module analysis demonstrated that VAV1, SYK, LYN and PTPN6 may play critical roles in the network. Additionally, similar observations were seen in a validation study where SYK, LYN and PTPN6 were markedly elevated in ATH. All in all, identification of these genes and pathways not only provides new insights into the pathogenesis of atherosclerosis, but may also aid in the development of prognostic and therapeutic biomarkers for advanced atheroma.

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