scholarly journals The underlying mechanisms of FGF2 on carotid atherosclerotic plaque development revealed by bioinformatics analysis

2021 ◽  
Author(s):  
Jian Li ◽  
Haifeng Wang ◽  
Chenjie Dong ◽  
Junling Huang ◽  
Wenlin Ma
Keyword(s):  
Smooth Muscle ◽  
Platelet Activation ◽  
Atherosclerotic Plaque ◽  
Noncoding Rna ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Carotid Atherosclerotic Plaque ◽  
Smooth Muscle Contractility ◽  
Plaque Development

IntroductionThe purpose of this study was to explore the regulatory mechanisms of FGF2 on carotid atherosclerotic plaque development using bioinformatics analysis.Material and methodsExpression profiles of 32 atheroma plaque (AP) and 32 paired distant macroscopically intact (DMI) tissues samples in GSE43292 dataset were downloaded from the Gene Expression Omnibus database. Following identification of differential expression genes (DEGs), correlation analysis of fibroblast growth factor 2 (FGF2) and DEGs was conducted. Subsequently, functional enrichment analysis and protein-protein interaction network for FGF2 significantly correlated DEGs were constructed. Then, microRNAs (miRNAs) that regulated FGF2 and regulatory pairs of long noncoding RNA (lncRNA)-miRNA were predicted to construct lncRNA-miRNA-FGF2 network.ResultsA total of 101 DEGs between AP and DMI samples were identified, and 31 DEGs were analyzed to have coexpression relationships with FGF2, including 23 positively correlated and 8 negatively correlated DEGs. VAV3 had the lowest r value among all FGF2 negatively correlated DEGs. FGF2 positively correlated DEGs was closely related to “regulation of smooth muscle contraction” [eg., Calponin 1 (CNN1)], while FGF2 negatively correlated DEGs was significantly associated with “platelet activation” [eg., Vav Guanine Nucleotide Exchange Factor 3 (VAV3)]. In addition, totally 12 miRNAs that regulated FGF2 were predicted, and hsa-miR-15a-5p and hsa-miR-16-5p were highlighted in lncRNA-miRNA-FGF2 regulatory network.ConclusionsCNN1 might cooperate with FGF2 to regulate smooth muscle contractility during CAP formation. VAV3 might cooperate with FGF2 to be responsible for the development of CAP through participating in platelet activation. Hsa-miR-15a-5p and hsa-miR-16-5p might participate in the development of CAP via regulating FGF2.

scholarly journals LASSO and Bioinformatics Analysis in the Identification of Key Genes for Prognostic Genes of Gynecologic Cancer

2021 ◽  
Vol 11 (11) ◽  
pp. 1177
Author(s):  
Shao-Hua Yu ◽  
Jia-Hua Cai ◽  
De-Lun Chen ◽  
Szu-Han Liao ◽  
Yi-Zhen Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endometrial Cancer ◽  
Pathway Analysis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gynecologic Cancer ◽  
Functional Enrichment ◽  
Lasso Regression ◽  
Potential Biomarker ◽  
Study Gene Expression

The aim of this study is to identify potential biomarkers for early diagnosis of gynecologic cancer in order to improve survival. Cervical cancer (CC) and endometrial cancer (EC) are the most common malignant tumors of gynecologic cancer among women in the world. As the underlying molecular mechanisms in both cervical and endometrial cancer remain unclear, a comprehensive and systematic bioinformatics analysis is required. In our study, gene expression profiles of GSE9750, GES7803, GES63514, GES17025, GES115810, and GES36389 downloaded from Gene Expression Omnibus (GEO) were utilized to analyze differential gene expression between cancer and normal tissues. A total of 78 differentially expressed genes (DEGs) common to CC and EC were identified to perform the functional enrichment analyses, including gene ontology and pathway analysis. KEGG pathway analysis of 78 DEGs indicated that three main types of pathway participate in the mechanism of gynecologic cancer such as drug metabolism, signal transduction, and tumorigenesis and development. Furthermore, 20 diagnostic signatures were confirmed using the least absolute shrink and selection operator (LASSO) regression with 10-fold cross validation. Finally, we used the GEPIA2 online tool to verify the expression of 20 genes selected by the LASSO regression model. Among them, the expression of PAMR1 and SLC24A3 in tumor tissues was downregulated significantly compared to the normal tissue, and found to be statistically significant in survival rates between the CC and EC of patients (p < 0.05). The two genes have their function: (1.) PAMR1 is a tumor suppressor gene, and many studies have proven that overexpression of the gene markedly suppresses cell growth, especially in breast cancer and polycystic ovary syndrome; (2.) SLC24A3 is a sodium–calcium regulator of cells, and high SLC24A3 levels are associated with poor prognosis. In our study, the gene signatures can be used to predict CC and EC prognosis, which could provide novel clinical evidence to serve as a potential biomarker for future diagnosis and treatment.

scholarly journals Development of Prognostic Indicator Based on Autophagy-Related lncRNA Analysis in Colon Adenocarcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Weige Zhou ◽  
Shijing Zhang ◽  
Hui-biao Li ◽  
Zheyou Cai ◽  
Shuting Tang ◽  
...  
Keyword(s):  
Risk Score ◽  
Noncoding Rna ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Colon Adenocarcinoma ◽  
High Risk Group ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Lasso Regression

There were no systematic researches about autophagy-related long noncoding RNA (lncRNA) signatures to predict the survival of patients with colon adenocarcinoma. It was necessary to set up corresponding autophagy-related lncRNA signatures. The expression profiles of lncRNAs which contained 480 colon adenocarcinoma samples were obtained from The Cancer Genome Atlas (TCGA) database. The coexpression network of lncRNAs and autophagy-related genes was utilized to select autophagy-related lncRNAs. The lncRNAs were further screened using univariate Cox regression. In addition, Lasso regression and multivariate Cox regression were used to develop an autophagy-related lncRNA signature. A risk score based on the signature was established, and Cox regression was used to test whether it was an independent prognostic factor. The functional enrichment of autophagy-related lncRNAs was visualized using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. Ten prognostic autophagy-related lncRNAs (AC027307.2, AC068580.3, AL138756.1, CD27-AS1, EIF3J-DT, LINC01011, LINC01063, LINC02381, AC073896.3, and SNHG16) were identified to be significantly different, which made up an autophagy-related lncRNA signature. The signature divided patients with colon adenocarcinoma into the low-risk group and the high-risk group. A risk score based on the signature was a significantly independent factor for the patients with colon adenocarcinoma (HR=1.088, 95%CI=1.057−1.120; P<0.001). Additionally, the ten lncRNAs were significantly enriched in autophagy process, metabolism, and tumor classical pathways. In conclusion, the ten autophagy-related lncRNAs and their signature might be molecular biomarkers and therapeutic targets for the patients with colon adenocarcinoma.

Differential Expression Profiles of Long Noncoding RNA and mRNA of Osteogenically Differentiated Mesenchymal Stem Cells in Ankylosing Spondylitis

2016 ◽  
Vol 43 (8) ◽  
pp. 1523-1531 ◽  
Author(s):  
Zhongyu Xie ◽  
Jinteng Li ◽  
Peng Wang ◽  
Yuxi Li ◽  
Xiaohua Wu ◽  
...  
Keyword(s):  
Stem Cells ◽  
Mesenchymal Stem Cells ◽  
Ankylosing Spondylitis ◽  
Osteogenic Differentiation ◽  
Noncoding Rna ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Qrt Pcr ◽  
Pcr Assays

Objective.We previously demonstrated that mesenchymal stem cells (MSC) from patients with ankylosing spondylitis (AS; ASMSC) have a greater osteogenic differentiation capacity than MSC from healthy donors (HDMSC) and that this difference underlies the pathogenesis of pathological osteogenesis in AS. Here we compared expression levels of long noncoding RNA (lncRNA) and mRNA between osteogenically differentiated ASMSC and HDMSC and explored the precise mechanism underlying abnormal osteogenic differentiation in ASMSC.Methods.HDMSC and ASMSC were induced with osteogenic differentiation medium for 10 days. Microarray analyses were then performed to identify lncRNA and mRNA differentially expressed between HDMSC and ASMSC, which were then subjected to bioinformatics analysis and confirmed by quantitative real-time PCR (qRT-PCR) assays. In addition, coding-non-coding gene co-expression (CNC) networks were constructed to examine the relationships between the lncRNA and mRNA expression patterns.Results.A total of 520 lncRNA and 665 mRNA were differentially expressed in osteogenically differentiated ASMSC compared with HDMSC. Bioinformatics analysis revealed 64 signaling pathways with significant differences, including transforming growth factor-β signaling. qRT-PCR assays confirmed the reliability of the microarray data. The CNC network indicated that 4 differentially expressed lncRNA, including lnc-ZNF354A-1, lnc-LIN54-1, lnc-FRG2C-3, and lnc-USP50-2 may be involved in the abnormal osteogenic differentiation of ASMSC.Conclusion.Our study characterized the differential lncRNA and mRNA expression profiles of osteogenically differentiated ASMSC and identified 4 lncRNA that may participate in the abnormal osteogenic differentiation of ASMSC. These results provide insight into the pathogenesis of pathological osteogenesis in AS.

scholarly journals Systematic Analysis of Long Noncoding RNA and mRNA in Granulosa Cells during the Hen Ovulatory Cycle

Animals ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1533
Author(s):  
Liang Li ◽  
Xun Deng ◽  
Silu Hu ◽  
Zhifu Cui ◽  
Zifan Ning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Follicle Development ◽  
Ovulatory Cycle ◽  
Lh Surge ◽  
Study Gene Expression ◽  
Three Stages

Long non-coding RNAs (lncRNAs) and mRNAs are temporally expressed during chicken follicle development. However, follicle transcriptome studies in chickens with timepoints relating to changes in luteinizing hormone (LH) levels are rare. In this study, gene expression in Rohman layers was investigated at three distinct stages of the ovulatory cycle: zeitgeber time 0 (ZT0, 9:00 a.m.), zeitgeber time 12 (ZT12, 9:00 p.m.), and zeitgeber time 20 (ZT20, 5:00 a.m.) representing the early, middle, and LH surge stages, respectively, of the ovulatory cycle. Gene expression profiles were explored during follicle development at ZT0, ZT12, and ZT20 using Ribo-Zero RNA sequencing. The three stages were separated into two major stages, including the pre-LH surge and the LH surge stages. A total of 12,479 mRNAs and 7528 lncRNAs were identified among the three stages, and 4531, 523 differentially expressed genes (DEGs) and 2367, 211 differentially expressed lncRNAs (DELs) were identified in the ZT20 vs. ZT12, and ZT12 vs. ZT0, comparisons. Functional enrichment analysis revealed that genes involved in cell proliferation and metabolism processes (lipid-related) were mainly enriched in the ZT0 and ZT12 stages, respectively, and genes related to oxidative stress, steroids regulation, and inflammatory process were enriched in the ZT20 stage. These findings provide the basis for further investigation of the specific genetic and molecular functions of follicle development in chickens.

scholarly journals Identification of miRNAs as the Crosstalk in the Interaction between Neural Stem/Progenitor Cells and Endothelial Cells

2020 ◽  
Vol 2020 ◽  
pp. 1-29
Author(s):  
Xin Wang ◽  
Simin Li ◽  
Yihong Ma ◽  
Yuzhen Xu ◽  
Anthony Chukwunonso Ogbuehi ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Progenitor Cells ◽  
Noncoding Rna ◽  
Drug Targets ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Chemical Compounds ◽  
Functional Enrichment ◽  
Environmental Chemical ◽  
Neural Stem Progenitor Cells

Aim. This study is aimed at identifying genetic and epigenetic crosstalk molecules and their target drugs involved in the interaction between neural stem/progenitor cells (NSPCs) and endothelial cells (ECs). Materials and Methods. Datasets pertaining to reciprocal mRNA and noncoding RNA changes induced by the interaction between NSPCs and ECs were obtained from the GEO database. Differential expression analysis (DEA) was applied to identify NSPC-induced EC alterations by comparing the expression profiles between monoculture of ECs and ECs grown in EC/NSPC cocultures. DEA was also utilized to identify EC-induced NSPC alterations by comparing the expression profiles between monoculture of NSPCs and NSPCs grown in EC/NSPC cocultures. The DEGs and DEmiRNAs shared by NSPC-induced EC alterations and EC-induced NSPC alterations were then identified. Furthermore, miRNA crosstalk analysis and functional enrichment analysis were performed, and the relationship between DEmiRNAs and small molecular drug targets/environment chemical compounds was investigated. Results. One dataset (GSE29759) was included and analyzed in this study. Six genes (i.e., MMP14, TIMP3, LOXL1, CCK, SMAD6, and HSPA2), three miRNAs (i.e., miR-210, miR-230a, and miR-23b), and three pathways (i.e., Akt, ERK1/2, and BMPs) were identified as crosstalk molecules. Six small molecular drugs (i.e., deptropine, fluphenazine, lycorine, quinostatin, resveratrol, and thiamazole) and seven environmental chemical compounds (i.e., folic acid, dexamethasone, choline, doxorubicin, thalidomide, bisphenol A, and titanium dioxide) were identified to be potential target drugs of the identified DEmiRNAs. Conclusion. To conclude, three miRNAs (i.e., miR-210, miR-230a, and miR-23b) were identified to be crosstalks linking the interaction between ECs and NSPCs by implicating in both angiogenesis and neurogenesis. These crosstalk molecules might provide a basis for devising novel strategies for fabricating neurovascular models in stem cell tissue engineering.

scholarly journals Long Noncoding RNA Expression Signatures of Colon Cancer Based on the ceRNA Network and Their Prognostic Value

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Yang Cheng ◽  
Lanlan Geng ◽  
Kunyuan Wang ◽  
Jingjing Sun ◽  
Wanfu Xu ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Survival Analysis ◽  
Noncoding Rna ◽  
Prognostic Value ◽  
Expression Profiles ◽  
Computational Method ◽  
Functional Enrichment ◽  
Gene Knockdown ◽  
Cerna Network ◽  
A Genome

Background. The specific functional roles of long noncoding RNAs (lncRNAs) as ceRNAs in colon cancer and their potential implications for colon cancer prognosis remain unclear. In the present study, a genome-wide analysis was performed to investigate the potential lncRNA-mediated ceRNA interplay in colon cancer based on the “ceRNA hypothesis.” The prognostic value of the lncRNAs was evaluated. Methods. A dysregulated lncRNA-associated ceRNA network was constructed based on the miRNA, lncRNA, and mRNA expression profiles in combination with the miRNA regulatory network by using an integrative computational method. Molecular biological techniques, including qPCR and gene knockdown techniques, were used to verify candidate targets in colon cancer. Survival analysis was performed to identify the candidate lncRNAs with prognostic value. Results. Our network analysis uncovered several novel lncRNAs as functional ceRNAs through crosstalk with miRNAs. The QRT-PCR assays of patient tissues as well as gene knockdown colon cancer cells confirmed the expression of top lncRNAs and their correlation with target genes in the ceRNA network. Functional enrichment analysis predicted that differentially expressed lncRNAs might participate in broad biological functions associated with tumor progression. Moreover, these lncRNAs may be involved in a range of cellular pathways, including the apoptosis, PI3K-AKT, and EGFR signaling pathways. The survival analysis showed that the expression level of several lncRNAs in the network was correlated with the prognosis of patients with colon cancer. Conclusions. This study uncovered a dysregulated lncRNA-associated ceRNA network in colon cancer. The function of the identified lncRNAs in colon cancer was preliminarily explored, and their potential prognostic value was evaluated. Our study demonstrated that lncRNAs could potentially serve as important regulators in the development and progression of colon cancer. Candidate prognostic lncRNA biomarkers in colon cancer were identified.

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