miR-432 is a novel biomarker for PCNSL and is associated with cell adhesion: An integrated bioinformatics analysis

Candidate Mirnas ◽

Ppi Networks

Abstract Background: Primary central nervous system lymphoma (PCNSL), a rare form of the non-Hodgkin's lymphoma (NHL), usually has a poor prognosis, and molecular pathogenesis of PCNSL has not been fully elucidated. Here, potential miRNA biomarkers were investigated in patients with PCNSL using an integrated bioinformatics analysis. Methods: Expression profile arrays (GSE122011, GSE139031, and GSE25297) were obtained from the Gene Expression Omnibus (GEO). Free-scale miRNA co-expression networks were constructed with 27 PCNSL patients from GSE122011 by the weighted gene co-expression network analysis (WGCNA) in order to identify candidate biomarkers. Subsequently, miRNA-miRNA networks were visualized with the Cytoscape. Expression of candidate miRNAs was assessed in serum samples from GSE139031, including 42 PCNSL patients and 77 non-cancer individuals, and the sensitivity and the specificity were assessed by the receiver operating characteristic (ROC) curve. From GSE25297, differentially expressed genes (DEGs) from the PCNSL tissues (n = 7) and the normal lymph nodes (n = 7) were compared, target genes of candidate miRNAs were downloaded from TargetScan database, and target genes that were also down-regulated in GSE25297 were used to construct the protein-protein interaction (PPI) networks and for the gene ontology (GO) analysis. Results: miRNAs were clustered into two groups with 8 modules in 27 patients with PCNSL. One group consisted of the yellow and the turquoise modules, and the second group consisted of the other six modules. In the miRNA-miRNA network, the highest nodes were observed between miR-432 and miR-330-3p, which were from the yellow and the turquoise modules, and only miR-432 was closely associated with both the yellow (0.977, P = 2.88E -18 ) and the turquoise modules (0.525, P = 0.005). Additionally, patients with PCNSL had higher serum miR-432 expression compared with that in the non-cancer controls in GSE139031, and miR-432 has a higher accuracy for discriminating between PCNSL and non-cancer samples (AUC: 0.77; 95% CI: 0.6923 to 0.8550). For target genes of miR-432, RASGRF , DGKG , SMIM22 , SPOCD1 , NRCAM , CNTN2 , PTPRD , POTED , IGSF3 , SLC24A2 , CTNND2 , AIF1L , TMEM229A , GLDN , and MOBP were down-regulated in the PCNSL tissues. Among them, CTNND2 , GLDN , NRCAM , and PTPRD were associated with cell adhesion. Conclusion: Up-regulated miR-432 expression is a novel biomarker for patients with PCNSL and may be associated with cell adhesion.

Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer’s Disease

10.1155/2020/4505720 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Weishuang Xue ◽

Jinwei Li ◽

Kailei Fu ◽

Weiyu Teng

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Peripheral Blood ◽

Bioinformatics Analysis ◽

Gene Expression Omnibus ◽

Venn Diagram ◽

Ppi Network ◽

Hub Genes ◽

Ppi Networks

Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. Methods. We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. Results. Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. Conclusions. Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

Exosomal hsa-miR-21-5p is a biomarker for breast cancer diagnosis

PeerJ ◽

10.7717/peerj.12147 ◽

2021 ◽

Vol 9 ◽

pp. e12147

Author(s):

Min Liu ◽

Fei Mo ◽

Xiaohan Song ◽

Yun He ◽

Yan Yuan ◽

...

Keyword(s):

Breast Cancer ◽

Target Genes ◽

Bioinformatics Analysis ◽

Expression Profiles ◽

Quantitative Polymerase Chain Reaction ◽

Delayed Diagnosis ◽

Breast Cancer Diagnosis ◽

Diagnostic Value ◽

Gene Expression Omnibus ◽

Protein Protein Interaction

Purpose Breast cancer (BC) is characterized by concealed onset, delayed diagnosis, and high fatality rates making it particularly dangerous to patients’ health. The purpose of this study was to use comprehensive bioinformatics analysis and experimental verification to find a new biomarker for BC diagnosis. Methods We comprehensively analyzed microRNA (miRNA) and mRNA expression profiles from the Gene Expression Omnibus (GEO) and screened out differentially-expressed (DE) miRNAs and mRNAs. We used the miRNet website to predict potential DE-miRNA target genes. Using the Database for Annotation, Visualization and Integrated Discovery (DAVID), we performed Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses on overlapping potential target genes and DE-mRNAs. The protein-protein interaction (PPI) network was then established. The miRNA-mRNA regulatory network was constructed using Cytoscape and the analysis results were visualized. We verified the expression of the most up-regulated DE-miRNA using reverse transcription and a quantitative polymerase chain reaction in BC tissue. The diagnostic value of the most up-regulated DE-miRNA was further explored across three levels: plasma-derived exosomes, cells, and cell exosomes. Results Our comprehensive bioinformatics analysis and experimental results showed that hsa-miR-21-5p was significantly up-regulated in BC tissue, cells, and exosomes. Our results also revealed that tumor-derived hsa-miR-21-5p could be packaged in exosomes and released into peripheral blood. Additionally, when evaluating the diagnostic value of plasma exosomal hsa-miR-21-5p, we found that it was significantly up-regulated in BC patients. Receiver operating characteristic (ROC) analysis also confirmed that hsa-miR-21-5p could effectively distinguish healthy people from BC patients. The sensitivity and specificity were 86.7% and 93.3%, respectively. Conclusion This study’s results showed that plasma exosomal hsa-miR-21-5p could be used as a biomarker for BC diagnosis.

The diagnostic values of circulating miRNAs for hypertension and bioinformatics analysis

Bioscience Reports ◽

10.1042/bsr20180525 ◽

2018 ◽

Vol 38 (4) ◽

Cited By ~ 4

Author(s):

Xiaoyi Zhang ◽

Xiaoyan Wang ◽

Jian Wu ◽

Juan Peng ◽

Xin Deng ◽

...

Keyword(s):

Operating Characteristic ◽

Target Genes ◽

Bioinformatics Analysis ◽

Normal Population ◽

Enrichment Analysis ◽

Roc Curves ◽

Serum Samples ◽

Gene Expressions ◽

Impact Risk ◽

Diagnostic Values

Few studies have compared the performances of those reported miRNAs as biomarkers for hypertension in a same cohort, we aimed to comprehensively examine the performances of those reported miRNAs as biomarkers for hypertension and identify the genes and pathways targetted by these miRNAs. Serum samples were collected from patients hospitalized for hypertension in Zhongshan Hospital. Gene expressions of 25 miRNAs were compared between hypertension and normal groups. Receiver operating characteristic (ROC) curves were used to evaluate the accuracy of those miRNAs as biomarkers for hypertension. miRWALK2.0 and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed to predict the target genes and pathways of selected miRNAs. A total of 164 participants were enrolled, amongst which 53 were patients with hypertension, 111 were normal population. MiR-122-5p (area under curve (AUC): 0.750), miR-199a-3p (AUC: 0.744), miR-208a-3p (AUC: 0.743), miR-423-5p (AUC: 0.740), and miR-223-5p (AUC: 0.718) showed better performance than others, and the best performance was the combination of miR-199a-3p, miR-208a-3p, miR-122-5p, and miR-223-3p (AUC: 0.80). Pathway analysis revealed that 94 pathways enriched with genes targetted by miR-199a-3p, miR-208a-3p, miR-122-5p, miR-223-5p. FoxO signaling was enriched with genes targetted by all the three miRNAs (miR-199a-3p, miR-208a-3p, miR-122-5p). The combination of miR-199a-3p, miR-208a-3p, miR-122-5p, and miR-223-3p has a good diagnostic performance for hypertension, and multitudes of possible mechanisms/pathways through which dysregulation of these miRNAs may impact risk of hypertension.

Bioinformatics Analysis of ZBTB16 as a Prognostic Marker for Ewing’s Sarcoma

10.1155/2021/1989917 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Ke Ding ◽

Wenli Qiu ◽

Dianbo Yu ◽

Huade Ma ◽

Kangqi Xie ◽

...

Keyword(s):

Survival Analysis ◽

Ewing’S Sarcoma ◽

Bioinformatics Analysis ◽

Ewing's Sarcoma ◽

Gene Expression Omnibus ◽

Functional Enrichment ◽

High Expression ◽

Ppi Networks ◽

High Expression Group

Objective. The purpose of this study is to identify novel biomarkers for the prognosis of Ewing’s sarcoma based on bioinformatics analysis. Methods. The GSE63157 and GSE17679 datasets contain patient and healthy control microarray data that were downloaded from the Gene Expression Omnibus (GEO) database and analyzed through R language software to obtain differentially expressed genes (DEGs). Firstly, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, protein-protein interaction (PPI) networks, and Cytoscape Molecular Complex Detection (MCODE) plug-in were then used to compute the highest scores of the module. After survival analysis, the hub genes were lastly obtained from the two module genes. Results. A total of 1181 DEGs were identified from the two GSEs. Through MCODE and survival analysis, we obtain 53 DEGs from the module and 29 overall survival- (OS-) related genes. ZBTB16 was the only downregulated gene after Venn diagrams. Survival analysis indicates that there was a significant correlation between the high expression of ZBTB16 and the OS of Ewing’s sarcoma (ES), and the low expression group had an unfavorable OS when compared to the high expression group. Conclusions. High expression of ZBTB16 may serve as a predictor biomarker of poor prognosis in ES patients.

Analysis of differential gene expression between right-sided and left-sided colon cancer by bioinformatics analysis

10.21203/rs.3.rs-23894/v1 ◽

2020 ◽

Author(s):

Qiangwei Chi ◽

Shizuan Chen ◽

Shaotang Li

Keyword(s):

Gene Expression ◽

Colon Cancer ◽

Bioinformatics Analysis ◽

Disease Free Survival ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Ppi Networks

Abstract Background Colon cancer is a common tumor of the digestive tract worldwide. Recent researches have revealed that colon cancer exhibits distinct differences in clinical and biological characteristics depending on the location of the tumor. However, the underlying genetic and molecular mechanism of the differences between right-sided colon cancer (RCC) and left-sided colon cancer (LCC) are not fully understood. This study aimed to identify molecular potential biomarkers and therapeutic targets for precise treatment of right-sided and left-sided colon cancer using bioinformatics analysis. Methods The gene microarray profile, named GSE44076, from the Gene Expression Omnibus (GEO) public database was downloaded and processed to then select differentially expressed genes (DEGs) on the base of two sample groups of RCC and LCC. Also, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, protein–protein interaction (PPI) network construction, module analysis, validation of hub genes, and survival analysis. Results Finally, we obtained 2259 DEGs between RCC and LCC, 1300 of which were upregulated in RCC and 945 of which were upregulated in LCC. The results of GO and KEGG analysis of the DEGs indicated that the biological functions of DEGs in RCC and LCC were significantly different. CTLA4, IL10, IL2RB, IFNG, NCAM1, EGFR, MYC, SRC, CUL3, and NCBP2 were identified from the PPI networks as the hub genes of RCC and LCC. Among the hub genes, the log-rank tests for overall survival (OS) and disease free survival (DFS) were applied. Moreover, all hub genes, except CUL3, had differential expression levels of miRNA between tumor group and normal group. Conclusion These hub genes and pathways identified based on bioinformatics analysis might conduce to explain the differences between RCC and LCC, and most of the hub genes were specific to the malignant tissues. Notably, these hub genes, especially the genes associated with immunotherapy such as CTLA4, might be potential specific targets or prognostic markers for precise treatment of colon cancer.

Identification of Key Genes and miRNAs in Osteosarcoma Patients with Chemoresistance by Bioinformatics Analysis

10.1155/2018/4761064 ◽

2018 ◽

Vol 2018 ◽

pp. 1-10 ◽

Cited By ~ 9

Author(s):

Binbin Xie ◽

Yiran Li ◽

Rongjie Zhao ◽

Yuzi Xu ◽

Yuhui Wu ◽

...

Keyword(s):

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Regulation Of Transcription ◽

Functional Annotations ◽

Ppi Networks ◽

Search Tool ◽

Poor Outcomes

Chemoresistance is a significant factor associated with poor outcomes of osteosarcoma patients. The present study aims to identify Chemoresistance-regulated gene signatures and microRNAs (miRNAs) in Gene Expression Omnibus (GEO) database. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) included positive regulation of transcription, DNA-templated, tryptophan metabolism, and the like. Then differentially expressed genes (DEGs) were uploaded to Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks, and 9 hub genes were screened, such as fucosyltransferase 3 (Lewis blood group) (FUT3) whose expression in chemoresistant samples was high, but with a better prognosis in osteosarcoma patients. Furthermore, the connection between DEGs and differentially expressed miRNAs (DEMs) was explored. GEO2R was utilized to screen out DEGs and DEMs. A total of 668 DEGs and 5 DEMs were extracted from GSE7437 and GSE30934 differentiating samples of poor and good chemotherapy reaction patients. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform GO and KEGG pathway enrichment analysis to identify potential pathways and functional annotations linked with osteosarcoma chemoresistance. The present study may provide a deeper understanding about regulatory genes of osteosarcoma chemoresistance and identify potential therapeutic targets for osteosarcoma.

Title: Weighted Gene Co-Expression Network Analysis Identifies Five Hub Genes Associated with Metastasis in Synovial Sarcoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210628112429 ◽

2021 ◽

Vol 24 ◽

Author(s):

Hongzeng Wu ◽

Benzheng Zhang ◽

Jiazheng Zhao ◽

Yi Zhao ◽

Xiaowei Ma ◽

...

Keyword(s):

Synovial Sarcoma ◽

Tumor Metastasis ◽

Gene Expression Omnibus ◽

Survival Ratio ◽

Hub Genes ◽

Metastatic Lesions ◽

Ppi Networks ◽

Malignant Soft Tissue ◽

Geo Database

Background: Synovial sarcoma (SS) refers to a malignant soft tissue sarcoma (STS) which often occurs in children and adults and has a poor prognosis in elderly patients. Patients with local lesions can be treated with extensive surgical resection combined with adjuvant or radiotherapy, whereas about half of the cases have recurrent diseases and metastatic lesions, and five-year survival ratio is assessed within the range of 27% - 55% only. Method: We downloaded a set of expression profile data (GSE40021) related to SS metastasis based on the Gene Expression Omnibus (GEO) database, and selected distinctly represented genes (DEGs) related to tumor metastasis. WGCNA was used to emphasize the DEGs related to tumor metastasis and obtain co-expression modules. Then, the module most related to SS metastasis was screened out. The genes enriched in this module were analyzed by Gene Ontology (GO) functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway improvement analysis. Cytoscape software was used for constructing protein-protein interaction (PPI) networks, and hub genes were screened in Oncomine analysis. Result: We selected 514 DEGs, consisting of 210 up-regulated genes and 304 down-regulated genes. Through WGCAN, we got seven co-expression modules and the module most related to SS metastasis was the turquoise module, which contained 66 genes. Finally, we screened out five hub genes (HJURP, NCAPG, TPX2, CENPA, NDC80) through CytoHubba and Oncomine analysis. Conclusion: In this study, we screened five hub genes that may help in clinical diagnosis and serve as the latent purpose of SS treatment.

Identification and Classification of Hubs in microRNA Target Gene Networks in Human Neural Stem/Progenitor Cells following Japanese Encephalitis Virus Infection

mSphere ◽

10.1128/msphere.00588-19 ◽

2019 ◽

Vol 4 (5) ◽

Author(s):

Sriparna Mukherjee ◽

Irshad Akbar ◽

Reshma Bhagat ◽

Bibhabasu Hazra ◽

Arindam Bhattacharyya ◽

...

Keyword(s):

Progenitor Cells ◽

Gene Networks ◽

Mirna Target ◽

Target Gene ◽

Target Genes ◽

Hub Genes ◽

Ppi Networks ◽

Neural Stem Progenitor Cells

ABSTRACT RNA viruses are known to modulate host microRNA (miRNA) machinery for their own benefit. Japanese encephalitis virus (JEV), a neurotropic RNA virus, has been reported to manipulate several miRNAs in neurons or microglia. However, no report indicates a complete sketch of the miRNA profile of neural stem/progenitor cells (NSPCs), hence the focus of our current study. We used an miRNA array of 84 miRNAs in uninfected and JEV-infected human neuronal progenitor cells and primary neural precursor cells isolated from aborted fetuses. Severalfold downregulation of hsa-miR-9-5p, hsa-miR-22-3p, hsa-miR-124-3p, and hsa-miR-132-3p was found postinfection in both of the cell types compared to the uninfected cells. Subsequently, we screened for the target genes of these miRNAs and looked for the biological pathways that were significantly regulated by the genes. The target genes involved in two or more pathways were sorted out. Protein-protein interaction (PPI) networks of the miRNA target genes were formed based on their interaction patterns. A binary adjacency matrix for each gene network was prepared. Different modules or communities were identified in those networks by community detection algorithms. Mathematically, we identified the hub genes by analyzing their degree centrality and participation coefficient in the network. The hub genes were classified as either provincial (P < 0.4) or connector (P > 0.4) hubs. We validated the expression of hub genes in both cell line and primary cells through qRT-PCR after JEV infection and respective miR mimic transfection. Taken together, our findings highlight the importance of specific target gene networks of miRNAs affected by JEV infection in NSPCs. IMPORTANCE JEV damages the neural stem/progenitor cell population of the mammalian brain. However, JEV-induced alteration in the miRNA expression pattern of the cell population remains an open question, hence warranting our present study. In this study, we specifically address the downregulation of four miRNAs, and we prepared a protein-protein interaction network of miRNA target genes. We identified two types of hub genes in the PPI network, namely, connector hubs and provincial hubs. These two types of miRNA target hub genes critically influence the participation strength in the networks and thereby significantly impact up- and downregulation in several key biological pathways. Computational analysis of the PPI networks identifies key protein interactions and hubs in those modules, which opens up the possibility of precise identification and classification of host factors for viral infection in NSPCs.

Identification of the Active Constituents and Significant Pathways of Shen-qi-Yi-zhu Decoction on Antigastric Cancer: A Network Pharmacology Research and Experimental Validation

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6642171 ◽

2021 ◽

Vol 2021 ◽

pp. 1-13

Author(s):

Shuhong Zeng ◽

Zhibao Yu ◽

Xintian Xu ◽

Yuanjie Liu ◽

Jiepin Li ◽

...

Keyword(s):

Experimental Validation ◽

Target Genes ◽

Cell Model ◽

Network Pharmacology ◽

Disease Network ◽

Systematic Method ◽

Ppi Networks ◽

Underlying Mechanisms

Shen-qi-Yi-zhu decoction (SQYZD) is an empirical prescription with antigastric cancer (GC) property created by Xu Jing-fan, a National Chinese Medical Master. However, its underlying mechanisms are still unclear. Based on network pharmacology and experimental verification, this study puts forward a systematic method to clarify the anti-GC mechanism of SQYZD. The active ingredients of SQYZD and their potential targets were acquired from the TCMSP database. The target genes related to GC gathered from GeneCards, DisGeNET, OMIM, TTD, and DrugBank databases were imported to establish protein-protein interaction (PPI) networks in GeneMANIA. Cytoscape was used to establish the drug-ingredients-targets-disease network. The hub target genes collected from the SQYZD and GC were parsed via GO and KEGG analysis. Our findings from network pharmacology were successfully validated using an in vitro HGC27 cell model experiment. In a word, this study proves that the combination of network pharmacology and in vitro experiments is effective in clarifying the potential molecular mechanism of traditional Chinese medicine (TCM).

Identification of Key miRNAs in the Treatment of Dabrafenib-Resistant Melanoma

10.1155/2021/5524486 ◽

2021 ◽

Vol 2021 ◽

pp. 1-14

Author(s):

Guangyu Gao ◽

Zhen Yao ◽

Jiaofeng Shen ◽

Yulong Liu

Keyword(s):

Drug Resistance ◽

Molecular Mechanism ◽

Target Genes ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Obvious Association

Dabrafenib resistance is a significant problem in melanoma, and its underlying molecular mechanism is still unclear. The purpose of this study is to research the molecular mechanism of drug resistance of dabrafenib and to explore the key genes and pathways that mediate drug resistance in melanoma. GSE117666 was downloaded from the Gene Expression Omnibus (GEO) database and 492 melanoma statistics were also downloaded from The Cancer Genome Atlas (TCGA) database. Besides, differentially expressed miRNAs (DEMs) were identified by taking advantage of the R software and GEO2R. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) and FunRich was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to identify potential pathways and functional annotations linked with melanoma chemoresistance. 9 DEMs and 872 mRNAs were selected after filtering. Then, target genes were uploaded to Metascape to construct protein-protein interaction (PPI) network. Also, 6 hub mRNAs were screened after performing the PPI network. Furthermore, a total of 4 out of 9 miRNAs had an obvious association with the survival rate ( P < 0.05 ) and showed a good power of risk prediction model of over survival. The present research may provide a deeper understanding of regulatory genes of dabrafenib resistance in melanoma.