Identification of hub genes and candidate drugs in hepatocellular carcinoma by integrated bioinformatics analysis

Background:Hepatocellular carcinoma (HCC) is the third cancer-related cause of death in the world. Until now, the involved mechanisms during the development of HCC are largely unknown. This study aims to explore the driven genes and potential drugs in HCC.Methods:Three mRNA expression datasets were used to analyze the differentially expressed genes (DEGs) in HCC. The bioinformatics approaches include identification of DEGs and hub genes, Gene Ontology terms analysis and Kyoto encyclopedia of genes and genomes enrichment analysis, construction of protein–protein interaction network. The expression levels of hub genes were validated based on The Cancer Genome Atlas, Gene Expression Profiling Interactive Analysis, and the Human Protein Atlas. Moreover, overall survival and disease-free survival analysis of HCC patients were further conducted by Kaplan–Meier plotter and Gene Expression Profiling Interactive Analysis. DGIdb database was performed to search the candidate drugs for HCC.Results:A total of 197 DEGs were identified. The protein–protein interaction network was constructed using Search Tool for the Retrieval of Interacting Genes software, 10 genes were selected by Cytoscape plugin cytoHubba and served as hub genes. These 10 genes were all closely related to the survival of HCC patients. DGIdb database predicted 29 small molecules as the possible drugs for treating HCC.Conclusion:Our study provides some new insights into HCC pathogenesis and treatments. The candidate drugs may improve the efficiency of HCC therapy in the future.     

Identification of G6PC as a potential prognostic biomarker in hepatocellular carcinoma based on bioinformatics analysis

Hepatocellular carcinoma (HCC) has high mortality and incidence rates around the world with limited therapeutic options. There is an urgent need for identification of novel therapeutic targets and biomarkers for early diagnosis and predicting patient survival with HCC.Several studies ({"type":"entrez-geo","attrs":{"text":"GSE102083","term_id":"102083"}}GSE102083, {"type":"entrez-geo","attrs":{"text":"GSE29722","term_id":"29722"}}GSE29722, {"type":"entrez-geo","attrs":{"text":"GSE101685","term_id":"101685"}}GSE101685, and {"type":"entrez-geo","attrs":{"text":"GSE112790","term_id":"112790"}}GSE112790) from the GEO database in HCC were screened and analyzed by GEO2R, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were conducted with the Database for Annotation, Visualization and Integrated Discovery. The protein-protein interaction network was plotted and the module analysis was performed using Search Tool for the Retrieval of Inter-acting Genes/Proteins database and Cytoscape. The expression and survival of key genes were identified using UALCAN, Kaplan–Meier Plotter and ONCOMINE online databases, and the immune infiltration level of key genes was analyzed via the Tumor Immune Estimation Resource (TIMER) database.Through database analysis, eight key genes were finally screened out, and the expressions of cyclin-dependent kinase regulatory subunit 2 and glucose-6-phosphatase catalytic (G6PC), which were closely related to the survival of HCC patients, was detected by using UALCAN. Further analysis on the differential expression of G6PC in multiple cancerous tumors and normal tissues revealed low expression in many solid tumors by Oncomine and TIMER. In addition, Kaplan–Meier plotter and UALCAN database analysis to access diseases prognosis suggested that low expression of G6PC was significantly associated with poor overall survival in HCC patients. Finally, TIMER database analysis showed a significant negative correlation between G6PC and infiltration levels of six kinds of immune cells. The somatic copy number alterations of G6PC were associated with B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, dentritic cells and neutrophils.These bioinformatic data identified G6PC as a potential key gene in the diagnosis and prognosis of HCC.     

Development and validation of a prognostic model related to pyroptosis-related genes for esophageal squamous cell carcinoma using bioinformatics analysis

BackgroundEsophageal squamous cell carcinoma (ESCC) is one of the most lethal malignant tumors worldwide, and a larger number of ESCC patients have unsatisfactory overall survival (OS) rates. While pyroptosis participates in the development of a variety of malignancies, the function of pyroptosis-related genes (PRGs) in ESCC is still obscure. The aim of this study was to construct the pyroptosis-related prognostic model for ESCC, which will be developed to stratify the risk hazards of ESCC patients and to provide theoretical evidence for individualized treatment.MethodsRNA-seq data of ESCC were download from the NCBI Gene Expression Omnibus (GEO) database. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to explore the potential biological functions or pathways. OS was considered as the primary prognosis outcome in this study. The riskscore was constructed by Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression analysis. The pyroptosis-related prognostic model was constructed based on all independent prognostic factors and verified by C-index, Receiver operating characteristic (ROC) curves, and Calibration curves, and the role of the riskscore in ESCC immunotherapy was evaluated by the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm.ResultsThe current study found 31 differentially expressed PRGs (P<0.001), and functional enrichment analysis showed these PRGs were enriched in positive regulation of cytokine production, interleukin-1 beta production. Univariate and multivariate Cox regression analysis were applied to validate that the riskscore based on four prognostic PRGs (HMGB1, IL-18, NLRP7, and PLCG1) was an independent prognostic factor for ESCC, and the C-index of prognostic model related to the riskscore (C-index =0.705) was higher than that of tumor node metastasis (TNM) stage (0.620). The low-risk group showed a better efficacy of immune checkpoint inhibitors.ConclusionsThe riskscore related to PRGs was one of the independent prognostic factors for ESCC. Moreover, the prognostic model related to the riskscore could be used to predict the OS of ESCC patients effectively. However, there still were several limitations in this study, such as no external validation sample. In summary, our data provides a novel perspective in exploring the potential prognostic biomarkers of ESCC.     

Identification of potential biomarkers of peripheral blood mononuclear cell in hepatocellular carcinoma using bioinformatic analysis: A protocol for systematic review and meta-analysis

Background:Hepatocellular carcinoma (HCC) is the cause of an overwhelming number of cancer-related deaths across the world. Developing precise and noninvasive biomarkers is critical for diagnosing HCC. Our research was designed to explore potentially useful biomarkers of host peripheral blood mononuclear cell (PBMC) in HCC by integrating comprehensive bioinformatic analysis.Methods:Gene expression data of PBMC in both healthy individuals and patients with HCC were extracted from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to annotate the function of DEGs. Protein-protein interaction analysis was performed to screen the hub genes from DEGs. cBioportal database analysis was performed to assess the prognostic significance of hub genes. The Cancer Cell Line Encyclopedia (CCLE) and The Human Protein Atlas (HPA) database analyses were performed to confirm the expression levels of the hub genes in HCC cells and tissue.Results:A total of 95 DEGs were screened. Results of the GO analysis revealed that DEGs were primarily involved in platelet degranulation, cytoplasm, and protein binding. Results of the KEGG analysis indicated that DEGs were primarily enriched in focal adhesion. Five genes, namely, myosin light chain kinase (MYLK), interleukin 1 beta (IL1B), phospholipase D1 (PLD1), cortactin (CTTN), and moesin (MSN), were identified as hub genes. A search in the CCLE and HPA database showed that the expression levels of these hub genes were remarkably increased in the HCC samples. Survival analysis revealed that the overexpression of MYLK, IL1B, and PLD1 may have a significant effect on HCC survival. The aberrant high expression levels of MYLK, IL1B, and PLD1 strongly indicated worse prognosis in patients with HCC.Conclusions:The identified hub genes may be closely linked with HCC tumorigenicity and may act as potentially useful biomarkers for the prognostic prediction of HCC in PBMC samples.     

Integrated bioinformatics analysis reveals CDK1 and PLK1 as potential therapeutic targets of lung adenocarcinoma

This study is to identify potential biomarkers and therapeutic targets for lung adenocarcinoma (LUAD).{"type":"entrez-geo","attrs":{"text":"GSE6044","term_id":"6044"}}GSE6044 and {"type":"entrez-geo","attrs":{"text":"GSE118370","term_id":"118370"}}GSE118370 raw data from the Gene Expression Omnibus database were normalized with Robust Multichip Average. After merging these two datasets, the combat function of sva packages was used to eliminate batch effects. Then, limma packages were used to filtrate differentially expressed genes. We constructed protein–protein interaction relationships using STRING database and hub genes were identified based on connectivity degrees. The cBioportal database was used to explore the alterations of the hub genes. The promoter methylation of cyclin dependent kinase 1 (CDK1) and polo-like Kinase 1 (PLK1) and their association with tumor immune infiltration in patients with LUAD were investigated using DiseaseMeth version 2.0 and TIMER databases. The Cancer Genome Atlas-LUAD dataset was used to perform gene set enrichment analysis.We identified 10 hub genes, which were upregulated in LUAD, among which 8 were successfully verified in the Cancer Genome Atlas and Oncomine databases. Kaplan–Meier analysis indicated that the expressions of CDK1 and PLK1 in LUAD patients were associated with overall survival and disease-free survival. The methylation levels in the promoter regions of these 2 genes in LUAD patients were lower than those in normal lung tissues. Their expressions in LUAD were associated with tumor stages and relative abundance of tumor infiltrating immune cells, such as B cells, CD4+ T cells, and macrophages. Moreover, cell cycle, DNA replication, homologous recombination, mismatch repair, P53 signaling pathway, and small cell lung cancer signaling were significantly enriched in CDK1 and PLK1 high expression phenotype.CDK1 and PLK1 may be used as potential biomarkers and therapeutic targets for LUAD.     

Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis

To better understand the molecular mechanism underlying the pathogenesis of multiple sclerosis (MS), we aimed to identify the key genes and microRNAs (miRNA) associated with MS and analyze their interactions. Differentially expressed genes (DEGs) and miRNAs (DEMs) based on the gene miRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE17846","term_id":"17846"}}GSE17846 and mRNA dataset {"type":"entrez-geo","attrs":{"text":"GSE21942","term_id":"21942"}}GSE21942 were determined using R software. Next, we performed functional enrichment analysis and constructed a protein–protein interaction network. Data validation was performed to ensure the reliability of hub genes. The miRNA-mRNA regulatory network was constructed. In total, 47 DEMs and 843 DEGs were identified. Protein–protein interaction network analysis identified several hub genes, including JUN, FPR2, AKT1, POLR2L, LYZ, CXCL8, HBB, CST3, CTSZ, and MMP9, especially LYZ and CXCL8. We constructed an miRNA-mRNA regulatory network and found that hsa-miR-142-3p, hsa-miR-107, hsa-miR-140-5p, and hsa-miR-613 were the most important miRNAs. This study reveals some key genes and miRNAs that may be involved in the pathogenesis of MS, providing potential targets for the diagnosis and treatment of MS.     

Identification of key biomarkers and functional pathways in osteosarcomas with lung metastasis: Evidence from bioinformatics analysis

Background:In osteosarcoma, the lung is the most common metastatic organ. Intensive work has been made to illuminate the pathogeny, but the specific metastatic mechanism remains unclear. Thus, we conducted the study to seek to find the key genes and critical functional pathways associated with progression and treatment in lung metastasis originating from osteosarcoma.Methods:Two independent datasets (GSE14359 and GSE85537) were screened out from the Gene Expression Omnibus (GEO) database and the overlapping differentially expressed genes (DEGs) were identified using GEO2R online platform. Subsequently, the Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were conducted using DAVID. Meanwhile, the protein-protein interaction (PPI) network constructed by STRING was visualized using Cytoscape. Afterwards, the key module and hub genes were extracted from the PPI network using the MCODE and cytoHubba plugin. Moreover, the raw data obtained from GSE73166 and GSE21257 were applied to verify the expression differences and conduct the survival analyses of hub genes, respectively. Finally, the interaction network of miRNAs and hub genes constructed by ENCORI was visualized using Cytoscape.Results:A total of 364 DEGs were identified, comprising 96 downregulated genes and 268 upregulated genes, which were mainly involved in cancer-associated pathways, adherens junction, ECM-receptor interaction, focal adhesion, MAPK signaling pathway. Subsequently, 10 hub genes were obtained and survival analysis demonstrated SKP2 and ASPM were closely related to poor prognosis of patients with osteosarcoma. Finally, hsa-miR-340-5p, has-miR-495-3p, and hsa-miR-96-5p were found to be most closely associated with these hub genes according to the interaction network of miRNAs and hub genes.Conclusion:The key genes and functional pathways identified in the study may contribute to understanding the molecular mechanisms involved in the carcinogenesis and progression of lung metastasis originating from osteosarcoma, and provide potential diagnostic and therapeutic targets.     

Identification of key genes and pathways associated with Crohn's disease by bioinformatics analysis

Abstract

Aims: Crohn's disease (CD) is a type of inflammatory bowel disease. The present study aimed to identify key genes and significant signaling pathways associated with CD by bioinformatics analysis. A total of 179?CD patients and 94 healthy controls from nine genome-wide gene expression datasets were included.

Results: MMP1 and CLDN8 were two key genes screened from the differentially expressed genes. Connectivity Map predicted several small molecules as possible adjuvant drugs to treat CD. Besides, we used weighted gene coexpression network analysis to explore the functional modules involved in CD pathogenesis. Seven main functional modules were identified, of which black module showed the highest correlation with CD. The genes in black module mainly enriched in interferon signaling and defense response to virus. Blue module was another important module and enriched in several signaling pathways, including extracellular matrix organization, inflammatory response and blood vessel development.

Conclusions: This study identified a number of key genes and pathways involved in CD and potential drugs to combat it, which might offer insights into CD pathogenesis and provide a clue to potential treatments.     

食管鳞癌组织及周围正常食管黏膜组织差异表达基因的筛选

目的:研究食管鳞癌组织及周围正常食管黏膜组织的差异表达基因,为寻找食管鳞癌早期诊断高敏感性,高特异性的分子指标提供理论依据.方法:分别抽提人食管鳞癌组织及周围正常食管黏膜组织总mRNA,逆转录成cDNA,用单标法以Cy3-dUTP为标记制成探针,与基因芯片进行杂交,筛选出差异表达的基因,并用生物信息学方法做进一步分析....     

非特异性间质性肺炎相关基因筛选和生物信息学分析

目的通过生物信息学的方法筛选非特异性间质性肺炎(nonspecific interstitial pneumonia, NSIP)的致病基因,为进一步研究提供靶点。 方法从GEO数据库下载基因芯片数据集GSE110147、GSE21369、GSE40839,使用limma包分析工具筛选正常组织与NSIP的差异表达基因。通过clusterProfiler包对差异表达基因进行GO分析和KEGG通路富集分析,找到NSIP发病过程中差异表达基因主要参与的生物功能及其集中的信号通路。利用STRING数据库和CYTOSCAPE软件构建蛋白相互作用网络,使用MCODE软件提取蛋白相互作用网络中的子网络模块。 结果3个数据集的差异表达基因做韦恩图得到3个共同差异表达基因。GO富集分析表明NSIP中上调的差异表达基因主要影响RNA剪接、抗病毒感染、对肽的细胞反应等相关的生物过程,富集的分子主要参与细胞组分的囊腔合成分泌、剪接复合体,富集的分子功能主要参与ATP酶活性,受体配体活性及DNA结合转录激活因子活性。NSIP中下调的蛋白主要涉及转移酶活性调节的生物过程。KEGG通路分析表明NSIP中上调的差异表达基因主要参与PI3K-Akt、人类乳头瘤病毒感染及MAPK等信号通路。 结论利用生物信息学筛选出差异表达基因,可能是NSIP发病机制的新靶点,对诊断治疗NSIP具有临床意义。     

Identification of a functional circRNA-miRNA-mRNA regulatory network in infantile hemangioma by bioinformatics analysis

Several circRNA have been reported to serve critical roles in various biological processes of human body. The present study aimed to build a circRNA-based competing endogenous RNA (ceRNA) network and explore the regulatory mechanisms of circRNA in infantile hemangiomas (IH). Differentially expressed circRNA, miRNA, and mRNA were downloaded from the gene expression synthesis (GEO) microarray database ({"type":"entrez-geo","attrs":{"text":"GSE98795","term_id":"98795"}}GSE98795, {"type":"entrez-geo","attrs":{"text":"GSE69136","term_id":"69136"}}GSE69136, and {"type":"entrez-geo","attrs":{"text":"GSE127487","term_id":"127487"}}GSE127487). Cancer-specific circRNA database (CSCD), miRDB and Targetscan were employed to predict the targets of RNA. A total of 855 DEcircRNAs, 69 differentially expressed miRNAs (DEmiRNAs), and 3233 differentially expressed mRNAs (DEmRNAs) appeared as genes that were aberrantly expressed in IH. The circRNA-miRNA-mRNA network was constructed based on 108 circRNAs, 7 miRNAs, 274 mRNAs in IH. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis indicated hypoxia-inducible factors (HIF)-1 signaling pathway and Notch signaling pathway were significantly enriched in IH with being constructed a ceRNA regulatory network. Furthermore, protein-protein interaction (PPI) network and Cytoscape showed the top 10 hub genes that regulate angiogenesis, namely FBXW7, CBLB, HECW2, FBXO32, FBXL7, KLHL5, EP300, MAPK1, MEF2C, and PLCG1. Our findings provide a deeper understanding the circRNA-related ceRNA regulatory mechanism in IH. This study further perfected the circRNA-miRNA-mRNA regulatory network related to IH and explored the potential function of mRNA in this network. It provides more understanding for the circRNA-related ceRNA regulation mechanism in the pathogenesis of IH.     

Identification of candidate biomarkers correlated with the pathogenesis and prognosis of breast cancer via integrated bioinformatics analysis

Background:This study was carried out to identify potential key genes associated with the pathogenesis and prognosis of breast cancer (BC).Methods:Seven GEO datasets ({"type":"entrez-geo","attrs":{"text":"GSE24124","term_id":"24124"}}GSE24124, {"type":"entrez-geo","attrs":{"text":"GSE32641","term_id":"32641"}}GSE32641, {"type":"entrez-geo","attrs":{"text":"GSE36295","term_id":"36295"}}GSE36295, {"type":"entrez-geo","attrs":{"text":"GSE42568","term_id":"42568"}}GSE42568, {"type":"entrez-geo","attrs":{"text":"GSE53752","term_id":"53752"}}GSE53752, {"type":"entrez-geo","attrs":{"text":"GSE70947","term_id":"70947"}}GSE70947, {"type":"entrez-geo","attrs":{"text":"GSE109169","term_id":"109169"}}GSE109169) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) between BC and normal breast tissue samples were screened by an integrated analysis of multiple gene expression profile datasets. Hub genes related to the pathogenesis and prognosis of BC were verified by employing protein–protein interaction (PPI) network.Results:Ten hub genes with high degree were identified, including CDK1, CDC20, CCNA2, CCNB1, CCNB2, BUB1, BUB1B, CDCA8, KIF11, and TOP2A. Lastly, the Kaplan–Meier plotter (KM plotter) online database demonstrated that higher expression levels of these genes were related to lower overall survival. Experimental validation showed that all 10 hub genes had the same expression trend as predicted.Conclusion:The findings of this research would provide some directive significance for further investigating the diagnostic and prognostic biomarkers to facilitate the molecular targeting therapy of BC, which could be used as a new biomarker for diagnosis and to guide the combination medicine of BC.     

Identification of CKS2 and RRM2 as potential markers of vitiligo using bioinformatics analysis

Previous studies have attempted to elucidate the molecular mechanism of vitiligo; however, its pathogenesis remains unclear. This study aimed to explore biomarkers related to vitiligo through bioinformatic analysis. The microarray datasets {"type":"entrez-geo","attrs":{"text":"GSE53146","term_id":"53146"}}GSE53146 and {"type":"entrez-geo","attrs":{"text":"GSE65127","term_id":"65127"}}GSE65127 were downloaded from the Gene Expression Omnibus database. Firstly, differentially expressed genes (DEGs) in {"type":"entrez-geo","attrs":{"text":"GSE53146","term_id":"53146"}}GSE53146 were screened, and then an enrichment analysis was performed. Secondly, the protein-protein interaction (PPI) network of DEGs was constructed using the STRING database, and the key genes were screened using the MCODE plugin in Cytoscape and verified using {"type":"entrez-geo","attrs":{"text":"GSE65127","term_id":"65127"}}GSE65127. Finally, quantiseq was used to evaluate immune cell infiltration in vitiligo, then to observe the correlation between biomarkers and immune cells. In total, 544 DEGs were identified, including 342 upregulated and 202 downregulated genes. Gene Ontology (GO) enrichment showed that DEGs were related to inflammatory and immune responses, and Kyoto Encyclopedia of Genes and Genomes enrichment showed that DEGs were involved in many autoimmune diseases. In the PPI network, 7 key genes, CENPN, CKS2, PLK4, RRM2, TPX2, CCNA2, and CDC45 were identified by MCODE cluster and verified using the {"type":"entrez-geo","attrs":{"text":"GSE65127","term_id":"65127"}}GSE65127 dataset. With an area under the curve (AUC) > 0.8 as the standard, 2 genes were screened, namely CKS2 and RRM2. Further immune infiltration analysis showed that M2 macrophages were involved in the pathogenesis of vitiligo, whereas CKS2 and RRM2 were both related to M2 macrophages. This study shows that CKS2 and RRM2 have potential as biomarkers of vitiligo and provides a theoretical basis for a better understanding of the pathogenesis of vitiligo.     

The clinical significance of thyroid hormone-responsive in thyroid carcinoma and its potential regulatory pathway

The study aimed to evaluate the clinical significance of thyroid hormone-responsive (THRSP) and explore its relevant pathways in thyroid carcinoma (THCA).The gene expression data of THRSP were obtained and the prognostic significance of THRSP in THCA was analyzed through various bioinformatics databases. Then, the factors influencing THRSP mRNA expression were explored, and the function of THRSP in predicting the lymph node metastasis (LNM) stage was determined. We further performed the enrichment analysis and constructed a protein–protein interaction (PPI) network to examine potential regulatory pathways associated with THRSP.THRSP gene expression was significantly increased in THCA compared with the normal tissues. High THRSP mRNA expression had a favorable overall survival (OS) in THCA patients (P < .05). Additionally, the mRNA expression of THRSP was related to stage, histological subtype, and methylation among THCA patients (all P < .05). Besides, THRSP served as a potent predictor in discriminating the LNM stage of thyroid cancer patients. According to Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene set enrichment analysis (GSEA) on THRSP-associated genes, THRSP was positively related to metabolic pathways.The upregulation of THRSP predicted a good OS in THCA patients. Furthermore, THRSP might inhibit THCA progression through positive regulation of metabolism-associated pathways.