Identification of MEG8-miR378d-SOBP Axis as a Novel Regulatory Network and Associated With Immune Infiltrates in Ovarian Carcinoma by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Jian Lei ◽  
Zhen-Yu He ◽  
Jun Wang ◽  
Min Hu ◽  
Ping Zhou ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Human Protein Atlas

Abstract BackgroundTo investigate the potential molecular mechanism of ovarian cancer (OC) evolution and immunological correlation using the integrated bioinformatics analysis.MethodsData from the Gene Expression Omnibus (GEO) was used to gain differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis were completed by utilizing the Database for Annotation, Visualization, and Integrated Discovery (DAVID). After multiple validation via The Cancer Genome Atlas (TCGA), Gene Expression Profiling Interactive Analysis 2 (GEPIA 2), the Human Protein Atlas (HPA) and Kaplan-Meier (KM) plotter, immune logical relationships of the key gene SOBP were evaluated based on Tumor Immune Estimation Resource (TIMER), and Gene Set Enrichment Analysis (GSEA) software. Finally, the lncRNAs-miRNAs-mRNAs sub-network was predicted by starBase, Targetscan, miRBD, and LncBase, individually. Correlation of expression and prognosis for mRNAs, miRNAs and lncRNAs were confirmed by TCGA, GEPIA 2, starBase, and KM.ResultsA total of 192 shared DEGs were discovered from the four data sets, including 125 upregulated and 67 downregulated genes. Functional enrichment analysis presented that they were mainly enriched in cartilage development, pathway in PI3K-Akt signaling pathway. Lower expression of SOBP was the independent prognostic factor for inferior prognosis in OC patients. Intriguingly, downregulated SOBP enhanced the infiltration levels of B cells, CD8+ T cells, Macrophage, Neutrophil and Dendritic cells. GSEA also disclosed low SOBP showed significantly association with the activation of various immune-related pathways. Finally, we firstly reported that MEG8-miR378d-SOBP axis was linked to development and prognosis of ovarian cancer through regulating cytokines pathway.Conclusions Our study establishes a novel MEG8-miR378d-SOBP axis in the development and prognosis of OC, and the triple sub-network probably affects the progression of ovarian tumor by regulating cytokines pathway.

scholarly journals Identification of ALDH3A2 as novel prognostic biomarker in gastric adenocarcinoma by integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Xiyi Wei ◽  
Jianping Shi ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
Cancer Genome Atlas

Abstract Extensive experiments and researches have elucidated that genes plays a pivotal role in tumorigenesis and development. Nonetheless, its latent involvement in gastric carcinoma (GC) remains to be further investigated. In this study, we identified overlapping differentially expressed genes (DEGs) by comparing the tumor tissue and adjacent normal tissue from Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database, which included 79 up-regulated and 10 down-regulated genes. Based on these genes, functional enrichment analysis, protein-protein interaction (PPI) and prognosis analysis were conducted, and thus the gene ALDH3A2 was chosen for further analysis. Then, we performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations and checkpoints) to comprehend the in-deep mechanism of ALDH3A2. In a word, ALDH3A2 might have potential reference value for the relief and immunotherapy, and become an independent predictive marker for the prognosis of GC.

scholarly journals Integrated Analyses Identify Immune-Related Signature Associated with Qingyihuaji Formula for Treatment of Pancreatic Ductal Adenocarcinoma Using Network Pharmacology and Weighted Gene Co-Expression Network

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Xiang Qian ◽  
Zhuo Chen ◽  
Sha Sha Chen ◽  
Lu Ming Liu ◽  
Ai Qin Zhang
Keyword(s):  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Ductal Adenocarcinoma ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Kaplan Meier ◽  
Human Protein Atlas

The study aimed to clarify the potential immune-related targets and mechanisms of Qingyihuaji Formula (QYHJ) against pancreatic cancer (PC) through network pharmacology and weighted gene co-expression network analysis (WGCNA). Active ingredients of herbs in QYHJ were identified by the TCMSP database. Then, the putative targets of active ingredients were predicted with SwissTargetPrediction and the STITCH databases. The expression profiles of GSE32676 were downloaded from the GEO database. WGCNA was used to identify the co-expression modules. Besides, the putative targets, immune-related targets, and the critical module genes were mapped with the specific disease to select the overlapped genes (OGEs). Functional enrichment analysis of putative targets and OGEs was conducted. The overall survival (OS) analysis of OGEs was investigated using the Kaplan-Meier plotter. The relative expression and methylation levels of OGEs were detected in UALCAN, human protein atlas (HPA), Oncomine, DiseaseMeth version 2.0 and, MEXPRESS database, respectively. Gene set enrichment analysis (GSEA) was conducted to elucidate the key pathways of highly-expressed OGEs further. OS analyses found that 12 up-regulated OGEs, including CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 that could be utilized as potential diagnostic indicators for PC. Further, methylation analyses suggested that the abnormal up-regulation of these OGEs probably resulted from hypomethylation, and GSEA revealed the genes markedly related to cell cycle and proliferation of PC. This study identified CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 might be used as reliable immune-related biomarkers for prognosis of PC, which may be essential immunotherapies targets of QYHJ.

scholarly journals Identification of novel potential biomarkers in hepatocarcinoma cancer; a transcriptome analysis

2021 ◽  
Author(s):  
Mohib kakar ◽  
Muhammad Mehboob ◽  
Muhammad Akram ◽  
Imran Iqbal ◽  
Hafza Ijaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Predictive Biomarkers ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Molecular Therapy ◽  
Hub Genes ◽  
Healthy Control

Abstract Objective The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Methods GEO contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server Gene Expression Omnibus. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and Functional Enrichment Analysis was performed to extract rational information from a set of DEGs. The Protein-Protein Relationship Networking search method has been used for extracting genes interacting. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. Results We identified the top 10 hub genes through Cytohubba plugin. These genes include Cell Cycle Regulatory Cyclins and Cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. Conclusion In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarkers studies that could promote selective molecular therapy for HCC.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further.Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database.Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4.Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

scholarly journals Identification of Novel Potential Biomarkers in Hepatocarcinoma Cancer; A Transcriptome Analysis

2021 ◽  
Author(s):  
Mohib kakar ◽  
Muhammad Mehboob ◽  
Muhammad Akram ◽  
Imran Iqbal ◽  
Hafza Ijaz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cancer Progression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Predictive Biomarker ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Molecular Therapy ◽  
Hub Genes ◽  
Healthy Control

Abstract The goal of this study was to understand possible core genes associated with hepatocellular carcinoma (HCC) pathogenesis and prognosis. Gene Expression Omnibus (GEO) contains datasets of gene expression, miRNA and methylation patterns of diseased and healthy/control patients. GSE62232 Dataset was selected by employing the server GEO. A total of 91 samples were collected, including 81 HCC samples and 10 healthy samples as control. GSE62232 was analyzed through GEO2R, and functional enrichment analysis was performed to extract rational information from a set of DEGs. The protein-protein relationship networking search method was used for extracting interacting genes. MCC method was used to calculate the top 10 genes according to their importance. Hub genes in the network were analyzed using GEPIA to estimate the effect of their differential expression on cancer progression. We identified the top 10 hub genes through Cytohubba plugin. These genes include cell cycle regulatory cyclins and cyclin-dependent proteins CCNA2, CCNB1 and CDK1. The pathogenesis and prognosis of HCC may be directly linked with the aforementioned genes. In this analysis, we found critical genes for HCC that showed recommendations for more diagnostic and predictive biomarker studies that could promote selective molecular therapy for HCC.

scholarly journals Role of COL3A1 and POSTN on Pathologic Stages of Esophageal Cancer

2020 ◽  
Vol 19 ◽  
pp. 153303382097748
Author(s):  
Shao-wei Zhang ◽  
Nan Zhang ◽  
Na Wang
Keyword(s):  
Gene Expression ◽  
Esophageal Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Protein Protein Interaction ◽  
And Control ◽  
The Impact

Background: Esophageal cancer (EC) is a primary malignant tumor originating from the esophageal of the epithelium. Surgical resection is a potential treatment for EC, but this is only appropriate for patients who have locally resectable lesions suitable for surgery. However, most patients with EC are at a late stage when diagnosed. Therefore, there is an urgent need to further explore the pathogenesis of EC to enable early diagnosis and treatment. Methods: Our study downloaded 2 expression spectrum datasets (GSE92396 and GSE100942) in the Gene Expression Omnibus (GEO) database. GEO2 R was used to identify the Differentially expressed genes (DEGs) between the samples of EC and control. Using the DAVID tool to make the Functional enrichment analysis. Constructing A protein–protein interaction (PPI) network. Identifying the Hub genes. The impact of hub gene expression on overall survival and their expression based on immunohistochemistry were analyzed. Associated microRNAs were also predicted. Results: There were 36 common DEGs identified. The analysis of GO and KEGG results shown that the variations were predominantly concentrated in the extracellular matrix (ECM), ECM organization, DNA binding, platelet activation, and ECM-receptor interactions. COL3A1 and POSTN had high expression in EC tissues which was compared with their expression in healthy tissues. Analysis of pathologic stages showed that when COL3A1 and POSTN were highly expressed, the stage of the pathologic of EC patients was relatively high (P < 0.005). Conclusions: COL3A1 and POSTN may play an important role in the advancement and occurrence of EC. These genes could provide some novel ideas and basis for the diagnosis and targeted treatment of EC.

scholarly journals Analysis of Serum miRNAs in Alzheimer’s Disease

2021 ◽  
Vol 36 ◽  
pp. 153331752110217
Author(s):  
Liu Lu ◽  
Wen-Zhuo Dai ◽  
Xi-Chen Zhu ◽  
Tao Ma
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Gene Interaction ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Mitogen Activated Protein Kinase ◽  
Regulatory Relationship

This paper was aimed to analyze the microRNA (miRNA) signatures in Alzheimer disease (AD) and find the significant expressions of miRNAs, their target genes, the functional enrichment analysis of the confirmed genes, and potential drug treatment. The miRNA expression information of the gene expression profile data was downloaded from the Gene Expression Omnibus database. The total data sample size is 1309, including 1021 AD samples and 288 normal samples. A total of 21 differentially expressed miRNAs were obtained, of which 16 (hsa-miR-6761-3p, hsa-miR-6747-3p, hsa-miR-6875-3p, hsa-miR-6754-3p, hsa-miR-6736-3p, hsa-miR-6762-3p, hsa-miR-6787-3p, hsa-miR-208a-5p, hsa-miR-6740-3p, hsa-miR-6778-3p, hsa-miR-595, hsa-miR-6753-3p, hsa-miR-4747-3p, hsa-miR-3646, hsa-miR-6716-3p and hsa-miR-4435) were up-regulated and 5 (hsa-miR-125a-3p, hsa-miR-22-3p, hsa-miR-24-3p, hsa-miR-6131 and hsa-miR-125b-1-3p) were down-regulated in AD. A total of 6 miRNAs (hsa-miR-595, hsa-miR-3646, hsa-miR-4435 hsa-miR-125a-3p, hsa-miR-22-3p and hsa-miR-24-3p) and 78 miRNA-disease-related gene sub-networks were predicted, and 116 ceRNA regulatory relationship pairs, and the ceRNA regulatory network were obtained. The results of enrichment analysis suggested that the main target pathways of several miRNAs differentially expressed in AD were mitogen-activated protein kinase signal pathway. According to the prediction results of Drug-Gene Interaction database 2.0, we obtained 53 pairs of drug-gene interaction, including 7 genes (PTGS2, EGFR, CALM1, PDE4D, FGFR2, HMGCR, cdk6) and 53 drugs. We hope our results are helpful to find a viable way to prevent, delay the onset, diagnose, and treat AD.

scholarly journals Identification of ALDH3A2 as a novel prognostic biomarker in gastric adenocarcinoma using integrated bioinformatics analysis

2020 ◽  
Author(s):  
Zhenhua Yin ◽  
Dejun Wu ◽  
Jianping Shi ◽  
Xiyi Wei ◽  
Nuyun Jin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Reference Value ◽  
Enrichment Analysis ◽  
Predictive Marker ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Fatty Aldehyde ◽  
Low Grade

Abstract Background: Extensive research has revealed that genes play a pivotal role in tumor development and growth. However, the underlying involvement of gene expression in gastric carcinoma (GC) remains to be investigated further. Methods: In this study, we identified overlapping differentially expressed genes (DEGs) by comparing tumor tissue with adjacent normal tissue using the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) database. Results: Our analysis identified 79 up-regulated and ten down-regulated genes. Functional enrichment analysis and prognosis analysis were conducted on the identified genes, and the fatty aldehyde dehydrogenase (FALDH) gene, ALDH3A2, was chosen for more detailed analysis. We performed Gene Set Enrichment Analysis (GSEA) and immunocorrelation analysis (infiltration, copy number alterations, and checkpoints) to elucidate the mechanisms of action of ALDH3A2 in depth. The immunohistochemical (IHC) result based on 140 paraffin-embedded human GC samples indicated that ALDH3A2 was over-expressed in low-grade GC cases and the OS of patients with low expression of ALDH3A2 was significantly shorter than those with high ALDH3A2 expression. In vitro results indicated that the expression of ALDH3A2 was negatively correlated with PDCD1, PDCD1LG2, and CTLA-4. Conclusion: We conclude that ALDH3A2 might be useful as a potential reference value for the relief and immunotherapy of GC, and also as an independent predictive marker for the prognosis of GC.

scholarly journals Identification of a FLG-wide-type bladder cancer subtype with poor prognosis and prediction use in immune checkpoint

2021 ◽  
Author(s):  
Liang Chen ◽  
Liulin Xiong ◽  
Weinan Chen ◽  
Lizhe An ◽  
Huanrui Wang ◽  
...  
Keyword(s):  
Bladder Cancer ◽  
Immune Checkpoint ◽  
Poor Prognosis ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Immune Biomarkers

Abstract Background Bladder cancer (BLCA) is one of most common urinary tract malignant tumor and immunotherapy have generated a great deal of interest in BLCA. Immune checkpoint blockade (ICB) therapy has significantly progressed the treatment of BLCA. Multiple studies have suggested that specific genetic mutations may serve as immune biomarkers for ICB therapy. Objective In this study, we aimed to investigate the role of mutations genes and subtypes in prognosis and immune checkpoint prediction in BLCA. Method Mutation information and expression profiles were acquired from The Cancer Genome Atlas (TCGA) database. Integrated bioinformatics analysis was carried out to explore the mutation genes of BLCA. Functional enrichment analysis Gene Ontology (GO) and Gene set enrichment analysis (GSEA) was conducted. The infiltrating immune cells and the prediction of ICB between different subtypes group were explored using immuCellAI algorithm. Results The mutation genes Filaggrin (FLG) gene were identified. Following the study on its subtypes and functional enrichment analysis, Sub2 of FLG-wide type was found to have relationships with poor prognosis and immune infiltration BLCA. What’s more, Sub2 of FLG-wide type may be used as a biomarker to predict the prognosis of BLCA patients receiving ICB. Conclusion This research provides a new basis and ideas for guiding the clinical application of BLCA immunotherapy.

scholarly journals Identification of LINC01503 as Biomarker Regulated by CTBP1 with Prognostic and Diagnostic Role in Epithelial Ovarian Cancer

2021 ◽  
Author(s):  
Yanchun Wang ◽  
Zheng Wei ◽  
Junping Zhang ◽  
Xuemei Wang ◽  
Xiaohua Li
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Underlying Mechanism ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
High Morbidity ◽  
Promote Cell Proliferation ◽  
Important Relationship

Abstract Background: Epithelial ovarian cancer (EOC) is a disease with high morbidity and mortality worldwide, which is seriously harmful to female health. LncRNA has an important relationship with the occurrence and development of tumors. Hence, the investigation of the underlying mechanism between LncRNA and EOC is of great importance.Results: In this study, we found that LINC01503 was highly expressed in EOC with a poor prognosis based on microarray datasets GSE119056 and GSE135886 obtained from Gene Expression Omnibus (GEO) database, and this result was verified by RT-qPCR. The database lncBase Predicted v.2 and starBase v2.0 were used to predict the targeted relationship of lncRNA-miRNA-mRNA, then the ceRNA network was established by Cytoscape software. Following, the expression and overall survival (OS) analysis of key lncRNAs were analyzed by GEPIA and Kaplan-Meier plotter database. Gene Ontology (GO) functional enrichment analysis was performed by DAVID database and enriched two cancer related biological processes (BP) that response to endoplasmic reticulum stress and IRE1-mediated unfolded protein. Moreover, we verified that LINC01503 was an oncogene regulated by C-terminal binding protein 1 (CTBP1) to promote cell proliferation, migration and inhibited cell apoptosis in ovarian cancer. Conclusion: In conclusion, these results identified LINC01503 as a potential gene for EOC diagnosis and prognosis.

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