The Role of Ferroptosis-Related Gene in the Immune Activity and Prognosis of Sepsis

IntroductionSepsis is a leading cause of mortality in intensive care units worldwide. Ferroptosis, a form of regulated cell-death–related iron, has been proven to be altered during sepsis, including increased iron transport and uptake into cells and decreased iron export. A better understanding of the role of ferroptosis in sepsis should expedite the identification of biomarkers for prognostic evaluation and therapeutic interventions.Material and methodsWe used the mRNA expression profiles of sepsis patients from Gene Expression Omnibus (GEO) to analyze the expression level of ferroptosis-related genes and construct molecular subtypes.ResultsTwo distinct ferroptosis patterns were determined, and the overall survival of the two clusters was highly significantly different. Gene comparison analysis was performed on these two groups, and there were a total of 106 differentially expressed genes(DEGs). Pathway enrichment analysis of these genes showed that ferroptosis and immune-related pathways were enriched, suggesting that immune pathways might be critically involved in sepsis. To systematically predict the prognosis of sepsis, we constructed a nomogram model, the calibration plot nomogram showed excellent concordance for the 7-, 14-, and 28-days predicted and actual overall survival probabilities. Finally, the results of bioinformatics analysis were validated in animal and cell modelsConclusionsIn this study, we construct a ferroptosis-related nomogram that can be used for prognostic prediction in sepsis. In addition, we revealed the ferroptosis played a non-negligible role in immune cell infiltration and guiding more effective immunotherapy strategies.

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Identification of the potential biomarkers in patients with glioma: a weighted gene co-expression network analysis

Carcinogenesis ◽

10.1093/carcin/bgz194 ◽

2019 ◽

Vol 41 (6) ◽

pp. 743-750 ◽

Cited By ~ 1

Author(s):

Ting-Yu Chen ◽

Yang Liu ◽

Liang Chen ◽

Jie Luo ◽

Chao Zhang ◽

...

Keyword(s):

Gene Expression ◽

Current Knowledge ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Module Preservation ◽

New Biomarkers

Abstract Glioma is the most common brain tumor with high mortality. However, there are still challenges for the timely and accurate diagnosis and effective treatment of the tumor. One hundred and twenty-one samples with grades II, III and IV from the Gene Expression Omnibus database were used to construct gene co-expression networks to identify hub modules closely related to glioma grade, and performed pathway enrichment analysis on genes from significant modules. In gene co-expression network constructed by 2345 differentially expressed genes from 121 gene expression profiles for glioma, we identified the black and blue modules that associated with grading. The module preservation analysis based on 118 samples indicates that the two modules were replicable. Enrichment analysis showed that the extracellular matrix genes were enriched for blue module, while cell division genes were enriched for black module. According to survival analysis, 21 hub genes were significantly up-regulated and one gene was significantly down-regulated. What’s more, IKBIP, SEC24D, and FAM46A are the genes with little attention among the 22 hub genes. In this study, IKBIP, SEC24D, and FAM46A related to glioma were mentioned for the first time to the current knowledge, which might provide a new idea for us to study the disease in the future. IKBIP, SEC24D and FAM46A among the 22 hub genes identified that are related to the malignancy degree of glioma might be used as new biomarkers to improve the diagnosis, treatment and prognosis of glioma.

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Prognostic Value of BIRC5 in Lung Adenocarcinoma Lacking EGFR, KRAS, and ALK Mutations by Integrated Bioinformatics Analysis

Disease Markers ◽

10.1155/2019/5451290 ◽

2019 ◽

Vol 2019 ◽

pp. 1-12 ◽

Cited By ~ 8

Author(s):

Yajuan Cao ◽

Weikang Zhu ◽

Wanqing Chen ◽

Jianchun Wu ◽

Guozhen Hou ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Lung Adenocarcinoma ◽

Prognostic Value ◽

Expression Profiles ◽

Prognostic Significance ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Hub Genes

Objective. This study was aimed at investigating the prognostic significance of Baculoviral IAP repeat containing 5 (BIRC5) in lung adenocarcinoma (LAD) lacking EGFR, KRAS, and ALK mutations (triple-negative (TN) adenocarcinomas). Methods. The gene expression profiles were obtained from Gene Expression Omnibus (GEO). The identification of the differentially expressed genes (DEGs) was performed by GeneSpring GX. Gene set enrichment analysis (GSEA) was used to execute gene ontology function and pathway enrichment analysis. The protein interaction network was constructed by Cytoscape. The hub genes were extracted by MCODE and cytoHubba plugin from the network. Then, using BIRC5 as a candidate, the prognostic value in LAD and TN adenocarcinomas was verified by the Kaplan-Meier plotter and The Cancer Genome Atlas (TCGA) database, respectively. Finally, the mechanism of BIRC5 was predicted by a coexpressed network and enrichment analysis. Results. A total of 38 upregulated genes and 121 downregulated genes were identified. 9 hub genes were extracted. Among them, the mRNA expression of 5 genes, namely, BIRC5, MCM4, CDC20, KIAA0101, and TRIP13, were significantly upregulated among TN adenocarcinomas (all P<0.05). Notably, only the overexpression of BIRC5 was associated with unfavorable overall survival (OS) in TN adenocarcinomas (log rank P=0.0037). TN adenocarcinoma patients in the BIRC5 high-expression group suffered from a significantly high risk of distant metastasis (P=0.046), advanced N stage (P=0.033), and tumor-bearing (P=0.031) and deceased status (P=0.003). The mechanism of BIRC5 and coexpressed genes may be linked closely with the cell cycle. Conclusion. Overexpressed in tumors, BIRC5 is associated with unfavorable overall survival in TN adenocarcinomas. BIRC5 is a potential predictor and therapeutic target in TN adenocarcinomas.

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Comprehensive bioinformatics analysis of mRNA expression profiles and identification of a miRNA–mRNA network associated with lupus nephritis

Lupus ◽

10.1177/0961203320925155 ◽

2020 ◽

Vol 29 (8) ◽

pp. 854-861

Author(s):

Jianbo Song ◽

Liqin Zhao ◽

Yuanping Li

Keyword(s):

Lupus Nephritis ◽

Mrna Expression ◽

Lupus Erythematosus ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Ppi Network

Objective Lupus nephritis (LN) is one of the serious complications of systemic lupus erythematosus. The aim of this study was to identify core genes and pathways involved in the pathogenesis of LN. Methods We screened differentially expressed genes (DEGs) in LN patients using mRNA expression profile data from the Gene Expression Omnibus. The functional and pathway enrichment analysis of DEGs was performed utilizing the Database for annotation, Visualization and Integrated Discovery. Target genes with differentially expressed miRNAs (DEMIs) were predicted using the miRTarBase database, and the intersection between these target genes and DEGs was selected to be studied further. Results In total, 107 common DEGs (CDEGs) were identified from the Tub_LN group and Glom_LN group, and 66 DEMIs were identified. Fifty-three hub genes and two significant modules were identified from the protein–protein interaction (PPI) network, and a miRNA–mRNA network was constructed. The CDEGs, module genes in the PPI network and genes intersecting with the CDEGs and target genes of DEMIs were all associated with the PI3K-Akt signalling pathway. Conclusion In summary, this study reveals some crucial genes and pathways potentially involving in the pathogenesis of LN. These findings provide a new insight for the research and treatment of LN.

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The relationship between LncRNAs and lung adenocarcinoma as well as their ceRNA network

Cancer Biomarkers ◽

10.3233/cbm-203078 ◽

2021 ◽

pp. 1-12

Author(s):

Yuxin Zhao ◽

Shuwen Ma ◽

Zhigang Cui ◽

Sixuan Li ◽

Yao Chen ◽

...

Keyword(s):

Lung Cancer ◽

Expression Profiles ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Lung Cancer Patients ◽

Protein Protein Interaction ◽

Normal Tissues ◽

Cerna Network ◽

Downstream Analysis

BACKGROUND: More and more studies have shown that long non-coding RNA (LncRNA) as a competing endogenous RNA (ceRNA) plays an important role in lung cancer. Therefore, we analyzed the RNA expression profiles of 82 lung cancer patients which were all from Gene Expression Omnibus (GEO). METHODS: Firstly, we used BLASTN (evalue = 1e-10) to annotate the gene sets, performed in-group correction and batched normalization of the four data sets with R. Secondly, we used the limma and sva packages to compare tumor tissues with normal tissues. Then through WGCNA, we obtained the 4 gene modules most related to the trait. RESULTS: We intersected the genes of above 4 modules with the differential expression genes: 28 LncRNAs (up: 5, down: 23) and 265 mRNAs (up:11, down: 254). Based on these genes, we picked up 6 LncRNAs (CCDC39, FAM182A, SRGAP3-AS2, ADAMTS9-AS2, AC020907.2, SFTA1P), then set and visualized the LncRNA-miRNA-mRNA ceRNA network with 12 miRNAs related to 12 mRNAs. Finally, we performed downstream analysis of 265 mRNAs by Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and Protein-Protein Interaction (PPI) network. CONCLUSION: After analyzing, we think this study provides a new direction for basic and clinical research related to LAD, and is expected to provide new targets for early diagnosis, prognostic evaluation and clinical treatment of lung cancer.

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Analysis of MCM Proteins’ Role as a Potential Target of Statins in Patients with Acute Type A Aortic Dissection through Bioinformatics

Genes ◽

10.3390/genes12030387 ◽

2021 ◽

Vol 12 (3) ◽

pp. 387

Author(s):

Zheyong Liang ◽

Yongjian Zhang ◽

Qiang Chen ◽

Junjun Hao ◽

Haichen Wang ◽

...

Keyword(s):

Aortic Dissection ◽

Molecular Mechanisms ◽

Vascular Diseases ◽

Enrichment Analysis ◽

Type A ◽

Protective Role ◽

Gene Expression Omnibus ◽

Pathway Enrichment Analysis ◽

Acute Type ◽

Type A Aortic Dissection

Acute aortic dissection is one of the most severe vascular diseases. The molecular mechanisms of aortic expansion and dissection are unclear. Clinical studies have found that statins play a protective role in aortic dissection development and therapy; however, the mechanism of statins’ effects on the aorta is unknown. The Gene Expression Omnibus (GEO) dataset GSE52093, GSE2450and GSE8686 were analyzed, and genes expressed differentially between aortic dissection samples and normal samples were determined using the Networkanalyst and iDEP tools. Weight gene correlation network analysis (WGCNA), functional annotation, pathway enrichment analysis, and the analysis of the regional variations of genomic features were then performed. We found that the minichromosome maintenance proteins (MCMs), a family of proteins targeted by statins, were upregulated in dissected aortic wall tissues and play a central role in cell-cycle and mitosis regulation in aortic dissection patients. Our results indicate a potential molecular target and mechanism for statins’ effects in patients with acute type A aortic dissection.

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

BioMed Research International ◽

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 ◽

Protein Protein Interaction ◽

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.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Identification of Differentially Expressed Genes and associated pathways common to Eyelid and Non-Ocular Basal Cell Carcinoma to understand the Molecular Biology of BCC

10.1101/2021.05.01.442022 ◽

2021 ◽

Author(s):

Perumal Jayaraj ◽

Seema Sen ◽

Pranjal Vats ◽

Shefali Dahiya ◽

Vanshika Mohindroo

Keyword(s):

Basal Cell Carcinoma ◽

Cell Carcinoma ◽

Basal Cell ◽

Expression Profiles ◽

Enrichment Analysis ◽

Bioinformatic Analysis ◽

Malignant Neoplasms ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Pathway Enrichment

Background: Eyelid BCC accounts for more than 90% of Eyelid malignant neoplasms. Various aberrant signalling pathways and genes in Non-Ocular BCC have been found whereas Eyelid bcc remains elusive. Objective: This study aims to find the common DEGs of Eyelid and Non-Ocular BCC using bioinformatic analysis and text mining to gain more insights into the molecular aspects common to both BCC non-ocular and Eyelid BCC and to identify common potential prognostic markers. Material and method: The Gene Expression profiles of Eyelid BCC (GSE103439) and Non-Ocular BCC (GSE53462) were obtained from the NCBI GEO database followed by identification of common DEGs. Protein-Protein interaction and Pathway Enrichment analysis of these screened genes was done using bioinformatic tools like STRING, Cytoscape and BiNGO, DAVID, KEGG respectively. Results: A total of 181 genes were found common in both datasets. A PPI network was formed for the screened genes and 20 HUB genes were sorted which included CTNNB1, MAPK14, BTRC, EGFR, ADAM17. Pathway enrichment of HUB genes showed that they were dysregulated in carcinogenic and apoptotic pathways that seem to play a role in the progression of both the BCC. Conclusion: The result and findings of bioinformatic analysis highlighted the molecular pathways and genes enriched in both Eyelid BCC as well as Non- Ocular BCC. The identified pathways should be studied further to recognise common molecular events that would lead to the progression of BCC. This may provide a window to explore the prognostic and therapeutic strategies common to both BCC. Keywords: Basal cell carcinoma (BCC), Cancer, Microarray, Ophthalmology, Tumour marker

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

BioMed Research International ◽

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 ◽

Protein Protein Interaction ◽

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.

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Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

Experimental Biology and Medicine ◽

10.1177/15353702211048757 ◽

2021 ◽

pp. 153537022110487

Author(s):

Zirui Zhu ◽

Rui Huang ◽

Baojun Huang

Keyword(s):

Messenger Rna ◽

Expression Profiles ◽

Clinical Stage ◽

Interaction Network ◽

Enrichment Analysis ◽

Rank Aggregation ◽

Circular Rnas ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

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