High UBE2T mRNA expression and its prognostic significance in Ovarian cancer: a study based on data mining

2020 ◽  
Author(s):  
Fu-Cheng Cai
Keyword(s):  
Ovarian Cancer ◽  
Dendritic Cell ◽  
Prognostic Significance ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rna Degradation ◽  
Gene Set Enrichment Analysis ◽  
Pathogenesis Related ◽  
Biologic Effect ◽  
The Difference

Abstract Background Ovarian cancer (OC) affects about 22 000 women annually in the US and ranks 5th in cancer deaths, largely due to diagnosed with advanced stage. Epithelial ovarian cancer (EOC) accounts for approximately 90% of all ovarian cancer cases. Our study was to assess the prognostic meaningful of UBE2T expression in OC dependent on data acquired from TCGA and so as to increase further knowledge into the biological pathways involved in OC pathogenesis related to UBE2T. Methods Information on gene expression and comparing clinical data were recognized and downloaded from TCGA. Gene set enrichment analysis (GSEA) created an arranged list of all genes s indicated by their connection with UBE2T expression. Results The scatter plot showed the difference of UBE2T expression between normal and tumor samples ( P <0.01). So as to decide the biological interaction network of UBE2T in OC, we used to tab Network in cBioPortal and the 50 most as often altered neighbor genes of UBE2T were demonstrated utilizing Network and the most frequent alterations were HES1. The GSEA results showed that cell cycle, DNA replication, RNA degradation, some cancers, spliceosome, Huntington’s disease, oxidative phosphorylation are differentially enriched in UBE2T high expression phenotype. Cumulative survive showed that dendritic cell of immune infiltrates statistically significant ( P <0.05) of UBE2T in OC suggesting that dendritic cell significantly affecting the prognosis, it is worth more research and exploration. Conclusion Our study found that the expression of UBE2T was significantly increased in OC patients and associated with several clinical features. UBE2T may be a potentially useful prognostic molecular biomarker of bad survival in OC, while further experimental ought to be performed to demonstrate the biologic effect of UBE2T.

scholarly journals High UBE2T mRNA expression and its prognostic significance in Ovarian cancer: a study based on data mining

2020 ◽  
Author(s):  
zenghong wu
Keyword(s):  
Ovarian Cancer ◽  
Dendritic Cell ◽  
Prognostic Significance ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Rna Degradation ◽  
Gene Set Enrichment Analysis ◽  
Pathogenesis Related ◽  
Biologic Effect ◽  
The Difference

Abstract Objection Ovarian cancer (OC) affects approximately 22 000 women annually in the US and ranks 5th in cancer deaths, largely due to diagnosed with advanced stage1. Epithelial ovarian cancer (EOC) accounts for approximately 90% of all ovarian cancer cases. Our study was to assess the prognostic meaningful of UBE2T expression in OC dependent on data acquired from TCGA and so as to increase further knowledge into the biological pathways involved in OC pathogenesis related to UBE2T.Method Information on gene expression and comparing clinical data were recognized and downloaded from TCGA. Gene set enrichment analysis (GSEA) created an arranged list of all genes s indicated by their connection with UBE2T expression.Results The scatter plot showed the difference of UBE2T expression between normal and tumor samples (P<0.01). In order to decide the biological interaction network of UBE2T in OC, we applied to tab Network in cBioPortal and the 50 most as often altered neighbor genes of UBE2T were showed utilizing Network and the most frequent alterations were HES1. The GSEA results showed that cell cycle, DNA replication, RNA degradation, some cancers, spliceosome, Huntington’s disease, oxidative phosphorylation are differentially enriched in UBE2T high expression phenotype. Cumulative survive showed that dendritic cell of immune infiltrates statistically significant (P<0.05) of UBE2T in OC indicating that dendritic cell significantly affecting the prognosis, it is worth further research and exploration.Conclusion Our study found that the expression of UBE2T was significantly increased in OC patients and associated with several clinical features. UBE2T may be a potentially useful prognostic molecular biomarker of bad survival in OC, while further experimental ought to be performed to demonstrate the biologic effect of UBE2T.

scholarly journals Potential Value of PRKDC as a Therapeutic Target and Prognostic Biomarker in Pan-Cancer

2021 ◽  
Author(s):  
Xiawei Yang ◽  
Xuyong Sun ◽  
Feng Yang ◽  
Liugen Lan ◽  
Ning Wen ◽  
...  
Keyword(s):  
Therapeutic Target ◽  
Prognostic Biomarker ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Clinical Information ◽  
Rna Degradation ◽  
Gene Set Enrichment Analysis ◽  
Survival Prognosis ◽  
Potential Value ◽  
Pan Cancer

Abstract Background While PRKDC (Protein Kinase, DNA-Activated, Catalytic Subunit) plays an important role in double-strand break (DSB) repair to retain genomic stability, there is still no pan-cancer analysis based on large clinical information on the relationship between PRKDC and different tumors. For the first time, this research used numerous databases to perform a pan-cancer review for PRKDC to explore the possible mechanism of PRKDC in the etiology and outcomes in various tumors. Methods PRKDC's expression profile and prognostic significance in pan-cancer were investigated based on various databases and online platforms, including TIMER2, GEPIA2, cBioPortal, CPTAC, and SangerBox. We applied the TIMER to identified the interlink of PRKDC and the immune infiltration in assorted tumors, and the SangerBox online platform was adopted to find out the relevance between PRKDC and immune checkpoint genes, TMB, and MSI in tumors. GeneMANIA tool was employed to create a Protein-Protein Interaction (PPI) analysis, gene set enrichment analysis (GSEA) was conducted to performed gene enrichment analysis. Results Overall, tumor tissue presented a higher degree of PRKDC expression than adjacent normal tissue. Meanwhile, patients with high PRKDC expression have a worse prognosis. PRKDC mutations were present in almost all TCGA tumors and might lead to a better survival prognosis. PRKDC expression level was shown a positive correlation with tumor-infiltrating immune cells (TIICs). PRKDC high expression cohorts were enriched in "cell cycle," "oocyte meiosis," and "RNA-degradation" signaling pathways. Conclusions This study revealed the potential value of PRKDC tumor immunology and as a therapeutic target and prognostic biomarker in pan-cancer.

Identification of key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma

2020 ◽  
Vol 15 ◽  
Author(s):  
Wei Han ◽  
Dongchen Lu ◽  
Chonggao Wang ◽  
Mengdi Cui ◽  
Kai Lu
Keyword(s):  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differential Expression Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Integrated Analysis ◽  
Papillary Thyroid ◽  
Gene Set Enrichment ◽  
Mirna Expression Data

Background: In the past decades, the incidence of thyroid cancer (TC) has been gradually increasing, owing to the widespread use of ultrasound scanning devices. However, the key mRNAs, miRNAs, and mRNA-miRNA network in papillary thyroid carcinoma (PTC) has not been fully understood. Material and Methods: In this study, multiple bioinformatics methods were employed, including differential expression analysis, gene set enrichment analysis, and miRNA-mRNA interaction network construction. Results: First, we investigated the key miRNAs that regulated significantly more differentially expressed genes based on GSEA method. Second, we searched for the key miRNAs based on the mRNA-miRNA interaction subnetwork involved in PTC. We identified hsa-mir-1275, hsa-mir-1291, hsa-mir-206 and hsa-mir-375 as the key miRNAs involved in PTC pathogenesis. Conclusion: The integrated analysis of the gene and miRNA expression data not only identified key mRNAs, miRNAs, and mRNA-miRNA network involved in papillary thyroid carcinoma, but also improved our understanding of the pathogenesis of PTC.

scholarly journals Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098213
Author(s):  
Xiaodong Deng ◽  
Yuhua Liang ◽  
Jianmei Hu ◽  
Yuhui Yang
Keyword(s):  
Diabetes Mellitus ◽  
Molecular Docking ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Network Pharmacology ◽  
Hub Genes ◽  
Topological Parameters

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

scholarly journals Decoding the molecular mechanism of parthenocarpy in Musa spp. through protein–protein interaction network

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Suthanthiram Backiyarani ◽  
Rajendran Sasikala ◽  
Simeon Sharmiladevi ◽  
Subbaraya Uma
Keyword(s):  
Candidate Genes ◽  
Protein Interaction ◽  
Target Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Auxin Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Protein Protein Interaction ◽  
The Difference

AbstractBanana, one of the most important staple fruit among global consumers is highly sterile owing to natural parthenocarpy. Identification of genetic factors responsible for parthenocarpy would facilitate the conventional breeders to improve the seeded accessions. We have constructed Protein–protein interaction (PPI) network through mining differentially expressed genes and the genes used for transgenic studies with respect to parthenocarpy. Based on the topological and pathway enrichment analysis of proteins in PPI network, 12 candidate genes were shortlisted. By further validating these candidate genes in seeded and seedless accession of Musa spp. we put forward MaAGL8, MaMADS16, MaGH3.8, MaMADS29, MaRGA1, MaEXPA1, MaGID1C, MaHK2 and MaBAM1 as possible target genes in the study of natural parthenocarpy. In contrary, expression profile of MaACLB-2 and MaZEP is anticipated to highlight the difference in artificially induced and natural parthenocarpy. By exploring the PPI of validated genes from the network, we postulated a putative pathway that bring insights into the significance of cytokinin mediated CLAVATA(CLV)–WUSHEL(WUS) signaling pathway in addition to gibberellin mediated auxin signaling in parthenocarpy. Our analysis is the first attempt to identify candidate genes and to hypothesize a putative mechanism that bridges the gaps in understanding natural parthenocarpy through PPI network.

CENPF/CDK1 Signaling Pathway Enhances the Progression of Adrenocortical Carcinoma by Regulating the G2/M-phase Cell Cycle

2021 ◽  
Author(s):  
Yugang Huang ◽  
Dan Li ◽  
Li Wang ◽  
Xiaomin Su ◽  
Xian-bin Tang
Keyword(s):  
Cell Cycle ◽  
Signaling Pathway ◽  
Adrenocortical Carcinoma ◽  
Immune Cell ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Phase Cell ◽  
Aberrant Expression ◽  
M Phase

Abstract Adrenocortical carcinoma (ACC) is an aggressive and rare malignant tumor and prone to local invasion and metastasis. While, overexpressed Centromere Protein F (CENPF) is closely related to oncogenesis of various neoplasms, including ACC. However, the prognosis and exact biological function of CENPF in ACC remains largely unclear. In present essay, the expression of CENPF in human ACC samples, GEO and TCGA databases depicted that CENPF were overtly hyper-expressed in ACC patients and positively correlated with tumor stage. The aberrant expression of CENPF was significantly correlated with unfavorable overall survival (OS) in ACC patients. Then, the application of gene-set enrichment analysis (GSEA) declared that CENPF was mainly involved in the G2/M-phase mediated cell cycle and p53 signaling pathway. Further, a small RNA interference experiment was conducted to demonstrate that the interaction between CENPF and CDK1 enhanced the G2/M-phase transition of mitosis, cell proliferation and might induce p53 mediated anti-tumor effect in human ACC cell line, SW13 cells. Lastly, two available therapeutic strategies, including immunotherapy and chemotherapy, have been further probed. Immune infiltration analysis highlighted that ACC patients with high CENPF expression harbored significantly different immune cell populations, and high TMB/MSI score. Then, the gene-drug interaction network stated that CENPF inhibitors, such as Cisplatin, Sunitinib, and Etoposide, might serve as potential drugs for the therapy of ACC. Briefly, CENPF and related genes might be served as a novel prognostic biomarker or latent therapeutic target for ACC patients.

scholarly journals Prognostic and immunological value of LTB4R in pan-cancer

2021 ◽  
Vol 18 (6) ◽  
pp. 9336-9356
Author(s):  
Sidan Long ◽  
◽  
Shuangshuang Ji ◽  
Kunmin Xiao ◽  
Peng Xue ◽  
...  
Keyword(s):  
Immune Cells ◽  
Prognostic Significance ◽  
Enrichment Analysis ◽  
Negative Influence ◽  
Leukotriene B4 ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Immune Infiltration ◽  
Significant Difference ◽  
Pan Cancer

<abstract> <sec><title>Background</title><p>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain.</p> </sec> <sec><title>Methods</title><p>We investigated the expression pattern and prognostic significance of LTB4R in pan-cancer across different databases, including ONCOMINE, PrognoScan, GEPIA, and Kaplan-Meier Plotter, in this study. Meanwhile, we explored the significance of LTB4R in tumor metastasis by HCMDB. Then functional enrichment analysis of related genes was performed using GeneMANIA and DAVID. Lastly, utilizing the TIMER datasets, we looked into the links between LTB4R expression and immune infiltration in malignancies.</p> </sec> <sec><title>Results</title><p>In general, tumor tissue displayed higher levels of LTB4R expression than normal tissue. Although LTB4R had a negative influence on pan-cancer, a high expression level of LTB4R was protective of LIHC (liver hepatocellular carcinoma) patients' survival. There was no significant difference in the distribution of LTB4R between non-metastatic and metastatic tumors. Based on Gene Set Enrichment Analysis, LTB4R was implicated in pathways involved in inflammation, immunity, metabolism, and cancer diseases. The correlation between immune cells and LTB4R was found to be distinct across cancer types. Furthermore, markers of infiltrating immune cells, such as Treg, T cell exhaustion and T helper cells, exhibited different LTB4R-related immune infiltration patterns.</p> </sec> <sec><title>Conclusion</title><p>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer.</p> </sec> </abstract>

scholarly journals Gene Expression Profile of Active HE4 Stimulation in Epithelial Ovarian Cancer Cells: Microarray Study and Comprehensive Bioinformatics Analysis

2020 ◽  
Author(s):  
Liancheng Zhu ◽  
Mingzi Tan ◽  
Haoya Xu ◽  
Bei Lin
Keyword(s):  
Ovarian Cancer ◽  
Epithelial Ovarian Cancer ◽  
Clinical Significance ◽  
Molecular Mechanisms ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Coexpression Analysis ◽  
Pathway Enrichment

Abstract Background.Human Epididymis Protein 4 (HE4) is a novel serum biomarker for diagnosis of epithelial ovarian cancer (EOC) with high specificity and sensitivity compared with CA125, and the increasing researches have been carried out on its roles in promoting carcinogenesis and chemoresistance in EOC in recent years, however, its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of HE4 stimulation and to identify the key genes and pathways mediating carcinogenesis in EOC using microarray and bioinformatics analysis.Methods. We established a stable HE4-silence ES-2 ovarian cancer cell line labeled as “S”, and its active HE4 protein stimulated cells labeled as “S4”. Human whole genome microarray analysis was used to identify deferentially expressed genes (DEGs) from triplicate samples of S4 and S cells. “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis (GSEA) were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal for WFDC2 coexpression analysis. GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction (qRT-PCR) was applied for validation. The protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape. Results.In total, 713 DEGs were found (164 up regulated and 549 down regulated) and further analyzed by GO, pathway enrichment and PPI analyses. We found that MAPK pathway accounted for a significant portion of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2 coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) that were also dramatically changed in S4 cells and validated by dataset GSE51088. Kaplan–Meier survival statistics revealed clinical significance for all of the 10 target genes. Finally, PPI was constructed, sixteen hub genes and eight molecular complex detections (MCODEs) were identified, the seeds of five most significant MCODEs were subjected to GO and KEGG enrichment analysis and their clinical significance was evaluated.Conclusions.By applying microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network of active HE4 stimulation in EOC cells. We offered several possible mechanisms and identified therapeutic and prognostic targets of HE4 in EOC.

TRPV4 is a Prognostic Biomarker That Correlates With the Immunosuppressive Microenvironment and Chemoresistance of Anti-Cancer Drugs

2021 ◽  
Author(s):  
kai wang ◽  
Jun xing Feng ◽  
Zhi ling Zheng ◽  
Ying ze Chai ◽  
Hui jun Yu ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Transient Receptor Potential ◽  
Immune Cell ◽  
Colon Adenocarcinoma ◽  
Enrichment Analysis ◽  
Receptor Potential ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Free Interval ◽  
Pan Cancer

Abstract Background: Transient receptor potential cation channel subfamily V member 4 (TRPV4) has been reported to regulate tumor progression in many tumor types. However, its association with the tumor immune microenvironment remains unclear.Methods: TRPV4 expression was assessed using data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database. The clinical features and prognostic roles of TRPV4 were assessed using TCGA cohort. Gene set enrichment analysis (GSEA) of TRPV4 was conducted using the R package clusterProfiler. We analyzed the association between TRPV4 and immune cell infiltration scores of TCGA samples downloaded from published articles and the TIMER2 database.Results: TRPV4 was highly expressed and associated with worse overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI), and progression-free interval (PFI) in colon adenocarcinoma (COAD) and ovarian cancer. Furthermore, TRPV4 expression was closely associated with immune regulation-related pathways. Moreover, tumor-associated macrophage (TAM) infiltration levels were positively correlated with TRPV4 expression in TCGA pan-cancer samples. Immunosuppressive genes such as PD-L1, PD-1, CTLA4, LAG3, TIGIT, TGFB1, and TGFBR1 were positively correlated with TRPV4 expression in most tumors.Conclusions: Our results suggest that TRPV4 is an oncogene and a prognostic marker in COAD and ovarian cancer. High TRPV4 expression is associated with tumor immunosuppressive status and may contribute to TAM infiltration based on TCGA data from pan-cancer samples.

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