scholarly journals Expression profiles and prognostic values of BolA family members in ovarian cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mingyang Zhu ◽  
Shiqi Xiao
Keyword(s):  
Ovarian Cancer ◽  
Metal Ion ◽  
Expression Profiles ◽  
Family Members ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Protein Disulfide Oxidoreductase

Abstract Background The BOLA gene family, comprising three members, is mainly involved in regulating intracellular iron homeostasis. Emerging evidence suggests that BolA family member 2 plays a vital role in tumorigenesis and hepatic cellular carcinoma progression. However, there was less known about its role in ovarian cancer. Methods In the present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BolA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein-protein interaction networks of BOLA proteins and their interactors by using the String database and Cytoscape software. In addition, we performed the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying BolA family members’ involvement in OC by using gene set enrichment analysis. Results The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than in normal ovarian tissues. Dysregulated mRNA expressions of three BolA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BolA family members in ovarian cancer. GO analysis indicated that BolA family members might regulate the function of metal ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BolA family members were mainly associated with oxidative phosphorylation, proteasome, protein export, and glutathione metabolism in ovarian cancer. Conclusion In brief, our finding may contribute to increasing currently limited prognostic biomarkers and treatment options for ovarian cancer.

scholarly journals Expression Profiles and Prognostic Values of BOLA Family members in Ovarian Cancer

2020 ◽  
Author(s):  
Mingyang Zhu ◽  
Shiqi Xiao
Keyword(s):  
Ovarian Cancer ◽  
Metal Ion ◽  
Expression Profiles ◽  
Family Members ◽  
Enrichment Analysis ◽  
Genetic Alterations ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Protein Disulfide Oxidoreductase

Abstract Background: The BOLA gene family, comprising 3 members, is mainly involved in the regulation of intracellular iron homeostasis. Emerging evidence suggests that BOLA family member 2 play vital roles in tumorigenesis and progression of hepatic cellular carcinoma. However, little known about its roles in ovarian cancer. Methods: In present study, we investigated the expression profiles, prognostic roles, and genetic alterations of three BOLA family members in patients with ovarian cancer through several public databases, containing Oncomine and Gene Expression Profiling Interactive Analysis, Human Protein Atlas, Kaplan–Meier plotter and cBioPortal. Then, we constructed the protein–protein interaction networks of BOLA proteins and their interactors by using String database and Cytoscape software. In addition, we performed the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment by the Annotation, Visualization, and Integrated Discovery database. Finally, we explored the mechanisms underlying the involvement of BOLA family members in OC by using gene set enrichment analysis. Results: The mRNA and protein expression levels of BOLA2 and BOLA3 were heavily higher in ovarian cancer tissues than that in normal ovarian tissues. Dysregulated mRNA expressions of three BOLA family members were significantly associated with prognosis in overall or subgroup analysis. Moreover, genetic alterations also occurred in three BOLA family members in ovarian cancer. Network analysis and enrichment analysis indicated that three BOLA family members and their 20 interactors were mainly associated with metal-ion binding and protein disulfide oxidoreductase activity. Gene set enrichment analysis indicated that BOLA family members were mainly associated with oxidative phosphorylation, proteasome, protein export and glutathione metabolism in ovarian cancer. Conclusions: In brief, the present comprehensive bioinformatics analysis revealed that BOLA1, 2, and 3 may be new prognostic biomarkers, and BOLA2 and BOLA3 may be a potential therapeutic target of precision therapy for patients with ovarian cancer, but further studies are demanded to certify this notion.

scholarly journals H2A Histone Family Member X (H2AX) Is Upregulated in Ovarian Cancer and Demonstrates Utility as a Prognostic Biomarker in Terms of Overall Survival

2020 ◽  
Vol 9 (9) ◽  
pp. 2844
Author(s):  
Sayeh Saravi ◽  
Eriko Katsuta ◽  
Jeyarooban Jeyaneethi ◽  
Hasnat A. Amin ◽  
Matthias Kaspar ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Overall Survival ◽  
Prognostic Biomarker ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Nucleotide Polymorphisms ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Normal Tissues

Background: H2AX can be of prognostic value in breast cancer, since in advanced stage patients with high levels, there was an association with worse overall survival (OS). However, the clinical relevance of H2AX in ovarian cancer (OC) remains to be elucidated. Methods: OC H2AX expression studied using the TCGA/GTEX datasets. Subsequently, patients were classified as either high or low in terms of H2AX expression to compare OS and perform gene set enrichment. qRT-PCR validated in-silico H2AX findings followed by immunohistochemistry on a tissue microarray. The association between single nucleotide polymorphisms in the area of H2AX; prevalence and five-year OC survival was tested in samples from the UK Biobank. Results: H2AX was significantly overexpressed in OCs compared to normal tissues, with higher expression associated with better OS (p = 0.010). Gene Set Enrichment Analysis demonstrated gene sets involved in G2/M checkpoint, DNA repair mTORC1 signalling were enriched in the H2AX highly expressing OCs. Polymorphisms in the area around the gene were associated with both OC prevalence (rs72997349-C, p = 0.005) and worse OS (rs10790282-G, p = 0.011). Finally, we demonstrated that H2AX gene expression correlated with γ-H2AX staining in vitro. Conclusions: Our findings suggest that H2AX can be a novel prognostic biomarker for OC.

scholarly journals Increased Expression of LYNX1 in Ovarian Serous Cystadenocarcinoma Predicts Poor Prognosis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Hui Liu ◽  
Ao Wang ◽  
Yushan Ma
Keyword(s):  
Ovarian Cancer ◽  
Univariate Analysis ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Serous Cystadenocarcinoma ◽  
Kaplan Meier ◽  
Pathologic Features ◽  
The Relationship

Few studies have reported the function of LYNX1 in ovarian cancer. We retrieved LYNX1 gene expression data and clinical information of 376 patients with ovarian cancer from The Cancer Genome Atlas (TCGA) project website. Wilcoxon signed-rank test and logistic regression were used to analyze the relationship between clinical pathologic features and LYNX1 expression. The Kaplan–Meier method was used to draw survival curves of patients, and Cox regression was used to calculate the relationship between LYNX1 expression and survival rate or the clinicopathological characteristics of the patients. Gene set enrichment analysis (GSEA) was performed, and the correlation between LYNX1 expression and cancer immune infiltrates was investigated via single sample gene set enrichment analysis (ssGSEA). High LYNX1 expression in ovarian serous cystadenocarcinoma (OVs) was associated with tumor residual disease (RD). In Kaplan–Meier survival analysis, patients with OVs who also displayed high LYNX1 expression had decreased overall survival (OS) and disease-specific survival (DSS) than those with low LYNX1 expression. Univariate analysis also supported that patients with high LYNX1 expression had lower OS than those with low LYNX1 expression. LYNX1 expression has the potential to be a prognostic molecular marker of poor survival in OVs.

scholarly journals CENPN Acts as a Novel Biomarker that Correlates With the Malignant Phenotypes of Glioma Cells

2021 ◽  
Vol 12 ◽  
Author(s):  
Hailong Wu ◽  
Yan Zhou ◽  
Haiyang Wu ◽  
Lixia Xu ◽  
Yan Yan ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Glioma Cells ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Migration And Invasion ◽  
Malignant Neoplasms ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Genome Atlas

Background: Gliomas are the most common intracranial malignant neoplasms and have high recurrence and mortality rates. Recent literatures have reported that centromere protein N (CENPN) participates in tumor development. However, the clinicopathologic significance and biological functions of CENPN in glioma are still unclear.Methods: Clinicopathologic data and gene expression profiles of glioma cases downloaded from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) databases were utilized to determine the associations between the expression of CENPN and clinical features of glioma. Kaplan-Meier and ROC curves were plotted for prognostic analysis. Gene set enrichment analysis (GSEA) and single sample gene set enrichment analysis (ssGSEA) were applied to identify immune-related functions and pathways associated with CENPN’ differential expression. In vitro experiments were conducted to investigate the impacts of CENPN on human glioma cells.Results: Elevated CENPN expression was associated with unfavorable clinical variables of glioma patients, which was validated in clinical specimens obtained from our institution by immunohistochemical staining (IHC). The GSEA and ssGSEA results revealed that CENPN expression was strongly correlated with inflammatory activities, immune-related signaling pathways and the infiltration of immune cells. Cell experiments showed that CENPN deficiency impaired cell proliferation, migration and invasion ability and increased glioma apoptosis.Conclusion: CENPN could be a promising therapeutic target for glioma.

scholarly journals Application of biclustering of gene expression data and gene set enrichment analysis methods to identify potentially disease causing nanomaterials

2015 ◽  
Vol 6 ◽  
pp. 2438-2448 ◽  
Author(s):  
Andrew Williams ◽  
Sabina Halappanavar
Keyword(s):  
Gene Expression ◽  
Pulmonary Fibrosis ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Data Driven ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Analysis Methods ◽  
Gene Sets

Background: The presence of diverse types of nanomaterials (NMs) in commerce is growing at an exponential pace. As a result, human exposure to these materials in the environment is inevitable, necessitating the need for rapid and reliable toxicity testing methods to accurately assess the potential hazards associated with NMs. In this study, we applied biclustering and gene set enrichment analysis methods to derive essential features of altered lung transcriptome following exposure to NMs that are associated with lung-specific diseases. Several datasets from public microarray repositories describing pulmonary diseases in mouse models following exposure to a variety of substances were examined and functionally related biclusters of genes showing similar expression profiles were identified. The identified biclusters were then used to conduct a gene set enrichment analysis on pulmonary gene expression profiles derived from mice exposed to nano-titanium dioxide (nano-TiO2), carbon black (CB) or carbon nanotubes (CNTs) to determine the disease significance of these data-driven gene sets. Results: Biclusters representing inflammation (chemokine activity), DNA binding, cell cycle, apoptosis, reactive oxygen species (ROS) and fibrosis processes were identified. All of the NM studies were significant with respect to the bicluster related to chemokine activity (DAVID; FDR p-value = 0.032). The bicluster related to pulmonary fibrosis was enriched in studies where toxicity induced by CNT and CB studies was investigated, suggesting the potential for these materials to induce lung fibrosis. The pro-fibrogenic potential of CNTs is well established. Although CB has not been shown to induce fibrosis, it induces stronger inflammatory, oxidative stress and DNA damage responses than nano-TiO2 particles. Conclusion: The results of the analysis correctly identified all NMs to be inflammogenic and only CB and CNTs as potentially fibrogenic. In addition to identifying several previously defined, functionally relevant gene sets, the present study also identified two novel genes sets: a gene set associated with pulmonary fibrosis and a gene set associated with ROS, underlining the advantage of using a data-driven approach to identify novel, functionally related gene sets. The results can be used in future gene set enrichment analysis studies involving NMs or as features for clustering and classifying NMs of diverse properties.

scholarly journals modEnrichr: a suite of gene set enrichment analysis tools for model organisms

2019 ◽  
Vol 47 (W1) ◽  
pp. W183-W190 ◽  
Author(s):  
Maxim V Kuleshov ◽  
Jennifer E L Diaz ◽  
Zachary N Flamholz ◽  
Alexandra B Keenan ◽  
Alexander Lachmann ◽  
...  
Keyword(s):  
Data Integration ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Protein Domain ◽  
Model Organisms ◽  
Gene Set Enrichment ◽  
Gene Set ◽  
Analysis Tools ◽  
Gene Sets

Abstract High-throughput experiments produce increasingly large datasets that are difficult to analyze and integrate. While most data integration approaches focus on aligning metadata, data integration can be achieved by abstracting experimental results into gene sets. Such gene sets can be made available for reuse through gene set enrichment analysis tools such as Enrichr. Enrichr currently only supports gene sets compiled from human and mouse, limiting accessibility for investigators that study other model organisms. modEnrichr is an expansion of Enrichr for four model organisms: fish, fly, worm and yeast. The gene set libraries within FishEnrichr, FlyEnrichr, WormEnrichr and YeastEnrichr are created from the Gene Ontology, mRNA expression profiles, GeneRIF, pathway databases, protein domain databases and other organism-specific resources. Additionally, libraries were created by predicting gene function from RNA-seq co-expression data processed uniformly from the gene expression omnibus for each organism. The modEnrichr suite of tools provides the ability to convert gene lists across species using an ortholog conversion tool that automatically detects the species. For complex analyses, modEnrichr provides API access that enables submitting batch queries. In summary, modEnrichr leverages existing model organism databases and other resources to facilitate comprehensive hypothesis generation through data integration.

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