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

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.

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DPYSL2 as potential diagnostic and prognostic biomarker linked to immune infiltration in lung adenocarcinoma

World Journal of Surgical Oncology ◽

10.1186/s12957-021-02379-z ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Yang-Jie Wu ◽

Ai-Tao Nai ◽

Gui-Cheng He ◽

Fei Xiao ◽

Zhi-Min Li ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Roc Curve ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

List Type ◽

Gene Set Enrichment ◽

Gene Set ◽

Normal Tissues ◽

Kaplan Meier ◽

Kaplan Meier Plotter

Abstract Background Dihydropyrimidinase like 2 (DPYSL2) has been linked to tumor metastasis. However, the function of DPSY2L in lung adenocarcinoma (LUAD) is yet to be explored. Methods Herein, we assessed DPYSL2 expression in various tumor types via online databases such as Oncomine and Tumor Immune Estimation Resource (TIMER). Further, we verified the low protein and mRNA expressions of DPYSL2 in LUAD via the ULCAN, The TCGA and GEPIA databases. We applied the ROC curve to examine the role of DPYSL2 in diagnosis. The prognostic significance of DPYSL2 was established through the Kaplan–Meier plotter and the Cox analyses (univariate and multivariate). TIMER was used to explore DPYSL2 expression and its connection to immune infiltrated cells. Through Gene Set Enrichment Analysis, the possible mechanism of DPYSL2 in LUAD was investigated. Results In this study, database analysis revealed lower DPYSL2 expression in LUAD than in normal tissues. The ROC curve suggested that expression of DPYSL2 had high diagnostic efficiency in LUAD. The DPYSL2 expression had an association with the survival time of LUAD patients in the Kaplan–Meier plotter and the Cox analyses. The results from TIMER depicted a markedly positive correlation of DPYSL2 expression with immune cells infiltrated in LUAD, such as macrophages, dendritic cells, CD4+ T cells, and neutrophils. Additionally, many gene markers for the immune system had similar positive correlations in the TIMER analysis. In Gene Set Enrichment Analysis, six immune-related signaling pathways were associated with DPYSL2. Conclusions In summary, DPYSL2 is a novel biomarker with diagnostic and prognostic potential for LUAD as well as an immunotherapy target. Highlights Expression of DPYSL2 was considerably lower in LUAD than in normal tissues. Investigation of multiple databases showed a high diagnostic value of DPYSL2 in LUAD. DPYSL2 can independently predict the LUAD outcomes. Immune-related mechanisms may be potential ways for DPYSL2 to play a role in LUAD.

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Increased Expression of LYNX1 in Ovarian Serous Cystadenocarcinoma Predicts Poor Prognosis

BioMed Research International ◽

10.1155/2020/1392674 ◽

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.

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

10.21203/rs.3.rs-95044/v1 ◽

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.

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

Journal of Ovarian Research ◽

10.1186/s13048-021-00821-0 ◽

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.

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Prognostic Relevance of BRCA1 Expression in Survival of Patients With Cervical Cancer

Frontiers in Oncology ◽

10.3389/fonc.2021.770103 ◽

2021 ◽

Vol 11 ◽

Author(s):

E Sun Paik ◽

Chi-Son Chang ◽

Ye Lin Chae ◽

So Young Oh ◽

Sun-Ju Byeon ◽

...

Keyword(s):

Cervical Cancer ◽

Overall Survival ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Differentially Expressed ◽

Brca1 Expression ◽

Gene Set Enrichment ◽

Cox Regression Analysis ◽

Gene Set ◽

Prognostic Relevance

ObjectiveBRCA1 expression can be lost by a variety of mechanisms including germline or somatic mutation and promotor hypermethylation. Given the potential importance of BRCA1 loss as a predictive and prognostic biomarker in several cancers, the objective of this study was to investigate BRCA1 expression using immunohistochemistry (IHC) in cervical cancer and its possible prognostic relevance.MethodsSeventy patients with cervical cancer were enrolled in this study. Samples from each tumor were stained for BRCA1 and reviewed independently by gynecologic pathologists blinded to the BRCA status. Kaplan–Meier methods were used to estimate overall survival according to BRCA1 expression. Differentially expressed genes (DEGs) by BRCA1 expression were selected using GSE44001 dataset, which included 300 samples treated with radical hysterectomy. In addition, cox regression analysis with backward elimination was performed to select independent prognostic markers. Gene set enrichment analysis (GSEA) was done using these DEGs.ResultsBRCA1 IHC was positive in 62.9% (44/70) of cases. Patients with BRCA1 expression showed better overall survival (100% vs. 76.2%, HR 0.20, 95% CI 0.04 – 0.99, p = 0.028) than those without BRCA1 expression. Analysis of gene expression profiles according to BRCA1 expression identified 321 differentially expressed mRNAs. Gene set enrichment analysis results showed two dysregulated pathways (VEGF_A_UP.V1_DN and E2F1_UP.V1_UP). Of these DEGs, alterations of 20 gene signatures were found to be independently associated with survival outcomes of patients.ConclusionsBRCA1 expression in cervical cancer tissue is associated with survival. In addition, the identification of specific gene alterations associated with BRCA1 expression could help to provide individualized prediction in these patients.

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Higher Acid-Base Imbalance Associated with Respiratory Failure Could Decrease the Survival of Patients with Scrub Typhus during Intensive Care Unit Stay: A Gene Set Enrichment Analysis

Journal of Clinical Medicine ◽

10.3390/jcm8101580 ◽

2019 ◽

Vol 8 (10) ◽

pp. 1580 ◽

Cited By ~ 1

Author(s):

Kyoung Min Moon ◽

Kyueng-Whan Min ◽

Mi-Hye Kim ◽

Dong-Hoon Kim ◽

Byoung Kwan Son ◽

...

Keyword(s):

Intensive Care Unit ◽

Intensive Care ◽

Respiratory Failure ◽

Scrub Typhus ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Acid Base ◽

Gene Set Enrichment ◽

Gene Set ◽

Gene Sets

Ninety percent of patients with scrub typhus (SC) with vasculitis-like syndrome recover after mild symptoms; however, 10% can suffer serious complications, such as acute respiratory failure (ARF) and admission to the intensive care unit (ICU). Predictors for the progression of SC have not yet been established, and conventional scoring systems for ICU patients are insufficient to predict severity. We aimed to identify simple and robust indicators to predict aggressive behaviors of SC. We evaluated 91 patients with SC and 81 non-SC patients who were admitted to the ICU, and 32 cases from the public functional genomics data repository for gene expression analysis. We analyzed the relationships between several predictors and clinicopathological characteristics in patients with SC. We performed gene set enrichment analysis (GSEA) to identify SC-specific gene sets. The acid-base imbalance (ABI), measured 24 h before serious complications, was higher in patients with SC than in non-SC patients. A high ABI was associated with an increased incidence of ARF, leading to mechanical ventilation and worse survival. GSEA revealed that SC correlated to gene sets reflecting inflammation/apoptotic response and airway inflammation. ABI can be used to indicate ARF in patients with SC and assist with early detection.

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Drug perturbation gene set enrichment analysis (dpGSEA): a new transcriptomic drug screening approach

BMC Bioinformatics ◽

10.1186/s12859-020-03929-0 ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Mike Fang ◽

Brian Richardson ◽

Cheryl M. Cameron ◽

Jean-Eudes Dazard ◽

Mark J. Cameron

Keyword(s):

Drug Targets ◽

T Regulatory Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Regulatory Cells ◽

Gene Set Enrichment ◽

Gene Set ◽

Gene Sets ◽

Gastroenteropancreatic Neuroendocrine Tumor ◽

Public Datasets

Abstract Background In this study, we demonstrate that our modified Gene Set Enrichment Analysis (GSEA) method, drug perturbation GSEA (dpGSEA), can detect phenotypically relevant drug targets through a unique transcriptomic enrichment that emphasizes biological directionality of drug-derived gene sets. Results We detail our dpGSEA method and show its effectiveness in detecting specific perturbation of drugs in independent public datasets by confirming fluvastatin, paclitaxel, and rosiglitazone perturbation in gastroenteropancreatic neuroendocrine tumor cells. In drug discovery experiments, we found that dpGSEA was able to detect phenotypically relevant drug targets in previously published differentially expressed genes of CD4+T regulatory cells from immune responders and non-responders to antiviral therapy in HIV-infected individuals, such as those involved with virion replication, cell cycle dysfunction, and mitochondrial dysfunction. dpGSEA is publicly available at https://github.com/sxf296/drug_targeting. Conclusions dpGSEA is an approach that uniquely enriches on drug-defined gene sets while considering directionality of gene modulation. We recommend dpGSEA as an exploratory tool to screen for possible drug targeting molecules.

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Transmembrane p24 Trafficking Protein 2 Regulates Inflammation Through the TLR4/NF-κB Signaling Pathway in Lung Adenocarcinoma

10.21203/rs.3.rs-794174/v1 ◽

2021 ◽

Author(s):

Longhua Feng ◽

Pengjiang Cheng ◽

Zhengyun Feng ◽

Xiaoyu Zhang

Keyword(s):

Lung Adenocarcinoma ◽

Signaling Pathway ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Inflammatory Factors ◽

Normal Tissues ◽

Kaplan Meier ◽

New Strategy

Abstract Background: To investigate the role of transmembrane p24 trafficking protein 2 (TMED2) in lung adenocarcinoma (LUAD) and determine whether TMED2 knockdown could inhibit LUAD in vitro and in vivo.Methods: TIMER2.0, Kaplan-Meier plotter, gene set enrichment analysis (GSEA), Target Gene, and pan-cancer systems were used to predict the potential function of TMED2. Western blotting and immunohistochemistry were performed to analyze TMED2 expression in different tissues or cell lines. The proliferation, development, and apoptosis of LUAD were observed using a lentivirus-mediated TMED2 knockdown. Bioinformatics and western blot analysis of TMED2 against inflammation via the TLR4/NF-κB signaling pathway were conducted. Results: TMED2 expression in LUAD tumor tissues was higher than that in normal tissues and positively correlated with poor survival in lung cancer and negatively correlated with apoptosis in LUAD. The expression of TMED2 was higher in tumors or HCC827 cells. TMED2 knockdown inhibited LUAD development in vitro and in vivo and increased the levels of inflammatory factors via the TLR4/NF-κB signaling pathway. TMED2 was correlated with TME, immune score, TME-associated immune cells, their target markers, and some mechanisms and pathways, as determined using the TIMER2.0, GO, and KEGG assays.Conclusions: TMED2 may regulate inflammation in LUAD through the TLR4/NF-κB signaling pathway, and enhance the proliferation, development, and prognosis of LUAD by regulating inflammation, which provide a new strategy for treating LUAD by regulating inflammation.

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