GPR143 is a Prognostic Biomarker Associated with Immune Infiltration in Melanoma

Abstract Background: Skin cutaneous melanoma (SKCM) is considered one of the most aggressive and lethal cancers of the skin. G-protein coupled receptor 143 (GPR143), which has been reported to cause congenital nystagmus, belongs to the superfamily of G protein-coupled receptors. Methods and Results: We analyzed the expression of GPR143 and survival of SKCM patients in SKCM via Gene Expression Profiling Interactive Analysis (GEPIA). Then, logistic regression and multivariate cox analysis was used to analyze the influence of GPR143 expression on clinicopathological elements and survival. We explored the immune response of 22 TIICs in SKCM via CIBERSORT and used TIMER to assess the correlation of GPR143 expression and immune infiltration level. Finally, we used gene set enrichment analysis (GSEA) to assess the TCGA dataset. The outcomes suggest that GPR143 expression in tumor samples is remarkedly higher than in normal samples and high GPR143 expression is associated with poorer prognosis. The result of multivariate analysis indicated that increased GPR143 expression is an independent prognostic factor for prognosis. We found GPR143 expression level has prominent negative correlations with infiltrating levels of B cell, CD8+ T cells, etc. GSEA indicated that pigment metabolic process, pigment biosynthetic process and other pathways were identified as differentially enriched pathways in Gene Ontology (GO). Oxidative phosphorylation, Parkinson’s disease and other pathways were showed significantly differential enrichment in GPR143 high expression phenotype in Kyoto Encyclopedia of Genes and Genomes (KEGG).Conclusions: In conclusion, GPR143 may be a novel prognostic biomarker and associated with immune infiltrates in SKCM.

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The G Protein-Coupled Estrogen Receptor (GPER) Expression Correlates with Pro-Metastatic Pathways in ER-Negative Breast Cancer: A Bioinformatics Analysis

Cells ◽

10.3390/cells9030622 ◽

2020 ◽

Vol 9 (3) ◽

pp. 622 ◽

Cited By ~ 4

Author(s):

Marianna Talia ◽

Ernestina De Francesco ◽

Damiano Rigiracciolo ◽

Maria Muoio ◽

Lucia Muglia ◽

...

Keyword(s):

Breast Cancer ◽

Estrogen Receptor ◽

Signaling Pathways ◽

G Protein ◽

Bioinformatics Analysis ◽

Enrichment Analysis ◽

R Package ◽

Gene Set Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

G Protein Coupled

The G protein-coupled estrogen receptor (GPER, formerly known as GPR30) is a seven-transmembrane receptor that mediates estrogen signals in both normal and malignant cells. In particular, GPER has been involved in the activation of diverse signaling pathways toward transcriptional and biological responses that characterize the progression of breast cancer (BC). In this context, a correlation between GPER expression and worse clinical-pathological features of BC has been suggested, although controversial data have also been reported. In order to better assess the biological significance of GPER in the aggressive estrogen receptor (ER)-negative BC, we performed a bioinformatics analysis using the information provided by The Invasive Breast Cancer Cohort of The Cancer Genome Atlas (TCGA) project and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) datasets. Gene expression correlation and the statistical analysis were carried out with R studio base functions and the tidyverse package. Pathway enrichment analysis was evaluated with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway on the Database for Annotation, Visualization and Integrated Discovery (DAVID) website, whereas gene set enrichment analysis (GSEA) was performed with the R package phenoTest. The survival analysis was determined with the R package survivALL. Analyzing the expression data of more than 2500 primary BC, we ascertained that GPER levels are associated with pro-migratory and metastatic genes belonging to cell adhesion molecules (CAMs), extracellular matrix (ECM)-receptor interaction, and focal adhesion (FA) signaling pathways. Thereafter, evaluating the disease-free interval (DFI) in ER-negative BC patients, we found that the subjects expressing high GPER levels exhibited a shorter DFI in respect to those exhibiting low GPER levels. Overall, our results may pave the way to further dissect the network triggered by GPER in the breast malignancies lacking ER toward a better assessment of its prognostic significance and the action elicited in mediating the aggressive features of the aforementioned BC subtype.

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NPM1 Is a Prognostic Biomarker Involved in Immune Infiltration of Lung Adenocarcinoma and Associated With m6A Modification and Glycolysis

Frontiers in Immunology ◽

10.3389/fimmu.2021.724741 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xu-Sheng Liu ◽

Lu-Meng Zhou ◽

Ling-Ling Yuan ◽

Yan Gao ◽

Xue-Yan Kui ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Prognostic Biomarker ◽

Aerobic Glycolysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Expression Level ◽

Data Sets ◽

Translational Initiation ◽

Immune Infiltration ◽

The Relationship

BackgroundOverexpression of NPM1 can promote the growth and proliferation of various tumor cells. However, there are few studies on the comprehensive analysis of NPM1 in lung adenocarcinoma (LUAD).MethodsTCGA and GEO data sets were used to analyze the expression of NPM1 in LUAD and clinicopathological analysis. The GO/KEGG enrichment analysis of NPM1 co-expression and gene set enrichment analysis (GSEA) were performed using R software package. The relationship between NPM1 expression and LUAD immune infiltration was analyzed using TIMER, GEPIA database and TCGA data sets, and the relationship between NPM1 expression level and LUAD m6A modification and glycolysis was analyzed using TCGA and GEO data sets.ResultsNPM1 was overexpressed in a variety of tumors including LUAD, and the ROC curve showed that NPM1 had a certain accuracy in predicting the outcome of tumors and normal samples. The expression level of NPM1 in LUAD is significantly related to tumor stage and prognosis. The GO/KEGG enrichment analysis indicated that NPM1 was closely related to translational initiation, ribosome, structural constituent of ribosome, ribosome, Parkinson disease, and RNA transport. GSEA showed that the main enrichment pathway of NPM1-related differential genes was mainly related to mTORC1 mediated signaling, p53 hypoxia pathway, signaling by EGFR in cancer, antigen activates B cell receptor BCR leading to generation of second messengers, aerobic glycolysis and methylation pathways. The analysis of TIMER, GEPIA database and TCGA data sets showed that the expression level of NPM1 was negatively correlated with B cells and NK cells. The TCGA and GEO data sets analysis indicated that the NPM1 expression was significantly correlated with one m6A modifier related gene (YTHDF2) and five glycolysis related genes (ENO1, HK2, LDHA, LDHB and SLC2A1).ConclusionNPM1 is a prognostic biomarker involved in immune infiltration of LUAD and associated with m6A modification and glycolysis. NPM1 can be used as an effective target for diagnosis and treatment of LUAD.

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GPER1 Silencing Suppresses the Proliferation, Migration, and Invasion of Gastric Cancer Cells by Inhibiting PI3K/AKT–Mediated EMT

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2020.591239 ◽

2020 ◽

Vol 8 ◽

Author(s):

En Xu ◽

Xuefeng Xia ◽

Chaoyu Jiang ◽

Zijian Li ◽

Zhi Yang ◽

...

Keyword(s):

Gastric Cancer ◽

Estrogen Receptor ◽

Cancer Cells ◽

G Protein ◽

Cancer Metastasis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Migration And Invasion ◽

Gastric Cancer Cells ◽

G Protein Coupled

G protein coupled estrogen receptor (GPER1) is a membrane estrogen receptor, belonging to the seven-transmembrane G protein-coupled receptors family, and has important biological functions in cancer. However, the functional role of GPER1 in gastric cancer (GC) remain incompletely understood. In the present study, we employed gene set enrichment analysis and discovered that GPER1 expression was concomitant with EMT process and was positively correlated with activation of the PI3K/AKT pathway in GC. Knockdown of GPER1 with siRNA suppressed the proliferation, migration, and invasion of AGS and MGC-803 GC cells. Knockdown of GPER1 also downregulated the mesenchymal markers N-cadherin and vimentin, upregulated E-cadherin, an epithelial marker, and suppressed expression of the Snail, Slug and Twist1 transcription factors, indicating that knockdown of GPER1 inhibited EMT. Moreover, 740Y-P, a PI3K activator, reversed the effects of GPER1 knockdown on EMT processes. Overexpression of GPER1 with plasmid can further prove these findings. In summary, these data demonstrate that GPER1 inhibition suppresses the proliferation, migration, and invasion of gastric cancer cells by inhibiting PI3K/AKT-mediated EMT. Our study elucidated the function of GPER1 in gastric cancer, and we identified PI3K/AKT-mediated EMT as a novel mechanism by which GPER1 contributes to proliferation, migration, and invasion of gastric cancer. These data suggest that combining inhibition of GPER1 and PI3K may be a potential therapeutic approach to inhibit gastric cancer metastasis.

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Screening and Identification of Four Prognostic Genes Related to Immune Infiltration and G-Protein Coupled Receptors Pathway in Lung Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2020.622251 ◽

2021 ◽

Vol 10 ◽

Author(s):

Yan Wang ◽

Liwei Qiu ◽

Yu Chen ◽

Xia Zhang ◽

Peng Yang ◽

...

Keyword(s):

Survival Rate ◽

Lung Adenocarcinoma ◽

G Protein ◽

Risk Score ◽

G Protein Coupled Receptors ◽

Gene Set Enrichment Analysis ◽

Ppi Network ◽

Immune Infiltration ◽

Key Genes ◽

G Protein Coupled

BackgroundLung adenocarcinoma (LUAD) is a common malignant tumor with the highest morbidity and mortality worldwide. The degree of tumor immune infiltration and clinical prognosis depend on immune-related genes, but their interaction with the tumor immune microenvironment, the specific mechanism driving immune infiltration and their prognostic value are still not very clear. Therefore, the aim of this work was focused on the elucidation of these unclear aspects.MethodsTCGA LUAD samples were divided into three immune infiltration subtypes according to the single sample gene set enrichment analysis (ssGSEA), in which the associated gene modules and hub genes were screened by weighted correlation network analysis (WGCNA). Four key genes related to immune infiltration were found and screened by differential expression analysis, univariate prognostic analysis, and Lasso-COX regression, and their PPI network was constructed. Finally, a Nomogram model based on the four genes and tumor stages was constructed and confirmed in two GEO data sets.ResultsAmong the three subtypes—high, medium, and low immune infiltration subtype—the survival rate of the patients in the high one was higher than the rate in the other two subtypes. The four key genes related to LUAD immune infiltration subtypes were CD69, KLRB1, PLCB2, and P2RY13. The PPI network revealed that the downstream genes of the G-protein coupled receptors (GPCRs) pathway were activated by these four genes through the S1PR1. The risk score signature based on these four genes could distinguish high and low-risk LUAD patients with different prognosis. The Nomogram constructed by risk score and clinical tumor stage showed a good ability to predict the survival rate of LUAD patients. The universality and robustness of the Nomogram was confirmed by two GEO datasets.ConclusionsThe prognosis of LUAD patients could be predicted by the constructed risk score signature based on the four genes, making this score a potential independent biomarker. The screening, identification, and analysis of these four genes could contribute to the understanding of GPCRs and LUAD immune infiltration, thus guiding the formulation of more effective immunotherapeutic strategies.

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Comprehensive Analysis of the Tumor Microenvironment and Ferroptosis-Related Genes Predict Prognosis with Ovarian Cancer

Frontiers in Genetics ◽

10.3389/fgene.2021.774400 ◽

2021 ◽

Vol 12 ◽

Author(s):

Xiao-xue Li ◽

Li Xiong ◽

Yu Wen ◽

Zi-jian Zhang

Keyword(s):

Ovarian Cancer ◽

Cox Regression ◽

Enrichment Analysis ◽

Roc Curves ◽

Gene Set Enrichment Analysis ◽

Drug Resistant ◽

Cox Regression Analysis ◽

Gene Set ◽

Immune Infiltration ◽

Tcga Dataset

The early diagnosis of ovarian cancer (OC) is critical to improve the prognosis and prevent recurrence of patients. Nevertheless, there is still a lack of factors which can accurately predict it. In this study, we focused on the interaction of immune infiltration and ferroptosis and selected the ESTIMATE algorithm and 15 ferroptosis-related genes (FRGs) to construct a novel E-FRG scoring model for predicting overall survival of OC patients. The gene expression and corresponding clinical characteristics were obtained from the TCGA dataset (n = 375), GSE18520 (n = 53), and GSE32062 (n = 260). A total of 15 FRGs derived from FerrDb with the immune score and stromal score were identified in the prognostic model by using least absolute shrinkage and selection operator (LASSO)–penalized COX regression analysis. The Kaplan–Meier survival analysis and time-dependent ROC curves performed a powerful prognostic ability of the E-FRG model via multi-validation. Gene Set Enrichment Analysis and Gene Set Variation Analysis elucidate multiple potential pathways between the high and low E-FRG score group. Finally, the proteins of different genes in the model were verified in drug-resistant and non–drug-resistant tumor tissues. The results of this research provide new prospects in the role of immune infiltration and ferroptosis as a helpful tool to predict the outcome of OC patients.

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Analysis of Ferroptosis-Mediated Modification Patterns and Tumor Immune Microenvironment Characterization in Uveal Melanoma

Frontiers in Cell and Developmental Biology ◽

10.3389/fcell.2021.685120 ◽

2021 ◽

Vol 9 ◽

Author(s):

Yi Jin ◽

Zhanwang Wang ◽

Dong He ◽

Yuxing Zhu ◽

Lian Gong ◽

...

Keyword(s):

Uveal Melanoma ◽

Enrichment Analysis ◽

Progression Free Survival ◽

Gene Set Enrichment Analysis ◽

Consensus Clustering ◽

Training Set ◽

Poor Overall Survival ◽

Competing Endogenous Rna Network ◽

Underlying Mechanisms ◽

Cox Analysis

Uveal melanoma (UVM) is an intraocular malignancy in adults in which approximately 50% of patients develop metastatic disease and have a poor prognosis. The need for immunotherapies has rapidly emerged, and recent research has yielded impressive results. Emerging evidence has implicated ferroptosis as a novel type of cell death that may mediate tumor-infiltrating immune cells to influence anticancer immunity. In this study, we first selected 11 ferroptosis regulators in UVM samples from the training set (TCGA and GSE84976 databases) by Cox analysis. We then divided these molecules into modules A and B based on the STRING database and used consensus clustering analysis to classify genes in both modules. According to the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA), the results revealed that the clusters in module A were remarkably related to immune-related pathways. Next, we applied the ESTIMATE and CIBERSORT algorithms and found that these ferroptosis-related patterns may affect a proportion of TME infiltrating cells, thereby mediating the tumor immune environment. Additionally, to further develop the prognostic signatures based on the immune landscape, we established a six-gene-regulator prognostic model in the training set and successfully verified it in the validation set (GSE44295 and GSE27831). Subsequently, we identified the key molecules, including ABCC1, CHAC1, and GSS, which were associated with poor overall survival, progression-free survival, disease-specific survival, and progression-free interval. We constructed a competing endogenous RNA network to further elucidate the mechanisms, which consisted of 29 lncRNAs, 12 miRNAs, and 25 ferroptosis-related mRNAs. Our findings indicate that the ferroptosis-related genes may be suitable potential biomarkers to provide novel insights into UVM prognosis and decipher the underlying mechanisms in tumor microenvironment characterization.

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Prognostic and immunological value of LTB4R in pan-cancer

Mathematical Biosciences and Engineering ◽

10.3934/mbe.2021459 ◽

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>LTB4 receptor 1 (LTB4R), as the high affinity leukotriene B4 receptor, is rapidly revealing its function in malignancies. However, it is still uncertain. </sec> <sec><title>Methods</title>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. </sec> <sec><title>Results</title>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. </sec> <sec><title>Conclusion</title>The LTB4R is associated with immune infiltrates and can be used as a prognostic biomarker in pan-cancer. </sec> </abstract>

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Identification and Validation of Immune-Related LncRNA Prognostic Signature for Lung Adenocarcinoma

Frontiers in Genetics ◽

10.3389/fgene.2021.681277 ◽

2021 ◽

Vol 12 ◽

Author(s):

Guomin Wu ◽

Qihao Wang ◽

Ting Zhu ◽

Linhai Fu ◽

Zhupeng Li ◽

...

Keyword(s):

Regression Analysis ◽

Lung Adenocarcinoma ◽

Clinical Features ◽

Cox Regression ◽

Differential Expression Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Prognostic Signature ◽

Cox Regression Analysis ◽

Immune Infiltration

This study aimed to establish a prognostic risk model for lung adenocarcinoma (LUAD). We firstly divided 535 LUAD samples in TCGA-LUAD into high-, medium-, and low-immune infiltration groups by consensus clustering analysis according to immunological competence assessment by single-sample gene set enrichment analysis (ssGSEA). Profile of long non-coding RNAs (lncRNAs) in normal samples and LUAD samples in TCGA was used for a differential expression analysis in the high- and low-immune infiltration groups. A total of 1,570 immune-related differential lncRNAs in LUAD were obtained by intersecting the above results. Afterward, univariate COX regression analysis and multivariate stepwise COX regression analysis were conducted to screen prognosis-related lncRNAs, and an eight-immune-related-lncRNA prognostic signature was finally acquired (AL365181.2, AC012213.4, DRAIC, MRGPRG-AS1, AP002478.1, AC092168.2, FAM30A, and LINC02412). Kaplan–Meier analysis and ROC analysis indicated that the eight-lncRNA-based model was accurate to predict the prognosis of LUAD patients. Simultaneously, univariate COX regression analysis and multivariate COX regression analysis were undertaken on clinical features and risk scores. It was illustrated that the risk score was a prognostic factor independent from clinical features. Moreover, immune data of LUAD in the TIMER database were analyzed. The eight-immune-related-lncRNA prognostic signature was related to the infiltration of B cells, CD4+ T cells, and dendritic cells. GSEA enrichment analysis revealed significant differences in high- and low-risk groups in pathways like pentose phosphate pathway, ubiquitin mediated proteolysis, and P53 signaling pathway. This study helps to treat LUAD patients and explore molecules related to LUAD immune infiltration to deeply understand the specific mechanism.

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Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

BMC Medical Genomics ◽

10.1186/s12920-021-00991-2 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Yang Shen ◽

Li-rong Xu ◽

Xiao Tang ◽

Chang-po Lin ◽

Dong Yan ◽

...

Keyword(s):

Immune Cells ◽

Plasma Cells ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Gamma Delta ◽

Hub Genes ◽

Gene Set Enrichment ◽

Bioinformatics Analyses ◽

Immune Infiltration ◽

Atheromatous Plaques

Abstract Background Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis. Methods Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927. Results Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques. Conclusions Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

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

Journal of Clinical Medicine ◽

10.3390/jcm9092844 ◽

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.

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