Dataset Information

Clinical and Expression Significance of AKT1 by Co-expression Network Analysis in Endometrial Cancer.

ABSTRACT: Introduction: Endometrial cancer is one of the most common uterine cancers worldwide. AKT is reported to regulate progesterone receptor B dependent transcription and angiogenesis in endometrial cancer. However, the potential mechanisms of AKT in the tumor progression of endometrial cancer remain unclear. Methods: We used GSE72708 with gene expression profiles of AKT regulation from the GEO database. We performed GSEA analysis to explore pathway enrichments. We found that most upregulated enriched pathways in siAKT group were associated with acid metabolism and immune network. Endometrial cancer and various signaling pathways were downregulated enriched. Moreover, different molecular mechanism of regulation between progestin (R5020) and AKT was identified, which were related to VEGF signaling pathway. The hub genes were evaluated by immunohistochemical staining of endometrial cancer tissues. Results: We screened out a total of 623 differentially expressed genes among different groups. According to weighted gene co-expression network analysis (WGCNA) method, four distinct modules were identified. We found brown module showed a very high positive correlation with siAKT group and a very high negative correlation with R5020 group. A total of six hub genes including PBK, BIRC5, AURKA, GTSE1, KNSTRN, and PSMB10 were finally identified associated with AKT1. In addition, the data also shows that the higher expression of AKT1, GTSE1, BIRC5, AURKA, and KNSTRN is significantly associate with poor prognosis of endometrial cancer. Conclusion: Our study identified six hub genes related to the prognosis of endometrial cancer, which may provide new insights into the underlying biological mechanisms driving the tumorigenesis of endometrial cancer, especially in AKT1 regulation.

SUBMITTER: Huo X

PROVIDER: S-EPMC6852383 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Clinical and Expression Significance of AKT1 by Co-expression Network Analysis in Endometrial Cancer.

Huo Xiao X Sun Hengzi H Liu Qian Q Ma Xiangwen X Peng Peng P Yu Mei M Zhang Ying Y Cao Dongyan D Shen Keng K

Frontiers in oncology 20191106

<b>Introduction:</b> Endometrial cancer is one of the most common uterine cancers worldwide. AKT is reported to regulate progesterone receptor B dependent transcription and angiogenesis in endometrial cancer. However, the potential mechanisms of AKT in the tumor progression of endometrial cancer remain unclear. <b>Methods:</b> We used GSE72708 with gene expression profiles of AKT regulation from the GEO database. We performed GSEA analysis to explore pathway enrichments. We found that most upreg ...[more]

PMID: 31781484

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Project description:PurposeTo identify key pathogenic genes and reveal the potential molecular mechanisms of endometrial cancer (EC) using bioinformatics analysis and immunohistochemistry validation.Materials and methodsThrough weighted gene co-expression network analysis (WGCNA), a co-expression network was constructed based on the top 25% variant genes in the GSE50830 dataset downloaded from gene expression omnibus (GEO). GO and KEGG pathway enrichment analyses were performed using the DAVID online tool. Candidate genes were selected using the cytoHubba plug-in of Cytoscape, mRNA expression levels and prognostic values in EC were analyzed by Oncomine, GEPIA, and Kaplan-Meier Plotter database to determine hub genes. One hub gene was validated by immunohistochemical (IHC) staining of 116 paraffin-embedded endometrial tissues and TCGA-UCEC cohort. Genes co-expressed with this hub gene were identified by LinkedOmics. Finally, its correlation with immune infiltration was evaluated by TIMER.ResultsThree co-expression modules and five candidate genes in each module were obtained by WGCNA; four hub genes were identified (LGR5, SST, ZNF558, and PTGDS). The mRNA levels of LGR5 and SST were significantly upregulated in EC, whereas those of ZNF558 and PTGDS were significantly downregulated; the expression of all four genes was associated with EC prognosis. Further validation demonstrated that PTGDS was significantly downregulated in the EC group compared with the atypical hyperplasia and normal endometrial groups, and its low expression was an independent risk factor for worse prognosis of EC. Biological function analysis indicated that PTGDS might be involved in the adaptive immune response, leukocyte migration, as well as in the regulation of cell adhesion molecules and chemokine signaling. Additionally, PTGDS expression was positively correlated with immune infiltration status of B cells, CD4+ T cells and macrophages.ConclusionLGR5, SST, ZNF558, and PTGDS may participate in the development, progression, and prognosis of EC, in which PTGDS may be a novel biomarker and therapeutic target for EC.

Project description:The incidence of endometrial cancer (EC) is intensively increasing. However, due to the complexity and heterogeneity of EC, the molecular targeted therapy is still limited. The reliable and accurate biomarkers for tumor progression are urgently demanded. After normalizing the data from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA), we utilized limma and WGCNA packages to identify differentially expressed genes (DEGs). The copy number variations of candidate genes were investigated by cBioPortal. Enrichment pathways analysis was performed by ClueGO and CluePedia. The methylation status was explored by UALCAN. ROC curve and survival analysis were conducted by SPSS and Kaplan-Meier. Infiltration immune cells in microenvironment were analyzed by TISIDB. Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) were applied to explore potential biological pathways. Immunohistochemistry staining (IHC), cell proliferation, cell apoptosis, colony formation, migration, invasion and scratch-wound assays were performed to investigate the function of key genes in vitro. In this study, four expression profile datasets were integrated to identify candidate genes. Combined with WGCNA analysis, the top ten candidates were screened out, whose abnormal methylation patterns were extremely correlated with their expression level and they were associated with tumor grades and predicted poor survival. GSEA and GSVA demonstrated they were involved in DNA replication and cell cycle transition in EC. Gene silencing of TICRR and PPIF dramatically inhibited cell growth, migration and epithelial-mesenchymal transition (EMT) and enhanced progesterone sensitivity. Additionally, from DrugBank database, cyclosporine may be effective for PPIF targeted therapy. By integrative bioinformatics analysis and in vitro experiments, our study shed novel light on the molecular mechanisms of EC. TICRR and PPIF may promise to be potential therapeutic targets for endometrial cancer.

Project description:In patients with head and neck cancer (HNC), lymph node (N) metastases are associated with cancer aggressiveness and poor prognosis. Identifying meaningful gene modules and representative biomarkers relevant to the N stage helps predict prognosis and reveal mechanisms underlying tumor progression. The present study used a step?wise approach for weighted gene co?expression network analysis (WGCNA). Dataset GSE65858 was subjected to WGCNA. RNA sequencing data of HNC downloaded from the Cancer Genome Atlas (TCGA) and dataset GSE39366 were utilized to validate the results. Following data preprocessing, 4,295 genes were screened, and blue and black modules associated with the N stage of HNC were identified. A total of 16 genes [keratinocyte differentiation associated protein, suprabasin, cornifelin (CNFN), small proline rich protein 1B, desmoglein 1 (DSG1), chromosome 10 open reading frame 99, keratin 16 pseudogene 3, gap junction protein ?2, dermokine, LY6/PLAUR domain containing 3, transmembrane protein 79, phospholipase A2 group IVE, transglutaminase 5, potassium two pore domain channel subfamily K member 6, involucrin, kallikrein related peptidase 8] that had a negative association with the N?stage in the blue module, and two genes (structural maintenance of chromosomes 4 and mutS homolog 6) that had a positive association in the black module, were identified to be candidate hub genes. Following further validation in TCGA and dataset GSE65858, it was identified that CNFN and DSG1 were associated with the clinical stage of HNC. Survival analysis of CNFN and DSG1 was subsequently performed. Patients with increased expression of CNFN displayed better survival probability in dataset GSE65858 and TCGA. Therefore, CNFN was selected as the hub gene for further verification in the Gene Expression Profiling Interactive Analysis database. Finally, functional enrichment and gene set enrichment analyses were performed using datasets GSE65858 and GSE39366. Three gene sets, namely 'P53 pathway', 'estrogen response early' and 'estrogen response late', were enriched in the two datasets. In conclusion, CNFN, identified via the WGCNA algorithm, may contribute to the prediction of lymph node metastases and prognosis, probably by regulating the pathways associated with P53, and the early and late estrogen response.

Project description:Objective: Cyclooxygenase-2 (COX-2) is a critical enzyme associated with inflammation and tumorigenesis. Although several studies have compared the expression of COX-2 in endometrial cancer tissues and normal tissues, the results have been inconsistent thus far. This study aims to conduct a meta-analysis to elucidate the role of COX-2 in the determination of the risk, prognosis, and clinical features of endometrial cancer. Methods: We retrieved the suitable studies on the association between COX-2 expression and endometrial cancer from PubMed, EMBASE, and Web of Science databases that were published between 1999 and September 31st, 2019. The hazard ratio (HR) and 95% confidence intervals (CIs) were retrieved to assess the relationship between COX-2 expression and the prognosis of endometrial cancer. The odds ratio (OR) and 95% CIs were calculated to evaluate the correlation between COX-2 expression and the risk and clinical features of endometrial cancer. Results: To investigate the association between COX-2 expression and the susceptibility, clinical features, and prognosis of endometrial cancer, we performed a meta-analysis on data from selected studies that collectively involved 273 normal individuals and 1,376 patients with endometrial cancer. Overall, the pooled analysis indicated that COX-2 expression was significantly associated with susceptibility (Caucasians, OR = 3.94, 95% CI = 2.17-7.17, P < 0.05; Asians, OR = 20.51, 95% CI = 8.54-49.26, P < 0.05), cancer stage (OR = 3.01, 95% CI = 1.95-4.67, P < 0.05), myometrial invasion (OR = 1.59, 95% CI = 1.17-2.15, P < 0.05), lymph node metastasis (OR = 1.63, 95% CI = 1.18-2.26, P < 0.05), and prognosis (OR = 2.91, 95% CI = 1.17-4.66, P < 0.05) in endometrial cancer. Conclusions: Our findings suggested that COX-2 overexpression is significantly associated with poor prognosis and advanced clinical features in endometrial cancer. Therefore, COX-2 may function as an effective prognostic biomarker and a potential therapeutic target for endometrial cancer.

Dataset Information

Clinical and Expression Significance of AKT1 by Co-expression Network Analysis in Endometrial Cancer.

Publications

Clinical and Expression Significance of AKT1 by Co-expression Network Analysis in Endometrial Cancer.

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