Dataset Information

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

ABSTRACT: The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway enrichment, followed by protein-protein interaction (PPI) network analysis. Finally, the K-clique method was applied to analyze sub-pathways. A total of 16 significant microRNAs, including hsa-miR-3622a and hsa-miR-29a, were identified (P<0.05). Following Cox's proportional regression analysis, hsa-miR-29a was screened as a prognostic marker of BUC risk (P=0.0449). A regulation network of hsa-miR-29a comprising 417 target genes was constructed. These target genes were primarily enriched in GO terms, including collagen fibril organization, extracellular matrix (ECM) organization and pathways, such as focal adhesion (P<0.05). A PPI network including 197 genes and 510 interactions, was constructed. The top 21 genes in the network module were enriched in GO terms, including collagen fibril organization and pathways, such as ECM receptor interaction (P<0.05). Finally, 4 sub-pathways of cysteine and methionine metabolism, including paths 00270_4, 00270_1, 00270_2 and 00270_5, were obtained (P<0.01) and identified to be enriched through DNA (cytosine-5)-methyltransferase (DNMT)3A, DNMT3B, methionine adenosyltransferase 2? (MAT2A) and spermine synthase (SMS). The identified microRNAs, particularly hsa-miR-29a and its 4 associated target genes DNMT3A, DNMT3B, MAT2A and SMS, may participate in the prognostic risk mechanism of BUC.

SUBMITTER: Gao J

PROVIDER: S-EPMC5754895 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

Gao Ji J Li Hongyan H Liu Lei L Song Lide L Lv Yanting Y Han Yuping Y

Oncology letters 20171003 6

The aim of the present study was to investigate risk-related microRNAs (miRs) for bladder urothelial carcinoma (BUC) prognosis. Clinical and microRNA expression data downloaded from the Cancer Genome Atlas were utilized for survival analysis. Risk factor estimation was performed using Cox's proportional regression analysis. A microRNA-regulated target gene network was constructed and presented using Cytoscape. In addition, the Database for Annotation, Visualization and Integrated Discovery was u ...[more]

PMID: 29344166

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Project description:BackgroundGenomic profiling can be used to identify the predictive effect of genomic subsets for determining prognosis in bladder urothelial carcinoma (BUC) after radical cystectomy. This study aimed to investigate potential gene and pathway markers associated with prognosis in BUC.MethodsA microarray dataset of BUC was obtained from The Cancer Genome Atlas database. Differentially expressed genes (DEGs) were identified by DESeq of the R platform. Kaplan-Meier analysis was applied for prognostic markers. Key pathways and genes were identified using bioinformatics tools, such as gene set enrichment analysis, gene ontology, the Kyoto Encyclopedia of Genes and Genomes, gene multiple association network integration algorithm (GeneMANIA), Search Tool for the Retrieval of Interacting Genes/Proteins, and Molecular Complex Detection.ResultsA comparative gene set enrichment analysis of tumor and adjacent normal tissues suggested BUC tumorigenesis resulted mainly from enrichment of cell cycle and DNA damage and repair-related biological processes and pathways, including TP53 and mitotic recombination. Two hundred and fifty-six genes were identified as potential prognosis-related DEGs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses showed that the potential prognosis-related DEGs were enriched in angiogenesis, including the cyclic adenosine monophosphate biosynthetic process, cyclic guanosine monophosphate-protein kinase G, mitogen-activated protein kinase, Rap1, and phosphoinositide-3-kinase-AKT signaling pathway. Nine hub genes, TAGLN, ACTA2, MYH11, CALD1, MYLK, GEM, PRELP, TPM2, and OGN, were identified from the intersection of protein-protein interaction and GeneMANIA networks. Module analysis of protein-protein interaction and GeneMANIA networks mainly showed enrichment of the cyclic guanosine monophosphate-protein kinase G signaling pathway, angiogenesis, cell proliferation, and differentiation, which are associated with tumor angiogenesis and cancer prognosis.ConclusionGenes and pathways related to cell cycle and DNA damage and repair may play a crucial role in BUC pathogenesis, whereas those pertaining to tumor angiogenesis may be key factors in influencing BUC prognosis, especially in advanced disease stages.

Project description:Bladder urothelial carcinoma (BLCA) is the most common malignant tumor of the urinary tract with a high lethality rate, and its immunotherapy resistance and tumor recurrence have become a major challenge in its clinical treatment. G Protein-Coupled Receptors (GPRs) are the largest family of receptors on the cell membrane surface, involved in multiple signaling pathways, and are excellent targets for oncology drug action. The transcriptome profile, single cell transcriptome profile, and clinical data of BLCA were extracted and integrated from TCGA and GEO databases, respectively. The GPR-related genes were obtained from GSEA-MSigDB database. The GPR-related gene signatures of 15 genes were constructed by using the methods of least absolute shrinkage and selection operator regression, multifactor Cox model. At the same time, tumor microenvironment (TME)-score signatures were constructed based on the immune microenvironment of BLCA, and GPR-TME-score signature was further constructed. The stability of this model was verified by using the external dataset GSE160693. We constructed risk groups by combining BLCA patient prognostic information, and with the help of BLCA scRNA transcriptome profiling, we explored differences in prognosis, immune scores, cell-cell interactions, tumor mutational burden, immune checkpoints, and response to immunotherapy in each risk group. We found that the GPR-TME-score signature was an independent prognostic factor for BLCA patients. the TME-score was a protective factor for the prognosis of BLCA patients. Among BLCA patients, GPR-high + TME-low risk group had the worst prognosis, while GPR-high + TME-high risk group had the best prognosis, and the latter had better immune score and immunotherapy response. The above differences in immune response among the subgroups may be related to the higher immune cell infiltration in the GPR-high + TME-high group. GPR-related gene signatures and TME are closely related to BLCA prognosis and immunotherapy, and GPR-related gene signature can be a useful tool to assess BLCA prognosis and immunotherapy response.

Project description:IntroductionBladder cancer is the most common urinary tract malignancy, and 90% of bladder tumors are urothelial cell carcinomas. Ferroptosis is a new form of cell death discovered in recent years, which is an iron-dependent form of cell death characterized by the lethal intracellular accumulation of lipid-based reactive oxygen species. Ferroptosis is considered to be a double-edged sword for cancer and cancer therapy.Materials and methodsIn the current study, expression profiles of bladder cancer (BLCA) specimens were obtained from The Cancer Genome Atlas (TCGA) RNA-Seq database. Ferroptosis-related genes were downloaded from the FerrDb website. The ferroptosis-related differentially expressed genes (DEGs) which were related to overall survival (OS) were first identified. The least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression methods were utilized to develop a ferroptosis-related prognostic model (FRPM). In addition, a nomogram model based on FRPM and clinicopathological features was successfully constructed and validated. In addition, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) methods were utilized in this study in order to compare the DEGs between the high-risk and low-risk groups. This study also adopted RT-qPCR, CCK-8 assay, and scratch assay methods to perform experimental verification processes.Results and discussionA 7-gene FRPM was constructed in this research investigation in order to stratify the patients into two groups according to their risk scores. The results of this study's survival analysis and time-dependent receiver operating characteristic (ROC) analysis demonstrated that the model had achieved a stable performance level. This multivariate Cox regression results revealed that the FRPM was an independent prognostic predictor for the OS of BLCA patients and the results were displayed using a nomogram. In addition, the ROC analysis, concordance index (C-index), calibration plots, and decision curve analysis (DCA) curves further indicated that this study's nomogram method enabled valuable prediction results. The functional enrichment analysis results suggested that the DEGs between the high- and low-risk groups played vital roles in the progression of the ferroptosis. Also, the ssGSEA indicated that the immune status was different between the two groups. This study found that the RT-qPCR results had confirmed the differential expressions of DEGs in the tissue samples, and the CCK-8 assay and scratch assay results confirmed the promoting effects of SCD on the proliferation and migration of tumor cells.ConclusionsThis study defined a novel prognostic model of seven ferroptosis-related genes, which proved to be independently associated with the OS of BLCA. A nomogram method was developed for the purpose of providing further insight into the accurate predictions of BLCA prognoses.

Project description:BackgroundThe aim of this study was to investigate the regulatory network of lncRNAs as competing endogenous RNAs (ceRNA) in bladder urothelial carcinoma (BUC) based on gene expression data derived from The Cancer Genome Atlas (TCGA).Materials and methodsRNA sequence profiles and clinical information from 414 BUC tissues and 19 non-tumor adjacent tissues were downloaded from TCGA. Differentially expressed RNAs derived from BUC and non-tumor adjacent samples were identified using the R package "edgeR". Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed using the "clusterProfiler" package. Gene ontology and protein-protein interaction (PPI) networks were analyzed for the differentially expressed mRNAs using the "STRING" database. The network for the dysregulated lncRNA associated ceRNAs was then constructed for BUC using miRcode, miRTarBase, miRDB, and TargetScan. Cox regression analysis was performed to identify independent prognostic RNAs associated with BUC overall survival (OS). Survival analysis for the independent prognostic RNAs within the ceRNA network was calculated using Kaplan-Meier curves.ResultsBased on our analysis, a total of 666, 1819 and 157 differentially expressed lncRNAs, mRNAs and miRNAs were identified respectively. The ceRNA network was then constructed and contained 59 lncRNAs, 23 DEmiRNAs, and 52 DEmRNAs. In total, 5 lncRNAs (HCG22, ADAMTS9-AS1, ADAMTS9-AS2, AC078778.1, and AC112721.1), 2 miRNAs (hsa-mir-145 and hsa-mir-141) and 6 mRNAs (ZEB1, TMEM100, MAP1B, DUSP2, JUN, and AIFM3) were found to be related to OS. Two lncRNAs (ADAMTS9-AS1 and ADAMTS9-AS2) and 4 mRNA (DUSP2, JUN, MAP1B, and TMEM100) were validated using GEPIA. Thirty key hub genes were identified using the ranking method of degree. KEGG analysis demonstrated that the majority of the DEmRNAs were involved in pathways associated with cancer.ConclusionOur findings provide an understanding of the important role of lncRNA-related ceRNAs in BUC. Additional experimental and clinical validations are required to support our findings.

Dataset Information

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

Publications

Identification and functional analysis of risk-related microRNAs for the prognosis of patients with bladder urothelial carcinoma.

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