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Identification of differentially expressed miRNAs and miRNA-targeted genes in bladder cancer.

ABSTRACT: Background:Differentially expressed genes and their post-transcriptional regulator-microRNAs (miRNAs), are potential keys to pioneering cancer diagnosis and treatment. The aim of this study was to investigate how the miRNA-mRNA interactions might affect the tumorigenesis of bladder cancer (BC) and to identify specific miRNA and mRNA genetic markers in the two BC types: non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC). Results:We identified 227 genes that interacted with 54 miRNAs in NMIBC, and 14 genes that interacted with 10 miRNAs in MIBC. Based on this data, we found extracellular matrix-related genes are highly enriched in NMIBC while genes related to core nuclear division are highly enriched in MIBC. Furthermore, using a transcriptional regulatory element database, we found indirect regulatory transcription factors (TFs) for enriched genes could regulate tumorigenesis with or without miRNAs. Materials and methods:Tissue samples from 234 patients histologically diagnosed with BC and 83 individuals without BC were analyzed using microarray and next-generation sequencing technology, and we used different cut-offs to identify differentially expressed mRNAs and miRNAs in NMIBC and MIBC. The selected mRNAs and miRNAs were paired using validated target datasets and according to inverse expression relationships. MiRNA interacted genes were compared with the TF-regulating genes in BC. Meanwhile, pathway enrichment analysis was performed to identify the functions of selected miRNAs and genes. Conclusions:Identification of differential gene expression in specific tumor types could facilitate development of cancer diagnosis and aid in the early detection of BC.

SUBMITTER: Lee JY

PROVIDER: S-EPMC6021253 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Identification of differentially expressed miRNAs and miRNA-targeted genes in bladder cancer.

Lee Jong-Young JY Yun Seok Joong SJ Jeong Pildu P Piao Xuan-Mei XM Kim Ye-Hwan YH Kim Jihye J Subramaniyam Sathiyamoorthy S Byun Young Joon YJ Kang Ho Won HW Seo Sung Phil SP Kim Jayoung J Kim Jung Min JM Yoo Eun Sang ES Kim Isaac Y IY Moon Sung-Kwon SK Choi Yung Hyun YH Kim Wun-Jae WJ

Oncotarget 20180207 45

<h4>Background</h4>Differentially expressed genes and their post-transcriptional regulator-microRNAs (miRNAs), are potential keys to pioneering cancer diagnosis and treatment. The aim of this study was to investigate how the miRNA-mRNA interactions might affect the tumorigenesis of bladder cancer (BC) and to identify specific miRNA and mRNA genetic markers in the two BC types: non-muscle invasive bladder cancer (NMIBC) and muscle invasive bladder cancer (MIBC).<h4>Results</h4>We identified 227 g ...[more]

PMID: 29963227

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Project description:BackgroundCurrent diagnosis and treatment of urinary bladder cancer (BC) has shown great progress with the utilization of microarrays.PurposeOur goal was to identify common differentially expressed (DE) genes among clinically relevant subclasses of BC using microarrays.Methodology/principal findingsBC samples and controls, both experimental and publicly available datasets, were analyzed by whole genome microarrays. We grouped the samples according to their histology and defined the DE genes in each sample individually, as well as in each tumor group. A dual analysis strategy was followed. First, experimental samples were analyzed and conclusions were formulated; and second, experimental sets were combined with publicly available microarray datasets and were further analyzed in search of common DE genes. The experimental dataset identified 831 genes that were DE in all tumor samples, simultaneously. Moreover, 33 genes were up-regulated and 85 genes were down-regulated in all 10 BC samples compared to the 5 normal tissues, simultaneously. Hierarchical clustering partitioned tumor groups in accordance to their histology. K-means clustering of all genes and all samples, as well as clustering of tumor groups, presented 49 clusters. K-means clustering of common DE genes in all samples revealed 24 clusters. Genes manifested various differential patterns of expression, based on PCA. YY1 and NFκB were among the most common transcription factors that regulated the expression of the identified DE genes. Chromosome 1 contained 32 DE genes, followed by chromosomes 2 and 11, which contained 25 and 23 DE genes, respectively. Chromosome 21 had the least number of DE genes. GO analysis revealed the prevalence of transport and binding genes in the common down-regulated DE genes; the prevalence of RNA metabolism and processing genes in the up-regulated DE genes; as well as the prevalence of genes responsible for cell communication and signal transduction in the DE genes that were down-regulated in T1-Grade III tumors and up-regulated in T2/T3-Grade III tumors. Combination of samples from all microarray platforms revealed 17 common DE genes, (BMP4, CRYGD, DBH, GJB1, KRT83, MPZ, NHLH1, TACR3, ACTC1, MFAP4, SPARCL1, TAGLN, TPM2, CDC20, LHCGR, TM9SF1 and HCCS) 4 of which participate in numerous pathways.Conclusions/significanceThe identification of the common DE genes among BC samples of different histology can provide further insight into the discovery of new putative markers.

Project description:INTRODUCTION: We previously identified common differentially expressed (DE) genes in bladder cancer (BC). In the present study we analyzed in depth, the expression of several groups of these DE genes. MATERIALS AND METHODS: Samples from 30 human BCs and their adjacent normal tissues were analyzed by whole genome cDNA microarrays, qRT-PCR and Western blotting. Our attention was focused on cell-cycle control and DNA damage repair genes, genes related to apoptosis, signal transduction, angiogenesis, as well as cellular proliferation, invasion and metastasis. Four publicly available GEO Datasets were further analyzed, and the expression data of the genes of interest (GOIs) were compared to those of the present study. The relationship among the GOI was also investigated. GO and KEGG molecular pathway analysis was performed to identify possible enrichment of genes with specific biological themes. RESULTS: Unsupervised cluster analysis of DNA microarray data revealed a clear distinction in BC vs. control samples and low vs. high grade tumors. Genes with at least 2-fold differential expression in BC vs. controls, as well as in non-muscle invasive vs. muscle invasive tumors and in low vs. high grade tumors, were identified and ranked. Specific attention was paid to the changes in osteopontin (OPN, SPP1) expression, due to its multiple biological functions. Similarly, genes exhibiting equal or low expression in BC vs. the controls were scored. Significant pair-wise correlations in gene expression were scored. GO analysis revealed the multi-facet character of the GOIs, since they participate in a variety of mechanisms, including cell proliferation, cell death, metabolism, cell shape, and cytoskeletal re-organization. KEGG analysis revealed that the most significant pathway was that of Bladder Cancer (p?=?1.5×10(-31)). CONCLUSIONS: The present work adds to the current knowledge on molecular signature identification of BC. Such works should progress in order to gain more insight into disease molecular mechanisms.

Project description:Introduction: Ulcerative colitis (UC) is a chronic inflammatory disease of the intestine whose cause and underlying mechanisms are not fully understood. The aim of this study was to use bioinformatics analysis to identify differentially expressed genes (DEGs) with diagnostic and therapeutic potential in UC. Materials and methods: Three UC datasets (GSE179285, GSE75214, GSE48958) were downloaded from the Gene Expression Omnibus (GEO) database. DEGs between normal and UC tissues were identified using the GEO2R online tool. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the DEGs were performed using Metascape. Protein-protein interaction network (PPI) analysis and visualization using STRING and Cytoscape. Finally, the miRNA gene regulatory network was constructed by Cytoscape to predict potential microRNAs (miRNAs) associated with DEGs. Results: A total of 446 DEGs were identified, consisting of 309 upregulated genes and 137 downregulated genes. The enriched functions and pathways of the DEGs include extracellular matrix, regulation of cell adhesion, inflammatory response, response to cytokine, monocarboxylic acid metabolic process, response to toxic substance. The analysis of KEGG pathway indicates that the DEGs were significantly enriched in Complement and coagulation cascades, Amoebiasis, TNF signaling pathway, bile secretion, and Mineral absorption. Combining the results of the PPI network and CytoHubba, 9 hub genes including CXCL8, ICAM1, CXCR4, CD44, IL1B, MMP9, SPP1, TIMP1, and HIF1A were selected. Based on the DEG-miRNAs network construction, 7 miRNAs including miR-335-5p, mir-204-5p, miR-93-5p, miR106a-5p, miR-21-5p, miR-146a-5p, and miR-155-5p were identified as potential critical miRNAs. Conclusion: In summary, we identified DEGs that may be involved in the progression or occurrence of UC. A total of 446 DEGs,9 hub genes and 7 miRNAs were identified, which may be considered as biomarkers of UC. Further studies, however, are needed to elucidate the biological functions of these genes in UC.

Project description:The significance of PLK1 (polo-like kinase 1) has become increasingly essential as both a biomarker and a target for cancer treatment. Here, we aimed to determine the downstream genes of PLK1 and their effects on the carcinogenesis and progression of bladder cancer.Specific siRNA was utilized to silence the target gene expression. The cell proliferation, invasion and migration of bladder cancer cells by MTT assay, BrdU assay and transwell assay. The differential expression genes were identified using Affymetrix HTA2.0 Array. The KEGG, GO and STRING analysis were used to analyze the signaling pathway and protein-protein interaction. Spearman analysis was used to analyze the correlation between protein and protein, between protein and clincopathologic characteristics.PLK1 siRNA hindered the proliferation, invasion and migration of bladder cancer cells, as determined by the MTT, BrdU and transwell assays. A total of 561 differentially expressed genes were identified using an Affymetrix HTA2.0 Array in PLK1 knockdown T24 cells. According to KEGG, GO and STRING analysis, five key genes (BUB1B, CCNB1, CDC25A, FBXO5, NDC80) were determined to be involved in cell proliferation, invasion and migration. PLK1 knockdown decreased BUB1B, CCNB1, CDC25A and NDC80 expressions but increased FBXO5 expression. BUB1B, CCNB1, CDC25A and NDC80 were positively correlated with cell proliferation, invasion, migration and PLK1 expression in tissues, but FBXO5 was negatively correlated with each of those factors. The results showed that the five genes expressions were significantly correlation with the PLK1 expression in normal bladder tissues and bladder cancer tissues. Four of them (BUB1B, CCNB1, CDC25A, NDC80) were obviously positive correlations with pT stage and metastasis. But FBXO5 was negative correlated with pT stage and metastasis. Furthermore, significant correlations were found between CCNB1 or CDC25A or NDC80 and histological grade; between BUB1B or NDC80 and recurrence.Five downstream genes of PLK1 were associated with the regulation of cell proliferation, invasion and migration in bladder cancer. Furthermore, these genes may play important roles in bladder cancer and become important biomarkers and targets for cancer treatment.

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Identification of differentially expressed miRNAs and miRNA-targeted genes in bladder cancer.

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Identification of differentially expressed miRNAs and miRNA-targeted genes in bladder cancer.

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