Your browser doesn't support javascript.
Mostrar: 20 | 50 | 100
Resultados 1 - 6 de 6
Mais filtros

Base de dados
Intervalo de ano de publicação
Medicine (Baltimore) ; 99(48): e23409, 2020 Nov 25.
Artigo em Inglês | MEDLINE | ID: mdl-33235120


BACKGROUND: Talaromyces marneffei (T marneffei), known as a significant pathogen in patients with AIDS in Southeast Asia, is a dimorphic fungus, which can cause deadly systematic infection in immunocompromised hosts. What is more, the dimorphic phase transition has been reported as a conspicuous process linked with virulence. Interestingly, the yeast form was found in infected individuals, representing the pathogenic phase. However, few researches were found to study the mechanism of dimorphic transition. Thus, a diverse insight into the dimorphic switch mechanism, is urgently needed and we are the first one to research the mechanism of dimorphism. METHODS: Firstly, we investigated the microarray of T. marneffei in the Gene Expression Omnibus database (GEO) for differentially expressed genes (DEGs). Then Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.8 was employed to analyze the underlying enrichment and pathway in biological process of DEGs. Meanwhile, protein-protein interaction (PPI) network was constructed using STRING database. On the strength of the theory that similar amino acid sequences share similar structures, which play a decisive role on the function of protein, three dimensional structures of hub-genes were predicted to further investigate the likely function of hub-genes. RESULTS: GSE51109 was elected as the eligible series for the purpose of our research, including GSM1238923 (GSM23), GSM1238924 (GSM24), and GSM1238925 (GSM25). PMAA_012920, PMAA_028730, PMAA_068140, PMAA_092900, PMAA_032350 were the most remarkable genes in all of the three PPI networks, thus, were viewed as hub-genes. With regard to the three-dimensional construction, except that there was no significant prediction structure of PMAA_092900 with the criterion seq identify > 30%, GMQE: 0-1, QMEAN4: -4-0, the parallel templates for four structures were Crystal structure of Saccharomyces cerevesiae mitochondrial NADP(+)-dependent isocitrate dehydrogenase in complex with isocitrate, Organellar two-pore channels (TPCs), Yeast Isocitrate Dehydrogenase (Apo Form) and Crystal Structure Of ATP-Dependent Phosphoenolpyruvate Carboxykinase From Thermus thermophilus HB8 in order. CONCLUSION: The dimorphic transition of T. marneffei was viewed as a pathogenic factor and DEGs were observed. In-depth study of the function and pathway of DEGs revealed that PMAA_012920, PMAA_028730, PMAA_068140, PMAA_092900, PMAA_032350 were most likely acting as the hub-genes and were likely taking effect through regulating energy metabolism.

Medicine (Baltimore) ; 99(18): e19986, 2020 May.
Artigo em Inglês | MEDLINE | ID: mdl-32358373


BACKGROUND: The incidence of triple negative breast cancer (TNBC) is at a relatively high level, and our study aimed to identify differentially expressed genes (DEGs) in TNBC and explore the key pathways and genes of TNBC. METHODS: The gene expression profiling (GSE86945, GSE86946 and GSE102088) data were obtained from Gene Expression Omnibus Datasets, DEGs were identified by using R software, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of DEGs were performed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) tools, and the protein-protein interaction (PPI) network of the DEGs was constructed by the STRING database and visualized by Cytoscape software. Finally, the survival value of hub DEGs in breast cancer patients were performed by the Kaplan-Meier plotter online tool. RESULTS: A total of 2998 DEGs were identified between TNBC and health breast tissue, including 411 up-regulated DEGs and 2587 down-regulated DEGs. GO analysis results showed that down-regulated DEGs were enriched in gene expression (BP), extracellular exosome (CC), and nucleic acid binding, and up-regulated were enriched in chromatin assembly (BP), nucleosome (CC), and DNA binding (MF). KEGG pathway results showed that DEGs were mainly enriched in Pathways in cancer and Systemic lupus erythematosus and so on. Top 10 hub genes were picked out from PPI network by connective degree, and 7 of top 10 hub genes were significantly related with adverse overall survival in breast cancer patients (P < .05). Further analysis found that only EGFR had a significant association with the prognosis of triple-negative breast cancer (P < .05). CONCLUSIONS: Our study showed that DEGs were enriched in pathways in cancer, top 10 DEGs belong to up-regulated DEGs, and 7 gene connected with poor prognosis in breast cancer, including HSP90AA1, SRC, HSPA8, ESR1, ACTB, PPP2CA, and RPL4. These can provide some guidance for our research on the diagnosis and prognosis of TNBC, and further research is needed to evaluate their value in the targeted therapy of TNBC.

Mineração de Dados/métodos , Regulação Neoplásica da Expressão Gênica/fisiologia , Neoplasias de Mama Triplo Negativas/genética , Bases de Dados Genéticas , Regulação para Baixo , Perfilação da Expressão Gênica , Ontologia Genética , Humanos , Análise de Sobrevida , Neoplasias de Mama Triplo Negativas/mortalidade , Regulação para Cima
Cell Physiol Biochem ; 48(2): 540-555, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30021196


BACKGROUND/AIMS: Accumulated evidence indicates that lncRNA NEAT1 has important roles in various malignant tumors. In this study, we conducted a comprehensive analysis to explore the exact role of NEAT1 in hepatocellular carcinoma (HCC). METHODS: The effects of NEAT1 on cell proliferation, apoptosis, migration, and invasion were measured by in vitro experiments. The expression level and clinical value of NEAT1 in HCC was evaluated based on data from The Cancer Genome Atlas (TCGA), Oncomine, and in-house real-time quantitative (RT-qPCR). Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) network analyses were conducted to investigate the potential molecular mechanisms of NEAT1. RESULTS: NEAT1 siRNA not only inhibited proliferation, migration, and invasion of HCC cells but also induced HCC cell apoptosis. A total of four records from TCGA, Oncomine, and RT-qPCR analysis were combined to assess the expression level of NEAT1 in HCC. The pooled standard mean deviation (SMD) indicated that NEAT1 was up-regulated in HCC (SMD = 0.54; 95% CI, 0.36-0.73; P < 0.0001). The area under the curve value of the summary receiver operating characteristic curve was 0.71. NEAT1 expression was also related to race (P = 0.025) and distant metastasis (P = 0.002). Additionally, the results of GO, KEGG pathway, and PPI network analyses suggest that NEAT1 may promote the progression of HCC by interacting with several tumor-related genes (SP1, MDM4, CREBBP, TRAF5, CASP8, TRAF1, KAT2A, and HIST4H4). CONCLUSIONS: NEAT1 contributes to the deterioration of HCC and provides a potential biomarker for the diagnosis and therapy of HCC.

Carcinoma Hepatocelular/patologia , Neoplasias Hepáticas/patologia , RNA Longo não Codificante/metabolismo , Apoptose , Área Sob a Curva , Carcinoma Hepatocelular/genética , Carcinoma Hepatocelular/mortalidade , Proteínas de Ciclo Celular , Movimento Celular , Proliferação de Células , Mineração de Dados , Regulação Neoplásica da Expressão Gênica , Células Hep G2 , Humanos , Estimativa de Kaplan-Meier , Neoplasias Hepáticas/genética , Estadiamento de Neoplasias , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Mapas de Interação de Proteínas , Proteínas Proto-Oncogênicas/genética , Proteínas Proto-Oncogênicas/metabolismo , Interferência de RNA , RNA Longo não Codificante/antagonistas & inibidores , RNA Longo não Codificante/genética , RNA Interferente Pequeno/metabolismo , Curva ROC , Reação em Cadeia da Polimerase em Tempo Real , Fator de Transcrição Sp1/genética , Fator de Transcrição Sp1/metabolismo
Med Sci Monit ; 24: 4807-4822, 2018 Jul 12.
Artigo em Inglês | MEDLINE | ID: mdl-29997385


BACKGROUND microRNAs (miRNAs) have a role as biomarkers in human cancer. The aim of this study was to use bioinformatics data, and review of cases identified from the literature, to investigate the role of microRNA-99a-3p (miR-99a-3p) in prostate cancer, including the identification of its target genes and signaling pathways. MATERIAL AND METHODS Meta-analysis from a literature review included 965 cases of prostate cancer. Bioinformatics databases interrogated for miR-99a-3p in prostate cancer included The Cancer Genome Atlas (TCGA), the Gene Expression Omnibus (GEO), and ArrayExpress. Twelve computational predictive algorithms were developed to integrate miR-99a-3p target gene prediction data. Bioinformatics analysis data from Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis were used investigate the possible pathways and target genes for miR-99a-3p in prostate cancer. RESULTS TCGA data showed that miR-99a was down-regulated in prostate cancer when compared with normal prostate tissue. Receiver-operating characteristic (ROC) curve area under the curve (AUC) for miR-99a-3p was 0.660 (95% CI, 0.587-0.732) or a moderate level of discriminations. Pathway analysis showed that miR-99a-3p was associated with the Wnt and vascular endothelial growth factor (VEGF) signaling pathways. The PPP3CA and HYOU1 genes, selected from the PPI network, were highly expressed in prostate cancer tissue compared with normal prostate tissue, and negatively correlated with the expression of miR-99a-3p. CONCLUSIONS In prostate cancer, miR-99a-3p expression was associated with the Wnt and VEGF signaling pathways, which might inhibit the expression of PPP3CA or HYOU1.

Biologia Computacional , Regulação Neoplásica da Expressão Gênica , MicroRNAs/genética , Neoplasias da Próstata/genética , Perfilação da Expressão Gênica , Ontologia Genética , Redes Reguladoras de Genes , Genoma Humano , Humanos , Masculino , MicroRNAs/metabolismo , Pessoa de Meia-Idade , Neoplasias da Próstata/patologia , Mapas de Interação de Proteínas/genética , Reprodutibilidade dos Testes
Cell Physiol Biochem ; 46(3): 925-952, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29669324


BACKGROUND/AIMS: Since the function of microRNA (miR)-210 in non-small cell lung cancer (NSCLC) remains unclear, we aimed to explore the clinical significance of miR-210 in NSCLC. METHODS: NSCLC-related data from 1673 samples on Gene Expression Omnibus and 1090 samples on The Cancer Genome Atlas were obtained and analyzed. The expression level of miR-210 was validated via real-time quantitative PCR analysis with 125 paired clinical samples. A meta-analysis was performed to generate a comprehensive understanding of miR-210 expression and its clinical significance in NSCLC. In addition, bioinformatics analysis was also conducted to reveal the potential underlying mechanism of miR-210 action in NSCLC. RESULTS: miR-210 expression was consistently elevated in NSCLC solid tissue samples. However, its expression was controversial in easily obtained body fluids (i.e., blood, plasma, and serum). Moreover, an overall pooled meta-analysis implied a comparatively higher level of miR-210 expression in NSCLC cancerous tissue than in normal control tissue (P < 0.001). In addition, a meta-analysis of outcome revealed a significant diagnostic capacity of miR-210 in NSCLC by detecting its expression in serum and sputum (area under the summary receiver operating characteristic curve 0.82 and 0.81, respectively). miR-210 overexpression was associated with poor progression-free survival (PFS) in NSCLC and was negatively related to overall survival and disease-free survival. Bioinformatic gene enrichment and annotation analyses showed that the target genes of miR-210 were greatly enriched in cell adhesion and plasma membrane, and three pathways were considered to be the main functional circuits of miR-210: renin secretion, the cGMP-PKG signaling pathway, and cell adhesion molecules. CONCLUSION: In NSCLC, miR-210 expression was elevated and overexpression indicated poor PFS. Expression level of miR-210 in serum and sputum showed significant diagnostic value for NSCLC.

Carcinoma Pulmonar de Células não Pequenas/patologia , Neoplasias Pulmonares/patologia , MicroRNAs/metabolismo , Área Sob a Curva , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma Pulmonar de Células não Pequenas/genética , Carcinoma Pulmonar de Células não Pequenas/mortalidade , Moléculas de Adesão Celular/metabolismo , GMP Cíclico/metabolismo , Proteínas Quinases Dependentes de GMP Cíclico/metabolismo , Bases de Dados Genéticas , Intervalo Livre de Doença , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/mortalidade , MicroRNAs/sangue , Prognóstico , Curva ROC , Renina/genética , Renina/metabolismo , Transdução de Sinais/genética , Escarro/metabolismo , Taxa de Sobrevida
FEBS Open Bio ; 8(1): 64-84, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29321958


There is accumulating evidence that miRNA might serve as potential diagnostic and prognostic markers for various types of cancer. Hepatocellular carcinoma (HCC) is the most common type of malignant lesion but the significance of miRNAs in HCC remains largely unknown. The present study aimed to establish the diagnostic value of miR-101-3p/5p in HCC and then further investigate the prospective molecular mechanism via a bioinformatic analysis. First, the miR-101 expression profiles and parallel clinical parameters from 362 HCC patients and 50 adjacent non-HCC tissue samples were downloaded from The Cancer Genome Atlas (TCGA). Second, we aggregated all miR-101-3p/5p expression profiles collected from published literature and the Gene Expression Omnibus and TCGA databases. Subsequently, target genes of miR-101-3p and miR-101-5p were predicted by using the miRWalk database and then overlapped with the differentially expressed genes of HCC identified by natural language processing. Finally, bioinformatic analyses were conducted with the overlapping genes. The level of miR-101 was significantly lower in HCC tissues compared with adjacent non-HCC tissues (P < 0.001), and the area under the curve of the low miR-101 level for HCC diagnosis was 0.925 (P < 0.001). The pooled summary receiver operator characteristic (SROC) of miR-101-3p was 0.86, and the combined SROC curve of miR-101-5p was 0.80. Bioinformatic analysis showed that the target genes of both miR-101-3p and miR-101-5p are involved in several pathways that are associated with HCC. The hub genes for miR-101-3p and miR-101-5p were also found. Our results suggested that both miR-101-3p and miR-101-5p might be potential diagnostic markers in HCC, and that they exert their functions via targeting various prospective genes in the same pathways.