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1.
Nat Commun ; 10(1): 3015, 2019 07 09.
Artigo em Inglês | MEDLINE | ID: mdl-31289271

RESUMO

The protein-protein interaction (PPI) network of an organism serves as a skeleton for its signaling circuitry, which mediates cellular response to environmental and genetic cues. Understanding this circuitry could improve the prediction of gene function and cellular behavior in response to diverse signals. To realize this potential, one has to comprehensively map PPIs and their directions of signal flow. While the quality and the volume of identified human PPIs improved dramatically over the last decade, the directions of these interactions are still mostly unknown, thus precluding subsequent prediction and modeling efforts. Here we present a systematic approach to orient the human PPI network using drug response and cancer genomic data. We provide a diffusion-based method for the orientation task that significantly outperforms existing methods. The oriented network leads to improved prioritization of cancer driver genes and drug targets compared to the state-of-the-art unoriented network.


Assuntos
Biologia Computacional/métodos , Neoplasias/genética , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/efeitos dos fármacos , Análise de Dados , Bases de Dados Genéticas/estatística & dados numéricos , Bases de Dados de Produtos Farmacêuticos/estatística & dados numéricos , Conjuntos de Dados como Assunto , Humanos , Mapas de Interação de Proteínas/genética , Software
2.
Medicine (Baltimore) ; 98(27): e16277, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277155

RESUMO

Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein-protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.


Assuntos
Biomarcadores Tumorais/genética , Biologia Computacional/métodos , Células Endoteliais/metabolismo , Regulação Neoplásica da Expressão Gênica , Herpesvirus Humano 8 , Mapas de Interação de Proteínas/genética , Sarcoma de Kaposi/genética , Biomarcadores Tumorais/biossíntese , DNA de Neoplasias/genética , Células Endoteliais/patologia , Células Endoteliais/virologia , Perfilação da Expressão Gênica/métodos , Ontologia Genética , Humanos , Mapeamento de Interação de Proteínas/métodos , Sarcoma de Kaposi/metabolismo , Sarcoma de Kaposi/virologia
3.
BMC Bioinformatics ; 20(Suppl 12): 320, 2019 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-31216985

RESUMO

BACKGROUND: As Genome-Wide Association Studies (GWAS) have been increasingly used with data from various populations, it has been observed that data from different populations reveal different sets of Single Nucleotide Polymorphisms (SNPs) that are associated with the same disease. Using Type II Diabetes (T2D) as a test case, we develop measures and methods to characterize the functional overlap of SNPs associated with the same disease across populations. RESULTS: We introduce the notion of an Overlap Matrix as a general means of characterizing the functional overlap between different SNP sets at different genomic and functional granularities. Using SNP-to-gene mapping, functional annotation databases, and functional association networks, we assess the degree of functional overlap across nine populations from Asian and European ethnic origins. We further assess the generalizability of the method by applying it to a dataset for another complex disease - Prostate Cancer. Our results show that more overlap is captured as more functional data is incorporated as we go through the pipeline, starting from SNPs and ending at network overlap analyses. We hypothesize that these observed differences in the functional mechanisms of T2D across populations can also explain the common use of different prescription drugs in different populations. We show that this hypothesis is concordant with the literature on the functional mechanisms of prescription drugs. CONCLUSION: Our results show that although the etiology of a complex disease can be associated with distinct processes that are affected in different populations, network-based annotations can capture more functional overlap across populations. These results support the notion that it can be useful to take ethnicity into account in making personalized treatment decisions for complex diseases.


Assuntos
Diabetes Mellitus Tipo 2/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único/genética , Grupo com Ancestrais do Continente Asiático , Diabetes Mellitus Tipo 2/tratamento farmacológico , Grupos Étnicos , Genoma Humano , Humanos , Masculino , Neoplasias da Próstata/genética , Mapas de Interação de Proteínas/genética
4.
Nat Commun ; 10(1): 2669, 2019 06 17.
Artigo em Inglês | MEDLINE | ID: mdl-31209209

RESUMO

The Mediator complex regulates transcription by connecting enhancers to promoters. High Mediator binding density defines super enhancers, which regulate cell-identity genes and oncogenes. Protein interactions of Mediator may explain its role in these processes but have not been identified comprehensively. Here, we purify Mediator from neural stem cells (NSCs) and identify 75 protein-protein interaction partners. We identify super enhancers in NSCs and show that Mediator-interacting chromatin modifiers colocalize with Mediator at enhancers and super enhancers. Transcription factor families with high affinity for Mediator dominate enhancers and super enhancers and can explain genome-wide Mediator localization. We identify E-box transcription factor Tcf4 as a key regulator of NSCs. Tcf4 interacts with Mediator, colocalizes with Mediator at super enhancers and regulates neurogenic transcription factor genes with super enhancers and broad H3K4me3 domains. Our data suggest that high binding-affinity for Mediator is an important organizing feature in the transcriptional network that determines NSC identity.


Assuntos
Regulação da Expressão Gênica no Desenvolvimento/fisiologia , Redes Reguladoras de Genes/fisiologia , Complexo Mediador/metabolismo , Células-Tronco Neurais/fisiologia , Neurogênese/genética , Fator de Transcrição 4/metabolismo , Linhagem Celular , Elementos Facilitadores Genéticos/genética , Histonas/metabolismo , Humanos , Histona Desmetilases com o Domínio Jumonji/metabolismo , Oxirredutases N-Desmetilantes/metabolismo , Regiões Promotoras Genéticas/genética , Mapeamento de Interação de Proteínas , Mapas de Interação de Proteínas/genética , Proteína-Arginina N-Metiltransferases/metabolismo , Transcrição Genética/fisiologia
5.
Biomed Res Int ; 2019: 7149296, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31073530

RESUMO

Background: The distinction between right-sided and left-sided colon adenocarcinoma has recently received considerable. This study aims to identify key MicroRNA (miRNA) and mRNAs in right-sided colon adenocarcinoma (RSCOAD) and left-sided colon adenocarcinoma (LSCOAD) by TCGA integration analysis. Methods: The miRNA and mRNA expression profiles of a large group of patients with RSCOAD and LSCOAD were obtained from TCGA. The differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were identified by TCGA integration analysis. The optimal diagnostic miRNA biomarkers for RSCOAD and LSCOAD were identified by Boruta algorithm. We established classification models to distinguish RSCOAD and LSCOAD. Protein-protein interaction (PPI) network analysis, DEmiRNA-DEmRNA interaction analysis, and functional annotation were performed. The expression of selected DEmiRNAs and DEmRNAs was validated by qRT-PCR. Results: A total of 2534 DEmRNAs (940 downregulated and 1594 upregulated mRNAs) and 54 DEmiRNAs (22 downregulated and 32 upregulated miRNAs) between RSCOAD and LSCOAD were identified. The feature selection procedure was to obtain 22 optimal diagnostic miRNAs biomarkers in RSCOAD compared to LSCOAD. The AUC of the random forests model was 0.869 and the specificity and sensitivity of this model were 79% and 84.6%, respectively. Three DEmiRNAs (hsa-miR-224-5p, hsa-miR-155-5p, and hsa-miR-31-5p) and five DEmRNAs (CXCR4, SMAD4, KRAS, FITM2, and PLAGL2) were identified key DEmiRNAs and DEmRNAs in RSCOAD compared to LSCOAD. The qRT-PCR results of CXCR4, FITM2, TFAP2A, ULBP2, hsa-miR-224-5p, and hsa-miR-155-5p were consistent with our integrated analysis. Conclusion: A total of three DEmiRNAs (hsa-miR-224-5p, hsa-miR-155-5p, and hsa-miR-31-5p) and five DEmRNAs (CXCR4, SMAD4, KRAS, FITM2, and PLAGL2) may be involved in the pathogenesis of RSCOAD and LSCOAD which may make a contribution for understanding mechanisms and developing therapeutic strategies for RSCOAD and LSCOAD.


Assuntos
Adenocarcinoma/genética , Neoplasias do Colo/genética , MicroRNAs/genética , RNA Mensageiro/genética , Adenocarcinoma/patologia , Biomarcadores Tumorais/genética , Neoplasias do Colo/patologia , Biologia Computacional , Regulação Neoplásica da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , Humanos , Anotação de Sequência Molecular , Proteínas de Neoplasias/genética , Mapas de Interação de Proteínas/genética , Transdução de Sinais/genética
6.
Mol Med Rep ; 19(6): 5263-5274, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31059041

RESUMO

Genetic biomarkers for the diagnosis of ankylosing spondylitis (AS) remain unreported except for human leukocyte antigen B27 (HLA­B27). Therefore, the aim of the present study was to screen the differentially expressed genes (DEGs), and those that also possess differential single nucleotide polymorphism (SNP) loci in the whole blood of AS patients compared with healthy controls by integrating two mRNA expression profiles (GSE73754 and GSE25101) and SNP microarray data (GSE39428) collected from the Gene Expression Omnibus (GEO). Using the t­test, 1,056 and 1,073 DEGs were identified in the GSE73754 and GSE25101 datasets, respectively. Among them, 234 DEGs were found to be shared in both datasets, which were subsequently overlapped with 122 differential SNPs of genes in the GSE39428 dataset, resulting in identification of two common genes [eukaryotic translation elongation factor 1 epsilon 1 (EEF1E1) and serpin family A member 1 (SERPINA1)]. Their expression levels were significantly upregulated and the average expression log R ratios of SNP sites in these genes were significantly higher in AS patients than those in controls. Function enrichment analysis revealed that EEF1E1 was involved in AS by influencing the aminoacyl­tRNA biosynthesis, while SERPINA1 may be associated with AS by participating in platelet degranulation. However, only the genotype and allele frequencies of SNPs (rs7763907 and rs7751386) in EEF1E1 between AS and controls were significantly different between AS and the controls, but not SERPINA1. These findings suggest that EEF1E1 may be an underlying genetic biomarker for the diagnosis of AS.


Assuntos
Biomarcadores/metabolismo , Fatores de Alongamento de Peptídeos/genética , Espondilite Anquilosante/diagnóstico , Proteínas Supressoras de Tumor/genética , Alelos , Estudos de Casos e Controles , Bases de Dados Genéticas , Frequência do Gene , Genótipo , Humanos , Polimorfismo de Nucleotídeo Único , Mapas de Interação de Proteínas/genética , RNA de Transferência/metabolismo , Espondilite Anquilosante/genética , Transcriptoma , alfa 1-Antitripsina/genética
7.
Int J Mol Sci ; 20(9)2019 May 09.
Artigo em Inglês | MEDLINE | ID: mdl-31075877

RESUMO

We investigated whether likely pathogenic variants co-segregating with gastroschisis through a family-based approach using bioinformatic analyses were implicated in body wall closure. Gene Ontology (GO)/Panther functional enrichment and protein-protein interaction analysis by String identified several biological networks of highly connected genes in UGT1A3, UGT1A4, UGT1A5, UGT1A6, UGT1A7, UGT1A8, UGT1A9, UGT1A10, AOX1, NOTCH1, HIST1H2BB, RPS3, THBS1, ADCY9, and FGFR4. SVS-PhoRank identified a dominant model in OR10G4 (also as heterozygous de novo), ITIH3, PLEKHG4B, SLC9A3, ITGA2, AOX1, and ALPP, including a recessive model in UGT1A7, UGT1A6, PER2, PTPRD, and UGT1A3. A heterozygous compound model was observed in CDYL, KDM5A, RASGRP1, MYBPC2, PDE4DIP, F5, OBSCN, and UGT1A. These genes were implicated in pathogenetic pathways involving the following GO related categories: xenobiotic, regulation of metabolic process, regulation of cell adhesion, regulation of gene expression, inflammatory response, regulation of vascular development, keratinization, left-right symmetry, epigenetic, ubiquitination, and regulation of protein synthesis. Multiple background modifiers interacting with disease-relevant pathways may regulate gastroschisis susceptibility. Based in our findings and considering the plausibility of the biological pattern of mechanisms and gene network modeling, we suggest that the gastroschisis developmental process may be the consequence of several well-orchestrated biological and molecular mechanisms which could be interacting with gastroschisis predispositions within the first ten weeks of development.


Assuntos
Parede Abdominal/patologia , Biologia Computacional/métodos , Gastrosquise/genética , Variação Genética , Ontologia Genética , Humanos , Padrões de Herança/genética , Mapas de Interação de Proteínas/genética , Recidiva
8.
Nat Commun ; 10(1): 2180, 2019 05 16.
Artigo em Inglês | MEDLINE | ID: mdl-31097707

RESUMO

Most combination therapies are developed based on targets of existing drugs, which only represent a small portion of the human proteome. We introduce a network controllability-based method, OptiCon, for de novo identification of synergistic regulators as candidates for combination therapy. These regulators jointly exert maximal control over deregulated genes but minimal control over unperturbed genes in a disease. Using data from three cancer types, we show that 68% of predicted regulators are either known drug targets or have a critical role in cancer development. Predicted regulators are depleted for known proteins associated with side effects. Predicted synergy is supported by disease-specific and clinically relevant synthetic lethal interactions and experimental validation. A significant portion of genes regulated by synergistic regulators participate in dense interactions between co-regulated subnetworks and contribute to therapy resistance. OptiCon represents a general framework for systemic and de novo identification of synergistic regulators underlying a cellular state transition.


Assuntos
Protocolos de Quimioterapia Combinada Antineoplásica/farmacologia , Biologia Computacional/métodos , Redes Reguladoras de Genes/efeitos dos fármacos , Neoplasias/genética , Mapas de Interação de Proteínas/efeitos dos fármacos , Células A549 , Algoritmos , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Conjuntos de Dados como Assunto , Sinergismo Farmacológico , Quimioterapia Combinada/métodos , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Redes Reguladoras de Genes/genética , Células HEK293 , Humanos , Células MCF-7 , Modelos Genéticos , Terapia de Alvo Molecular/métodos , Mutação , Neoplasias/tratamento farmacológico , Neoplasias/patologia , Mapas de Interação de Proteínas/genética , Transdução de Sinais/efeitos dos fármacos , Transdução de Sinais/genética
9.
Lipids Health Dis ; 18(1): 107, 2019 May 01.
Artigo em Inglês | MEDLINE | ID: mdl-31043156

RESUMO

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) refers to a series of diseases caused by atherosclerosis (AS). It is one of the most important causes of death worldwide. According to the inflammatory response theory, macrophages play a critical role in AS. However, the potential targets associated with macrophages in the development of AS are still obscure. This study aimed to use bioinformatics tools for screening and identifying molecular targets in AS macrophages. METHODS: Two expression profiling datasets (GSE7074 and GSE9874) were obtained from the Gene Expression Omnibus dataset, and differentially expressed genes (DEGs) between non-AS macrophages and AS macrophages were identified. Functional annotation of the DEGs was performed by analyzing the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. STRING and Cytoscape were employed for constructing a protein-protein interaction network and analyzing hub genes. RESULTS: A total of 98 DEGs were distinguished between non-AS macrophages and AS macrophages. The functional variations in DEGs were mainly enriched in response to hypoxia, respiratory gaseous exchange, protein binding, and intracellular, ciliary tip, early endosome membrane, and Lys63-specific deubiquitinase activities. Three genes were identified as hub genes, including KDELR3, CD55, and DYNC2H1. CONCLUSION: Hub genes and DEGs identified by using microarray techniques can be used as diagnostic and therapeutic biomarkers for AS.


Assuntos
Aterosclerose/genética , Biomarcadores/metabolismo , Macrófagos/metabolismo , Análise de Sequência com Séries de Oligonucleotídeos , Análise por Conglomerados , Perfilação da Expressão Gênica , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Anotação de Sequência Molecular , Mapas de Interação de Proteínas/genética
10.
PLoS Comput Biol ; 15(5): e1007052, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-31075101

RESUMO

Protein domains are basic functional units of proteins. Many protein domains are pervasive among diverse biological processes, yet some are associated with specific pathways. Human complex diseases are generally viewed as pathway-level disorders. Therefore, we hypothesized that pathway-specific domains could be highly informative for human diseases. To test the hypothesis, we developed a network-based scoring scheme to quantify specificity of domain-pathway associations. We first generated domain profiles for human proteins, then constructed a co-pathway protein network based on the associations between domain profiles. Based on the score, we classified human protein domains into pathway-specific domains (PSDs) and non-specific domains (NSDs). We found that PSDs contained more pathogenic variants than NSDs. PSDs were also enriched for disease-associated mutations that disrupt protein-protein interactions (PPIs) and tend to have a moderate number of domain interactions. These results suggest that mutations in PSDs are likely to disrupt within-pathway PPIs, resulting in functional failure of pathways. Finally, we demonstrated the prediction capacity of PSDs for disease-associated genes with experimental validations in zebrafish. Taken together, the network-based quantitative method of modeling domain-pathway associations presented herein suggested underlying mechanisms of how protein domains associated with specific pathways influence mutational impacts on diseases via perturbations in within-pathway PPIs, and provided a novel genomic feature for interpreting genetic variants to facilitate the discovery of human disease genes.


Assuntos
Doença/etiologia , Domínios Proteicos , Mapas de Interação de Proteínas , Animais , Animais Geneticamente Modificados , Biologia Computacional , Doença da Artéria Coronariana/etiologia , Doença da Artéria Coronariana/genética , Doença da Artéria Coronariana/metabolismo , Doença/genética , Predisposição Genética para Doença , Variação Genética , Estudo de Associação Genômica Ampla , Humanos , Modelos Animais , Modelos Biológicos , Mutação , Polimorfismo de Nucleotídeo Único , Domínios Proteicos/genética , Mapeamento de Interação de Proteínas , Mapas de Interação de Proteínas/genética , Peixe-Zebra/genética
11.
Cell Prolif ; 52(4): e12634, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31094043

RESUMO

OBJECTIVES: Guillain-Barré syndrome (GBS) is a type of acute autoimmune disease, which occurs in peripheral nerves and their roots. There is extensive evidence that suggests many immune-associated genes have essential roles in GBS. However, the associations between immune genes and GBS have not been sufficiently examined as most previous studies have only focused on individual genes rather than their entire interaction networks. MATERIALS AND METHODS: In this study, multiple levels of data including immune-associated genes, GBS-associated genes, protein-protein interaction (PPI) networks and gene expression profiles were integrated, and an immune or GBS-directed neighbour co-expressed network (IOGDNC network) and a GBS-directed neighbour co-expressed network (GDNC network) were constructed. RESULTS: Our analysis shows the immune-associated genes are strongly related to GBS-associated genes whether at the interaction level or gene expression level. Five immune-associated modules were also identified which could distinguish between GBS and normal samples. In addition, functional analysis indicated that immune-associated genes are essential in GBS. CONCLUSIONS: Overall, these results highlight a strong relationship between immune-associated genes and GBS existed and provide a potential role for immune-associated genes as novel diagnostic and therapeutic biomarkers for GBS.


Assuntos
Síndrome de Guillain-Barré/genética , Transcriptoma/genética , Humanos , Mapas de Interação de Proteínas/genética
12.
Nat Commun ; 10(1): 1841, 2019 04 23.
Artigo em Inglês | MEDLINE | ID: mdl-31015463

RESUMO

Transcriptional reprogramming of cellular metabolism is a hallmark of cancer. However, systematic approaches to study the role of transcriptional regulators (TRs) in mediating cancer metabolic rewiring are missing. Here, we chart a genome-scale map of TR-metabolite associations in human cells using a combined computational-experimental framework for large-scale metabolic profiling of adherent cell lines. By integrating intracellular metabolic profiles of 54 cancer cell lines with transcriptomic and proteomic data, we unraveled a large space of associations between TRs and metabolic pathways. We found a global regulatory signature coordinating glucose- and one-carbon metabolism, suggesting that regulation of carbon metabolism in cancer may be more diverse and flexible than previously appreciated. Here, we demonstrate how this TR-metabolite map can serve as a resource to predict TRs potentially responsible for metabolic transformation in patient-derived tumor samples, opening new opportunities in understanding disease etiology, selecting therapeutic treatments and in designing modulators of cancer-related TRs.


Assuntos
Transformação Celular Neoplásica/patologia , Regulação Neoplásica da Expressão Gênica , Neoplasias/genética , Mapas de Interação de Proteínas/genética , Fatores de Transcrição/metabolismo , Linhagem Celular Tumoral , Transformação Celular Neoplásica/genética , Transformação Celular Neoplásica/metabolismo , Perfilação da Expressão Gênica/métodos , Genoma Humano , Humanos , Redes e Vias Metabólicas , Metaboloma , Metabolômica/métodos , Neoplasias/metabolismo , Neoplasias/patologia , Mapeamento de Interação de Proteínas , Proteômica/métodos , Transcriptoma
13.
Biomed Res Int ; 2019: 2725192, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31032340

RESUMO

To better understand the molecular mechanism for the pathogenesis of follicular thyroid carcinoma (FTC), this study aimed at identifying key miRNAs and their target genes associated with FTC, as well as analyzing their interactions. Based on the gene microarray data GSE82208 and microRNA dataset GSE62054, the differentially expressed genes (DEGs) and microRNAs (DEMs) were obtained using R and SAM software. The common DEMs from R and SAM were fed to three different bioinformatic tools, TargetScan, miRDB, and miRTarBase, respectively, to predict their biological targets. With DEGs intersected with target genes of DEMs, the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed through the DAVID database. Then a protein-protein interaction (PPI) network was constructed by STRING. Finally, the module analysis for PPI network was performed by MCODE and BiNGO. A total of nine DEMs were identified, and their function might work through regulating hub genes in the PPI network especially KIT and EGFR. KEGG analysis showed that intersection genes were enriched in the PI3K-Akt signaling pathway and microRNAs in cancer. In conclusion, the study of miRNA-mRNA network would offer molecular support for differential diagnosis between malignant FTC and benign FTA, providing new insights into the potential targets for follicular thyroid carcinoma diagnosis and treatment.


Assuntos
Adenocarcinoma Folicular/genética , MicroRNAs/genética , Mapas de Interação de Proteínas/genética , Transcriptoma/genética , Adenocarcinoma Folicular/patologia , Biomarcadores Tumorais/genética , Biologia Computacional , Regulação Neoplásica da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , Humanos , Fosfatidilinositol 3-Quinases/genética , Proteínas Proto-Oncogênicas c-akt/genética , Transdução de Sinais/genética , Software
14.
Mol Cell ; 74(4): 758-770.e4, 2019 05 16.
Artigo em Inglês | MEDLINE | ID: mdl-30982746

RESUMO

The cyclin-dependent kinases Cdk4 and Cdk6 form complexes with D-type cyclins to drive cell proliferation. A well-known target of cyclin D-Cdk4,6 is the retinoblastoma protein Rb, which inhibits cell-cycle progression until its inactivation by phosphorylation. However, the role of Rb phosphorylation by cyclin D-Cdk4,6 in cell-cycle progression is unclear because Rb can be phosphorylated by other cyclin-Cdks, and cyclin D-Cdk4,6 has other targets involved in cell division. Here, we show that cyclin D-Cdk4,6 docks one side of an alpha-helix in the Rb C terminus, which is not recognized by cyclins E, A, and B. This helix-based docking mechanism is shared by the p107 and p130 Rb-family members across metazoans. Mutation of the Rb C-terminal helix prevents its phosphorylation, promotes G1 arrest, and enhances Rb's tumor suppressive function. Our work conclusively demonstrates that the cyclin D-Rb interaction drives cell division and expands the diversity of known cyclin-based protein docking mechanisms.


Assuntos
Proliferação de Células/genética , Ciclina D/genética , Mapas de Interação de Proteínas/genética , Proteína do Retinoblastoma/genética , Ciclo Celular/genética , Proteína Substrato Associada a Crk/genética , Ciclina D/química , Quinase 4 Dependente de Ciclina/química , Quinase 4 Dependente de Ciclina/genética , Quinase 6 Dependente de Ciclina/química , Quinase 6 Dependente de Ciclina/genética , Ciclinas/genética , Fase G1/genética , Humanos , Simulação de Acoplamento Molecular , Fosforilação/genética , Ligação Proteica/genética , Conformação Proteica em alfa-Hélice/genética , Proteína do Retinoblastoma/química , Proteína p107 Retinoblastoma-Like/genética , Fase S/genética
15.
Med Sci Monit ; 25: 2488-2504, 2019 Apr 05.
Artigo em Inglês | MEDLINE | ID: mdl-30948703

RESUMO

BACKGROUND Globally, gastric cancer (GC) is the third most common source of cancer-associated mortality. The aim of this study was to identify key genes and circular RNAs (circRNAs) in GC diagnosis, prognosis, and therapy and to further explore the potential molecular mechanisms of GC. MATERIAL AND METHODS Differentially expressed genes (DEGs) and circRNAs (DE circRNAs) between GC tissues and adjacent non-tumor tissues were identified from 3 mRNA and 3 circRNA expression profiles. Functional analyses were performed, and protein-protein interaction (PPI) networks were constructed. The significant modules and key genes in the PPI networks were identified. Kaplan-Meier analysis was performed to evaluate the prognostic value of these key genes. Potential miRNA-binding sites of the DE circRNAs and target genes of these miRNAs were predicted and used to construct DE circRNA-miRNA-mRNA networks. RESULTS A total of 196 upregulated and 311 downregulated genes were identified in GC. The results of functional analysis showed that these DEGs were significantly enriched in a variety of functions and pathways, including extracellular matrix-related pathways. Ten hub genes (COL1A1, COL3A1, COL1A2, COL5A2, FN1, THBS1, COL5A1, SPARC, COL18A1, and COL11A1) were identified via PPI network analysis. Kaplan-Meier analysis revealed that 7 of these were associated with a poor overall survival in GC patients. Furthermore, we identified 2 DE circRNAs, hsa_circ_0000332 and hsa_circ_0021087. To reveal the potential molecular mechanisms of circRNAs in GC, DE circRNA-microRNA-mRNA networks were constructed. CONCLUSIONS Key candidate genes and circRNAs were identified, and novel PPI and circRNA-microRNA-mRNA networks in GC were constructed. These may provide useful information for the exploration of potential biomarkers and targets for the diagnosis, prognosis, and therapy of GC.


Assuntos
RNA/genética , Neoplasias Gástricas/genética , Biomarcadores , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , Humanos , Estimativa de Kaplan-Meier , MicroRNAs/genética , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Prognóstico , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/genética , RNA/metabolismo , RNA Mensageiro/genética
16.
PLoS Comput Biol ; 15(4): e1006888, 2019 04.
Artigo em Inglês | MEDLINE | ID: mdl-30995217

RESUMO

In response to a need for improved treatments, a number of promising novel targeted cancer therapies are being developed that exploit human synthetic lethal interactions. This is facilitating personalised medicine strategies in cancers where specific tumour suppressors have become inactivated. Mainly due to the constraints of the experimental procedures, relatively few human synthetic lethal interactions have been identified. Here we describe SLant (Synthetic Lethal analysis via Network topology), a computational systems approach to predicting human synthetic lethal interactions that works by identifying and exploiting conserved patterns in protein interaction network topology both within and across species. SLant out-performs previous attempts to classify human SSL interactions and experimental validation of the models predictions suggests it may provide useful guidance for future SSL screenings and ultimately aid targeted cancer therapy development.


Assuntos
Mapas de Interação de Proteínas/genética , Mutações Sintéticas Letais , Algoritmos , Animais , Inteligência Artificial , Biologia Computacional , Descoberta de Drogas , Ontologia Genética , Genes Essenciais , Humanos , Modelos Biológicos , Terapia de Alvo Molecular , Família Multigênica , Neoplasias/genética , Neoplasias/metabolismo , Neoplasias/terapia , Mapeamento de Interação de Proteínas/estatística & dados numéricos , Mapas de Interação de Proteínas/efeitos dos fármacos , Biologia Sintética , Mutações Sintéticas Letais/genética , Proteínas Supressoras de Tumor/genética , Proteínas Supressoras de Tumor/metabolismo
17.
Med Sci Monit ; 25: 2609-2622, 2019 Apr 09.
Artigo em Inglês | MEDLINE | ID: mdl-30965350

RESUMO

BACKGROUND More and more recent studies have clearly shown that long non-coding RNA (lncRNA) should be considered as a fundamental part of the ceRNA network, mainly because lncRNA can act as miRNA sponges to regulate the protein-coding gene expression. Nevertheless, it is still not clear how lncRNA-mediated ceRNAs function in cervical squamous cell carcinoma (CESC). Moreover, information about the ceRNA regulatory mechanism is also remarkably limited; thus, prediction of CESC prognosis using ceRNA-related information remains challenging. MATERIAL AND METHODS We collected 306 RNA (lncRNA, miRNA, and mRNA) expression profile datasets obtained from cervical squamous cancer tissues plus 3 more from adjacent cervical tissues via the TCGA database. Subsequently, we constructed a lncRNAs-miRNAs-mRNAs CESC ceRNA network, and Gene Ontology (GO) analysis was carried out. RESULTS We identified a total of 30 DElncRNAs, 70 DEmiRNAs, and 1089 DEmRNAs in CESC. Subsequently, to reveal the expression patterns of dysregulated genes, weighted gene co-expression network analysis was carried out, resulting in 3 co-expression modules with significantly related clinical properties. The constructed aberrant lncRNAs-miRNAs-mRNAs CESC ceRNA network was composed of 17 DEmiRNAs, 5 DElncRNAs, and 7 DEmRNAs. Moreover, the survival analysis was performed for DElncRNAs, DEmiRNAs, and DEmRNAs. CONCLUSIONS The present study shows the involvement of the lncRNA-related ceRNA network in the pathogenesis of CESC. We believe the newly generated ceRNA network will provide more insights into the lncRNA-mediated ceRNA regulatory mechanisms.


Assuntos
Carcinoma de Células Escamosas/genética , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , RNA Longo não Codificante/genética , RNA Neoplásico/genética , Neoplasias do Colo do Útero/genética , Feminino , Ontologia Genética , Genes Neoplásicos , Humanos , Estimativa de Kaplan-Meier , MicroRNAs/genética , MicroRNAs/metabolismo , Pessoa de Meia-Idade , Mapas de Interação de Proteínas/genética , RNA Longo não Codificante/metabolismo , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , RNA Neoplásico/metabolismo
18.
Mol Med Rep ; 19(5): 3989-4000, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30942443

RESUMO

Type 1 diabetes (T1D) is an autoimmune disease that is typically diagnosed in children. The aim of the present study was to identify potential genes involved in the pathogenesis of childhood T1D. Two datasets of mRNA expression in children with T1D were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) in children with T1D were identified. Functional analysis was performed and a protein­protein interaction (PPI) network was constructed, as was a transcription factor (TF)­target network. The expression of selected DEGs was further assessed using reverse transcription­quantitative polymerase chain reaction (RT­qPCR) analysis. Electronic validation and diagnostic value analysis of the identified DEGs [cytokine inducible SH2 containing protein (CISH), SR­related CTD associated factor 11 (SCAF11), estrogen receptor 1 (ESR1), Rho GTPase activating protein 25 (ARHGAP25), major histocompatibility complex, class II, DR ß4 (HLA­DRB4) and interleukin 23 subunit α (IL23A)] was performed in the GEO dataset. Compared with the normal control group, a total of 1,467 DEGs with P<0.05 were identified in children with T1D. CISH and SCAF11 were determined to be the most up­ and downregulated genes, respectively. Heterogeneous nuclear ribonucleoprotein D (HNRNPD; degree=33), protein kinase AMP­activated catalytic subunit α1 (PRKAA1; degree=11), integrin subunit α4 (ITGA4; degree=8) and ESR1 (degree=8) were identified in the PPI network as high­degree genes. ARHGAP25 (degree=12), HNRNPD (degree=10), HLA­DRB4 (degree=10) and IL23A (degree=9) were high­degree genes identified in the TF­target network. RT­qPCR revealed that the expression of HNRNPD, PRKAA1, ITGA4 and transporter 2, ATP binding cassette subfamily B member was consistent with the results of the integrated analysis. Furthermore, the results of the electronic validation were consistent with the bioinformatics analysis. SCAF11, CISH and ARHGAP25 were identified to possess value as potential diagnostic markers for children with T1D. In conclusion, identifying DEGs in children with T1D may contribute to our understanding of its pathogenesis, and such DEGs may be used as diagnostic biomarkers for children with T1D.


Assuntos
Diabetes Mellitus Tipo 1/diagnóstico , Transcriptoma , Área Sob a Curva , Estudos de Casos e Controles , Criança , Diabetes Mellitus Tipo 1/genética , Receptor alfa de Estrogênio/genética , Receptor alfa de Estrogênio/metabolismo , Feminino , Redes Reguladoras de Genes , Humanos , Masculino , Mapas de Interação de Proteínas/genética , Curva ROC , Fatores de Processamento de Serina-Arginina/genética , Fatores de Processamento de Serina-Arginina/metabolismo , Proteínas Supressoras da Sinalização de Citocina/genética , Proteínas Supressoras da Sinalização de Citocina/metabolismo
19.
Molecules ; 24(7)2019 Apr 05.
Artigo em Inglês | MEDLINE | ID: mdl-30959812

RESUMO

Peptide⁻protein interactions are corner-stones of living functions involved in essential mechanisms, such as cell signaling. Given the difficulty of obtaining direct experimental structural biology data, prediction of those interactions is of crucial interest for the rational development of new drugs, notably to fight diseases, such as cancer or Alzheimer's disease. Because of the high flexibility of natural unconstrained linear peptides, prediction of their binding mode in a protein cavity remains challenging. Several theoretical approaches have been developed in the last decade to address this issue. Nevertheless, improvements are needed, such as the conformation prediction of peptide side-chains, which are dependent on peptide length and flexibility. Here, we present a novel in silico method, Iterative Residue Docking and Linking (IRDL), to efficiently predict peptide⁻protein interactions. In order to reduce the conformational space, this innovative method splits peptides into several short segments. Then, it uses the performance of intramolecular covalent docking to rebuild, sequentially, the complete peptide in the active site of its protein target. Once the peptide is constructed, a rescoring step is applied in order to correctly rank all IRDL solutions. Applied on a set of 11 crystallized peptide⁻protein complexes, the IRDL method shows promising results, since it is able to retrieve experimental binding conformations with a Root Mean Square Deviation (RMSD) below 2 Šin the top five ranked solutions. For some complexes, IRDL method outperforms two other docking protocols evaluated in this study. Hence, IRDL is a new tool that could be used in drug design projects to predict peptide⁻protein interactions.


Assuntos
Fenômenos Biofísicos , Peptídeos/química , Mapas de Interação de Proteínas/genética , Proteínas/química , Sítios de Ligação , Simulação por Computador , Humanos , Simulação de Acoplamento Molecular , Peptídeos/genética , Ligação Proteica , Conformação Proteica , Proteínas/genética
20.
Med Sci Monit ; 25: 2246-2256, 2019 Mar 27.
Artigo em Inglês | MEDLINE | ID: mdl-30916045

RESUMO

BACKGROUND Rheumatoid arthritis (RA) has a high prevalence in the elderly population. The genes and pathways in the inflamed synovium in patients with RA are poorly understood. This study aimed to identify differentially expressed genes (DEGs) linked to the progression of synovial inflammation in RA using bioinformatics analysis. MATERIAL AND METHODS Gene expression profiles of datasets GSE55235 and GSE55457 were acquired from the Gene Expression Omnibus (GEO) database. DEGs were identified using Morpheus software, and co-expressed DEGs were identified with Venn diagrams. Protein-protein interaction (PPI) networks were assembled with Cytoscape software and separated into subnetworks using the Molecular Complex Detection (MCODE) algorithm. The functions of the top module were assessed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. RESULTS DEGs that were upregulated were significantly enhanced in protein binding, the cell cytosol, organization of the extracellular matrix (ECM), regulation of RNA transcription, and cell adhesion. DEGs that were downregulated were associated with control of the immune response, B-cell and T-cell receptor signaling pathway regulation. KEGG pathway analysis showed that upregulated DEGs enhanced pathways associated with the cell adherens junction, osteoclast differentiation, and hereditary cardiomyopathies. Downregulated DEGs were enriched in primary immunodeficiency, cell adhesion molecules (CAMs), cytokine-cytokine receptor interaction, and hematopoietic cell lineages. CONCLUSIONS The findings from this bioinformatics network analysis study identified molecular mechanisms and the key hub genes that may contribute to synovial inflammation in patients with RA.


Assuntos
Artrite Reumatoide/genética , Artrite Reumatoide/fisiopatologia , Membrana Sinovial/fisiologia , Artrite Reumatoide/metabolismo , China , Biologia Computacional/métodos , Bases de Dados Genéticas , Perfilação da Expressão Gênica/métodos , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Inflamação/metabolismo , Osteoartrite/genética , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas/genética , Transdução de Sinais , Software , Membrana Sinovial/imunologia , Membrana Sinovial/metabolismo , Transcriptoma/genética
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