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1.
Medicine (Baltimore) ; 100(17): e25596, 2021 Apr 30.
Artículo en Inglés | MEDLINE | ID: mdl-33907110

RESUMEN

BACKGROUND: As the most common type of cerebrovascular disease, ischemic stroke is the disturbance of cerebrovascular circulation caused by various factors, with complex pathogenesis. At present, the molecular mechanism of ischemic stroke is still unclear, and there lacks early diagnostic markers. Therefore, there is an urgent need to find effective preventive measures, active diagnostic methods and rapid treatment measures. In recent years, related studies have displayed that long noncoding RNAs (lncRNAs) is related to the prognosis of ischemic stroke. However, the results are not supported by some evidence. Therefore, in this study, meta-analysis was used to analyze the relationship between lncRNAs and the prognosis of ischemic stroke. In addition, we carried out bioinformatics analysis to study the action mechanism and related pathways of lncRNAs in ischemic stroke. METHODS: Literature search was operated on databases up to March 2021, including China National Knowledge Infrastructure, Chinese Biomedical literature Database, Chinese Scientific and Journal Database, Wan Fang database, Web of Science, PubMed, and EMBASE. The relationship between lncRNAs expression and survival outcome was estimated by hazard ratio (HR) and 95% confidence interval (CI). Meta-analysis was conducted on the Stata 16.0. Starbase v2.0 software predicts microRNAs (miRNAs) that interacts with lncRNAs. In addition, HMDD v2.0 database filters out miRNAs related to ischemic stroke. Furthermore, Consite transcription factor database was used to predict the transcription factors of each lncRNAs and miRNA. At the same time, the transcription factors related to ischemic stroke were screened out after intersection. miRwalk online software was applied to predict the target mRNA of each miRNA, and the common target genes were screened by consistent method. The molecular regulatory network map of lncRNAs in ischemic stroke was drawn. Based on the overlapping target genes, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) network analysis were carried out to explore the possible mechanism. RESULTS: The results of this meta-analysis would be submitted to peer-reviewed journals for publication. CONCLUSION: This study will provide evidence-based medical evidence for the relationship between lncRNA and the prognosis of ischemic stroke. What is more, bioinformatics analysis will provide ideas for the study of ischemic stroke mechanism. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also should not damage participants' rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/QBZW6.


Asunto(s)
Biología Computacional/métodos , ARN Largo no Codificante/sangre , Biomarcadores/sangre , Bases de Datos Genéticas , Ontología de Genes , Humanos , /mortalidad , Metaanálisis como Asunto , MicroARNs/sangre , Pronóstico , Modelos de Riesgos Proporcionales , Mapeo de Interacción de Proteínas , Proyectos de Investigación , Análisis de Supervivencia , Factores de Transcripción/sangre
2.
Nat Commun ; 12(1): 2070, 2021 04 06.
Artículo en Inglés | MEDLINE | ID: mdl-33824334

RESUMEN

The Drosophila tumour necrosis factor (TNF) ligand-receptor system consists of a unique ligand, Eiger (Egr), and two receptors, Grindelwald (Grnd) and Wengen (Wgn), and therefore provides a simple system for exploring the interplay between ligand and receptors, and the requirement for Grnd and Wgn in TNF/Egr-mediated processes. Here, we report the crystallographic structure of the extracellular domain (ECD) of Grnd in complex with Egr, a high-affinity hetero-hexameric assembly reminiscent of human TNF:TNFR complexes. We show that ectopic expression of Egr results in internalisation of Egr:Grnd complexes in vesicles, a step preceding and strictly required for Egr-induced apoptosis. We further demonstrate that Wgn binds Egr with much reduced affinity and is localised in intracellular vesicles that are distinct from those containing Egr:Grnd complexes. Altogether, our data provide insight into ligand-mediated activation of Grnd and suggest that distinct affinities of TNF ligands for their receptors promote different and non-redundant cellular functions.


Asunto(s)
Proteínas de Drosophila/metabolismo , Drosophila melanogaster/citología , Drosophila melanogaster/metabolismo , Receptores del Factor de Necrosis Tumoral/metabolismo , Secuencia de Aminoácidos , Animales , Apoptosis , Vesículas Citoplasmáticas/metabolismo , Proteínas de Drosophila/química , Endocitosis , Discos Imaginales/citología , Discos Imaginales/metabolismo , Proteínas de la Membrana/química , Proteínas de la Membrana/metabolismo , Unión Proteica , Dominios Proteicos , Mapeo de Interacción de Proteínas
3.
BMC Cancer ; 21(1): 381, 2021 Apr 09.
Artículo en Inglés | MEDLINE | ID: mdl-33836688

RESUMEN

BACKGROUND: The role of glycolysis in tumorigenesis has received increasing attention and multiple glycolysis-related genes (GRGs) have been proven to be associated with tumor metastasis. Hence, we aimed to construct a prognostic signature based on GRGs for clear cell renal cell carcinoma (ccRCC) and to explore its relationships with immune infiltration. METHODS: Clinical information and RNA-sequencing data of ccRCC were obtained from The Cancer Genome Atlas (TCGA) and ArrayExpress datasets. Key GRGs were finally selected through univariate COX, LASSO and multivariate COX regression analyses. External and internal verifications were further carried out to verify our established signature. RESULTS: Finally, 10 GRGs including ANKZF1, CD44, CHST6, HS6ST2, IDUA, KIF20A, NDST3, PLOD2, VCAN, FBP1 were selected out and utilized to establish a novel signature. Compared with the low-risk group, ccRCC patients in high-risk groups showed a lower overall survival (OS) rate (P = 5.548Ee-13) and its AUCs based on our established signature were all above 0.70. Univariate/multivariate Cox regression analyses further proved that this signature could serve as an independent prognostic factor (all P < 0.05). Moreover, prognostic nomograms were also created to find out the associations between the established signature, clinical factors and OS for ccRCC in both the TCGA and ArrayExpress cohorts. All results remained consistent after external and internal verification. Besides, nine out of 21 tumor-infiltrating immune cells (TIICs) were highly related to high- and low- risk ccRCC patients stratified by our established signature. CONCLUSIONS: A novel signature based on 10 prognostic GRGs was successfully established and verified externally and internally for predicting OS of ccRCC, helping clinicians better and more intuitively predict patients' survival.


Asunto(s)
Biomarcadores de Tumor , Carcinoma de Células Renales/genética , Carcinoma de Células Renales/mortalidad , Glucólisis/genética , Neoplasias Renales/genética , Neoplasias Renales/mortalidad , Carcinoma de Células Renales/diagnóstico , Carcinoma de Células Renales/metabolismo , Biología Computacional/métodos , Femenino , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Ontología de Genes , Humanos , Estimación de Kaplan-Meier , Neoplasias Renales/diagnóstico , Neoplasias Renales/metabolismo , Linfocitos Infiltrantes de Tumor/inmunología , Linfocitos Infiltrantes de Tumor/metabolismo , Masculino , Clasificación del Tumor , Estadificación de Neoplasias , Nomogramas , Pronóstico , Modelos de Riesgos Proporcionales , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas , Curva ROC , Reproducibilidad de los Resultados , Transducción de Señal , Transcriptoma
4.
BMC Cancer ; 21(1): 411, 2021 Apr 15.
Artículo en Inglés | MEDLINE | ID: mdl-33858375

RESUMEN

BACKGROUND: Little data is available on prognostic biomarkers and effective treatment options for Kidney Renal Papillary Cell Carcinoma (KIRP) patients, to find potential prognostic biomarkers and new targets was an urgent mission for KIRP therapy. METHODS: The differentially expressed autophagy-related genes (DEARGs) were screened out according to the RNA sequencing data in The Cancer Genome Atlas database, then identified survival-related DEARGs to establish a prognostic model for survival predicting of KIRP patients. Then we verified the robustness and validity of the prognostic risk model through clinicopathological data. At last, we evaluate the prognostic value of genes that formed the prognostic risk model individually. RESULTS: We analyzed the expression of 232 autophagy-related genes (ARGs) in 289 KIRP and 32 non-tumor tissue cases, and 40 mRNAs were screened out as DEARGs. The functional and pathway enrichment analysis was done and protein-protein interaction network was constructed for all DEARGs. To sift candidate DEARGs associated with KIRP patients' survival and create an autophagy-related risk prognostic model, univariate and multivariate Cox regression analysis were did separately. Eventually 3 desirable independent prognostic DEARGs (P4HB, NRG1, and BIRC5) were picked out and used for construct the autophagy-related risk model. The accuracy of the prognostic risk model for survival prediction was assessed by Kaplan-Meier plotter, receiver-operator characteristic curve, and clinicopathological correlational analyses. The prognostic value of above 3 genes was verified individually by survival analysis and expression analysis on mRNA and protein level. CONCLUSIONS: The autophagy-related prognostic model is accurate and applicable, it can predict OS independently for KIRP patients. Three independent prognostic DEARGs can benefit for facilitate personalized target treatment too.


Asunto(s)
Proteínas Relacionadas con la Autofagia/genética , Biomarcadores de Tumor , Carcinoma de Células Renales/diagnóstico , Carcinoma de Células Renales/genética , Neoplasias Renales/diagnóstico , Neoplasias Renales/genética , Autofagia/genética , Carcinoma de Células Renales/mortalidad , Perfilación de la Expresión Génica , Humanos , Neoplasias Renales/mortalidad , Pronóstico , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas , Curva ROC , Reproducibilidad de los Resultados , Transcriptoma
5.
Medicine (Baltimore) ; 100(16): e25433, 2021 Apr 23.
Artículo en Inglés | MEDLINE | ID: mdl-33879674

RESUMEN

ABSTRACT: Discoid lupus erythematosus (DLE) is the most common skin manifestation of lupus; however, the molecular mechanisms underlying DLE remain unknown. Therefore, we aimed to identify key differentially expressed genes (DEGs) in discoid lupus skin and investigate their potential pathways.To identify candidate genes involved in the occurrence and development of the disease, we downloaded the microarray datasets GSE52471 and GSE72535 from the Gene Expression Database (GEO). DEGs between discoid lupus skin and normal controls were selected using the GEO2R tool and Venn diagram software (http://bioinformatics.psb.ugent.be/webtools/Venn/). The Database for Annotation, Visualization, and Integrated Discovery (DAVID), Enrichr, and Cytoscape ClueGo were used to analyze the Kyoto Encyclopedia of Gene and Genome pathways and gene ontology. Protein-protein interactions (PPIs) of these DEGs were further assessed using the Search Tool for the Retrieval Interacting Genes version 10.0.Seventy three DEGs were co-expressed in both datasets. DEGs were predominantly upregulated in receptor signaling pathways of the immune response. In the PPI network, 69 upregulated genes were selected. Furthermore, 4 genes (CXCL10, ISG15, IFIH1, and IRF7) were found to be significantly upregulated in the RIG-I-like receptor signaling pathway, from analysis of Enrichr and Cytoscape ClueGo.The results of this study may provide new insights into the potential molecular mechanisms of DLE. However, further experimentation is required to confirm these findings.


Asunto(s)
Redes Reguladoras de Genes/inmunología , Lupus Eritematoso Discoide/genética , Quimiocina CXCL10/genética , Biología Computacional , Citocinas/genética , Proteína 58 DEAD Box/metabolismo , Conjuntos de Datos como Asunto , Perfilación de la Expresión Génica , Humanos , Factor 7 Regulador del Interferón/genética , Helicasa Inducida por Interferón IFIH1/genética , Lupus Eritematoso Discoide/epidemiología , Lupus Eritematoso Discoide/inmunología , Lupus Eritematoso Discoide/patología , Análisis de Secuencia por Matrices de Oligonucleótidos , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/genética , Mapas de Interacción de Proteínas/inmunología , Receptores Inmunológicos/metabolismo , Transducción de Señal/genética , Transducción de Señal/inmunología , Piel/inmunología , Piel/patología , Programas Informáticos , Ubiquitinas/genética , Regulación hacia Arriba/inmunología
6.
Medicine (Baltimore) ; 100(16): e25452, 2021 Apr 23.
Artículo en Inglés | MEDLINE | ID: mdl-33879677

RESUMEN

BACKGROUND: Currently, an increasing number of long noncoding RNAs (LncRNAs) have been reported to be abnormally expressed in human carcinomas and play a vital role in tumourigenesis. Some studies have been carried out to investigate the influence of the expression of LncRNA human urothelial carcinoma associated 1 (UCA1) on prognosis and clinical significance in patients with esophageal cancer, but the results are contradictory and uncertain. A meta-analysis and was conducted with controversial data to accurately assess the issue. We collected relevant TCGA data to further testify the result. In addition, bioinformatics analysis was conducted to investigate the mechanism and related pathways of LncRNA UCA1 in esophageal carcinoma. METHODS: Wanfang, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, the Chongqing VIP Chinese Science and Technology Periodical Database, PubMed, Embase, and Web of Science were thoroughly searched for relevant information. Two reviewers independently performed data extraction and literature quality evaluation. Odd ratio and its 95% confidence intervals were applied to evaluate the relationship between LncRNA UCA1 and clinicopathological characteristics of esophageal carcinoma patients. Hazard ratios and its 95% confidence intervals were adopted to assess the prognostic effects of LncRNA UCA1 on overall survival and disease-free survival. Meta-analysis was performed with Stata 14.0 software. To further assess the function of LncRNA UCA1 in esophageal carcinoma, relevant data from The Cancer Genome Atlas (TCGA) database was collected. Three databases, miRWalk, TargetScan, and miRDB, were used for prediction of target genes. Genes present in these 3 databases were considered as predicted target genes of LncRNA UCA1. Venny 2.1 were used for intersection analysis. Subsequently, GO, KEGG, and PPI network analysis were conducted based on the overlapping target genes of LncRNA UCA1 to explore the possible molecular mechanism in esophageal carcinoma. RESULTS: This study provides a high-quality medical evidence for the correlation between LncRNA UCA1 expression and overall survival, and between disease-free survival and clinicopathological features. Based on bioinformatics analysis, this study enhanced the understanding of the mechanism and related pathways of LncRNA UCA1 in esophageal carcinoma. CONCLUSION: The study provides updated evidence to evaluate whether the expression of LncRNA UCA1 is in association with poor prognosis in patients with esophageal carcinoma. ETHICS AND DISSEMINATION: The private information from individuals will not be published. This systematic review also should not damage participants' rights. Ethical approval is not available. The results may be published in a peer-reviewed journal or disseminated in relevant conferences. OSF REGISTRATION NUMBER: DOI 10.17605/OSF.IO/8MCHW.


Asunto(s)
Biomarcadores de Tumor/metabolismo , Carcinoma/mortalidad , Neoplasias Esofágicas/mortalidad , ARN Largo no Codificante/metabolismo , Biomarcadores de Tumor/análisis , Carcinoma/genética , Carcinoma/patología , Biología Computacional , Supervivencia sin Enfermedad , Neoplasias Esofágicas/genética , Neoplasias Esofágicas/patología , Esófago/patología , Regulación Neoplásica de la Expresión Génica , Humanos , Metaanálisis como Asunto , Pronóstico , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/genética , ARN Largo no Codificante/análisis , Revisiones Sistemáticas como Asunto
7.
Nat Commun ; 12(1): 2173, 2021 04 12.
Artículo en Inglés | MEDLINE | ID: mdl-33846289

RESUMEN

The closely related inhibitory killer-cell immunoglobulin-like receptors (KIR), KIR2DL2 and KIR2DL3, regulate the activation of natural killer cells (NK) by interacting with the human leukocyte antigen-C1 (HLA-C1) group of molecules. KIR2DL2, KIR2DL3 and HLA-C1 are highly polymorphic, with this variation being associated with differences in the onset and progression of some human diseases. However, the molecular bases underlying these associations remain unresolved. Here, we determined the crystal structures of KIR2DL2 and KIR2DL3 in complex with HLA-C*07:02 presenting a self-epitope. KIR2DL2 differed from KIR2DL3 in docking modality over HLA-C*07:02 that correlates with variabilty of recognition of HLA-C1 allotypes. Mutagenesis assays indicated differences in the mechanism of HLA-C1 allotype recognition by KIR2DL2 and KIR2DL3. Similarly, HLA-C1 allotypes differed markedly in their capacity to inhibit activation of primary NK cells. These functional differences derive, in part, from KIR2DS2 suggesting KIR2DL2 and KIR2DL3 binding geometries combine with other factors to distinguish HLA-C1 functional recognition.


Asunto(s)
Antígenos HLA-C/metabolismo , Simulación del Acoplamiento Molecular , Receptores KIR2DL2/química , Receptores KIR2DL2/metabolismo , Receptores KIR2DL3/química , Receptores KIR2DL3/metabolismo , Células HEK293 , Humanos , Células Asesinas Naturales/inmunología , Ligandos , Proteínas Mutantes/química , Proteínas Mutantes/metabolismo , Péptidos/química , Unión Proteica , Mapeo de Interacción de Proteínas
8.
BMC Cancer ; 21(1): 244, 2021 Mar 08.
Artículo en Inglés | MEDLINE | ID: mdl-33685397

RESUMEN

BACKGROUND: RNA-binding proteins (RBPs) play crucial and multifaceted roles in post-transcriptional regulation. While RBPs dysregulation is involved in tumorigenesis and progression, little is known about the role of RBPs in bladder cancer (BLCA) prognosis. This study aimed to establish a prognostic model based on the prognosis-related RBPs to predict the survival of BLCA patients. METHODS: We downloaded BLCA RNA sequence data from The Cancer Genome Atlas (TCGA) database and identified RBPs differentially expressed between tumour and normal tissues. Then, functional enrichment analysis of these differentially expressed RBPs was conducted. Independent prognosis-associated RBPs were identified by univariable and multivariable Cox regression analyses to construct a risk score model. Subsequently, Kaplan-Meier and receiver operating characteristic curves were plotted to assess the performance of this prognostic model. Finally, a nomogram was established followed by the validation of its prognostic value and expression of the hub RBPs. RESULTS: The 385 differentially expressed RBPs were identified included 218 and 167 upregulated and downregulated RBPs, respectively. The eight independent prognosis-associated RBPs (EFTUD2, GEMIN7, OAS1, APOBEC3H, TRIM71, DARS2, YTHDC1, and RBMS3) were then used to construct a prognostic prediction model. An in-depth analysis showed lower overall survival (OS) in patients in the high-risk subgroup compared to that in patients in the low-risk subgroup according to the prognostic model. The area under the curve of the time-dependent receiver operator characteristic (ROC) curve were 0.795 and 0.669 for the TCGA training and test datasets, respectively, showing a moderate predictive discrimination of the prognostic model. A nomogram was established, which showed a favourable predictive value for the prognosis of BLCA. CONCLUSIONS: We developed and validated the performance of a prognostic model for BLCA that might facilitate the development of new biomarkers for the prognostic assessment of BLCA patients.


Asunto(s)
Biomarcadores de Tumor/genética , Regulación Neoplásica de la Expresión Génica , Nomogramas , Proteínas de Unión al ARN/genética , Neoplasias de la Vejiga Urinaria/mortalidad , Biología Computacional , Conjuntos de Datos como Asunto , Humanos , Estimación de Kaplan-Meier , Valor Predictivo de las Pruebas , Pronóstico , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/genética , RNA-Seq , Curva ROC , Medición de Riesgo/métodos , Factores de Riesgo , Tasa de Supervivencia , Vejiga Urinaria/patología , Neoplasias de la Vejiga Urinaria/genética , Neoplasias de la Vejiga Urinaria/patología
9.
BMC Cancer ; 21(1): 259, 2021 Mar 10.
Artículo en Inglés | MEDLINE | ID: mdl-33691643

RESUMEN

BACKGROUND: The incidence and mortality of lung cancer are the highest among all cancers. Patients with systemic sclerosis show a four-fold greater risk of lung cancer than the general population. However, the underlying mechanism remains poorly understood. METHODS: The expression profiles of 355 peripheral blood samples were integratedly analyzed, including 70 cases of lung cancer, 61 cases of systemic sclerosis, and 224 healthy controls. After data normalization and cleaning, differentially expressed genes (DEGs) between disease and control were obtained and deeply analyzed by bioinformatics methods. The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed online by DAVID and KOBAS. The protein-protein interaction (PPI) networks were constructed from the STRING database. RESULTS: From a total of 14,191 human genes, 299 and 1644 genes were identified as DEGs in systemic sclerosis and lung cancer, respectively. Among them, 64 DEGs were overlapping, including 36 co-upregulated, 10 co-downregulated, and 18 counter-regulated DEGs. Functional and enrichment analysis showed that the two diseases had common changes in immune-related genes. The expression of innate immune response and response to virus-related genes increased significantly, while the expression of negative regulation of cell cycle-related genes decreased notably. In contrast, the expression of mitophagy regulation, chromatin binding and fatty acid metabolism-related genes showed distinct trends. CONCLUSIONS: Stable differences and similarities between systemic sclerosis and lung cancer were revealed. In peripheral blood, enhanced innate immunity and weakened negative regulation of cell cycle may be the common mechanisms of the two diseases, which may be associated with the high risk of lung cancer in systemic sclerosis patients. On the other hand, the counter-regulated DEGs can be used as novelbiomarkers of pulmonary diseases. In addition, fat metabolism-related DEGs were consideredto be associated with clinical blood lipid data.


Asunto(s)
Biomarcadores de Tumor/genética , Regulación Neoplásica de la Expresión Génica/inmunología , Redes Reguladoras de Genes , Neoplasias Pulmonares/genética , Esclerodermia Sistémica/genética , Estudios de Casos y Controles , Biología Computacional , Conjuntos de Datos como Asunto , Perfilación de la Expresión Génica , Voluntarios Sanos , Humanos , Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/epidemiología , Neoplasias Pulmonares/inmunología , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/genética , Factores de Riesgo , Esclerodermia Sistémica/epidemiología , Esclerodermia Sistémica/inmunología
10.
BMC Cancer ; 21(1): 277, 2021 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-33722210

RESUMEN

BACKGROUND: As one of the novel molecules, circRNA has been identified closely involved in the pathogenesis of many diseases. However, the function of circRNA in acute myeloid leukemia (AML) still remains unknown. METHODS: In the current study, the RNA expression profiles were obtained from Gene Expression Omnibus (GEO) datasets. The differentially expressed RNAs were identified using R software and the competing endogenous RNA (ceRNA) network was constructed using Cytoscape. Functional and pathway enrichment analyses were performed to identify the candidate circRNA-mediated aberrant signaling pathways. The hub genes were identified by MCODE and CytoHubba plugins of Cytoscape, and then a subnetwork regulatory module was established. RESULTS: A total of 27 circRNA-miRNA pairs and 208 miRNA-mRNA pairs, including 12 circRNAs, 24 miRNAs and 112 mRNAs were included in the ceRNA network. Subsequently, a subnetwork, including 4 circRNAs, 5 miRNAs and 6 mRNAs, was established based on related circRNA-miRNA-mRNA regulatory modules. CONCLUSIONS: In summary, this work analyzes the characteristics of circRNA as competing endogenous RNA in AML pathogenesis, which would provide hints for developing novel prognostic, diagnostic and therapeutic strategy for AML.


Asunto(s)
Biomarcadores de Tumor/metabolismo , Regulación Neoplásica de la Expresión Génica , Redes Reguladoras de Genes , Leucemia Mieloide Aguda/genética , ARN Circular/metabolismo , Biomarcadores de Tumor/análisis , Biología Computacional , Conjuntos de Datos como Asunto , Perfilación de la Expresión Génica , Humanos , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/mortalidad , MicroARNs/metabolismo , Análisis de Secuencia por Matrices de Oligonucleótidos , Pronóstico , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/genética , ARN Circular/análisis , ARN Mensajero/metabolismo , Transducción de Señal/genética , Análisis de Supervivencia
11.
Nat Commun ; 12(1): 1796, 2021 03 19.
Artículo en Inglés | MEDLINE | ID: mdl-33741907

RESUMEN

Most diseases disrupt multiple proteins, and drugs treat such diseases by restoring the functions of the disrupted proteins. How drugs restore these functions, however, is often unknown as a drug's therapeutic effects are not limited to the proteins that the drug directly targets. Here, we develop the multiscale interactome, a powerful approach to explain disease treatment. We integrate disease-perturbed proteins, drug targets, and biological functions into a multiscale interactome network. We then develop a random walk-based method that captures how drug effects propagate through a hierarchy of biological functions and physical protein-protein interactions. On three key pharmacological tasks, the multiscale interactome predicts drug-disease treatment, identifies proteins and biological functions related to treatment, and predicts genes that alter a treatment's efficacy and adverse reactions. Our results indicate that physical interactions between proteins alone cannot explain treatment since many drugs treat diseases by affecting the biological functions disrupted by the disease rather than directly targeting disease proteins or their regulators. We provide a general framework for explaining treatment, even when drugs seem unrelated to the diseases they are recommended for.


Asunto(s)
Complejos Multiproteicos/metabolismo , Preparaciones Farmacéuticas/administración & dosificación , Mapas de Interacción de Proteínas/efectos de los fármacos , Proteínas/metabolismo , Algoritmos , Animales , Biología Computacional/métodos , Quimioterapia/métodos , Humanos , Modelos Teóricos , Unión Proteica/efectos de los fármacos , Mapeo de Interacción de Proteínas/métodos
12.
Methods Mol Biol ; 2212: 347-376, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33733367

RESUMEN

As practitioners, we aim to provide a consolidated introduction of tidy data science along with routine packages for relational data representation and interpretation, with the focus on analytics related to human genetic interactions. We describe three showcases (also made available at https://23verse.github.io/gini ), all done so via the R one-liner, in this chapter defined as a sequential pipeline of elementary functions chained together achieving a complex task. We guide the readers through step-by-step instructions on (case 1) performing network module analysis of genetic interactions, followed by visualization and interpretation; (case 2) implementing a practical strategy of how to identify and interpret tissue-specific genetic interactions; and (case 3) carrying out interaction-based tissue clustering and differential interaction analysis. All showcases demonstrate simplistic beauty and efficient nature of this analytics. We anticipate that mastering a dozen of one-liners to efficiently interpret genetic interactions is very timely now; opportunities for computational translational research are arising for data scientists to harness therapeutic potential of human genetic interaction data that are ever-increasingly available.


Asunto(s)
Algoritmos , Ciencia de los Datos/estadística & datos numéricos , Epistasis Genética , Redes Reguladoras de Genes , Programas Informáticos , Animales , Proteína BRCA1/genética , Proteína BRCA1/metabolismo , Proteína BRCA2/genética , Proteína BRCA2/metabolismo , Interpretación Estadística de Datos , Genoma Humano , Genotipo , Humanos , Ratones , Especificidad de Órganos , Fenotipo , Poli(ADP-Ribosa) Polimerasa-1/genética , Poli(ADP-Ribosa) Polimerasa-1/metabolismo , Mapeo de Interacción de Proteínas
13.
Nat Commun ; 12(1): 1396, 2021 03 02.
Artículo en Inglés | MEDLINE | ID: mdl-33654096

RESUMEN

Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.


Asunto(s)
Aminoácidos/genética , Proteínas Bacterianas/genética , Proteínas Bacterianas/metabolismo , Evolución Molecular , Genoma Bacteriano , Mapeo de Interacción de Proteínas , Proteínas Bacterianas/química , Secuencia de Bases , Escherichia coli/genética , Células Eucariotas/metabolismo , Proteínas de la Membrana/metabolismo , Simulación del Acoplamiento Molecular , Unión Proteica , Proteoma/metabolismo
14.
Medicine (Baltimore) ; 100(12): e24669, 2021 Mar 26.
Artículo en Inglés | MEDLINE | ID: mdl-33761636

RESUMEN

ABSTRACT: Neutrophils have crucial roles in defensing against infection and adaptive immune responses. This study aimed to investigate the genetic mechanism in neutrophils in response to sepsis-induced immunosuppression.The GSE64457 dataset was downloaded from the Gene Expression Omnibus database and the neutrophil samples (D3-4 and D6-8 post sepsis shock) were assigned into two groups. The differentially expressed genes (DEGs) were identified. The Short Time-series Expression Miner (STEM) clustering analysis was conducted to select the consistently changed DEGs post sepsis shock. The overlapping genes between the DEGs and the deposited genes associated with immune, sepsis, and immunosuppression in the AmiGO2 and Comparative Toxicogenomics Database were screened out and used for the construction of the protein-protein interaction (PPI) network. The expression of several hub genes in sepsis patients was validated using the PCR analysis. The drugs targeting the hub genes and the therapy strategies for sepsis or immunosuppression were reviewed and used to construct the drug-gene-therapy-cell network to illustrate the potential therapeutic roles of the hub genes.A total of 357 overlapping DEGs between the two groups were identified and were used for the STEM clustering analysis, which generated four significant profiles with 195 upregulated (including annexin A1, ANXA1; matrix metallopeptidase 9, MMP9; and interleukin 15, IL-15) and 151 downregulated DEGs (including, AKT1, IFN-related genes, and HLA antigen genes). Then, a total of 34 of the 151 downregulated DEGs and 39 of the 195 upregulated DEGs were shared between the databases and above DEGs, respectively. The PPI network analysis identified a downregulated module including IFN-related genes. The deregulation of DEGs including AKT1 (down), IFN-inducible protein 6 (IFI6, down), IL-15 (up), and ANXA1 (up) was verified in the neutrophils from patients with sepsis-induced immunosuppression as compared with controls. Literature review focusing on the therapy showed that the upregulation of IL-15, IFN, and HLA antigens are the management targets. Besides, the AKT1 gene was targeted by gemcitabine.These findings provided additional clues for understanding the mechanisms of sepsis-induced immunosuppression. The drugs targeting AKT1 might provide now clues for the management strategy of immunosuppression with the intention to prevent neutrophil infiltration.


Asunto(s)
Regulación de la Expresión Génica/inmunología , Tolerancia Inmunológica/genética , Neutrófilos/inmunología , Síndrome de Respuesta Inflamatoria Sistémica/inmunología , Anciano , Anexina A1/genética , Anexina A1/metabolismo , Estudios de Casos y Controles , Biología Computacional , Conjuntos de Datos como Asunto , Femenino , Perfilación de la Expresión Génica , Redes Reguladoras de Genes/inmunología , Humanos , Interleucina-15/genética , Interleucina-15/metabolismo , Masculino , Persona de Mediana Edad , Proteínas Mitocondriales/genética , Proteínas Mitocondriales/metabolismo , Neutrófilos/metabolismo , Mapeo de Interacción de Proteínas , Mapas de Interacción de Proteínas/inmunología , Proteínas Proto-Oncogénicas c-akt/genética , Proteínas Proto-Oncogénicas c-akt/metabolismo , Transducción de Señal/inmunología , Síndrome de Respuesta Inflamatoria Sistémica/sangre , Síndrome de Respuesta Inflamatoria Sistémica/genética
15.
Int J Mol Sci ; 22(4)2021 Feb 03.
Artículo en Inglés | MEDLINE | ID: mdl-33546420

RESUMEN

Members of the Tribbles (TRIB) family of pseudokinases are critical components of intracellular signal transduction pathways in physiological and pathological processes. TRIBs, including TRIB2, have been previously shown as signaling mediators and scaffolding proteins regulating numerous cellular events such as proliferation, differentiation and cell death through protein stability and activity. However, the signaling network associated with TRIB2 and its binding partners in granulosa cells during ovarian follicular development is not fully defined. We previously reported that TRIB2 is differentially expressed in growing dominant follicles while downregulated in ovulatory follicles following the luteinizing hormone (LH) surge or human chorionic gonadotropin (hCG) injection. In the present study, we used the yeast two-hybrid screening system and in vitro coimmunoprecipitation assays to identify and confirm TRIB2 interactions in granulosa cells (GCs) of dominant ovarian follicles (DFs), which yielded individual candidate binding partners including calmodulin 1 (CALM1), inhibin subunit beta A (INHBA), inositol polyphosphate phosphatase-like 1 (INPPL1), 5'-nucleotidase ecto (NT5E), stearoyl-CoA desaturase (SCD), succinate dehydrogenase complex iron sulfur subunit B (SDHB) and Ras-associated protein 14 (RAB14). Further analyses showed that all TRIB2 binding partners are expressed in GCs of dominant follicles but are differentially regulated throughout the different stages of follicular development. CRISPR/Cas9-driven inhibition along with pQE-driven overexpression of TRIB2 showed that TRIB2 differently regulates expression of binding partners, which reveals the importance of TRIB2 in the control of gene expression linked to various biological processes such as proliferation, differentiation, cell migration, apoptosis, calcium signaling and metabolism. These data provide a larger view of potential TRIB2-regulated signal transduction pathways in GCs and provide strong evidence that TRIB2 may act as a regulator of target genes during ovarian follicular development.


Asunto(s)
Proteínas Quinasas Dependientes de Calcio-Calmodulina/metabolismo , Proteínas Portadoras/genética , Proteínas Portadoras/metabolismo , Regulación de la Expresión Génica , Células de la Granulosa/metabolismo , Animales , Biomarcadores , Bovinos , Regulación hacia Abajo , Femenino , Folículo Ovárico/metabolismo , Unión Proteica , Mapeo de Interacción de Proteínas , Técnicas del Sistema de Dos Híbridos
16.
Nucleic Acids Res ; 49(4): 1859-1871, 2021 02 26.
Artículo en Inglés | MEDLINE | ID: mdl-33524155

RESUMEN

Animal models are crucial for advancing our knowledge about the molecular pathways involved in human diseases. However, it remains unclear to what extent tissue expression of pathways in healthy individuals is conserved between species. In addition, organism-specific information on pathways in animal models is often lacking. Within these limitations, we explore the possibilities that arise from publicly available data for the animal models mouse, rat, and pig. We approximate the animal pathways activity by integrating the human counterparts of curated pathways with tissue expression data from the models. Specifically, we compare whether the animal orthologs of the human genes are expressed in the same tissue. This is complicated by the lower coverage and worse quality of data in rat and pig as compared to mouse. Despite that, from 203 human KEGG pathways and the seven tissues with best experimental coverage, we identify 95 distinct pathways, for which the tissue expression in one animal model agrees better with human than the others. Our systematic pathway-tissue comparison between human and three animal modes points to specific similarities with human and to distinct differences among the animal models, thereby suggesting the most suitable organism for modeling a human pathway or tissue.


Asunto(s)
Modelos Animales , Animales , Expresión Génica , Genoma , Humanos , Ratones , Especificidad de Órganos , Mapeo de Interacción de Proteínas , Ratas , Porcinos
17.
Nucleic Acids Res ; 49(4): 1951-1971, 2021 02 26.
Artículo en Inglés | MEDLINE | ID: mdl-33524141

RESUMEN

Glucocorticoid receptor (GR) is an essential transcription factor (TF), controlling metabolism, development and immune responses. SUMOylation regulates chromatin occupancy and target gene expression of GR in a locus-selective manner, but the mechanism of regulation has remained elusive. Here, we identify the protein network around chromatin-bound GR by using selective isolation of chromatin-associated proteins and show that the network is affected by receptor SUMOylation, with several nuclear receptor coregulators and chromatin modifiers preferring interaction with SUMOylation-deficient GR and proteins implicated in transcriptional repression preferring interaction with SUMOylation-competent GR. This difference is reflected in our chromatin binding, chromatin accessibility and gene expression data, showing that the SUMOylation-deficient GR is more potent in binding and opening chromatin at glucocorticoid-regulated enhancers and inducing expression of target loci. Blockage of SUMOylation by a SUMO-activating enzyme inhibitor (ML-792) phenocopied to a large extent the consequences of GR SUMOylation deficiency on chromatin binding and target gene expression. Our results thus show that SUMOylation modulates the specificity of GR by regulating its chromatin protein network and accessibility at GR-bound enhancers. We speculate that many other SUMOylated TFs utilize a similar regulatory mechanism.


Asunto(s)
Cromatina/metabolismo , Receptores de Glucocorticoides/metabolismo , Sumoilación , Sitios de Unión , Regulación de la Expresión Génica , Células HEK293 , Humanos , Co-Represor 1 de Receptor Nuclear/metabolismo , Coactivador 1 de Receptor Nuclear , Mapeo de Interacción de Proteínas , Proteínas Modificadoras Pequeñas Relacionadas con Ubiquitina/metabolismo , Sumoilación/efectos de los fármacos
18.
Methods Mol Biol ; 2218: 303-317, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33606241

RESUMEN

Protein-protein interactions (PPIs) play a central role in all cellular processes. The discovery of green fluorescent protein (GFP) and split varieties, which are functionally reconstituted by complementation, led to the development of the bimolecular fluorescence complementation (BiFC) assay for the investigation of PPI in vivo. BiFC became a popular tool, as it is a convenient and quick technology to directly visualize PPI in a wide variety of living cells. In combination with the transparency of the early zebrafish embryo, it also permits detection of PPI in the context of an entire living organism, which performs all spatial and temporal regulations missing in in vitro systems like tissue culture. However, the application of BiFC in some research areas including the study of zebrafish is limited due to the lack of efficient and convenient BiFC expression vectors. Here, we describe the engineering of a novel set of Gateway®-adapted BiFC destination vectors to investigate PPI with all possible permutations for BiFC experiments. Moreover, we demonstrate the versatility of these destination vectors by confirming the interaction between zebrafish Bucky ball and RNA helicase Vasa in living embryos.


Asunto(s)
Bioensayo/métodos , Microscopía Fluorescente/métodos , Proteínas de Pez Cebra/metabolismo , Pez Cebra/metabolismo , Animales , Embrión no Mamífero/metabolismo , Fluorescencia , Vectores Genéticos/metabolismo , Proteínas Fluorescentes Verdes/metabolismo , Proteínas Luminiscentes/metabolismo , Mapeo de Interacción de Proteínas/métodos , ARN Helicasas/metabolismo
19.
Biomed Res Int ; 2021: 6752141, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33521130

RESUMEN

Background: Thyroid cancer is the most common endocrine malignancy, with a recent global increase of 20% in age-related incidence. Ultrasonography and ultrasonography-guided fine-needle aspiration biopsy (FNAB) are the most widely used diagnostic tests for thyroid nodules; however, it is estimated that up to 25% of thyroid biopsies are cytologically inconclusive. Molecular markers can help guide patient-oriented and targeted treatment of thyroid nodules and thyroid cancer. Methods: Datasets related to papillary thyroid cancer (PTC) or thyroid carcinoma (GSE129562, GSE3678, GSE54958, GSE138042, and GSE124653) were downloaded from the GEO database and analysed using the Limma package of R software. For functional enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology were applied to differentially expressed genes (DEGs) using the Metascape website. A protein-protein interaction (PPI) network was built from the STRING database. Gene expression, protein expression, immunohistochemistry, and potential functional gene survival were analysed using the GEPIA website, the Human Protein Atlas website, and the UALCAN website. Potential target miRNAs were predicted using the miRDB and Starbase datasets. Results: We found 219 upregulated and 310 downregulated DEGs, with a cut-off of p < 0.01 and ∣log FC | >1.5. The DEGs in papillary thyroid cancer were mainly enriched in extracellular structural organisation. At the intersection of the PPI network and Metascape MCODEs, the hub genes in common were identified as FN1, APOE, CLU, and SDC2. In the targeted regulation network of miRNA-mRNA, the hsa-miR-424-5p was found to synchronously modulate two hub genes. Survival analysis showed that patients with high expression of CLU and APOE had better prognosis. Conclusions: CLU and APOE are involved in the molecular mechanism of papillary thyroid cancer. The hsa-miR-424-5p might have the potential to reverse the processes of papillary thyroid cancer by modulating the hub genes. These are potential targets for the treatment of patients with papillary thyroid cancer.


Asunto(s)
Redes Reguladoras de Genes , MicroARNs/metabolismo , ARN Mensajero/metabolismo , Cáncer Papilar Tiroideo/genética , Neoplasias de la Tiroides/genética , Nódulo Tiroideo/genética , Apolipoproteínas E/genética , Biopsia , Biopsia con Aguja Fina , Análisis por Conglomerados , Clusterina/genética , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Humanos , MicroARNs/genética , Análisis de Secuencia por Matrices de Oligonucleótidos , Mapeo de Interacción de Proteínas , Cáncer Papilar Tiroideo/patología , Glándula Tiroides/patología , Neoplasias de la Tiroides/patología , Nódulo Tiroideo/patología , Ultrasonografía
20.
BMC Bioinformatics ; 22(1): 34, 2021 Jan 29.
Artículo en Inglés | MEDLINE | ID: mdl-33514304

RESUMEN

BACKGROUND: Network alignment (NA) can transfer functional knowledge between species' conserved biological network regions. Traditional NA assumes that it is topological similarity (isomorphic-like matching) between network regions that corresponds to the regions' functional relatedness. However, we recently found that functionally unrelated proteins are as topologically similar as functionally related proteins. So, we redefined NA as a data-driven method called TARA, which learns from network and protein functional data what kind of topological relatedness (rather than similarity) between proteins corresponds to their functional relatedness. TARA used topological information (within each network) but not sequence information (between proteins across networks). Yet, TARA yielded higher protein functional prediction accuracy than existing NA methods, even those that used both topological and sequence information. RESULTS: Here, we propose TARA++ that is also data-driven, like TARA and unlike other existing methods, but that uses across-network sequence information on top of within-network topological information, unlike TARA. To deal with the within-and-across-network analysis, we adapt social network embedding to the problem of biological NA. TARA++ outperforms protein functional prediction accuracy of existing methods. CONCLUSIONS: As such, combining research knowledge from different domains is promising. Overall, improvements in protein functional prediction have biomedical implications, for example allowing researchers to better understand how cancer progresses or how humans age.


Asunto(s)
Algoritmos , Mapeo de Interacción de Proteínas , Proteínas , Animales , Biología Computacional , Ratones , Anotación de Secuencia Molecular , Proteínas/genética , Saccharomyces cerevisiae , Alineación de Secuencia
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