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1.
Medicine (Baltimore) ; 98(37): e17100, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31517839

RESUMO

BACKGROUND: Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumors in head and neck, but its molecular mechanism is not clear. METHODS: Weighted gene co-expression network analysis (WGCNA) combining with gene differential expression analysis, survival analysis to screen key modules and hub genes related to the progress of TSCC. Gene Set Enrichment Analysis (GSEA) was used to identify biological pathways that might be involved. RESULTS: Weighted gene co-expression network was constructed based on dataset GSE34105. The blue module and turquoise module most related to the progress of TSCC were identified by the network. Gene Ontology (GO) enrichment analysis showed that 2 key modules were significantly enriched in apoptosis and immunity related biological processes and pathway. Network topology analysis, gene difference analysis and survival analysis were used to screen 9 hub genes (NOC2L, AIMP2, ANXA2, DIABLO, H2AFZ, MANBAL, PRDX6, SNX14, TIMM23). The expression of hub genes was significantly correlated with the prognosis of TSCC. GSEA showed that the high expression group of hub genes was mainly enriched in olfactory transduction, neuroactive ligand receptor interaction, nicotinate and nicotinamide metabolism, and the low expression group was mainly enriched in base excision repair, cysteine and methionine metabolism, oxidative phosphorylation. CONCLUSION: Two key modules and 9 hub genes screened by WGCNA were closely related to the occurrence and prognosis of TSCC. Hub genes can be used as biomarkers and potential therapeutic targets for the accurate diagnosis and treatment of TSCC in the future.


Assuntos
Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Carcinoma de Células Escamosas de Cabeça e Pescoço/genética , Neoplasias da Língua/genética , Perfilação da Expressão Gênica/estatística & dados numéricos , Humanos , Modelos Lineares , Prognóstico , Neoplasias da Língua/classificação
2.
Pestic Biochem Physiol ; 158: 112-120, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31378345

RESUMO

Cytochrome P450s (P450s) confer resistance against herbicides, and this is increasingly becoming a concern for weed control. As a widespread Gramineae weed in paddy fields, Echinocloa glabrescens has become resistant to the acetolactate synthase (ALS)-inhibiting triazolopyrimidine herbicide penoxsulam. In this study, we found that the GR50 of the resistant population (SHQP-R) decreased substantially from 25.6 to 5.0 and 6.2 g a.i. ha-1 after treatment with the P450 inhibitors piperonyl butoxide (PBO) and malathion, respectively. However, P450 inhibitors almost had no effects on the susceptibility of the sensitive population (JYJD-S) to penoxsulam. To investigate the mechanisms of metabolic resistance, transcriptome sequencing analysis was performed to find candidate genes that may confer resistance to penoxsulam in E. glabrescens. A total of 233 P450 differentially expressed genes (DEGs) were identified by transcriptome sequencing. We found that the metabolic process and metabolic pathways were the most highly enriched in DEGs. Further, twenty-seven candidate P450 DEGs were selected for qPCR validation analyses. After penoxsulam treatment, the relative expression levels were significantly higher in SHQP-R than in JYJD-S. Among these, the relative expression of twenty-three P450 DEGs (eighteen from the CYP72A-71C-74A-96A-734A subfamily; five from CYP81E1-94C1-94B3-714C1-714C2) were upregulated and four P450 DEGs (from CYP724B1-711A1-707A7-97B2) were downregulated. Changes in the expression of these candidate P450 genes in E. glabrescens were in response to penoxsulam, which provides preliminary evidence for the role of P450s in herbicide metabolism in E. glabrescens. However, further functional studies on metabolic resistance to penoxsulam in a resistant E. glabrescens population are required.


Assuntos
Sistema Enzimático do Citocromo P-450/metabolismo , Echinochloa/efeitos dos fármacos , Echinochloa/metabolismo , Perfilação da Expressão Gênica/métodos , Sulfonamidas/farmacologia , Uridina/análogos & derivados , Sistema Enzimático do Citocromo P-450/genética , Echinochloa/genética , Resistência a Herbicidas/genética , Malation/farmacologia , Butóxido de Piperonila/farmacologia , Uridina/farmacologia
3.
Medicine (Baltimore) ; 98(34): e16916, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31441872

RESUMO

BACKGROUND: Colorectal Cancer (CRC) is a highly heterogeneous disease. RNA profiles of bulk tumors have enabled transcriptional classification of CRC. However, such ways of sequencing can only target a cell colony and obscure the signatures of distinct cell populations. Alternatively, single-cell RNA sequencing (scRNA-seq), which can provide unbiased analysis of all cell types, opens the possibility to map cellular heterogeneity of CRC unbiasedly. METHODS: In this study, we utilized scRNA-seq to profile cells from cancer tissue of a CRC patient. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to understand the roles of genes within the clusters. RESULTS AND CONCLUSION: The 2824 cells were analyzed and categorized into 5 distinct clusters by scRNA-seq. For every cluster, specific cell markers can be applied, indicating each 1 of them different from another. We discovered that the tumor of CRC displayed a clear sign of heterogenicity, while genes within each cluster serve different functions. GO term analysis also stated that different cluster's relatedness towards the tumor of CRC differs. Three clusters participate in peripheral works in cells, including, energy transport, extracellular matrix generation, etc; Genes in other 2 clusters participate more in immunology processes. Lastly, trajectory plot analysis also supports the viewpoint, in that some clusters present in different states and pseudo-time, while others present in a single state or pseudo time. Our analysis provides more insight into the heterogeneity of CRC, which can provide assistance to further researches on this topic.


Assuntos
Neoplasias Colorretais/genética , Perfilação da Expressão Gênica/métodos , Heterogeneidade Genética , Análise de Sequência de RNA/métodos , Idoso , Biomarcadores Tumorais/genética , Feminino , Humanos
4.
BMC Bioinformatics ; 20(1): 379, 2019 Jul 08.
Artigo em Inglês | MEDLINE | ID: mdl-31286861

RESUMO

BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with noisy single cell mRNA-sequencing data (scRNA-seq), where the models generalize well, despite the zero-inflation of the data. A class of neural networks, namely autoencoders, has been useful for denoising of single cell data, imputation of missing values and dimensionality reduction. RESULTS: Here, we present a striking feature with the potential to greatly increase the usability of autoencoders: With specialized training, the autoencoder is not only able to generalize over the data, but also to tease apart biologically meaningful modules, which we found encoded in the representation layer of the network. Our model can, from scRNA-seq data, delineate biological meaningful modules that govern a dataset, as well as give information as to which modules are active in each single cell. Importantly, most of these modules can be explained by known biological functions, as provided by the Hallmark gene sets. CONCLUSIONS: We discover that tailored training of an autoencoder makes it possible to deconvolute biological modules inherent in the data, without any assumptions. By comparisons with gene signatures of canonical pathways we see that the modules are directly interpretable. The scope of this discovery has important implications, as it makes it possible to outline the drivers behind a given effect of a cell. In comparison with other dimensionality reduction methods, or supervised models for classification, our approach has the benefit of both handling well the zero-inflated nature of scRNA-seq, and validating that the model captures relevant information, by establishing a link between input and decoded data. In perspective, our model in combination with clustering methods is able to provide information about which subtype a given single cell belongs to, as well as which biological functions determine that membership.


Assuntos
Perfilação da Expressão Gênica/métodos , Redes Neurais (Computação) , RNA Mensageiro/química , Análise de Sequência de RNA/métodos , Aprendizado de Máquina não Supervisionado , Análise por Conglomerados , RNA Mensageiro/metabolismo , Análise de Célula Única
5.
BMC Bioinformatics ; 20(1): 378, 2019 Jul 08.
Artigo em Inglês | MEDLINE | ID: mdl-31286864

RESUMO

BACKGROUND: The QuantiGene® Plex 2.0 platform (ThermoFisher Scientific) combines bDNA with the Luminex/xMAP magnetic bead capturing technology to assess differential gene expression in a compound exposure setting. This technology allows multiplexing in a single well of a 96 or 384 multi-well plate and can thus be used in high throughput drug discovery mode. Data interpretation follows a three-step normalization/transformation flow in which raw median fluorescent gene signals are transformed to fold change values with the use of proper housekeeping genes and negative controls. Clear instructions on how to assess the data quality and tools to perform this analysis in high throughput mode are, however, currently lacking. RESULTS: In this paper we introduce QGprofiler, an open source R based shiny application. QGprofiler allows for proper QuantiGene® Plex 2.0 assay optimization, choice of housekeeping genes and data pre-processing up to fold change, including appropriate QC metrics. In addition, QGprofiler allows for an Akaike information criterion based dose response fold change model selection and has a built-in tool to detect the cytotoxic potential of compounds evaluated in a high throughput screening campaign. CONCLUSION: QGprofiler is a user friendly, open source available R based shiny application, which is developed to support drug discovery campaigns. In this context, entire compound libraries/series can be tested in dose response against a gene signature of choice in search for new disease relevant chemical entities. QGprofiler is available at: https://qgprofiler.openanalytics.eu/app/QGprofiler.


Assuntos
Descoberta de Drogas/métodos , Perfilação da Expressão Gênica/métodos , Software
6.
Medicine (Baltimore) ; 98(27): e16225, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277135

RESUMO

MicroRNAs (miRNAs) play a great contribution to the development of diabetic nephropathy (DN). The aim of this study was to explore potential miRNAs-genes regulatory network and biomarkers for the pathogenesis of DN using bioinformatics methods.Gene expression profiling data related to DN (GSE1009) was obtained from the Gene Expression Omnibus (GEO) database, and then differentially expressed genes (DEGs) between DN patients and normal individuals were screened using GEO2R, followed by a series of bioinformatics analyses, including identifying key genes, conducting pathway enrichment analysis, predicting and identifying key miRNAs, and establishing regulatory relationships between key miRNAs and their target genes.A total of 600 DEGs associated with DN were identified. An additional 7 key DEGs, including 6 downregulated genes, such as vascular endothelial growth factor α (VEGFA) and COL4A5, and 1 upregulated gene (CCL19), were identified in another dataset (GSE30528) from glomeruli samples. Pathway analysis showed that the down- and upregulated DEGs were enriched in 14 and 6 pathways, respectively, with 7 key genes mainly involved in extracellular matrix-receptor interaction, PI3K/Akt signaling, focal adhesion, and Rap1 signaling. The relationships between miRNAs and target genes were constructed, showing that miR-29 targeted COL4A and VEGFA, miR-200 targeted VEGFA, miR-25 targeted ITGAV, and miR-27 targeted EGFR.MiR-29 and miR-200 may play important roles in DN. VEGFA and COL4A5 were targeted by miR-29 and VEGFA by miR-200, which may mediate multiple signaling pathways leading to the pathogenesis and development of DN.


Assuntos
Biologia Computacional/métodos , Nefropatias Diabéticas/genética , Perfilação da Expressão Gênica/métodos , MicroRNAs/genética , Regulação para Cima , Redes Reguladoras de Genes , Humanos , Análise em Microsséries
7.
Medicine (Baltimore) ; 98(27): e16240, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277141

RESUMO

Osteoarthritis (OA), also known as degenerative arthritis, affects millions of people all over the world. OA occurs when the cartilage wears down over time, which is a worldwide complaint. The aim of this study was to screen and verify hub genes involved in developmental chondrogenesis as well as to explore potential molecular mechanisms.The expression profiles of GSE51812 were downloaded from the Gene Expression Omnibus (GEO) database, which contained 9 samples, including 6-week pre-chondrocytes (PC, 6 independent specimens) and 17-week fetal periarticular resting chondrocytes (RC, 3 independent specimens). The raw data were integrated to obtain differentially expressed genes (DEGs) and were further analyzed with bioinformatics analysis. The Gene Ontology (GO) and pathway enrichment of DEGs were conducted via Database for Annotation, Visualization, and Integrated Discovery (DAVID). The protein-protein interaction (PPI) networks of the DEGs were constructed based on data from the search tool for the retrieval of interacting genes (STRING) database. An intersection figure was provided to show the relationship between the DEGs identified in this study and genes from any existed related studies.A total of 9486 DEGs, including 4821 upregulated genes and 4665 downregulated genes were observed. The top 30 developmental chondrogenesis associated genes were identified, including matrix metalloproteinase (MMP)1, MMP3, MMP13, prostaglandin-endoperoxide synthase 2 (PTGS2), and so on. The majority of DEGs, including PTGS2, CCL20, CHI3L1, LIF, CXCL8, and CXCL12 were intensively enriched in immune-associated biological process terms, including inflammatory, and immune responses. Additionally, the majority of DEGs were mainly enriched in NF-kappa ß (NF-kß) signaling pathway and tumor necrosis factor (TNF) signaling pathway. The hub genes identified in STRING and Cytoscape databases included MMP1, MMP3, MMP13, PTGS2 and so on. Among the top 30 upregulated and downregulated DEGs, there were 15 genes have been reported to be associated with OA or developmental chondrogenesis.This large scale gene expression study observed genes associated with human developmental chondrogenesis and their relative GO function, which may offer opportunities for the research for cartilage tissue engineering and novel insights into the prevention of OA in the near future.


Assuntos
Condrogênese/genética , Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica , Osteoartrite/genética , Biomarcadores/metabolismo , Bases de Dados Genéticas , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Osteoartrite/patologia , Transdução de Sinais
8.
Medicine (Baltimore) ; 98(27): e16269, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277149

RESUMO

Esophageal squamous cell carcinoma (ESCC) is a malignancy that severely threatens human health and carries a high incidence rate and a low 5-year survival rate. MicroRNAs (miRNAs) are commonly accepted as a key regulatory function in human cancer, but the potential regulatory mechanisms of miRNA-mRNA related to ESCC remain poorly understood.The GSE55857, GSE43732, and GSE6188 miRNA microarray datasets and the gene expression microarray datasets GSE70409, GSE29001, and GSE20347 were downloaded from Gene Expression Omnibus databases. The differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) were obtained using GEO2R. Gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed by Database for Annotation, Visualization and Integrated Discovery (DAVID). A protein-protein interaction (PPI) network and functional modules were established using the STRING database and were visualized by Cytoscape. Kaplan-Meier analysis was constructed based on The Cancer Genome Atlas (TCGA) database.In total, 26 DEMs and 280 DEGs that consisted of 96 upregulated and 184 downregulated genes were screened out. A functional enrichment analysis showed that the DEGs were mainly enriched in the ECM-receptor interaction and cytochrome P450 metabolic pathways. In addition, MMP9, PCNA, TOP2A, MMP1, AURKA, MCM2, IVL, CYP2E1, SPRR3, FOS, FLG, TGM1, and CYP2C9 were considered to be hub genes owing to high degrees in the PPI network. MiR-183-5p was with the highest connectivity target genes in hub genes. FOS was predicted to be a common target gene of the significant DEMs. Hsa-miR-9-3p, hsa-miR-34c-3p and FOS were related to patient prognosis and higher expression of the transcripts were associated with a poor OS in patients with ESCC.Our study revealed the miRNA-mediated hub genes regulatory network as a model for predicting the molecular mechanism of ESCC. This may provide novel insights for unraveling the pathogenesis of ESCC.


Assuntos
Biologia Computacional/métodos , Neoplasias Esofágicas/genética , Carcinoma de Células Escamosas do Esôfago/genética , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , MicroRNAs/genética , RNA Neoplásico/genética , Bases de Dados Genéticas , Neoplasias Esofágicas/metabolismo , Carcinoma de Células Escamosas do Esôfago/metabolismo , Ontologia Genética , Redes Reguladoras de Genes , Humanos , Análise em Microsséries
9.
Medicine (Baltimore) ; 98(27): e16273, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277152

RESUMO

BACKGROUND: Although the outcome of patients with gastric cancer (GC) has improved significantly with the recent implementation of annual screening programs. Reliable prognostic biomarkers are still needed due to the disease heterogeneity. Increasing pieces of evidence revealed an association between immune signature and GC prognosis. Thus, we aim to build an immune-related signature that can estimate prognosis for GC. METHODS: For identification of a prognostic immune-related gene signature (IRGS), gene expression profiles and clinical information of patients with GC were collected from 3 public cohorts, divided into training cohort (n = 300) and 2 independent validation cohorts (n = 277 and 433 respectively). RESULTS: Within 1811 immune genes, a prognostic IRGS consisting of 16 unique genes was constructed which was significantly associated with survival (hazard ratio [HR], 3.9 [2.78-5.47]; P < 1.0 × 10). In the validation cohorts, the IRGS significantly stratified patients into high- vs low-risk groups in terms of prognosis across (HR, 1.84 [1.47-2.30]; P = 6.59 × 10) and within subpopulations with stage I&II disease (HR, 1.96 [1.34-2.89]; P = 4.73 × 10) and was prognostic in univariate and multivariate analyses. Several biological processes, including TGF-ß and EMT signaling pathways, were enriched in the high-risk group. T cells CD4 memory resting and Macrophage M2 were significantly higher in the high-risk risk group compared with the low-risk group. CONCLUSION: In short, we developed a prognostic IRGS for estimating prognosis in GC, including stage I&II disease, providing new insights into the identification of patients with GC with a high risk of mortality.


Assuntos
Biomarcadores Tumorais/imunologia , DNA de Neoplasias/genética , Perfilação da Expressão Gênica/métodos , Regulação Neoplásica da Expressão Gênica , Neoplasias Gástricas/genética , Transcriptoma/genética , Biomarcadores Tumorais/genética , DNA de Neoplasias/imunologia , Feminino , Humanos , Masculino , Prognóstico , Fatores de Risco , Neoplasias Gástricas/imunologia , Neoplasias Gástricas/metabolismo
10.
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
11.
Gene ; 714: 143996, 2019 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-31348980

RESUMO

The uniquely human α7-nAChR gene (CHRFAM7A) is evolved from the fusion of two partially duplicated genes, FAM7 and α7-nAChR gene (CHRNA7), and is inserted on same chromosome 15, 5' end of the CHRNA7 gene. Transcription of CHRFAM7A gene produces a 1256-bp open reading frame encoding dup-α7-nAChR, where a 27-aminoacid residues from FAM7 replaced the 146-aminoacid residues of the N-terminal extracellular ligand binding domain of α7-nAChR. In vitro, dup-α7-nAChR has been shown to form hetero-pentamer with α7-nAChR and dominant-negatively regulates the channel functions of α7-nAChR. However, the contribution of CHRFAM7A gene to the biology of α7-nAChR in the brain in vivo remains largely a matter of conjecture. CHRFAM7A transgenic mouse was created and differentially expressed proteins were profiled from the whole brain using iTRAQ-2D-LC-MS/MS proteomic technology. Proteins with a fold change of ≥1.2 or ≤0.83 and p < 0.05 were considered to be significant. Bioinformatics analysis showed that over-expression of the CHRFAM7A gene significantly modulated the proteins commonly involved in the signaling pathways of α7-nAChR-mediated neuropsychiatric disorders including Parkinson's disease, Alzheimer's disease, Huntington's disease, and alcoholism, suggesting that the CHRFAM7A gene contributes to the pathogenesis of neuropsychiatric disorders mostly likely through fine-tuning the functions of α7-nAChR in the brain.


Assuntos
Camundongos Transgênicos/genética , Receptor Nicotínico de Acetilcolina alfa7/genética , Animais , Encéfalo/metabolismo , Cromatografia Líquida/métodos , Cromossomos Humanos Par 15/genética , Perfilação da Expressão Gênica/métodos , Genes Duplicados/genética , Humanos , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Proteômica/métodos , Transdução de Sinais/genética , Espectrometria de Massas em Tandem/métodos
12.
BMC Bioinformatics ; 20(1): 369, 2019 Jul 01.
Artigo em Inglês | MEDLINE | ID: mdl-31262249

RESUMO

BACKGROUND: Single cell RNA sequencing (scRNA-seq) brings unprecedented opportunities for mapping the heterogeneity of complex cellular environments such as bone marrow, and provides insight into many cellular processes. Single cell RNA-seq has a far larger fraction of missing data reported as zeros (dropouts) than traditional bulk RNA-seq, and unsupervised clustering combined with Principal Component Analysis (PCA) can be used to overcome this limitation. After clustering, however, one has to interpret the average expression of markers on each cluster to identify the corresponding cell types, and this is normally done by hand by an expert curator. RESULTS: We present a computational tool for processing single cell RNA-seq data that uses a voting algorithm to automatically identify cells based on approval votes received by known molecular markers. Using a stochastic procedure that accounts for imbalances in the number of known molecular signatures for different cell types, the method computes the statistical significance of the final approval score and automatically assigns a cell type to clusters without an expert curator. We demonstrate the utility of the tool in the analysis of eight samples of bone marrow from the Human Cell Atlas. The tool provides a systematic identification of cell types in bone marrow based on a list of markers of immune cell types, and incorporates a suite of visualization tools that can be overlaid on a t-SNE representation. The software is freely available as a Python package at https://github.com/sdomanskyi/DigitalCellSorter . CONCLUSIONS: This methodology assures that extensive marker to cell type matching information is taken into account in a systematic way when assigning cell clusters to cell types. Moreover, the method allows for a high throughput processing of multiple scRNA-seq datasets, since it does not involve an expert curator, and it can be applied recursively to obtain cell sub-types. The software is designed to allow the user to substitute the marker to cell type matching information and apply the methodology to different cellular environments.


Assuntos
Células da Medula Óssea/citologia , Perfilação da Expressão Gênica/métodos , Análise de Sequência de RNA/métodos , Software , Algoritmos , Células da Medula Óssea/metabolismo , Análise por Conglomerados , Humanos , Análise de Componente Principal , Análise de Célula Única
13.
J Cancer Res Clin Oncol ; 145(8): 1977-1986, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31309300

RESUMO

CONTEXT: Parathyroid carcinoma (PC) is a rare endocrine malignancy with no approved systemic therapies for unresectable locally invasive or distant metastatic disease. Understanding the molecular changes in advanced PC can provide better understanding of this disease and potentially help directing targeted therapy. OBJECTIVE: To evaluate tumor-specific genetic changes using next-generation sequencing (NGS) panels. DESIGN: All patients with advanced PC were tested for hot-spot panels using NGS panels including a 50-gene panel, a 409-gene panel if the standard 50-gene panel (Ion Torrent, Life Technology) was negative or a FoundationOne panel. SETTING: The University of Texas MD Anderson Cancer Center, Houston, Texas, USA. PATIENTS OR OTHER PARTICIPANTS: 11 patients with advanced PC were selected to undergo molecular testing. MAIN OUTCOME MEASURE(S): Genetic profiles of advanced PC. RESULTS: Among the 11 patients, 4 patients had the 50-gene panel only, 6 had 409-gene panel after a negative 50-gene panel and 1 had FoundationOne. One patient who had 50-gene panel only also had his metastatic site (esophagus) of his tumor tested with FoundationOne. The most common mutations identified were in the PI3 K (PIK3CA, TSC1 and ATM) (4/11 patients) and TP53 (3/11) pathways. Genes not previously reported to be mutated in PC included: SDHA, TERT promoter and DICER1. Actionable mutations were found in 54% (6/11) of the patients. CONCLUSIONS: Mutational profiling using NGS panels in advanced PC has yielded important potentially targetable genetic alterations. Larger studies are needed to identify commonly mutated genes in advanced PC patients. Development of novel therapies targeting these cellular pathways should be considered.


Assuntos
Carcinoma/genética , Perfilação da Expressão Gênica , Técnicas de Diagnóstico Molecular/métodos , Monitorização Fisiológica/métodos , Neoplasias das Paratireoides/genética , Adulto , Idoso , Protocolos de Quimioterapia Combinada Antineoplásica/uso terapêutico , Carcinoma/diagnóstico , Carcinoma/patologia , Carcinoma/terapia , Análise Mutacional de DNA/métodos , Progressão da Doença , Feminino , Seguimentos , Perfilação da Expressão Gênica/métodos , Sequenciamento de Nucleotídeos em Larga Escala , Humanos , Masculino , Pessoa de Meia-Idade , Técnicas de Diagnóstico Molecular/tendências , Terapia de Alvo Molecular/métodos , Terapia de Alvo Molecular/tendências , Neoplasias das Paratireoides/diagnóstico , Neoplasias das Paratireoides/patologia , Neoplasias das Paratireoides/terapia
14.
Nat Commun ; 10(1): 3101, 2019 07 15.
Artigo em Inglês | MEDLINE | ID: mdl-31308377

RESUMO

The identification of cancer-promoting genetic alterations is challenging particularly in highly unstable and heterogeneous cancers, such as esophageal adenocarcinoma (EAC). Here we describe a machine learning algorithm to identify cancer genes in individual patients considering all types of damaging alterations simultaneously. Analysing 261 EACs from the OCCAMS Consortium, we discover helper genes that, alongside well-known drivers, promote cancer. We confirm the robustness of our approach in 107 additional EACs. Unlike recurrent alterations of known drivers, these cancer helper genes are rare or patient-specific. However, they converge towards perturbations of well-known cancer processes. Recurrence of the same process perturbations, rather than individual genes, divides EACs into six clusters differing in their molecular and clinical features. Experimentally mimicking the alterations of predicted helper genes in cancer and pre-cancer cells validates their contribution to disease progression, while reverting their alterations reveals EAC acquired dependencies that can be exploited in therapy.


Assuntos
Adenocarcinoma/genética , Antineoplásicos/uso terapêutico , Biomarcadores Tumorais/genética , Neoplasias Esofágicas/genética , Perfilação da Expressão Gênica/métodos , Medicina de Precisão/métodos , Antineoplásicos/farmacologia , Biomarcadores Tumorais/antagonistas & inibidores , Biologia Computacional/métodos , Conjuntos de Dados como Assunto , Progressão da Doença , Dosagem de Genes , Regulação Neoplásica da Expressão Gênica/efeitos dos fármacos , Instabilidade Genômica , Humanos , Aprendizado de Máquina , Modelos Genéticos , Família Multigênica/efeitos dos fármacos , Taxa de Mutação , Polimorfismo de Nucleotídeo Único
15.
Cancer Imaging ; 19(1): 48, 2019 Jul 15.
Artigo em Inglês | MEDLINE | ID: mdl-31307537

RESUMO

BACKGROUND: Imaging techniques can provide information about the tumor non-invasively and have been shown to provide information about the underlying genetic makeup. Correlating image-based phenotypes (radiomics) with genomic analyses is an emerging area of research commonly referred to as "radiogenomics" or "imaging-genomics". The purpose of this study was to assess the potential for using an automated, quantitative radiomics platform on magnetic resonance (MR) breast imaging for inferring underlying activity of clinically relevant gene pathways derived from RNA sequencing of invasive breast cancers prior to therapy. METHODS: We performed quantitative radiomic analysis on 47 invasive breast cancers based on dynamic contrast enhanced 3 Tesla MR images acquired before surgery and obtained gene expression data by performing total RNA sequencing on corresponding fresh frozen tissue samples. We used gene set enrichment analysis to identify significant associations between the 186 gene pathways and the 38 image-based features that have previously been validated. RESULTS: All radiomic size features were positively associated with multiple replication and proliferation pathways and were negatively associated with the apoptosis pathway. Gene pathways related to immune system regulation and extracellular signaling had the highest number of significant radiomic feature associations, with an average of 18.9 and 16 features per pathway, respectively. Tumors with upregulation of immune signaling pathways such as T-cell receptor signaling and chemokine signaling as well as extracellular signaling pathways such as cell adhesion molecule and cytokine-cytokine interactions were smaller, more spherical, and had a more heterogeneous texture upon contrast enhancement. Tumors with higher expression levels of JAK/STAT and VEGF pathways had more intratumor heterogeneity in image enhancement texture. Other pathways with robust associations to image-based features include metabolic and catabolic pathways. CONCLUSIONS: We provide further evidence that MR imaging of breast tumors can infer underlying gene expression by using RNA sequencing. Size and shape features were appropriately correlated with proliferative and apoptotic pathways. Given the high number of radiomic feature associations with immune pathways, our results raise the possibility of using MR imaging to distinguish tumors that are more immunologically active, although further studies are necessary to confirm this observation.


Assuntos
Neoplasias da Mama/diagnóstico por imagem , Perfilação da Expressão Gênica/métodos , Genômica/métodos , Imagem por Ressonância Magnética/métodos , Idoso , Apoptose , Neoplasias da Mama/genética , Feminino , Humanos , Fenótipo
16.
BMC Med Genet ; 20(1): 104, 2019 06 11.
Artigo em Inglês | MEDLINE | ID: mdl-31185929

RESUMO

BACKGROUND: A multidirectional relationship has been demonstrated between myocardial infarction (MI) and depression. However, the causal genetic factors and molecular mechanisms underlying this interaction remain unclear. The main purpose of this study was to identify potential candidate genes for the interaction between the two diseases. METHODS: Using a bioinformatics approach and existing gene expression data in the biomedical discovery support system (BITOLA), we defined the starting concept X as "Myocardial Infarction" and end concept Z as "Major Depressive Disorder" or "Depressive disorder". All intermediate concepts relevant to the "Gene or Gene Product" for MI and depression were searched. Gene expression data and tissue-specific expression of potential candidate genes were evaluated using the Human eFP (electronic Fluorescent Pictograph) Browser, and intermediate concepts were filtered by manual inspection. RESULTS: Our analysis identified 128 genes common to both the "MI" and "depression" text mining concepts. Twenty-three of the 128 genes were selected as intermediates for this study, 9 of which passed the manual filtering step. Among the 9 genes, LCAT, CD4, SERPINA1, IL6, and PPBP failed to pass the follow-up filter in the Human eFP Browser, due to their low levels in the heart tissue. Finally, four genes (GNB3, CNR1, MTHFR, and NCAM1) remained. CONCLUSIONS: GNB3, CNR1, MTHFR, and NCAM1 are putative new candidate genes that may influence the interactions between MI and depression, and may represent potential targets for therapeutic intervention.


Assuntos
Biologia Computacional/métodos , Mineração de Dados/métodos , Transtorno Depressivo Maior/genética , Predisposição Genética para Doença/genética , Infarto do Miocárdio/genética , Perfilação da Expressão Gênica/métodos , Perfilação da Expressão Gênica/estatística & dados numéricos , Humanos , Reprodutibilidade dos Testes
17.
Nat Commun ; 10(1): 2760, 2019 06 24.
Artigo em Inglês | MEDLINE | ID: mdl-31235787

RESUMO

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure.


Assuntos
Redes Reguladoras de Genes/genética , Insuficiência Cardíaca/genética , Miócitos Cardíacos/patologia , Fosfoproteínas Fosfatases/metabolismo , Animais , Benzenoacetamidas , Células Cultivadas , Conjuntos de Dados como Assunto , Modelos Animais de Doenças , Feminino , Perfilação da Expressão Gênica/métodos , Regulação da Expressão Gênica , Técnicas de Silenciamento de Genes , Estudo de Associação Genômica Ampla , Insuficiência Cardíaca/etiologia , Insuficiência Cardíaca/metabolismo , Insuficiência Cardíaca/patologia , Humanos , Masculino , Redes e Vias Metabólicas/genética , Camundongos , Camundongos Knockout , Pessoa de Meia-Idade , Fosfoproteínas Fosfatases/genética , Cultura Primária de Células , Piridinas , Locos de Características Quantitativas/genética , Ratos , Ratos Sprague-Dawley , Análise de Sequência de RNA/métodos
18.
Medicine (Baltimore) ; 98(23): e15871, 2019 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-31169691

RESUMO

To evaluate the ability of a radiomics signature based on 3T dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to distinguish between low and non-low Oncotype DX (OD) risk groups in estrogen receptor (ER)-positive invasive breast cancers.Between May 2011 and March 2016, 67 women with ER-positive invasive breast cancer who performed preoperative 3T MRI and OD assay were included. We divided the patients into low (OD recurrence score [RS] <18) and non-low risk (RS ≥18) groups. Extracted radiomics features included 8 morphological, 76 histogram-based, and 72 higher-order texture features. A radiomics signature (Rad-score) was generated using the least absolute shrinkage and selection operator (LASSO). Univariate and multivariate logistic regression analyses were performed to investigate the association between clinicopathologic factors, MRI findings, and the Rad-score with OD risk groups, and the areas under the receiver operating characteristic curves (AUC) were used to assess classification performance of the Rad-score.The Rad-score was constructed for each tumor by extracting 10 (6.3%) from 158 radiomics features. A higher Rad-score (odds ratio [OR], 65.209; P <.001), Ki-67 expression (OR, 17.462; P = .007), and high p53 (OR = 8.449; P = .077) were associated with non-low OD risk. The Rad-score classified low and non-low OD risk with an AUC of 0.759.The Rad-score showed the potential for discrimination between low and non-low OD risk groups in patients with ER-positive invasive breast cancers.


Assuntos
Neoplasias da Mama/diagnóstico por imagem , Neoplasias da Mama/genética , Genômica/métodos , Processamento de Imagem Assistida por Computador/métodos , Imagem por Ressonância Magnética/métodos , Receptores Estrogênicos/biossíntese , Adulto , Neoplasias da Mama/patologia , Meios de Contraste/administração & dosagem , Feminino , Perfilação da Expressão Gênica/métodos , Perfilação da Expressão Gênica/normas , Humanos , Pessoa de Meia-Idade , Recidiva Local de Neoplasia/genética , Recidiva Local de Neoplasia/patologia , Compostos Organometálicos/administração & dosagem , Curva ROC , Reprodutibilidade dos Testes , Medição de Risco , Sensibilidade e Especificidade
19.
Gene ; 710: 375-386, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31200084

RESUMO

Cynanchum thesioides are upright, xerophytic shrubs that are widely distributed in arid and semi-arid areas of China, North Korea, Mongolia and Siberia. To date, little is known about the molecular mechanisms of drought resistance in C. thesioides. To better understand drought resistance, we used transcriptome analysis and Illumina sequencing technology on C. thesioides, to identify drought-responsive genes. Using de novo assembly 55,268 unigenes were identified from 207.58 Gb of clean data. Amongst these, 36,265 were annotated with gene descriptions, conserved domains, gene ontology terms and metabolic pathways. The sequencing results showed that genes that were differentially expressed (DEGs) under drought stress were enriched in pathways such as carbon metabolism, starch and sucrose metabolism, amino acid biosynthesis, phenylpropanoid biosynthesis and plant hormone signal transduction. Moreover, many functional genes were up-regulated under severe drought stress to enhance tolerance. Weighted gene co-expression network analysis showed that there were key hub genes related to drought stress. Hundreds of candidate genes were identified under severe drought stress, including transcriptional factors such as MYB, G2-like, ERF, C2H2, NAC, NF-X1, GRF, HD-ZIP, HB-other, HSF, C3H, GRAS, WRKY, bHLH and Trihelix. These data are a valuable resource for further investigation into the molecular mechanism for drought stress in C. thesioides and will facilitate exploration of drought resistance genes.


Assuntos
Cynanchum/genética , Secas , Perfilação da Expressão Gênica/métodos , Redes Reguladoras de Genes , Regulação da Expressão Gênica de Plantas , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Anotação de Sequência Molecular , Proteínas de Plantas/genética , Análise de Sequência de RNA/métodos , Estresse Fisiológico
20.
Gene ; 710: 406-414, 2019 Aug 20.
Artigo em Inglês | MEDLINE | ID: mdl-31200087

RESUMO

Integrins are cell attachment receptors that function in the communication between the intracellular and extracellular compartments. Integrins and extra cellular matrix (ECM) collaborate to regulate gene expression by extracellular signal-regulated kinases (ERKs). Integrins as regulators, have critical role in ECM remodeling. Fibrosis is the hallmark of obesity and insulin resistance originated by aberrant ECM remodeling. Therefore deciphering integrins' expression profile in cells at different conditions is worthy. The aim of this study is evaluation of integrins' gene expression profile changes in mouse 3T3-L1 preadipocytes, adipocytes, insulin resistant and hypertrophic adipocytes. For this purpose, we differentiated mouse 3T3-L1 preadipocytes to adipocytes, insulin resistant and hypertrophied adipocytes and assayed integrins' gene expression in four conditions by real time-PCR. Also the proteins expression changes of ERK and collagen VI assayed by Western blotting. Data analysis has shown that integrins' gene expression changes throughout adipocyte differentiation and pathological processes. The expressions of many integrins genes were significantly up- or down-regulated by >1.5-fold during differentiation, insulin resistant, and hypertrophic adipocytes. In addition to changes in the type of integrin, the integrins expression levels were different. Integrins, on the whole were more expressed in pathological processes relative to normal adipocytes. Also, phosphorylation of ERK 1,2 was increased >1.5-fold in differentiated, insulin resistant and hypertrophied adipocytes versus preadipocytes. Collagen VI only increased 2-fold in hypertrophied adipocytes. Examination of the total integrin gene family expression during adipocyte differentiation and pathological processes, leads to the identification of differential integrin gene expression. These results suggest that the type of integrin may not only play a role in adipocyte differentiation but also in pathological processes which may associate to increased ERK pathway activity in these conditions.


Assuntos
Adipócitos/citologia , Adipócitos/patologia , Perfilação da Expressão Gênica/métodos , Integrinas/genética , Células 3T3-L1 , Adipócitos/metabolismo , Animais , Diferenciação Celular , Colágeno Tipo VII/metabolismo , Regulação da Expressão Gênica , Hipertrofia , Resistência à Insulina , Sistema de Sinalização das MAP Quinases , Camundongos , Família Multigênica , Fosforilação
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