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1.
Brief Bioinform ; 2020 Jan 31.
Artigo em Inglês | MEDLINE | ID: mdl-32003790

RESUMO

Moonlighting proteins provide more options for cells to execute multiple functions without increasing the genome and transcriptome complexity. Although there have long been calls for computational methods for the prediction of moonlighting proteins, no method has been designed for determining moonlighting long noncoding ribonucleicacidz (RNAs) (mlncRNAs). Previously, we developed an algorithm MoonFinder for the identification of mlncRNAs at the genome level based on the functional annotation and interactome data of lncRNAs and proteins. Here, we update MoonFinder to MoonFinder v2.0 by providing an extensive framework for the detection of protein modules and the establishment of RNA-module associations in human. A novel measure, moonlighting coefficient, was also proposed to assess the confidence of an ncRNA acting in a moonlighting manner. Moreover, we explored the expression characteristics of mlncRNAs in sepsis, in which we found that mlncRNAs tend to be upregulated and differentially expressed. Interestingly, the mlncRNAs are mutually exclusive in terms of coexpression when compared to the other lncRNAs. Overall, MoonFinder v2.0 is dedicated to the prediction of human mlncRNAs and thus bears great promise to serve as a valuable R package for worldwide research communities (https://cran.r-project.org/web/packages/MoonFinder/index.html). Also, our analyses provide the first attempt to characterize mlncRNA expression and coexpression properties in adult sepsis patients, which will facilitate the understanding of the interaction and expression patterns of mlncRNAs.

3.
RNA Biol ; 17(1): 13-22, 2020 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-31533522

RESUMO

The CRISPR-Cas9 system has become the most promising and versatile tool for genetic manipulation applications. Albeit the technology has been broadly adopted by both academic and pharmaceutic societies, the activity (on-target) and specificity (off-target) of CRISPR-Cas9 are decisive factors for any application of the technology. Several in silico gRNA activity and specificity predicting models and web tools have been developed, making it much more convenient and precise for conducting CRISPR gene editing studies. In this review, we present an overview and comparative analysis of machine and deep learning (MDL)-based algorithms, which are believed to be the most effective and reliable methods for the prediction of CRISPR gRNA on- and off-target activities. As an increasing number of sequence features and characteristics are discovered and are incorporated into the MDL models, the prediction outcome is getting closer to experimental observations. We also introduced the basic principle of CRISPR activity and specificity and summarized the challenges they faced, aiming to facilitate the CRISPR communities to develop more accurate models for applying.

4.
BMC Bioinformatics ; 20(Suppl 26): 628, 2019 Dec 16.
Artigo em Inglês | MEDLINE | ID: mdl-31839008

RESUMO

BACKGROUND: Development of new drugs is a time-consuming and costly process, and the cost is still increasing in recent years. However, the number of drugs approved by FDA every year per dollar spent on development is declining. Drug repositioning, which aims to find new use of existing drugs, attracts attention of pharmaceutical researchers due to its high efficiency. A variety of computational methods for drug repositioning have been proposed based on machine learning approaches, network-based approaches, matrix decomposition approaches, etc. RESULTS: We propose a novel computational method for drug repositioning. We construct and decompose three-dimensional tensors, which consist of the associations among drugs, targets and diseases, to derive latent factors reflecting the functional patterns of the three kinds of entities. The proposed method outperforms several baseline methods in recovering missing associations. Most of the top predictions are validated by literature search and computational docking. Latent factors are used to cluster the drugs, targets and diseases into functional groups. Topological Data Analysis (TDA) is applied to investigate the properties of the clusters. We find that the latent factors are able to capture the functional patterns and underlying molecular mechanisms of drugs, targets and diseases. In addition, we focus on repurposing drugs for cancer and discover not only new therapeutic use but also adverse effects of the drugs. In the in-depth study of associations among the clusters of drugs, targets and cancer subtypes, we find there exist strong associations between particular clusters. CONCLUSIONS: The proposed method is able to recover missing associations, discover new predictions and uncover functional clusters of drugs, targets and diseases. The clustering of drugs, targets and diseases, as well as the associations among the clusters, provides a new guiding framework for drug repositioning.


Assuntos
Biologia Computacional , Reposicionamento de Medicamentos , Análise por Conglomerados , Biologia Computacional/métodos , Reposicionamento de Medicamentos/métodos , Humanos , Aprendizado de Máquina
5.
Vet Microbiol ; 235: 209-219, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31383304

RESUMO

Porcine epidemic diarrhea virus (PEDV), the causative agent of PED, is an enveloped, positive-stranded RNA virus in the genus Alphacoronavirus, family Coronaviridae, order Nidovirales. PEDV non-structural accessory protein ORF3 is an ion channel related to viral infectivity and pathogenicity. Our previous study showed that PEDV ORF3 has expression characteristic of aggregation in cytoplasm, but its biological function remains elusive. Thus in this study, we initiated the construction of various vectors to express ORF3, and found ORF3 localized in the cytoplasm in the aggregation manner. Subsequently, confocal microscopy analysis showed that the aggregated ORF3 localized in endoplasmic reticulum (ER) to trigger ER stress response via up-regulation of GRP78 protein expression and activation of PERK-eIF2α signaling pathway. In addition, our results showed that PEDV ORF3 could induce the autophagy through inducing conversion of LC3-I to LC3-II, but couldn't influence the apoptosis. In contrast, conversion of LC3-I/LC3-II could be significantly inhibited by 4-PBA, an ER stress inhibitor, indicating that ORF3-induced autophagy is dependent on ER stress response. This work not only provides some new findings for the biological function of the PEDV ORF3 protein, but also help us for the further understanding the molecular interaction between PEDV ORF3 protein and cells.


Assuntos
Autofagia , Estresse do Retículo Endoplasmático , Retículo Endoplasmático/virologia , Fases de Leitura Aberta , Vírus da Diarreia Epidêmica Suína/patogenicidade , Proteínas Virais/genética , Animais , Retículo Endoplasmático/patologia , Vetores Genéticos , Células HEK293 , Células HeLa , Proteínas de Choque Térmico/genética , Humanos , Transdução de Sinais , Suínos , Células Vero , Replicação Viral
6.
Plant Cell ; 31(9): 2152-2168, 2019 09.
Artigo em Inglês | MEDLINE | ID: mdl-31221737

RESUMO

FYVE domain protein required for endosomal sorting1 (FREE1), a plant-specific endosomal sorting complex required for transport-I component, is essential for the biogenesis of multivesicular bodies (MVBs), vacuolar degradation of membrane protein, cargo vacuolar sorting, autophagic degradation, and vacuole biogenesis in Arabidopsis (Arabidopsis thaliana). Here, we report the characterization of RESURRECTION1 (RST1) as a suppressor of free1 that, when mutated as a null mutant, restores the normal MVB and vacuole formation of a FREE1-RNAi knockdown line and consequently allows survival. RST1 encodes an evolutionarily conserved multicellular organism-specific protein, which contains two Domain of Unknown Function 3730 domains, showing no similarity to known proteins, and predominantly localizes in the cytosol. The depletion of FREE1 causes substantial accumulation of RST1, and transgenic Arabidopsis plants overexpressing RST1 display retarded seedling growth with dilated MVBs, and inhibition of endocytosed FM4-64 dye to the tonoplast, suggesting that RST1 has a negative role in vacuolar transport. Consistently, enhanced endocytic degradation of membrane vacuolar cargoes occurs in the rst1 mutant. Further transcriptomic comparison of rst1 with free1 revealed a negative association between gene expression profiles, demonstrating that FREE1 and RST1 have antagonistic functions. Thus, RST1 is a negative regulator controlling membrane protein homeostasis and FREE1-mediated functions in plants.

7.
BMC Bioinformatics ; 20(1): 23, 2019 Jan 14.
Artigo em Inglês | MEDLINE | ID: mdl-30642247

RESUMO

BACKGROUND: Clustering molecular network is a typical method in system biology, which is effective in predicting protein complexes or functional modules. However, few studies have realized that biological molecules are spatial-temporally regulated to form a dynamic cellular network and only a subset of interactions take place at the same location in cells. RESULTS: In this study, considering the subcellular localization of proteins, we first construct a co-localization human protein interaction network (PIN) and systematically investigate the relationship between subcellular localization and biological functions. After that, we propose a Locational and Topological Overlap Model (LTOM) to preprocess the co-localization PIN to identify functional modules. LTOM requires the topological overlaps, the common partners shared by two proteins, to be annotated in the same localization as the two proteins. We observed the model has better correspondence with the reference protein complexes and shows more relevance to cancers based on both human and yeast datasets and two clustering algorithms, ClusterONE and MCL. CONCLUSION: Taking into consideration of protein localization and topological overlap can improve the performance of module detection from protein interaction networks.


Assuntos
Algoritmos , Biologia Computacional/métodos , Bases de Dados de Proteínas , Proteínas de Neoplasias/metabolismo , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas , Proteínas de Saccharomyces cerevisiae/metabolismo , Humanos , Proteínas de Neoplasias/química , Proteínas de Saccharomyces cerevisiae/química
8.
Cancer Manag Res ; 10: 5083-5089, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30464608

RESUMO

Purpose: DKK1 is an antagonist of the Wnt signaling pathway that has various roles in human physiology. Notably, aberrant DKK1 expression is observed in several cancers. In this retrospective study, we assessed the association between DKK1 expression levels and head and neck squamous cell carcinoma (HNSCC) and its prognostic value. Materials and methods: Using RNA-seq data from HNSCC tumors (N=520) and adjacent normal tissue (N=44) in The Cancer Genome Atlas, we evaluated DKK1 expression levels. Additionally, we evaluated the association of DKK1 expression levels and pathophysiological features of patients with HNSCC and the value of DKK1 expression for prediction of overall survival (OS). We also explored the correlation between DKK1 expression and methylation of its promoter in HNSCC. Results: DKK1 expression was significantly upregulated in HNSCC compared with normal tissues. Moreover, DKK1 expression was significantly associated with smoking, alcohol abuse, sex, human papillomavirus status, tumor site, tumor invasion, and pathologic stage in HNSCC patients. Kaplan-Meier curves showed that high DKK1 expression was correlated with inferior OS. In addition, univariate and multivariate analyses showed that elevated DKK1 expression was an independent prognostic factor for poor OS (HR: 1.85, 95% CI: 1.31-2.62, P<0.001). Regression analysis identified a strong negative correlation between DKK1 expression and methylation of its promoter. Conclusion: These findings support the hypothesis that elevated DKK1 expression is modulated via methylation of its promoter and indicate that DKK1 expression is a highly informative prognostic biomarker for patients with HNSCC.

9.
Virus Res ; 255: 55-67, 2018 08 15.
Artigo em Inglês | MEDLINE | ID: mdl-30006004

RESUMO

Stress granules (SGs) are host translationally silent ribonucleo-proteins formed in cells in response to multiple types of environmental stress, including viral infection. We previously showed that the nuclear protein, 68-kDa Src-associated in mitosis protein (Sam68), is recruited to cytoplasm and form the Sam68-positive SGs at 6 hpi, but the Sam68-positive SGs disassembled beyond 12 hpi, suggesting that the SGs might be inhibited during the late stage of Enterovirus 71 (EV71) infection. However, the mechanism and function of this process remains poorly understood. Thus in this study, we demonstrated that EV71 initially induced SGs formation at the early stage of EV71 infection, and confirmed that 2Apro of EV71 was the key viral component that triggered SG formation. In contrast, SGs were diminished as EV71 infection proceeding. At the same time, arsenite-induced SGs were also blocked at the late stage of EV71 infection. This disruption of SGs was caused by viral protease 3Cpro-mediated G3BP1 cleavage. Furthermore, we demonstrated that over-expression of G3BP1-SGs negatively impacted viral replication at the cytopathic effect (CPE), protein, RNA, and viral titer levels. Our novel finding may not only help us to better understand the mechanism how EV71 interacts with the SG response, but also provide mechanistic linkage between cellular stress responses and innate immune activation during EV71 infection.


Assuntos
Cisteína Endopeptidases/metabolismo , Grânulos Citoplasmáticos/metabolismo , DNA Helicases/metabolismo , Enterovirus Humano A/fisiologia , Infecções por Enterovirus/virologia , Proteínas de Ligação a Poli-ADP-Ribose/metabolismo , RNA Helicases/metabolismo , Proteínas com Motivo de Reconhecimento de RNA/metabolismo , Proteínas Virais/metabolismo , Arsenitos/toxicidade , Cisteína Endopeptidases/genética , Citoplasma/metabolismo , Grânulos Citoplasmáticos/enzimologia , Grânulos Citoplasmáticos/virologia , DNA Helicases/genética , Enterovirus Humano A/metabolismo , Infecções por Enterovirus/metabolismo , Infecções por Enterovirus/patologia , Expressão Gênica , Células HeLa , Interações Hospedeiro-Patógeno , Humanos , Proteínas de Ligação a Poli-ADP-Ribose/genética , RNA Helicases/genética , Proteínas com Motivo de Reconhecimento de RNA/genética , Estresse Fisiológico/efeitos dos fármacos , Estresse Fisiológico/fisiologia , Proteínas Virais/genética , Replicação Viral
10.
Bioinformatics ; 34(20): 3519-3528, 2018 10 15.
Artigo em Inglês | MEDLINE | ID: mdl-29771280

RESUMO

Motivation: Moonlighting proteins are a class of proteins having multiple distinct functions, which play essential roles in a variety of cellular and enzymatic functioning systems. Although there have long been calls for computational algorithms for the identification of moonlighting proteins, research on approaches to identify moonlighting long non-coding RNAs (lncRNAs) has never been undertaken. Here, we introduce a novel methodology, MoonFinder, for the identification of moonlighting lncRNAs. MoonFinder is a statistical algorithm identifying moonlighting lncRNAs without a priori knowledge through the integration of protein interactome, RNA-protein interactions and functional annotation of proteins. Results: We identify 155 moonlighting lncRNA candidates and uncover that they are a distinct class of lncRNAs characterized by specific sequence and cellular localization features. The non-coding genes that transcript moonlighting lncRNAs tend to have shorter but more exons and the moonlighting lncRNAs have a variable localization pattern with a high chance of residing in the cytoplasmic compartment in comparison to the other lncRNAs. Moreover, moonlighting lncRNAs and moonlighting proteins are rather mutually exclusive in terms of both their direct interactions and interacting partners. Our results also shed light on how the moonlighting candidates and their interacting proteins implicated in the formation and development of cancers and other diseases. Availability and implementation: The code implementing MoonFinder is supplied as an R package in the supplementary material. Supplementary information: Supplementary data are available at Bioinformatics online.


Assuntos
Proteínas/genética , RNA Longo não Codificante/genética , Éxons , Genômica , Humanos , Análise de Sequência de RNA/métodos
11.
IET Syst Biol ; 12(2): 55-61, 2018 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-29533218

RESUMO

Computational clustering methods help identify functional modules in protein-protein interaction (PPI) network, in which proteins participate in the same biological pathways or specific functions. Subcellular localisation is crucial for proteins to implement biological functions and each compartment accommodates specific portions of the protein interaction structure. However, the importance of protein subcellular localisation is often neglected in the studies of module identification. In this study, the authors propose a novel procedure, subcellular module identification with localisation expansion (SMILE), to identify super modules that consist of several subcellular modules performing specific biological functions among cell compartments. These super modules identified by SMILE are more functionally diverse and have been verified to be more associated with known protein complexes and biological pathways compared with the modules identified from the global PPI networks in both the compartmentalised PPI and InWeb_InBioMap datasets. The authors' results reveal that subcellular localisation is a principal feature of functional modules and offers important guidance in detecting biologically meaningful results.


Assuntos
Análise por Conglomerados , Mapas de Interação de Proteínas , Algoritmos , Mapeamento de Interação de Proteínas , Proteínas
12.
J Mol Cell Biol ; 10(2): 130-138, 2018 04 01.
Artigo em Inglês | MEDLINE | ID: mdl-29390072

RESUMO

Subcellular localization is pivotal for RNAs and proteins to implement biological functions. The localization diversity of protein interactions has been studied as a crucial feature of proteins, considering that the protein-protein interactions take place in various subcellular locations. Nevertheless, the localization diversity of non-coding RNA (ncRNA) target proteins has not been systematically studied, especially its characteristics in cancers. In this study, we provide a new algorithm, non-coding RNA target localization coefficient (ncTALENT), to quantify the target localization diversity of ncRNAs based on the ncRNA-protein interaction and protein subcellular localization data. ncTALENT can be used to calculate the target localization coefficient of ncRNAs and measure how diversely their targets are distributed among the subcellular locations in various scenarios. We focus our study on long non-coding RNAs (lncRNAs), and our observations reveal that the target localization diversity is a primary characteristic of lncRNAs in different biotypes. Moreover, we found that lncRNAs in multiple cancers, differentially expressed cancer lncRNAs, and lncRNAs with multiple cancer target proteins are prone to have high target localization diversity. Furthermore, the analysis of gastric cancer helps us to obtain a better understanding that the target localization diversity of lncRNAs is an important feature closely related to clinical prognosis. Overall, we systematically studied the target localization diversity of the lncRNAs and uncovered its association with cancer.


Assuntos
Regulação Neoplásica da Expressão Gênica , Neoplasias/genética , Proteínas/genética , RNA não Traduzido/genética , Algoritmos , Animais , Genômica , Humanos , Neoplasias/patologia , Proteínas/análise , Neoplasias Gástricas/genética , Neoplasias Gástricas/patologia
13.
J Proteome Res ; 16(8): 3019-3029, 2017 08 04.
Artigo em Inglês | MEDLINE | ID: mdl-28707887

RESUMO

Spatial-temporal regulation among proteins forms dynamic networks in cells. Coexistence in common cell compartments can improve biological reliability of the protein-protein interactions. However, this is usually overlooked by most proteomic studies and leads to unrealistic discoveries. In this paper, we systematically characterize the interaction localization diversity in the human protein interactome using the localization coefficient, a novel metric proposed for assessing how diversely the interactions localize among cell compartments. Our analysis reveals the following: (1) the subcellular networks of the nucleus, cytosol, and mitochondrion are dense but the interactions tend to localize in specific cell compartments, whereas the subnetworks of the secretory-pathway, membrane, and extracellular region are sparse but the interactions are diversely localized; (2) the housekeeping proteins tend to appear in multiple compartments, while the tissue-specific proteins present a relatively flat profile of localization breadth; (3) the autophagy proteins tend to diversely localize in multiple compartments, especially those with high connectivity, compared with the apoptosis proteins; (4) the proteins targeted by small-molecule drugs show no preference for compartments, whereas the proteins directed by antibody-based drugs tend to belong to transmembrane regions with a strong diversity. In summary, our analysis provides a comprehensive view of the subcellular localization for interacting proteins, demonstrates that localization diversity is an important feature of protein interactions, and shows its ability to highlight meaningful biological functions.


Assuntos
Compartimento Celular , Mapas de Interação de Proteínas/fisiologia , Proteoma/análise , Frações Subcelulares/química , Humanos , Espaço Intracelular/química , Mapeamento de Interação de Proteínas , Proteômica/métodos , Análise Espaço-Temporal , Frações Subcelulares/fisiologia
14.
Mol Biosyst ; 12(10): 3057-66, 2016 10 20.
Artigo em Inglês | MEDLINE | ID: mdl-27452923

RESUMO

The global increase of gene expression has been frequently established in cancer microarray studies. However, many genes may not deliver informative signals for a given experiment, due to insufficient expression or even non-expression, despite the DNA microarrays massively measuring genes in parallel. Hence the informative gene set, rather than the whole genome, should be more reasonable to represent the genome expression level. We observed that the trend of over-expression for informative genes is more obvious in human cancers, which is to some extent masked using the whole genome without any filtering. Accordingly we proposed a novel normalization method, Informative CrossNorm (ICN), which performs the cross normalization (CrossNorm) on the expression matrix merely containing the informative genes. ICN outperforms other methods with a consistently high precision, F-score, and Matthews correlation coefficient as well as an acceptable recall based on three available spiked-in datasets with ground truth. In addition, nine potential therapeutic target genes for esophageal squamous cell carcinoma (ESCC) were identified using ICN integrated with a protein-protein interaction network, which biologically demonstrates that ICN shows superior performance. Consequently, it is expected that ICN could be applied routinely in cancer microarray studies.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Expressão Gênica , Carcinoma de Células Escamosas/genética , Bases de Dados Genéticas , Neoplasias Esofágicas/genética , Carcinoma de Células Escamosas do Esôfago , Redes Reguladoras de Genes , Humanos , Neoplasias/genética , Neoplasias/metabolismo , Mapeamento de Interação de Proteínas/métodos , Mapas de Interação de Proteínas , Reprodutibilidade dos Testes , Fluxo de Trabalho
15.
Sci Rep ; 6: 18898, 2016 Jan 06.
Artigo em Inglês | MEDLINE | ID: mdl-26732145

RESUMO

Normalization is essential to get rid of biases in microarray data for their accurate analysis. Existing normalization methods for microarray gene expression data commonly assume a similar global expression pattern among samples being studied. However, scenarios of global shifts in gene expressions are dominant in cancers, making the assumption invalid. To alleviate the problem, here we propose and develop a novel normalization strategy, Cross Normalization (CrossNorm), for microarray data with unbalanced transcript levels among samples. Conventional procedures, such as RMA and LOESS, arbitrarily flatten the difference between case and control groups leading to biased gene expression estimates. Noticeably, applying these methods under the strategy of CrossNorm, which makes use of the overall statistics of the original signals, the results showed significantly improved robustness and accuracy in estimating transcript level dynamics for a series of publicly available datasets, including titration experiment, simulated data, spike-in data and several real-life microarray datasets across various types of cancers. The results have important implications for the past and the future cancer studies based on microarray samples with non-negligible difference. Moreover, the strategy can also be applied to other sorts of high-throughput data as long as the experiments have global expression variations between conditions.


Assuntos
Biologia Computacional/métodos , Perfilação da Expressão Gênica/métodos , Neoplasias/terapia , Simulação por Computador , Conjuntos de Dados como Assunto , Humanos , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Reprodutibilidade dos Testes
16.
Artigo em Chinês | MEDLINE | ID: mdl-27101688

RESUMO

Laryngeal interarytenoid neurilemmomas (LIN) is a benign encapsulated tumor originating from the schwann cells lining nerve fibers. Even though LINs are extremely rare in incidence, they could present with potential threat to the airway and thus requiring prompt diagnosis and treatment. Here, we report two cases of LINs. Both patients underwent excision of the tumor via microlaryngeal endoscopic procedures and recovered well postoperatively without complications. No recurrence was observed postoperatively on routine follow-up after 14 months.


Assuntos
Endoscopia , Laringe/cirurgia , Neurilemoma/cirurgia , Procedimentos Cirúrgicos Otorrinolaringológicos , Humanos , Laringe/patologia , Período Pós-Operatório
17.
Nucleic Acids Res ; 43(Database issue): D578-82, 2015 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-25274736

RESUMO

Increasing evidence reveals that diverse non-coding RNAs (ncRNAs) play critically important roles in viral infection. Viruses can use diverse ncRNAs to manipulate both cellular and viral gene expression to establish a host environment conducive to the completion of the viral life cycle. Many host cellular ncRNAs can also directly or indirectly influence viral replication and even target virus genomes. ViRBase (http://www.rna-society.org/virbase) aims to provide the scientific community with a resource for efficient browsing and visualization of virus-host ncRNA-associated interactions and interaction networks in viral infection. The current version of ViRBase documents more than 12,000 viral and cellular ncRNA-associated virus-virus, virus-host, host-virus and host-host interactions involving more than 460 non-redundant ncRNAs and 4400 protein-coding genes from between more than 60 viruses and 20 hosts. Users can query, browse and manipulate these virus-host ncRNA-associated interactions. ViRBase will be of help in uncovering the generic organizing principles of cellular virus-host ncRNA-associated interaction networks in viral infection.


Assuntos
Bases de Dados Genéticas , RNA não Traduzido/metabolismo , Viroses/genética , Viroses/virologia , Sítios de Ligação , Internet , Proteínas/metabolismo , Viroses/metabolismo , Vírus/metabolismo
18.
Gene ; 506(1): 36-42, 2012 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-22771920

RESUMO

Nowadays, some researchers normalized DNA methylation arrays data in order to remove the technical artifacts introduced by experimental differences in sample preparation, array processing and other factors. However, other researchers analyzed DNA methylation arrays without performing data normalization considering that current normalizations for methylation data may distort real differences between normal and cancer samples because cancer genomes may be extensively subject to hypomethylation and the total amount of CpG methylation might differ substantially among samples. In this study, using eight datasets by Infinium HumanMethylation27 assay, we systemically analyzed the global distribution of DNA methylation changes in cancer compared to normal control and its effect on data normalization for selecting differentially methylated (DM) genes. We showed more differentially methylated (DM) genes could be found in the Quantile/Lowess-normalized data than in the non-normalized data. We found the DM genes additionally selected in the Quantile/Lowess-normalized data showed significantly consistent methylation states in another independent dataset for the same cancer, indicating these extra DM genes were effective biological signals related to the disease. These results suggested normalization can increase the power of detecting DM genes in the context of diagnostic markers which were usually characterized by relatively large effect sizes. Besides, we evaluated the reproducibility of DM discoveries for a particular cancer type, and we found most of the DM genes additionally detected in one dataset showed the same methylation directions in the other dataset for the same cancer type, indicating that these DM genes were effective biological signals in the other dataset. Furthermore, we showed that some DM genes detected from different studies for a particular cancer type were significantly reproducible at the functional level.


Assuntos
Metilação de DNA , Neoplasias/genética , Algoritmos , Neoplasias Colorretais/genética , Interpretação Estatística de Dados , Bases de Dados de Ácidos Nucleicos , Genoma Humano , Humanos , Neoplasias Renais/genética , Neoplasias Pulmonares/genética , Análise de Sequência com Séries de Oligonucleotídeos/estatística & dados numéricos , Reprodutibilidade dos Testes , Neoplasias Gástricas/genética
19.
Artigo em Chinês | MEDLINE | ID: mdl-22506428

RESUMO

OBJECTIVE: To study the significance of exposure of the recurrent laryngeal nerve (RLN ) in thyroid gland surgery. METHOD: Three hundred and thirty-two thyroidectomy cases were studied from January 2008 to June 2011. All patients had general anesthesia, and RLN were exposed during operation. One hundred and thirty-one cases were operated with total lobectomies, 138 cases with subtotal thyroidectomy, 51 cases with total lobectomies and contralateral subtotal thyroidectomy, 12 cases with total thyroidectomy. RESULT: Five hundred and thirty-three RLNs were exposed, 4 cases came with hoarseness postoperatively, All cases recovered within 3 months. CONCLUSION: Exposure the recurrent laryngeal nerve in the thyroidectomy was available and could protect RLN.


Assuntos
Nervo Laríngeo Recorrente/cirurgia , Tireoidectomia/métodos , Adolescente , Adulto , Idoso , Feminino , Rouquidão/cirurgia , Humanos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos , Adulto Jovem
20.
Med Oncol ; 29(4): 2473-80, 2012 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-22246523

RESUMO

Survivin has been shown to be an ideal target for cancer gene therapy because of its strong antiapoptotic effect. MicroRNA-34a (miR-34a) can function as a tumor suppressor in some cancers through negative regulation of gene expression. However, the relationship between miR-34a and survivin in larynx squamous cell carcinoma (LSCC) has not been explored. The abundance of survivin mRNA and miR-34a in LSCC tissues were measured using quantitative real-time polymerase chain reaction. Their expression levels were analyzed and correlated with tumor differentiation, lymphatic metastasis, clinical stages, and survival rates. MiR-34a mimic was transfected using liposomes to increase its level in LSCC cancer cell line, Hep-2. The effects of miR-34a on survivin protein expression were tested using western blot analysis. Cell cycle analyses were performed using flow cytometry. The results showed that transfection of miR-34a mimic significantly suppressed cell proliferation with decreased survivin protein expression, but did not affect mRNA expression level. The results from LSCC tissue samples showed that miR-34a was downregulated, while survivin expression was upregulated. The miR-34a levels were negatively correlated with histologic differentiation and were positively correlated with survival rate. MiR-34a significantly suppressed cell proliferation by arresting cells at G0/G1 phase in Hep-2 cells. These results indicated that miR-34a may affect the occurrence of LSCC by targeting survivin.


Assuntos
Carcinoma de Células Escamosas/genética , Proteínas Inibidoras de Apoptose/genética , Neoplasias Laríngeas/genética , MicroRNAs/fisiologia , Adulto , Idoso , Carcinoma de Células Escamosas/mortalidade , Carcinoma de Células Escamosas/patologia , Ciclo Celular , Linhagem Celular Tumoral , Intervalo Livre de Doença , Humanos , Neoplasias Laríngeas/mortalidade , Neoplasias Laríngeas/patologia , Sistema de Sinalização das MAP Quinases , Pessoa de Meia-Idade , Survivina
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