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2.
Toxicol Lett ; 316: 73-84, 2019 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-31513886

RESUMO

In the liver microenvironment, interactions among diverse types of hepatic cells are involved in liver fibrosis. In fibrotic tissues, exosomes act as transporters in intercellular communication. Long non-coding RNAs (lncRNAs) are involved in the activation of hepatic stellate cells (HSCs), which are participants in liver fibrosis. However, the functions of exosomal lncRNAs in liver fibrosis induced by arsenite are undefined. The purposes of the present study were (a) to determine if lncRNAs secreted from human hepatic (L-02) cells exposed to arsenite are shuttled to hepatic stellate LX-2 cells and (b) to establish their effects on LX-2 cells. In mice, MALAT1 was overexpressed in the progression of liver fibrosis induced by arsenite as well as in L-02 cells exposed to arsenite. Co-cultures with arsenite-treated L-02 cells induced the activation of LX-2 cells and overexpression of MALAT1. Arsenite-treated L-02 cells transported MALAT1 into LX-2 cells. Downregulation of MALAT1, which reduced the MALAT1 levels in exosomes derived from arsenite-treated L-02 cells, inhibited the activation of LX-2 cells. Additionally, exosomal MALAT1 derived from arsenite-treated L-02 cells promoted the activation of LX-2 cells via microRNA-26b regulation of COL1A2. Furthermore, circulating exosomal MALAT1 was up-regulated in people exposed to arsenite. In sum, exosomes derived from arsenite-treated hepatic cells transferred MALAT1 to HSCs, which induced their activation. These findings support the concept that, during liver fibrosis induced by arsenite, exosomal lncRNAs are involved in cell-cell communication.


Assuntos
Arsenitos , Doença Hepática Induzida por Substâncias e Drogas/metabolismo , Exossomos/metabolismo , Células Estreladas do Fígado/metabolismo , Cirrose Hepática Experimental/metabolismo , Fígado/metabolismo , MicroRNAs/metabolismo , RNA Longo não Codificante/metabolismo , Compostos de Sódio , Animais , Linhagem Celular , Doença Hepática Induzida por Substâncias e Drogas/etiologia , Doença Hepática Induzida por Substâncias e Drogas/genética , Doença Hepática Induzida por Substâncias e Drogas/patologia , Técnicas de Cocultura , Colágeno Tipo I/genética , Colágeno Tipo I/metabolismo , Exossomos/genética , Exossomos/ultraestrutura , Regulação da Expressão Gênica , Células Estreladas do Fígado/ultraestrutura , Humanos , Fígado/ultraestrutura , Cirrose Hepática Experimental/induzido quimicamente , Cirrose Hepática Experimental/genética , Cirrose Hepática Experimental/patologia , Masculino , Camundongos , MicroRNAs/genética , RNA Longo não Codificante/genética , Transdução de Sinais
3.
Aging (Albany NY) ; 11(16): 6312-6335, 2019 Aug 21.
Artigo em Inglês | MEDLINE | ID: mdl-31434796

RESUMO

Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase. Clinical and biomarker information was fused using an iCluster plus algorithm, which significantly distinguished patients into high- and low-mortality risk groups (Pdiscovery = 0.01 and Pvalidation = 2.71×10-3). Further, potential functional DNA methylation-gene expression-overall survival pathways were evaluated by causal mediation analysis. The effect of DNA methylation level on LUAD survival was significantly mediated through gene expression level. By adding DNA methylation and gene expression biomarkers to a model of only clinical data, the AUCs of the trans-omics model improved by 18.3% (to 87.2%) and 16.4% (to 85.3%) in discovery and validation phases, respectively. Further, concordance index of the nomogram was 0.81 and 0.77 in discovery and validation phases, respectively. Based on systematic review of published literatures, our model was superior to all existing models for early-stage LUAD. In summary, our trans-omics model may help physicians accurately identify patients with high mortality risk.

4.
Eur J Epidemiol ; 34(8): 753-763, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31152367

RESUMO

Current experimental and epidemiological studies provide inconsistent evidence toward the association between tea consumption and cancer incidence. We investigated whether tea consumption was associated with the incidence of all cancers and six leading types of cancer (lung cancer, stomach cancer, colorectal cancer, liver cancer, female breast cancer and cervix uteri cancer) among 455,981 participants aged 30-79 years in the prospective cohort China Kadoorie Biobank. Tea consumption was assessed at baseline (2004-2008) with an interviewer-administered questionnaire. Cancer cases were identified by linkage to the national health insurance system. Cox proportional hazard regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). In the present population, daily tea consumers were more likely to be current smokers and daily alcohol consumers. 22,652 incident cancers occurred during 10.1 years follow-up (5.04 cases/1000 person-years). When we restricted analyses to non-smokers and non-excessive alcohol consumers to minimize confounding, tea consumption was not associated with all cancers (daily consumers who added tea leaves > 4.0 g/day vs. less-than-weekly consumers: HR, 1.03; 95%CI, 0.93-1.13), lung cancer (HR, 1.08; CI, 0.84-1.40), colorectal cancer (HR, 1.08; CI, 0.81-1.45) and liver cancer (HR, 1.08; CI, 0.75-1.55), yet might be associated with increased risk of stomach cancer (HR, 1.46; CI, 1.07-1.99). In both less-than-daily and daily tea consumers, all cancer risk increased with the amount of tobacco smoked or alcohol consumed. Our findings suggest tea consumption may not provide preventive effect against cancer incidence.


Assuntos
Grupo com Ancestrais do Continente Asiático/estatística & dados numéricos , Cafeína/efeitos adversos , Neoplasias/epidemiologia , Neoplasias/etiologia , Medição de Risco/métodos , Chá/efeitos adversos , Adulto , Idoso , Consumo de Bebidas Alcoólicas/epidemiologia , Neoplasias da Mama/epidemiologia , Neoplasias da Mama/etiologia , China/epidemiologia , Neoplasias Colorretais/epidemiologia , Neoplasias Colorretais/etiologia , Feminino , Humanos , Incidência , Neoplasias Hepáticas/epidemiologia , Neoplasias Hepáticas/etiologia , Masculino , Pessoa de Meia-Idade , Modelos de Riscos Proporcionais , Estudos Prospectivos , Fatores de Risco , População Rural , Neoplasias Gástricas/epidemiologia , Neoplasias Gástricas/etiologia , Fumar Tabaco/epidemiologia , Neoplasias do Colo do Útero/epidemiologia , Neoplasias do Colo do Útero/etiologia
5.
BMJ Open ; 9(5): e023724, 2019 May 16.
Artigo em Inglês | MEDLINE | ID: mdl-31101692

RESUMO

INTRODUCTION: Left ventricular ejection fraction (LVEF) ≤35%, as current significant implantable cardioverter-defibrillator (ICD) indication for primary prevention of sudden cardiac death (SCD) in heart failure (HF) patients, has been widely recognised to be inefficient. Improvement of patient selection for low LVEF (≤35%) is needed to optimise deployment of ICD. Most of the existing prediction models are not appropriate to identify ICD candidates at high risk of SCD in HF patients with low LVEF. Compared with traditional statistical analysis, machine learning (ML) can employ computer algorithms to identify patterns in large datasets, analyse rules automatically and build both linear and non-linear models in order to make data-driven predictions. This study is aimed to develop and validate new models using ML to improve the prediction of SCD in HF patients with low LVEF. METHODS AND ANALYSIS: We will conduct a retroprospective, multicentre, observational registry of Chinese HF patients with low LVEF. The HF patients with LVEF ≤35% after optimised medication at least 3 months will be enrolled in this study. The primary endpoints are all-cause death and SCD. The secondary endpoints are malignant arrhythmia, sudden cardiac arrest, cardiopulmonary resuscitation and rehospitalisation due to HF. The baseline demographic, clinical, biological, electrophysiological, social and psychological variables will be collected. Both ML and traditional multivariable Cox proportional hazards regression models will be developed and compared in the prediction of SCD. Moreover, the ML model will be validated in a prospective study. ETHICS AND DISSEMINATION: The study protocol has been approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (2017-SR-06). All results of this study will be published in international peer-reviewed journals and presented at relevant conferences. TRIAL REGISTRATION NUMBER: ChiCTR-POC-17011842; Pre-results.

6.
Mol Oncol ; 13(5): 1235-1248, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30924596

RESUMO

Smoking cessation prolongs survival and decreases mortality of patients with non-small-cell lung cancer (NSCLC). In addition, epigenetic alterations of some genes are associated with survival. However, potential interactions between smoking cessation and epigenetics have not been assessed. Here, we conducted an epigenome-wide interaction analysis between DNA methylation and smoking cessation on NSCLC survival. We used a two-stage study design to identify DNA methylation-smoking cessation interactions that affect overall survival for early-stage NSCLC. The discovery phase contained NSCLC patients from Harvard, Spain, Norway, and Sweden. A histology-stratified Cox proportional hazards model adjusted for age, sex, clinical stage, and study center was used to test DNA methylation-smoking cessation interaction terms. Interactions with false discovery rate-q ≤ 0.05 were further confirmed in a validation phase using The Cancer Genome Atlas database. Histology-specific interactions were identified by stratification analysis in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients. We identified one CpG probe (cg02268510SIPA 1L3 ) that significantly and exclusively modified the effect of smoking cessation on survival in LUAD patients [hazard ratio (HR)interaction  = 1.12; 95% confidence interval (CI): 1.07-1.16; P = 4.30 × 10-7 ]. Further, the effect of smoking cessation on early-stage LUAD survival varied across patients with different methylation levels of cg02268510SIPA 1L3 . Smoking cessation only benefited LUAD patients with low methylation (HR = 0.53; 95% CI: 0.34-0.82; P = 4.61 × 10-3 ) rather than medium or high methylation (HR = 1.21; 95% CI: 0.86-1.70; P = 0.266) of cg02268510SIPA 1L3 . Moreover, there was an antagonistic interaction between elevated methylation of cg02268510SIPA 1L3 and smoking cessation (HRinteraction  = 2.1835; 95% CI: 1.27-3.74; P = 4.46 × 10-3 ). In summary, smoking cessation benefited survival of LUAD patients with low methylation at cg02268510SIPA 1L3 . The results have implications for not only smoking cessation after diagnosis, but also possible methylation-specific drug targeting.

7.
Cancer Epidemiol Biomarkers Prev ; 28(5): 935-942, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-30700444

RESUMO

BACKGROUND: Platelets are a critical element in coagulation and inflammation, and activated platelets are linked to cancer risk through diverse mechanisms. However, a causal relationship between platelets and risk of lung cancer remains unclear. METHODS: We performed single and combined multiple instrumental variable Mendelian randomization analysis by an inverse-weighted method, in addition to a series of sensitivity analyses. Summary data for associations between SNPs and platelet count are from a recent publication that included 48,666 Caucasian Europeans, and the International Lung Cancer Consortium and Transdisciplinary Research in Cancer of the Lung data consisting of 29,266 cases and 56,450 controls to analyze associations between candidate SNPs and lung cancer risk. RESULTS: Multiple instrumental variable analysis incorporating six SNPs showed a 62% increased risk of overall non-small cell lung cancer [NSCLC; OR, 1.62; 95% confidence interval (CI), 1.15-2.27; P = 0.005] and a 200% increased risk for small-cell lung cancer (OR, 3.00; 95% CI, 1.27-7.06; P = 0.01). Results showed only a trending association with NSCLC histologic subtypes, which may be due to insufficient sample size and/or weak effect size. A series of sensitivity analysis retained these findings. CONCLUSIONS: Our findings suggest a causal relationship between elevated platelet count and increased risk of lung cancer and provide evidence of possible antiplatelet interventions for lung cancer prevention. IMPACT: These findings provide a better understanding of lung cancer etiology and potential evidence for antiplatelet interventions for lung cancer prevention.

8.
Epigenetics ; 14(2): 118-129, 2019 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-30665327

RESUMO

Hypoxia occurs frequently in human cancers and promotes stabilization and activation of hypoxia inducible factor (HIF). HIF-1α is specific for the hypoxia response, and its degradation mediated by three enzymes EGLN1, EGLN2 and EGLN3. Although EGLNs expression has been found to be related to prognosis of many cancers, few studies examined DNA methylation in EGLNs and its relationship to prognosis of early-stage non-small cell lung cancer (NSCLC). We analyzed EGLNs DNA methylation data from tumor tissue samples of 1,230 early-stage NSCLC patients, as well as gene expression data from The Cancer Genome Atlas. The sliding windows sequential forward feature selection method and weighted random forest were used to screen out the candidate CpG probes in lung adenocarcinomas (LUAD) and lung squamous cell carcinomas patients, respectively, in both discovery and validation phases. Then Cox regression was performed to evaluate the association between DNA methylation and overall survival. Among the 34 CpG probes in EGLNs, DNA methylation at cg25923056EGLN2 was identified to be significantly associated with LUAD survival (HR = 1.02, 95% CI: 1.01-1.03, P = 9.90 × 10-5), and correlated with EGLN2 expression (r = - 0.36, P = 1.52 × 10-11). Meanwhile, EGLN2 expression was negatively correlated with HIF1A expression in tumor tissues (r = - 0.30, P = 4.78 × 10-8) and significantly (P = 0.037) interacted with HIF1A expression on overall survival. Therefore, DNA methylation of EGLN2- HIF1A is a potential marker for LUAD prognosis and these genes are potential treatment targets for further development of HIF-1α inhibitors in lung cancer therapy.

9.
Metallomics ; 11(2): 483-495, 2019 Feb 20.
Artigo em Inglês | MEDLINE | ID: mdl-30643918

RESUMO

Arsenic is an environmental toxicant and human carcinogen. The liver is the main site of arsenic storage and metabolism. Exposure to excessive arsenic causes liver damage and release of pro-inflammatory factors, which in turn lead to liver fibrosis. Gasdermin D (GSDMD), a mediator of pyroptosis, has low expression in hepatic tumor cells. In L-02 cells, arsenite caused increases of GSDMD and cleaved caspase-1 levels and decreases of caspase-1 and miR-379-5p levels. It also promoted the release of IL-1ß in a concentration- and time-dependent manner. Luciferase reporter assays showed that GSDMD was a direct target of miR-379-5p. In L-02 cells, the over-expression of miR-379-5p blocked the arsenite-induced increases of GSDMD levels and the release of IL-1ß, effects that were reversed by up-regulation of GSDMD. LX-2 cells, cultured in the media from arsenite-treated L-02 cells, showed elevated levels of proliferating cell nuclear antigen (PCNA), collagen I, vimentin, and α-smooth muscle actin (α-SMA), which indicated activation of these cells. Activation of LX-2 cells by media from arsenite-treated L-02 cells was inhibited by IL-1ß neutralizing antibody. The media from arsenite-treated L-02 cells transfected with an miR-379-5p mimic inhibited the activation of LX-2 cells, a process that was reversed by up-regulation of GSDMD and by co-treatment with human recombinant IL-1ß. Chronic exposure to arsenite induced, in liver tissue of mice, morphological damage, collagen deposition, and activation of hepatic stellate cells (HSCs). In liver tissue of arsenite-exposed mice, the levels of miR-379-5p were lower, but the levels of GSDMD and cleaved caspase-1 were elevated, and in sera from arsenite-exposed mice, the IL-1ß levels were elevated. These results indicate that, by elevating the secretion of IL-1ß, miR-379-5p regulation of GSDMD is involved in arsenite-induced activation of HSCs and in hepatic fibrosis. This establishes a previously unknown molecular mechanism for arsenite-induced liver damage, inflammation, and fibrosis.

10.
EBioMedicine ; 40: 318-326, 2019 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-30594555

RESUMO

BACKGROUND: Ovarian cancer (OV) is the most lethal gynecological cancer in women. We aim to develop a generalized, individualized immune prognostic signature that can stratify and predict overall survival for ovarian cancer. METHODS: The gene expression profiles of ovarian cancer tumor tissue samples were collected from 17 public cohorts, including 2777 cases totally. Single sample gene set enrichment (ssGSEA) analysis was used for the immune genes from ImmPort database to develop an immune-based prognostic score for OV (IPSOV). The signature was trained and validated in six independent datasets (n = 519, 409, 606, 634, 415, 194). FINDINGS: The IPSOV significantly stratified patients into low- and high-immune risk groups in the training set and in the 5 validation sets (HR range: 1.71 [95%CI: 1.32-2.19; P = 4.04 × 10-5] to 2.86 [95%CI: 1.72-4.74; P = 4.89 × 10-5]). Further, we compared IPSOV with nine reported ovarian cancer prognostic signatures as well as the clinical characteristics including stage, grade and debulking status. The IPSOV achieved the highest mean C-index (0.625) compared with the other signatures (0.516 to 0.602) and clinical characteristics (0.555 to 0.583). Further, we integrated IPSOV with stage, grade and debulking, which showed improved prognostic accuracy than clinical characteristics only. INTERPRETATION: The proposed clinical-immune signature is a promising biomarker for estimating overall survival in ovarian cancer. Prospective studies are needed to further validate its analytical accuracy and test the clinical utility. FUND: This work was supported by National Key Research and Development Program of China, National Natural Science Foundation of China and Natural Science Foundation of the Jiangsu Higher Education Institutions of China.


Assuntos
Biomarcadores Tumorais , Imunidade/genética , Neoplasias Ovarianas/genética , Neoplasias Ovarianas/imunologia , Idoso , Biologia Computacional/métodos , Bases de Dados Genéticas , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Humanos , Imunomodulação/genética , Estimativa de Kaplan-Meier , Pessoa de Meia-Idade , Anotação de Sequência Molecular , Gradação de Tumores , Estadiamento de Neoplasias , Neoplasias Ovarianas/diagnóstico , Neoplasias Ovarianas/mortalidade , Prognóstico , Reprodutibilidade dos Testes , Transcriptoma
11.
Hum Genomics ; 12(1): 49, 2018 11 06.
Artigo em Inglês | MEDLINE | ID: mdl-30400837

RESUMO

BACKGROUND: Modeling thousands of markers simultaneously has been of great interest in testing association between genetic biomarkers and disease or disease-related quantitative traits. Recently, an expectation-maximization (EM) approach to Bayesian variable selection (EMVS) facilitating the Bayesian computation was developed for continuous or binary outcome using a fast EM algorithm. However, it is not suitable to the analyses of time-to-event outcome in many public databases such as The Cancer Genome Atlas (TCGA). RESULTS: We extended the EMVS to high-dimensional parametric survival regression framework (SurvEMVS). A variant of cyclic coordinate descent (CCD) algorithm was used for efficient iteration in M-step, and the extended Bayesian information criteria (EBIC) was employed to make choice on hyperparameter tuning. We evaluated the performance of SurvEMVS using numeric simulations and illustrated the effectiveness on two real datasets. The results of numerical simulations and two real data analyses show the well performance of SurvEMVS in aspects of accuracy and computation. Some potential markers associated with survival of lung or stomach cancer were identified. CONCLUSIONS: These results suggest that our model is effective and can cope with high-dimensional omics data.

12.
Cancer Epidemiol Biomarkers Prev ; 27(12): 1527-1535, 2018 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-30185536

RESUMO

BACKGROUND: Previous studies support a tumor-suppressor role for LRRC3B across various types of cancers. We aimed to investigate the association between DNA methylation of LRRC3B and overall survival (OS) for patients with early-stage non-small cell lung cancer (NSCLC). METHODS: This study included 1,230 patients with early-stage NSCLC. DNA was extracted from lung tumor tissues and DNA methylation was measured using Illumina Infinium HumanMethylation450 BeadChips. The association between DNA methylation and OS was first tested using Cox regression on a discovery cohort and then validated in an independent cohort. Next, the association between DNA methylation and gene expression was investigated in two independent cohorts. Finally, the association between gene expression and OS was investigated in three independent groups of patients. RESULTS: Three novel DNA methylation sites in LRRC3B were significantly associated with OS in two groups of patients. Patients with hypermethylation in the DNA methylation sites had significantly longer survival than the others in both the discovery cohort (HR, 0.62; P = 2.02 × 10-05) and validation cohort (HR, 0.55; P = 4.44 × 10-04). The three DNA methylation sites were significantly associated with LRRC3B expression, which was also associated with OS. CONCLUSIONS: Using clinical data from a large population, we illustrated the association between DNA methylation of LRRC3B and OS of early-stage NSCLC. IMPACT: We provide evidence of plausibility for building biomarkers on DNA methylation of LRRC3B for OS of early-stage NSCLC, thus filling a gap between previous in vitro studies and clinical applications.

13.
Bioinformatics ; 2018 Sep 08.
Artigo em Inglês | MEDLINE | ID: mdl-30202885

RESUMO

Motivation: Stitching together trans-omics data is a powerful approach to assess the complex mechanisms of cancer occurrence, progression, and treatment. However, the integration process suffers from the "block missing" phenomena when part of individuals lacks some omics data. Methods: We proposed a k-nearest neighbor (kNN) weighted imputation method for trans-omics block missing data (TOBMIkNN) to handle gene-absence individuals in RNA-seq datasets using external information obtained from DNA methylation probe datasets. Referencing to multi-hot deck, mean imputation, as well as missing cases deletion, we assess the relative error, absolute error, inter-omics correlation structure change and variable selection. Results: The proposed method, TOBMIkNN reliably imputed RNA-seq data by borrowing information from DNA methylation data, and showed superiority over the other three methods in imputation error and stability of correlation structure. Our study indicates that TOBMIkNN can be used as an advisable method for trans-omics block-missing data imputation. Availability: TOBMIkNN is freely available at https://github.com/XuesiDong/TOBMI. Supplementary Information: Supplementary data are available at Bioinformatics online.

14.
JAMA ; 320(9): 934-935, 2018 09 04.
Artigo em Inglês | MEDLINE | ID: mdl-30193268
15.
J Thorac Imaging ; 2018 Aug 28.
Artigo em Inglês | MEDLINE | ID: mdl-30157095

RESUMO

PURPOSE: Pulmonary hypertension (PH) parameters such as pulmonary artery or right ventricular size can be measured easily on computed tomography (CT). However, there are limited data on electrocardiographically (ECG) gated CT. We sought to determine age-specific and sex-specific normal reference values for PH parameters normalized by body surface area (BSA) using ECG-gated cardiac CT in a Chinese population. MATERIALS AND METHODS: In total, we enrolled 519 non-PH patients undergoing ECG-gated CT coronary angiography and measured PH parameters, including main pulmonary artery (MPA) and right pulmonary artery (RPA) diameters and distension, the ratio of MPA to ascending aorta (AAO) diameter (MPA/AAO), and the ratio of right ventricular to left ventricular diameter (RV/LV). Maximum MPA and RPA diameters were also normalized to BSA (nMPA, nRPA). RESULTS: Age, sex, BSA, and body mass index (BMI) were variably associated with PH parameters. Age was an independent predictor of all PH parameters. The maximum MPA diameter (26.5±2.7 mm), maximum RPA diameter (20.9±3.0 mm), nMPA (15.8±2.0 mm/m), nRPA (12.4±2.0 mm/m), and RV/LV (0.85±0.11) increased with age. MPA/AAO (0.80±0.10), MPA, and RPA distension (25.4%±7.1%; 23.3%±6.7%) correlated negatively with age. Although absolute MPA and RPA diameters were slightly larger in men, women had significantly larger nMPA and nRPA values. MPA and RPA sizes and RV/LV were correlated positively with BSA and BMI. CONCLUSIONS: Using ECG-gated cardiac CT, we determined the normal reference values of PH parameters for non-PH adult Chinese patients, and these values were variably influenced by age, sex, BSA, and BMI.

16.
Environ Health ; 17(1): 68, 2018 08 22.
Artigo em Inglês | MEDLINE | ID: mdl-30134906

RESUMO

BACKGROUND: Increasing evidence suggests that welding fume exposure is associated with systemic inflammation. Although celluar metabolites may be associated with inflammation, there is limited information on metabolomic changes during welding fume exposure. Such changes may play an important role in the occurrence, development, and prevention of metal-associated diseases. We aim to investigate human metabolomics changes pre- and post-welding fume exposure. METHODS: This study included 52 boilermakers totally. We collected plasma samples pre- and post-shift welding fume exposure and prepared samples using the automated MicroLab STAR® system. Metabolite concentrations were measured using ultra performance liquid chromatography - tandem mass spectrometer (UPLC-MS/MS) methods. Two-way analysis of variance was used to test the significance of metabolite changes with false discovery rate correction. RESULTS: Analysis detected several metabolic changes after welding fume exposure, mainly involved in the lipid pathway [glucocorticoid class (cortisol, corticosterone, and cortisone), acylcarnitine class, and DiHOME species (9,10-DiHOME and 12,13-DiHOME)], amino acid utilization (isoleucine, proline and phenylalanine), and S-(3-hydroxypropyl) mercapturic acid (3-HPMA). These compounds are all associated with inflammation according to previous studies. Further, additive interaction effects linked smoking and 3-HPMA levels. In the metabolite set enrichment analysis for diseases, the top two disease-associated metabolite pathways were systemic inflammation-related diseases including rheumatoid arthritis and systemic lupus erythematosus. CONCLUSIONS: This global metabolomics study shows evidence that metabolite changes during welding fume exposure are closely associated with systemic inflammation. The altered metabolites detected may be potential health monitoring biomarkers for boilermakers, especially for inflammation-related disease prevention.

17.
Gene ; 673: 174-180, 2018 Oct 05.
Artigo em Inglês | MEDLINE | ID: mdl-29908285

RESUMO

Currently, genetic risk score (GRS) model has been a widely used method to evaluate the genetic effect of cancer risk prediction, but seldom studies investigated their discriminatory power, especially for colorectal cancer (CRC) risk prediction. In this study, we applied both simulation and real data to comprehensively compare the discriminability of different GRS models. The GRS models were fitted by logistic regression with three scenarios, including simple count GRS (SC-GRS), logistic regression weighted GRS (LR-GRS, including DL-GRS and OR-GRS) and explained variance weighted GRS (EV-GRS, including EV_DL-GRS and EV_OR-GRS) models. The model performance was evaluated by receiver operating characteristic (ROC) curves and area under curves (AUC) metric, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). In real data analysis, as DL-GRS and EV_DL-GRS models were carried with serious over-fitting, the other three models were kept for further comparison. Compared to unweighted SC-GRS model, reclassification was significantly decreased in OR-GRS model (NRI = -0.082, IDI = -0.002, P < 0.05), while EV_OR-GRS model showed negative NRI and IDI (NRI = -0.077, IDI = -5.54E-04, P < 0.05) compared to OR-GRS model. Besides, traditional model with smoking status (AUC = 0.523) performed lower discriminability compared to the combined model (AUC = 0.607) including genetic (i.e., SC-GRS) and smoking factors. Similarly, the findings from simulation were all consistent to real data results. It is plausible that SC-GRS model could be optimal for predicting genetic risk of CRC. Moreover, the addition of more significant genetic variants to traditional model could further improve predictive power on CRC risk prediction.


Assuntos
Neoplasias Colorretais/genética , Variação Genética , Polimorfismo de Nucleotídeo Único , Medição de Risco/métodos , Algoritmos , Área Sob a Curva , Simulação por Computador , Feminino , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Humanos , Masculino , Modelos Estatísticos , Curva ROC , Análise de Regressão , Fatores de Risco
18.
EBioMedicine ; 32: 93-101, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29859855

RESUMO

Recent technological advancements have permitted high-throughput measurement of the human genome, epigenome, metabolome, transcriptome, and proteome at the population level. We hypothesized that subsets of genes identified from omic studies might have closely related biological functions and thus might interact directly at the network level. Therefore, we conducted an integrative analysis of multi-omic datasets of non-small cell lung cancer (NSCLC) to search for association patterns beyond the genome and transcriptome. A large, complex, and robust gene network containing well-known lung cancer-related genes, including EGFR and TERT, was identified from combined gene lists for lung adenocarcinoma. Members of the hypoxia-inducible factor (HIF) gene family were at the center of this network. Subsequent sequencing of network hub genes within a subset of samples from the Transdisciplinary Research in Cancer of the Lung-International Lung Cancer Consortium (TRICL-ILCCO) consortium revealed a SNP (rs12614710) in EPAS1 associated with NSCLC that reached genome-wide significance (OR = 1.50; 95% CI: 1.31-1.72; p = 7.75 × 10-9). Using imputed data, we found that this SNP remained significant in the entire TRICL-ILCCO consortium (p = .03). Additional functional studies are warranted to better understand interrelationships among genetic polymorphisms, DNA methylation status, and EPAS1 expression.


Assuntos
Adenocarcinoma/genética , Fatores de Transcrição Hélice-Alça-Hélice Básicos/genética , Carcinoma Pulmonar de Células não Pequenas/genética , Subunidade alfa do Fator 1 Induzível por Hipóxia/genética , Neoplasias Pulmonares/genética , Adenocarcinoma/patologia , Adenocarcinoma de Pulmão , Idoso , Carcinoma Pulmonar de Células não Pequenas/patologia , Metilação de DNA/genética , Feminino , Regulação Neoplásica da Expressão Gênica , Estudos de Associação Genética , Predisposição Genética para Doença , Humanos , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único
19.
Mol Oncol ; 12(6): 913-924, 2018 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-29656435

RESUMO

B-cell translocation gene 2 (BTG2) is a tumour suppressor protein known to be downregulated in several types of cancer. In this study, we investigated a potential role for BTG2 in early-stage non-small cell lung cancer (NSCLC) survival. We analysed BTG2 methylation data from 1230 early-stage NSCLC patients from five international cohorts, as well as gene expression data from 3038 lung cancer cases from multiple cohorts. Three CpG probes (cg01798157, cg06373167, cg23371584) that detected BTG2 hypermethylation in tumour tissues were associated with lower overall survival. The prognostic model based on methylation could distinguish patient survival in the four cohorts [hazard ratio (HR) range, 1.51-2.21] and the independent validation set (HR = 1.85). In the expression analysis, BTG2 expression was positively correlated with survival in each cohort (HR range, 0.28-0.68), which we confirmed with meta-analysis (HR = 0.61, 95% CI 0.54-0.68). The three CpG probes were all negatively correlated with BTG2 expression. Importantly, an integrative model of BTG2 methylation, expression and clinical information showed better predictive ability in the training set and validation set. In conclusion, the methylation and integrated prognostic signatures based on BTG2 are stable and reliable biomarkers for early-stage NSCLC. They may have new applications for appropriate clinical adjuvant trials and personalized treatments in the future.

20.
Clin Epigenetics ; 10: 41, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29619118

RESUMO

Background: KDM lysine demethylase family members are related to lung cancer clinical outcomes and are potential biomarkers for chemotherapeutics. However, little is known about epigenetic alterations in KDM genes and their roles in lung cancer survival. Methods: Tumor tissue samples of 1230 early-stage non-small cell lung cancer (NSCLC) patients were collected from the five independent cohorts. The 393 methylation sites in KDM genes were extracted from epigenome-wide datasets and analyzed by weighted random forest (Ranger) in discovery phase and validation dataset, respectively. The variable importance scores (VIS) for the sites in top 5% of both discovery and validation sets were carried forward for Cox regression to further evaluate the association with patient's overall survival. TCGA transcriptomic data were used to evaluate the correlation with the corresponding DNA methylation. Results: DNA methylation at sites cg11637544 in KDM2A and cg26662347 in KDM1A were in the top 5% of VIS in both discovery phase and validation for squamous cell carcinomas (SCC), which were also significantly associated with SCC survival (HRcg11637544 = 1.32, 95%CI, 1.16-1.50, P = 1.1 × 10-4; HRcg26662347 = 1.88, 95%CI, 1.37-2.60, P = 3.7 × 10-3), and correlated with corresponding gene expression (cg11637544 for KDM2A, P = 1.3 × 10-10; cg26662347 for KDM1A P = 1.5 × 10-5). In addition, by using flexible criteria for Ranger analysis followed by survival classification tree analysis, we identified four clusters for adenocarcinomas and five clusters for squamous cell carcinomas which showed a considerable difference of clinical outcomes with statistical significance. Conclusions: These findings highlight the association between somatic DNA methylation in KDM genes and early-stage NSCLC patient survival, which may reveal potential epigenetic therapeutic targets.

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