The current World Health Organization (WHO) classification of nasopharyngeal carcinoma (NPC) conveys little prognostic information. This study aimed to propose an NPC histopathologic classification that can potentially be used to predict prognosis and treatment response.We initially developed a histopathologic classification based on the morphologic traits and cell differentiation of tumors of 2716 NPC patients who were identified at Sun Yat-sen University Cancer Center (SYSUCC) (training cohort). Then, the proposed classification was applied to 1702 patients (retrospective validation cohort) from hospitals outside SYSUCC and 1613 patients (prospective validation cohort) from SYSUCC. The efficacy of radiochemotherapy and radiotherapy modalities was compared between the proposed subtypes. We used Cox proportional hazards models to estimate hazard ratios (HRs) with 95% confidence intervals (CI) for overall survival (OS).The 5-year OS rates for all NPC patients who were diagnosed with epithelial carcinoma (EC; 3708 patients), mixed sarcomatoid-epithelial carcinoma (MSEC; 1247 patients), sarcomatoid carcinoma (SC; 823 patients), and squamous cell carcinoma (SCC; 253 patients) were 79.4%, 70.5%, 59.6%, and 42.6%, respectively (P < 0.001). In multivariate models, patients with MSEC had a shorter OS than patients with EC (HR = 1.44, 95% CI = 1.27-1.62), SC (HR = 2.00, 95% CI = 1.76-2.28), or SCC (HR = 4.23, 95% CI = 3.34-5.38). Radiochemotherapy significantly improved survival compared with radiotherapy alone for patients with EC (HR = 0.67, 95% CI = 0.56-0.80), MSEC (HR = 0.58, 95% CI = 0.49-0.75), and possibly for those with SCC (HR = 0.63; 95% CI = 0.40-0.98), but not for patients with SC (HR = 0.97, 95% CI = 0.74-1.28).The proposed classification offers more information for the prediction of NPC prognosis compared with the WHO classification and might be a valuable tool to guide treatment decisions for subtypes that are associated with a poor prognosis.
<p>Supplementary Table 1. Missing rates for three risk factors by study site in BEAGESS Supplementary Table 2. Genome-wide significant single nucleotide polymorphisms (SNPs) selected for GxE analysis. Supplementary Table 3. Odds ratios (95% confidence intervals) for risk factors in the BEACON study according to the number of minor alleles (rs2687201 or rs10419226), using a combined BE/EA case group. Inverse probability weighting techniques were used to account for the missing risk factor data in the GXE interaction analysis. The weights were computed based on a logistic regression model fit to the indicator variable of the risk factor being observed, adjusting for case control status, region (Australia, Europe, North America), age, sex, SNP genotype, and four principal components. Supplementary Table 4. Odds ratios (95% confidence intervals) for risk factors in the BEACON study according to the number of minor alleles (rs2687201 or rs10419226), using a combined BE/EA case group. Supplementary Table 5. Thirteen imputed SNPs found to interact with GERD more significantly than rs2687201 in relation to risk of Barrett's esophagus (BE). Supplementary Table 6.1 Annotations for top SNPs identified in GxE analysis (ordered by interaction P value). Supplementary Table 6.2 Genotype-Tissue Expression (GTEx) eQTL analysis of top 14 SNPs identified.</p>
<p>Supplementary Tables 1-4. Supplementary Table 1. Odds ratios (ORs) and 95% confidence intervals (CIs) of nasopharyngeal carcinoma (NPC) associated with oral health among ever smokers in southern China (2010-2014). Supplementary Table 2. Stratified odds ratios (ORs) and 95% confidence intervals (CIs) of nasopharyngeal carcinoma (NPC) associated with number of teeth lost after age 20 years.* Supplementary Table 3. Stratified odds ratios (ORs) and 95% confidence intervals (CIs)of nasopharyngeal carcinoma (NPC) associated with frequency of tooth brushing.* Supplementary Table 4. Odds ratios (ORs) and 95% confidence intervals (CIs) of nasopharyngeal carcinoma (NPC) associated with oral health in southern China - restricted to cases interviewed within 30 days of diagnosis (2010-2014).</p>
Abstract Background: Microbiomic research has grown in popularity in recent decades. The widespread use of next-generation sequencing technologies, including 16S rRNA gene-based and metagenomic shotgun-based methods, has produced a wealth of microbiome data. At present, most software and analysis workflows for analysis and processing of microbiomic data are command line-based, which requires considerable computing time and makes interaction difficult. Results: To provide a command-line free, multifunctional, user interface friendly and online/local deployable microbiome analysis tool, we developed Microbiome Automated Analysis Workflows (MAAWf). MAAWf is composed of a whole metagenomic shotgun workflow (WMS) and a 16S Sequencing Workflow. The WMS analysis workflow assesses taxonomy, protein-coding genes, metabolic pathways, carbohydrate-active enzymes (CAZy) and antibiotic resistance genes (ARGs). The 16S ribosomal RNA (rRNA) analysis workflow counts and clusters operational taxonomic units (OTUs), estimates alpha- and beta-diversity and inter-group differences, and performs functional analysis. We also compared MAAWf with other commonly avaiable analysis tools using two public datasets. The MAAWf pipeline was established using the Ubuntu 16.04.6 LTS kernel with primary sequence files such as FASTQ format and taxonomic format such as OTU or BIOM formats. Following analysis of public 16S and WMS datasets, MAAWf obtained similar results to DIAMOND-MEGAN6, MG-RAST, DADA2 and QIIME2, but the running time was much shorter. Conclusions: MAAWf is a visual, integrated, rapid analysis tool that enables remote and local computing of microbiome data.
Results from randomized trials of antioxidant supplementation have cast doubt on observational data linking diets high in antioxidants to a reduced risk of cardiovascular diseases. We hypothesized that supplementation of one or a few antioxidants might not simulate the complex actions of all antioxidants in the human diet. We therefore investigated the association between dietary Non Enzymatic Antioxidant Capacity (NEAC), reflecting the antioxidant potential of the whole diet, and the risk of myocardial infarction (MI).In the Swedish National March Cohort, 34 543 men and women free from cardiovascular diseases and cancer were followed through record linkages from 1997 until 2010. NEAC was assessed with a validated food-frequency questionnaire at baseline. The distribution of NEAC was categorized into sex-specific quartiles. We fitted multivariable Cox proportional hazards regression models to estimate hazard ratios (HRs) with 95% confidence intervals (CIs).During a mean follow-up time of 12.7 years, we identified 1142 incident cases of MI. Successively higher quartiles (Qs) of dietary NEAC were accompanied by a monotonic trend of decreasing MI incidence, both for overall MI (HR Q4 vs Q1: 0.77; 95% CI: 0.61-0.96; p for trend = 0.008) and non-fatal MI (HR Q4 vs Q1: 0.72; 95% CI: 0.56-0.92; p for trend = 0.004). No such association was found for fatal MI.A diet rich in antioxidants might protect from MI.
Background: Early diagnosis of esophageal squamous cell carcinoma (ESCC) remains a challenge due to the lack of specific blood biomarkers. We aimed to develop a serum multi-protein signature for early detection of ESCC.Methods: We selected 70 healthy controls, 30 precancerous patients, 60 stage I patients, 70 stage II patients and 70 stage III/IV ESCC patients from a completed ESCC case-control study in a high-risk area of China. Olink Multiplex Oncology II targeted proteomics panel was used to simultaneously detect the levels of 92 cancer-related proteins in serum using proximity extension assay.Findings: We found that 10 upregulated and 13 downregulated protein biomarkers in serum could distinguish the early ESCC from healthy controls and their serum levels had significant dose-response relationships with ESCC progression. Applying least absolute shrinkage and selection operator (LASSO) regression and backward elimination algorithm, ANXA1 (annexin A1), hK8 (kallikrein-8), hK14(kallikrein-14), VIM (vimentin), and RSPO3 (R-spondin-3) were kept in final model to discriminate early ESCC cases from healthy controls with an area under curve (AUC) of 0.936 (95% confidence interval: 0.899~0.973). The average accuracy rates of the five-protein classifier were 0.861 and 0.825 in training and test data by five-fold cross-validation.Interpretation: Our study suggested that a combination of ANXA1, hK8, hK14, VIM and RSPO3 serum proteins could be considered as a potential tool for screening and early diagnosis of ESCC. Our results, however, need be confirmed in external case-control studies and prospective studies. Funding Statement: This work was supported by National Natural Science Foundation of China (81973116, 91846302, 81573229 and 81502870), National Key Research and Development program of China (2017YFC0907002 and 2017YFC0907003), International S&T Cooperation Program of China (2015DFE32790), European Research Council (682663), Medical and Health Technology Development Plan of Shandong Province (2018WS331). The funding sources had no role in the study design, interpretation of results, writing the manuscript or decision to submit the manuscript for the publication. The corresponding author has full access to all the data and assumes final responsibility for the decision to submit for publication. Declaration of Interests: The authors declare no potential conflicts of interest. Ethics Approval Statement: The study protocol was approved by the Institutional Review Boards of the School of Life Sciences, Fudan University (date: February 19, 2009), Qilu Hospital, Shandong University (date: March 8, 2010), and Stockholm Ethical Vetting Board (2018/357-31). The study was carried out in accordance with the approved protocol, and all participants provided written informed consent.
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