Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer(NSCLC)risk,biological mechanisms of these variants remain largely unknown.By integr...Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer(NSCLC)risk,biological mechanisms of these variants remain largely unknown.By integrating a large-scale genotype data of 15581 lung adenocarcinoma(AD)cases,8350 squamous cell carcinoma(SqCC)cases,and 27355 controls,as well as multiple transcriptome and epigenomic databases,we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants.We identified 3064 credible risk variants for NSCLC,which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites.Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific.Functional annotation and genebased analysis implicated 894 target genes,including 274 specifics for AD and 123 for SqCC,which were overrepresented in somatic driver genes(ER=1.95,P=0.005).Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways,while SqCC genes were homologous recombination deficiency related.Our results illustrate the molecular basis of both wellstudied and new susceptibility loci of NSCLC,providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.展开更多
Quantile regression links the whole distribution of an outcome to the covariates of interest and has become an important alternative to commonly used regression models.However,the presence of censored data such as sur...Quantile regression links the whole distribution of an outcome to the covariates of interest and has become an important alternative to commonly used regression models.However,the presence of censored data such as survival time,often the main endpoint in cancer studies,has hampered the use of quantile regression techniques because of the incompleteness of data.With the advent of the precision medicine era and availability of high throughput data,quantile regression with high-dimensional predictors has attracted much attention and provided added insight compared to traditional regression approaches.This paper provides a practical guide for using quantile regression for right censored outcome data with covariates of low-or highdimensionality.We frame our discussion using a dataset from the Boston Lung Cancer Survivor Cohort,a hospital-based prospective cohort study,with the goals of broadening the scope of cancer research,maximizing the utility of collected data,and offering useful statistical alternatives.We use quantile regression to identify clinical and molecular predictors,for example CpG methylation sites,associated with high-risk lung cancer patients,for example those with short survival.展开更多
To the Editor:Preterm birth(PTB),defined as livebirth before 37 completed weeks of gestation,is associated with a high degree of immaturity of various organs,and thus are at greater risk.of a range of short-term and l...To the Editor:Preterm birth(PTB),defined as livebirth before 37 completed weeks of gestation,is associated with a high degree of immaturity of various organs,and thus are at greater risk.of a range of short-term and long-term comorbidities.[1]The estimated PTB prevalence in Bangladesh,already among the highest at 19.1%,[2] is even higher in rural areas in Bangladesh,[3]posing a significant economic and emotional burden to these families and the country.展开更多
基金the Key International(Regional)Cooperative Research Project(No.81820108028)the National Natural Science Foundation of China(Nos.81521004,81922061,81973123,and 81803306)+2 种基金the Science Foundation for Distinguished Young Scholars of Jiangsu(No.BK20160046)the Priority Academic Program for the Development of Jiangsu Higher Education Institutions(Public Health and Preventive Medicine).the National Cancer Institute,National Institutes of Health of USA through grants U01-CA063673,UM1-CA167462,and U01-CA167462.
文摘Although genome-wide association studies have identified more than eighty genetic variants associated with non-small cell lung cancer(NSCLC)risk,biological mechanisms of these variants remain largely unknown.By integrating a large-scale genotype data of 15581 lung adenocarcinoma(AD)cases,8350 squamous cell carcinoma(SqCC)cases,and 27355 controls,as well as multiple transcriptome and epigenomic databases,we conducted histology-specific meta-analyses and functional annotations of both reported and novel susceptibility variants.We identified 3064 credible risk variants for NSCLC,which were overrepresented in enhancer-like and promoter-like histone modification peaks as well as DNase I hypersensitive sites.Transcription factor enrichment analysis revealed that USF1 was AD-specific while CREB1 was SqCC-specific.Functional annotation and genebased analysis implicated 894 target genes,including 274 specifics for AD and 123 for SqCC,which were overrepresented in somatic driver genes(ER=1.95,P=0.005).Pathway enrichment analysis and Gene-Set Enrichment Analysis revealed that AD genes were primarily involved in immune-related pathways,while SqCC genes were homologous recombination deficiency related.Our results illustrate the molecular basis of both wellstudied and new susceptibility loci of NSCLC,providing not only novel insights into the genetic heterogeneity between AD and SqCC but also a set of plausible gene targets for post-GWAS functional experiments.
基金This study was supported by the National Institute of Health(U01CA209414).
文摘Quantile regression links the whole distribution of an outcome to the covariates of interest and has become an important alternative to commonly used regression models.However,the presence of censored data such as survival time,often the main endpoint in cancer studies,has hampered the use of quantile regression techniques because of the incompleteness of data.With the advent of the precision medicine era and availability of high throughput data,quantile regression with high-dimensional predictors has attracted much attention and provided added insight compared to traditional regression approaches.This paper provides a practical guide for using quantile regression for right censored outcome data with covariates of low-or highdimensionality.We frame our discussion using a dataset from the Boston Lung Cancer Survivor Cohort,a hospital-based prospective cohort study,with the goals of broadening the scope of cancer research,maximizing the utility of collected data,and offering useful statistical alternatives.We use quantile regression to identify clinical and molecular predictors,for example CpG methylation sites,associated with high-risk lung cancer patients,for example those with short survival.
基金This study was supported by grants from the State's Key Project of Research and Development Program(No.2016YFE0204900)the U.S.National Institute of Envi-ronmental Health Sciences(NIEHS)of the National Institutes of Health(NIH)grant(No.R01 ES015533)+3 种基金National Natural Science Foundation of China(No.81530088)the Key International(Regional)Cooperative Research Project(No.81820108028)National Key Research and Development Program of China(No.2018YFC0910500)the Priority Academic Program Development of Jjiangsu Higher Education Institutions.Sponsors had no role in the design of the study,the collection and analysis of data,or the preparation of the manuscript.
文摘To the Editor:Preterm birth(PTB),defined as livebirth before 37 completed weeks of gestation,is associated with a high degree of immaturity of various organs,and thus are at greater risk.of a range of short-term and long-term comorbidities.[1]The estimated PTB prevalence in Bangladesh,already among the highest at 19.1%,[2] is even higher in rural areas in Bangladesh,[3]posing a significant economic and emotional burden to these families and the country.