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1.
Nat Commun ; 11(1): 2220, 2020 05 11.
Artigo em Inglês | MEDLINE | ID: mdl-32393777

RESUMO

Few germline mutations are known to affect lung cancer risk. We performed analyses of rare variants from 39,146 individuals of European ancestry and investigated gene expression levels in 7,773 samples. We find a large-effect association with an ATM L2307F (rs56009889) mutation in adenocarcinoma for discovery (adjusted Odds Ratio = 8.82, P = 1.18 × 10-15) and replication (adjusted OR = 2.93, P = 2.22 × 10-3) that is more pronounced in females (adjusted OR = 6.81 and 3.19 and for discovery and replication). We observe an excess loss of heterozygosity in lung tumors among ATM L2307F allele carriers. L2307F is more frequent (4%) among Ashkenazi Jewish populations. We also observe an association in discovery (adjusted OR = 2.61, P = 7.98 × 10-22) and replication datasets (adjusted OR = 1.55, P = 0.06) with a loss-of-function mutation, Q4X (rs150665432) of an uncharacterized gene, KIAA0930. Our findings implicate germline genetic variants in ATM with lung cancer susceptibility and suggest KIAA0930 as a novel candidate gene for lung cancer risk.


Assuntos
Adenocarcinoma/genética , Proteínas Mutadas de Ataxia Telangiectasia/genética , Neoplasias Pulmonares/genética , Idoso , Alelos , Bases de Dados Genéticas , Grupo com Ancestrais do Continente Europeu/genética , Feminino , Predisposição Genética para Doença , Técnicas de Genotipagem , Mutação em Linhagem Germinativa , Heterozigoto , Humanos , Judeus/genética , Masculino , Pessoa de Meia-Idade , Mutação de Sentido Incorreto , Razão de Chances , Análise de Sequência com Séries de Oligonucleotídeos , Linhagem , RNA-Seq , Fatores de Risco
2.
Oncotarget ; 10(19): 1760-1774, 2019 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-30956756

RESUMO

The development of cancer is driven by the accumulation of many oncogenesis-related genetic alterations and tumorigenesis is triggered by complex networks of involved genes rather than independent actions. To explore the epistasis existing among oncogenesis-related genes in lung cancer development, we conducted pairwise genetic interaction analyses among 35,031 SNPs from 2027 oncogenesis-related genes. The genotypes from three independent genome-wide association studies including a total of 24,037 lung cancer patients and 20,401 healthy controls with Caucasian ancestry were analyzed in the study. Using a two-stage study design including discovery and replication studies, and stringent Bonferroni correction for multiple statistical analysis, we identified significant genetic interactions between SNPs in RGL1:RAD51B (OR=0.44, p value=3.27x10-11 in overall lung cancer and OR=0.41, p value=9.71x10-11 in non-small cell lung cancer), SYNE1:RNF43 (OR=0.73, p value=1.01x10-12 in adenocarcinoma) and FHIT:TSPAN8 (OR=1.82, p value=7.62x10-11 in squamous cell carcinoma) in our analysis. None of these genes have been identified from previous main effect association studies in lung cancer. Further eQTL gene expression analysis in lung tissues provided information supporting the functional role of the identified epistasis in lung tumorigenesis. Gene set enrichment analysis revealed potential pathways and gene networks underlying molecular mechanisms in overall lung cancer as well as histology subtypes development. Our results provide evidence that genetic interactions between oncogenesis-related genes play an important role in lung tumorigenesis and epistasis analysis, combined with functional annotation, provides a valuable tool for uncovering functional novel susceptibility genes that contribute to lung cancer development by interacting with other modifier genes.

3.
Stat Med ; 38(6): 1013-1035, 2019 03 15.
Artigo em Inglês | MEDLINE | ID: mdl-30460712

RESUMO

Hierarchical modeling is the preferred approach of modeling neighborhood effects. When both residential and workplace neighborhoods are known, a bivariate (residential-workplace) neighborhood random effect that quantifies the extent that a neighborhood's residential and workplace effects are correlated may be modeled. However, standard statistical software for hierarchical models does not easily allow correlations between the random effects of distinct clustering variables to be incorporated. To overcome this challenge, we develop a Bayesian model and an accompanying estimation procedure that allows for correlated bivariate neighborhood effects and allows individuals to reside or work in multiple neighborhoods, cross-sectional and longitudinal heterogeneity between individuals, and serial correlation between repeated observations over time. Simulation studies that vary key model parameters evaluate how well each aspect of the model is identified by the data. We apply the model to the motivating Framingham Heart Study linked food establishment data to examine whether (i) proximity to fast-food establishments is associated with body mass index, (ii) workplace neighborhood exposure associations are larger than those for residential neighborhood exposure, and (iii) residential neighborhood exposure associations correlate with workplace neighborhood exposure. Comparisons of the full model to models with restricted versions of the covariance structure illustrate the impact of including each feature of the covariance structure.


Assuntos
Índice de Massa Corporal , Fast Foods/estatística & dados numéricos , Modelos Estatísticos , Características de Residência/estatística & dados numéricos , Local de Trabalho/estatística & dados numéricos , Teorema de Bayes , Estudos Transversais , Fast Foods/efeitos adversos , Humanos , Estudos Longitudinais , Software
4.
Carcinogenesis ; 39(9): 1135-1140, 2018 09 21.
Artigo em Inglês | MEDLINE | ID: mdl-29924316

RESUMO

To identify genetic variation associated with lung cancer risk, we performed a genome-wide association analysis of 685 lung cancer cases that had a family history of two or more first or second degree relatives compared with 744 controls without lung cancer that were genotyped on an Illumina Human OmniExpressExome-8v1 array. To ensure robust results, we further evaluated these findings using data from six additional studies that were assembled through the Transdisciplinary Research on Cancer of the Lung Consortium comprising 1993 familial cases and 33 690 controls. We performed a meta-analysis after imputation of all variants using the 1000 Genomes Project Phase 1 (version 3 release date September 2013). Analyses were conducted for 9 327 222 SNPs integrating data from the two sources. A novel variant on chromosome 4p15.31 near the LCORL gene and an imputed rare variant intergenic between CDKN2A and IFNA8 on chromosome 9p21.3 were identified at a genome-wide level of significance for squamous cell carcinomas. Additionally, associations of CHRNA3 and CHRNA5 on chromosome 15q25.1 in sporadic lung cancer were confirmed at a genome-wide level of significance in familial lung cancer. Previously identified variants in or near CHRNA2, BRCA2, CYP2A6 for overall lung cancer, TERT, SECISPB2L and RTEL1 for adenocarcinoma and RAD52 and MHC for squamous carcinoma were significantly associated with lung cancer.


Assuntos
Adenocarcinoma/genética , Carcinoma de Células Escamosas/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/genética , Estudos de Casos e Controles , Cromossomos Humanos Par 15/genética , Cromossomos Humanos Par 4 , Cromossomos Humanos Par 9/genética , Humanos , Pulmão/patologia , Anamnese , Polimorfismo de Nucleotídeo Único/genética
5.
BMC Genomics ; 18(1): 789, 2017 Oct 16.
Artigo em Inglês | MEDLINE | ID: mdl-29037167

RESUMO

BACKGROUND: Accurate inference of genetic ancestry is of fundamental interest to many biomedical, forensic, and anthropological research areas. Genetic ancestry memberships may relate to genetic disease risks. In a genome association study, failing to account for differences in genetic ancestry between cases and controls may also lead to false-positive results. Although a number of strategies for inferring and taking into account the confounding effects of genetic ancestry are available, applying them to large studies (tens thousands samples) is challenging. The goal of this study is to develop an approach for inferring genetic ancestry of samples with unknown ancestry among closely related populations and to provide accurate estimates of ancestry for application to large-scale studies. METHODS: In this study we developed a novel distance-based approach, Ancestry Inference using Principal component analysis and Spatial analysis (AIPS) that incorporates an Inverse Distance Weighted (IDW) interpolation method from spatial analysis to assign individuals to population memberships. RESULTS: We demonstrate the benefits of AIPS in analyzing population substructure, specifically related to the four most commonly used tools EIGENSTRAT, STRUCTURE, fastSTRUCTURE, and ADMIXTURE using genotype data from various intra-European panels and European-Americans. While the aforementioned commonly used tools performed poorly in inferring ancestry from a large number of subpopulations, AIPS accurately distinguished variations between and within subpopulations. CONCLUSIONS: Our results show that AIPS can be applied to large-scale data sets to discriminate the modest variability among intra-continental populations as well as for characterizing inter-continental variation. The method we developed will protect against spurious associations when mapping the genetic basis of a disease. Our approach is more accurate and computationally efficient method for inferring genetic ancestry in the large-scale genetic studies.


Assuntos
Genética Populacional/métodos , Europa (Continente) , Genoma Humano/genética , Humanos , Filogenia , Análise de Componente Principal
6.
Nat Genet ; 49(7): 1126-1132, 2017 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-28604730

RESUMO

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.


Assuntos
Estudo de Associação Genômica Ampla , Neoplasias Pulmonares/genética , Adenocarcinoma/genética , Adenocarcinoma de Pulmão , Adulto , Idoso , Mapeamento Cromossômico , Grupo com Ancestrais do Continente Europeu/genética , Saúde da Família , Feminino , Predisposição Genética para Doença , Genótipo , Humanos , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/etnologia , Masculino , Pessoa de Meia-Idade , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas , Fumar/epidemiologia , Homeostase do Telômero/genética
7.
Cancer Epidemiol Biomarkers Prev ; 26(1): 126-135, 2017 01.
Artigo em Inglês | MEDLINE | ID: mdl-27697780

RESUMO

BACKGROUND: Common cancers develop through a multistep process often including inherited susceptibility. Collaboration among multiple institutions, and funding from multiple sources, has allowed the development of an inexpensive genotyping microarray, the OncoArray. The array includes a genome-wide backbone, comprising 230,000 SNPs tagging most common genetic variants, together with dense mapping of known susceptibility regions, rare variants from sequencing experiments, pharmacogenetic markers, and cancer-related traits. METHODS: The OncoArray can be genotyped using a novel technology developed by Illumina to facilitate efficient genotyping. The consortium developed standard approaches for selecting SNPs for study, for quality control of markers, and for ancestry analysis. The array was genotyped at selected sites and with prespecified replicate samples to permit evaluation of genotyping accuracy among centers and by ethnic background. RESULTS: The OncoArray consortium genotyped 447,705 samples. A total of 494,763 SNPs passed quality control steps with a sample success rate of 97% of the samples. Participating sites performed ancestry analysis using a common set of markers and a scoring algorithm based on principal components analysis. CONCLUSIONS: Results from these analyses will enable researchers to identify new susceptibility loci, perform fine-mapping of new or known loci associated with either single or multiple cancers, assess the degree of overlap in cancer causation and pleiotropic effects of loci that have been identified for disease-specific risk, and jointly model genetic, environmental, and lifestyle-related exposures. IMPACT: Ongoing analyses will shed light on etiology and risk assessment for many types of cancer. Cancer Epidemiol Biomarkers Prev; 26(1); 126-35. ©2016 AACR.


Assuntos
Predisposição Genética para Doença/epidemiologia , Variação Genética/genética , Estudo de Associação Genômica Ampla/métodos , Neoplasias/genética , Polimorfismo de Nucleotídeo Único/genética , Feminino , Genótipo , Humanos , Masculino , Neoplasias/epidemiologia , Neoplasias/fisiopatologia , Prevalência , Prognóstico , Medição de Risco , Seleção Genética
8.
Arthritis Rheumatol ; 69(5): 1054-1066, 2017 05.
Artigo em Inglês | MEDLINE | ID: mdl-28029757

RESUMO

OBJECTIVE: To identify risk alleles relevant to the causal and biologic mechanisms of antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). METHODS: A genome-wide association study and subsequent replication study were conducted in a total cohort of 1,986 cases of AAV (patients with granulomatosis with polyangiitis [Wegener's] [GPA] or microscopic polyangiitis [MPA]) and 4,723 healthy controls. Meta-analysis of these data sets and functional annotation of identified risk loci were performed, and candidate disease variants with unknown functional effects were investigated for their impact on gene expression and/or protein function. RESULTS: Among the genome-wide significant associations identified, the largest effect on risk of AAV came from the single-nucleotide polymorphism variants rs141530233 and rs1042169 at the HLA-DPB1 locus (odds ratio [OR] 2.99 and OR 2.82, respectively) which, together with a third variant, rs386699872, constitute a triallelic risk haplotype associated with reduced expression of the HLA-DPB1 gene and HLA-DP protein in B cells and monocytes and with increased frequency of complementary proteinase 3 (PR3)-reactive T cells relative to that in carriers of the protective haplotype. Significant associations were also observed at the SERPINA1 and PTPN22 loci, the peak signals arising from functionally relevant missense variants, and at PRTN3, in which the top-scoring variant correlated with increased PRTN3 expression in neutrophils. Effects of individual loci on AAV risk differed between patients with GPA and those with MPA or between patients with PR3-ANCAs and those with myeloperoxidase-ANCAs, but the collective population attributable fraction for these variants was substantive, at 77%. CONCLUSION: This study reveals the association of susceptibility to GPA and MPA with functional gene variants that explain much of the genetic etiology of AAV, could influence and possibly be predictors of the clinical presentation, and appear to alter immune cell proteins and responses likely to be key factors in the pathogenesis of AAV.


Assuntos
Granulomatose com Poliangiite/genética , Cadeias beta de HLA-DP/genética , Poliangiite Microscópica/genética , Mieloblastina/genética , Proteína Tirosina Fosfatase não Receptora Tipo 22/genética , Linfócitos T/metabolismo , alfa 1-Antitripsina/genética , Adulto , Vasculite Associada a Anticorpo Anticitoplasma de Neutrófilos/genética , Autoantígenos/imunologia , Linfócitos B/metabolismo , Estudos de Casos e Controles , Feminino , Expressão Gênica , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Antígenos HLA-DP/metabolismo , Cadeias beta de HLA-DP/metabolismo , Haplótipos , Humanos , Masculino , Pessoa de Meia-Idade , Monócitos/metabolismo , Mieloblastina/imunologia , Neutrófilos/metabolismo , Razão de Chances , Peroxidase/imunologia , Polimorfismo de Nucleotídeo Único , Linfócitos T/imunologia
9.
Clin Cancer Res ; 23(2): 399-406, 2017 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-27435399

RESUMO

PURPOSE: We have previously demonstrated that patients with metastatic colorectal cancer who exhibit immune responses to a dendritic cell (DC) vaccine have superior recurrence-free survival following surgery, compared with patients in whom responses do not occur. We sought to characterize the patterns of T-lymphocyte infiltration and somatic mutations in metastases that are associated with and predictive of response to the DC vaccine. EXPERIMENTAL DESIGN: Cytotoxic, memory, and regulatory T cells in resected metastases and surrounding normal liver tissue from 22 patients (11 responders and 11 nonresponders) were enumerated by immunohistochemistry prior to vaccine administration. In conjunction with tumor sequencing, the combined multivariate and collapsing method was used to identify gene mutations that are associated with vaccine response. We also derived a response prediction score for each patient using his/her tumor genotype data and variant association effect sizes computed from the other 21 patients; greater weighting was placed on gene products with cell membrane-related functions. RESULTS: There was no correlation between vaccine response and intratumor, peritumor, or hepatic densities of T-cell subpopulations. Associated genes were found to be enriched in the PI3K/Akt/mTOR signaling axis (P < 0.001). Applying a consistent prediction score cutoff over 22 rounds of leave-one-out cross-validation correctly inferred vaccine response in 21 of 22 patients (95%). CONCLUSIONS: Adjuvant DC vaccination has shown promise as a form of immunotherapy for patients with metastatic colorectal cancer. Its efficacy may be influenced by somatic mutations that affect pathways involving PI3K, Akt, and mTOR, as well as tumor surface proteins. Clin Cancer Res; 23(2); 399-406. ©2016 AACR.


Assuntos
Vacinas Anticâncer/administração & dosagem , Terapia Baseada em Transplante de Células e Tecidos , Neoplasias Colorretais/terapia , Imunoterapia , Proteínas de Membrana/sangue , Idoso , Vacinas Anticâncer/imunologia , Neoplasias Colorretais/sangue , Neoplasias Colorretais/genética , Neoplasias Colorretais/imunologia , Células Dendríticas/imunologia , Células Dendríticas/transplante , Resistencia a Medicamentos Antineoplásicos/imunologia , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Mutação , Metástase Neoplásica , Fosfatidilinositol 3-Quinases/genética , Proteínas Proto-Oncogênicas c-akt/genética , Transdução de Sinais , Linfócitos T/imunologia , Linfócitos T/patologia , Linfócitos T Citotóxicos/imunologia , Linfócitos T Citotóxicos/patologia , Serina-Treonina Quinases TOR/genética
10.
Cancer Epidemiol Biomarkers Prev ; 25(8): 1208-15, 2016 08.
Artigo em Inglês | MEDLINE | ID: mdl-27222311

RESUMO

BACKGROUND: Although genome-wide association studies (GWAS) have identified many genetic variants that are strongly associated with lung cancer, these variants have low penetrance and serve as poor predictors of lung cancer in individuals. We sought to increase the predictive value of germline variants by considering their cumulative effects in the context of biologic pathways. METHODS: For individuals in the Environment and Genetics in Lung Cancer Etiology study (1,815 cases/1,971 controls), we computed pathway-level susceptibility effects as the sum of relevant SNP variant alleles weighted by their log-additive effects from a separate lung cancer GWAS meta-analysis (7,766 cases/37,482 controls). Logistic regression models based on age, sex, smoking, genetic variants, and principal components of pathway effects and pathway-smoking interactions were trained and optimized in cross-validation and further tested on an independent dataset (556 cases/830 controls). We assessed prediction performance using area under the receiver operating characteristic curve (AUC). RESULTS: Compared with typical binomial prediction models that have epidemiologic predictors (AUC = 0.607) in addition to top GWAS variants (AUC = 0.617), our pathway-based smoking-interactive multinomial model significantly improved prediction performance in external validation (AUC = 0.656, P < 0.0001). CONCLUSIONS: Our biologically informed approach demonstrated a larger increase in AUC over nongenetic counterpart models relative to previous approaches that incorporate variants. IMPACT: This model is the first of its kind to evaluate lung cancer prediction using subtype-stratified genetic effects organized into pathways and interacted with smoking. We propose pathway-exposure interactions as a potentially powerful new contributor to risk inference. Cancer Epidemiol Biomarkers Prev; 25(8); 1208-15. ©2016 AACR.


Assuntos
Predisposição Genética para Doença , Variação Genética , Neoplasias Pulmonares/genética , Fumar/epidemiologia , Idoso , Idoso de 80 Anos ou mais , Estudos de Casos e Controles , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Razão de Chances , Polimorfismo de Nucleotídeo Único , Curva ROC , Fatores de Risco
11.
BMC Bioinformatics ; 17: 122, 2016 Mar 09.
Artigo em Inglês | MEDLINE | ID: mdl-26961892

RESUMO

BACKGROUND: Identifying subpopulations within a study and inferring intercontinental ancestry of the samples are important steps in genome wide association studies. Two software packages are widely used in analysis of substructure: Structure and Eigenstrat. Structure assigns each individual to a population by using a Bayesian method with multiple tuning parameters. It requires considerable computational time when dealing with thousands of samples and lacks the ability to create scores that could be used as covariates. Eigenstrat uses a principal component analysis method to model all sources of sampling variation. However, it does not readily provide information directly relevant to ancestral origin; the eigenvectors generated by Eigenstrat are sample specific and thus cannot be generalized to other individuals. RESULTS: We developed FastPop, an efficient R package that fills the gap between Structure and Eigenstrat. It can: 1, generate PCA scores that identify ancestral origins and can be used for multiple studies; 2, infer ancestry information for data arising from two or more intercontinental origins. We demonstrate the use of FastPop using 2318 SNP markers selected from the genome based on high variability among European, Asian and West African (African) populations. We conducted an analysis of 505 Hapmap samples with European, African or Asian ancestry along with 19661 additional samples of unknown ancestry. The results from FastPop are highly consistent with those obtained by Structure across the 19661 samples we studied. The correlations of the results between FastPop and Structure are 0.99, 0.97 and 0.99 for European, African and Asian ancestry scores, respectively. Compared with Structure, FastPop is more efficient as it finished ancestry inference for 19661 samples in 16 min compared with 21-24 h required by Structure. FastPop also provided scores based on SNP weights so the scores of reference population can be applied to other studies provided the same set of markers are used. We also present application of the method for studying four continental populations (European, Asian, African, and Native American). CONCLUSIONS: We developed an algorithm that can infer ancestries on data involving two or more intercontinental origins. It is efficient for analyzing large datasets. Additionally the PCA derived scores can be applied to multiple data sets to ensure the same ancestry analysis is applied to all studies.


Assuntos
Algoritmos , Grupos de Populações Continentais/genética , Grupos Étnicos/genética , Genética Populacional , Estudo de Associação Genômica Ampla/métodos , Polimorfismo de Nucleotídeo Único/genética , Análise de Componente Principal , Software , Teorema de Bayes , Genótipo , Projeto HapMap , Humanos
12.
BMC Med Genomics ; 8: 77, 2015 Nov 17.
Artigo em Inglês | MEDLINE | ID: mdl-26576671

RESUMO

BACKGROUND: Comparative analysis of gene expression in human tissues is important for understanding the molecular mechanisms underlying tissue-specific control of gene expression. It can also open an avenue for using gene expression in blood (which is the most easily accessible human tissue) to predict gene expression in other (less accessible) tissues, which would facilitate the development of novel gene expression based models for assessing disease risk and progression. Until recently, direct comparative analysis across different tissues was not possible due to the scarcity of paired tissue samples from the same individuals. METHODS: In this study we used paired whole blood/lung gene expression data from the Genotype-Tissue Expression (GTEx) project. We built a generalized linear regression model for each gene using gene expression in lung as the outcome and gene expression in blood, age and gender as predictors. RESULTS: For ~18 % of the genes, gene expression in blood was a significant predictor of gene expression in lung. We found that the number of single nucleotide polymorphisms (SNPs) influencing expression of a given gene in either blood or lung, also known as the number of quantitative trait loci (eQTLs), was positively associated with efficacy of blood-based prediction of that gene's expression in lung. This association was strongest for shared eQTLs: those influencing gene expression in both blood and lung. CONCLUSIONS: In conclusion, for a considerable number of human genes, their expression levels in lung can be predicted using observable gene expression in blood. An abundance of shared eQTLs may explain the strong blood/lung correlations in the gene expression.


Assuntos
Sangue/metabolismo , Biologia Computacional , Perfilação da Expressão Gênica , Pulmão/metabolismo , Humanos , Especificidade de Órgãos , Polimorfismo de Nucleotídeo Único , Locos de Características Quantitativas
13.
Hum Mol Genet ; 24(25): 7406-20, 2015 Dec 20.
Artigo em Inglês | MEDLINE | ID: mdl-26483192

RESUMO

Results from genome-wide association studies (GWAS) have indicated that strong single-gene effects are the exception, not the rule, for most diseases. We assessed the joint effects of germline genetic variations through a pathway-based approach that considers the tissue-specific contexts of GWAS findings. From GWAS meta-analyses of lung cancer (12 160 cases/16 838 controls), breast cancer (15 748 cases/18 084 controls) and prostate cancer (14 160 cases/12 724 controls) in individuals of European ancestry, we determined the tissue-specific interaction networks of proteins expressed from genes that are likely to be affected by disease-associated variants. Reactome pathways exhibiting enrichment of proteins from each network were compared across the cancers. Our results show that pathways associated with all three cancers tend to be broad cellular processes required for growth and survival. Significant examples include the nerve growth factor (P = 7.86 × 10(-33)), epidermal growth factor (P = 1.18 × 10(-31)) and fibroblast growth factor (P = 2.47 × 10(-31)) signaling pathways. However, within these shared pathways, the genes that influence risk largely differ by cancer. Pathways found to be unique for a single cancer focus on more specific cellular functions, such as interleukin signaling in lung cancer (P = 1.69 × 10(-15)), apoptosis initiation by Bad in breast cancer (P = 3.14 × 10(-9)) and cellular responses to hypoxia in prostate cancer (P = 2.14 × 10(-9)). We present the largest comparative cross-cancer pathway analysis of GWAS to date. Our approach can also be applied to the study of inherited mechanisms underlying risk across multiple diseases in general.


Assuntos
Estudo de Associação Genômica Ampla/métodos , Neoplasias da Mama/genética , Feminino , Predisposição Genética para Doença , Variação Genética/genética , Humanos , Neoplasias Pulmonares/genética , Masculino , Polimorfismo de Nucleotídeo Único/genética , Neoplasias da Próstata/genética
14.
Am J Hum Genet ; 96(2): 301-8, 2015 Feb 05.
Artigo em Inglês | MEDLINE | ID: mdl-25640678

RESUMO

PARK2, a gene associated with Parkinson disease, is a tumor suppressor in human malignancies. Here, we show that c.823C>T (p.Arg275Trp), a germline mutation in PARK2, is present in a family with eight cases of lung cancer. The resulting amino acid change, p.Arg275Trp, is located in the highly conserved RING finger 1 domain of PARK2, which encodes an E3 ubiquitin ligase. Upon further analysis, the c.823C>T mutation was detected in three additional families affected by lung cancer. The effect size for PARK2 c.823C>T (odds ratio = 5.24) in white individuals was larger than those reported for variants from lung cancer genome-wide association studies. These data implicate this PARK2 germline mutation as a genetic susceptibility factor for lung cancer. Our results provide a rationale for further investigations of this specific mutation and gene for evaluation of the possibility of developing targeted therapies against lung cancer in individuals with PARK2 variants by compensating for the loss-of-function effect caused by the associated variation.


Assuntos
Predisposição Genética para Doença/genética , Neoplasias Pulmonares/genética , Ubiquitina-Proteína Ligases/genética , Sequência de Bases , Primers do DNA/genética , Exoma/genética , Feminino , Mutação em Linhagem Germinativa/genética , Humanos , Masculino , Dados de Sequência Molecular , Mutação de Sentido Incorreto/genética , Razão de Chances , Linhagem , Análise de Sequência de DNA
15.
BMC Genomics ; 15: 223, 2014 Mar 21.
Artigo em Inglês | MEDLINE | ID: mdl-24656147

RESUMO

BACKGROUND: Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data-derived predictor of known cancer associated genes. RESULTS: We found that the traditional approach of identifying cancer genes--identifying differentially expressed genes--is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results were consistent across 4 major types of cancer: breast, colorectal, lung, and prostate. We used recently reported cancer-associated genes (2011-2012) for validation and found that novel cancer-associated genes can be best identified by elevated variance of the gene expression in tumor samples. CONCLUSIONS: The observation that the high interindividual variation of gene expression in tumor tissues is the best predictor of cancer-associated genes is likely a result of tumor heterogeneity on gene level. Computer simulation demonstrates that in the case of heterogeneity, an assessment of variance in tumors provides a better identification of cancer genes than does the comparison of the expression in normal and tumor tissues. Our results thus challenge the current paradigm that comparing the mean expression between normal and tumorous tissues is the best approach to identifying cancer-associated genes; we found that the high interindividual variation in expression is a better approach, and that using variation would improve our chances of identifying cancer-associated genes.


Assuntos
Genômica , Neoplasias/genética , Análise de Sequência com Séries de Oligonucleotídeos , Simulação por Computador , Regulação Neoplásica da Expressão Gênica , Genoma Humano , Humanos , Modelos Logísticos , Neoplasias/patologia
16.
Stat Med ; 32(28): 4924-37, 2013 Dec 10.
Artigo em Inglês | MEDLINE | ID: mdl-23839782

RESUMO

The most common data structures in the biomedical studies have been matched or unmatched designs. Data structures resulting from a hybrid of the two may create challenges for statistical inferences. The question may arise whether to use parametric or nonparametric methods on the hybrid data structure. The Early Treatment for Retinopathy of Prematurity study was a multicenter clinical trial sponsored by the National Eye Institute. The design produced data requiring a statistical method of a hybrid nature. An infant in this multicenter randomized clinical trial had high-risk prethreshold retinopathy of prematurity that was eligible for treatment in one or both eyes at entry into the trial. During follow-up, recognition visual acuity was accessed for both eyes. Data from both eyes (matched) and from only one eye (unmatched) were eligible to be used in the trial. The new hybrid nonparametric method is a meta-analysis based on combining the Hodges-Lehmann estimates of treatment effects from the Wilcoxon signed rank and rank sum tests. To compare the new method, we used the classic meta-analysis with the t-test method to combine estimates of treatment effects from the paired and two sample t-tests. We used simulations to calculate the empirical size and power of the test statistics, as well as the bias, mean square and confidence interval width of the corresponding estimators. The proposed method provides an effective tool to evaluate data from clinical trials and similar comparative studies.


Assuntos
Metanálise como Assunto , Ensaios Clínicos Controlados Aleatórios como Assunto/métodos , Estatísticas não Paramétricas , Resultado do Tratamento , Simulação por Computador , Humanos , Recém-Nascido , Recém-Nascido Prematuro , Retinopatia da Prematuridade/terapia , Acuidade Visual
17.
J Bioinform Comput Biol ; 10(2): 1241013, 2012 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-22809348

RESUMO

Identifying genes associated with cancer development is typically accomplished by comparing mean expression values in normal and tumor tissues, which identifies differentially expressed (DE) genes. Interindividual variation (IV) in gene expression is indirectly included in DE gene identification because given the same absolute differences in means, genes with lower variance tend to have lower p-values. We explored the direct use of IV in gene expression to identify candidate genes associated with cancer development. We focused on prostate (PCa) and lung (LC) cancers and compared IV in the expression level of genes shown to be cancer related with that in all other genes in the human genome. Compared with all those other genes, cancer-related genes tended to have greater IV in normal tissues and a greater increase in IV during the transition from normal to tumorous tissue. Genes without significantly different mean expression values between tumor and normal tissues but with greater IV in tumor than in normal tissue (note: the DE-based approach completely ignores those genes) had stronger associations with clinically important features like Gleason score in PCa or tumor histology in LC than all other genes were. Our results suggest that analyzing IV in gene expression level is useful in identifying novel candidate genes associated with cancer development.


Assuntos
Regulação Neoplásica da Expressão Gênica , Variação Genética , Neoplasias/genética , Biomarcadores Tumorais/genética , Perfilação da Expressão Gênica , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/metabolismo , Masculino , Neoplasias/metabolismo , Neoplasias da Próstata/genética , Neoplasias da Próstata/metabolismo
18.
Cancer Genomics Proteomics ; 9(3): 109-14, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-22593245

RESUMO

BACKGROUND: Identification of genes that are differently expressed is a common approach used to analyze genetic mechanisms underlying cancer development. However, recent study results suggest that many such genes relate to a small number of biological functions. We hypothesized that analysis of these functions provides a better understanding of tumor biology than does actual identification of these genes. MATERIALS AND METHODS: We re-analyzed publicly available gene expression data for paired samples of prostate tumor and adjacent normal tissue from the same patients to identify genes differently expressed in individual tumors and then used them to identify the functions. RESULTS: We found significant interindividual variation in the type and the number of functions. After adjusting for redundancy and nonspecificity of the functional terms, we identified seven functions. Several of them showed a strong association with clinical traits, e.g. age at diagnosis, preoperative prostate-specific antigen concentration, Gleason grade, and biochemical recurrence. Actin cytoskeleton was the function most frequently associated with clinical traits. Of note, the association between function and clinical traits was much stronger than that between the genes differently expressed and those traits. CONCLUSION: Different prostate tumors differ in their functional profiles. Functions of differently expressed genes are strongly associated with clinical traits. This suggests that analysis of functions of differently expressed genes may provide a better description of tumor biology than does analysis of the respective genes.


Assuntos
Neoplasias da Próstata/genética , Análise por Conglomerados , Perfilação da Expressão Gênica/métodos , Humanos , Masculino , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/patologia
19.
BMC Med Genomics ; 2: 48, 2009 Aug 04.
Artigo em Inglês | MEDLINE | ID: mdl-19653896

RESUMO

BACKGROUND: The genetic mechanisms of prostate tumorigenesis remain poorly understood, but with the advent of gene expression array capabilities, we can now produce a large amount of data that can be used to explore the molecular and genetic mechanisms of prostate tumorigenesis. METHODS: We conducted a meta-analysis of gene expression data from 18 gene array datasets targeting transition from normal to localized prostate cancer and from localized to metastatic prostate cancer. We functionally annotated the top 500 differentially expressed genes and identified several candidate pathways associated with prostate tumorigeneses. RESULTS: We found the top differentially expressed genes to be clustered in pathways involving integrin-based cell adhesion: integrin signaling, the actin cytoskeleton, cell death, and cell motility pathways. We also found integrins themselves to be downregulated in the transition from normal prostate tissue to primary localized prostate cancer. Based on the results of this study, we developed a collagen hypothesis of prostate tumorigenesis. According to this hypothesis, the initiating event in prostate tumorigenesis is the age-related decrease in the expression of collagen genes and other genes encoding integrin ligands. This concomitant depletion of integrin ligands leads to the accumulation of ligandless integrin and activation of integrin-associated cell death. To escape integrin-associated death, cells suppress the expression of integrins, which in turn alters the actin cytoskeleton, elevates cell motility and proliferation, and disorganizes prostate histology, contributing to the histologic progression of prostate cancer and its increased metastasizing potential. CONCLUSION: The results of this study suggest that prostate tumor progression is associated with the suppression of integrin-based cell adhesion. Suppression of integrin expression driven by integrin-mediated cell death leads to increased cell proliferation and motility and increased tumor malignancy.

20.
Int J Cancer ; 125(11): 2603-8, 2009 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-19551858

RESUMO

Housekeeping (HK) genes are involved in basic cellular functions and tend to be constitutively expressed across various tissues and conditions. A number of studies have analyzed the value of HK genes as an internal standard for assessing gene expression, but the role of HK genes in cancer development has never been specifically addressed. In this study, we sought to evaluate the expression of HK genes during prostate tumorigenesis. We performed a meta-analysis of gene expression during the transition from normal prostate (NP) to localized prostate cancer (LPC) (i.e., NP > LPC) and from localized to metastatic prostate cancer (MPC) (i.e., LPC > MPC). We found that HK genes are more likely to be differentially expressed during prostate tumorigenesis than is the average gene in the human genome, suggesting that prostate tumorigenesis is driven by modulation of the expression of HK genes. Cell-cycle genes and proliferation markers were up-regulated in both NP > LPC and LPC > MPC transitions. We also found that the genes encoding ribosomal proteins were up-regulated in the NP > LPC and down-regulated in the LPC > MPC transition. The expression of heat shock proteins was up-regulated during the LPC > MPC transition, suggesting that in its advanced stages, prostate tumor is under cellular stress. The results of these analyses suggest that during prostate tumorigenesis, there is a period when the tumor is under cellular stress and, therefore, may be the most vulnerable and responsive to treatment.


Assuntos
Regulação Neoplásica da Expressão Gênica , Genes Essenciais/genética , Neoplasias da Próstata/genética , Genoma Humano , Humanos , Masculino , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/patologia
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