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1.
Cancer Epidemiol Biomarkers Prev ; 29(11): 2180-2186, 2020 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-32855268

RESUMO

BACKGROUND: The smoking behavior of American Indians (AI) differs from that of non-Hispanic whites (NHW). Typically light smokers, cessation interventions in AIs are generally less effective. To develop more effective cessation programs for AIs, clinicians, researchers, and public health workers need a better understanding of the genetic factors involved in their smoking behavior. Our aim was to assess whether SNPs associated with smoking behavior in NHWs are also associated with smoking in AIs. METHODS: We collected questionnaire data on smoking behaviors and analyzed blood and saliva samples from two Tribal populations with dramatically different cultures and smoking prevalence, one in the Northern Plains (n = 323) and the other in the Southwest (n = 176). A total of 384 SNPs were genotyped using an Illumina custom GoldenGate platform. Samples were also assessed for cotinine and 3-hydroxycotinine as markers of nicotine intake and nicotine metabolite ratio. RESULTS: Among 499 participants, we identified, in the Northern Plains sample only, a variant of the gamma-aminobutyric acid receptor subunit alpha-2 (GABRA2) (rs2119767) on chromosome 4p that was associated with many of the intake biomarkers of smoking we examined, suggesting a role for this gene in modifying smoking behavior in this population. We also identified three SNPs, in the Southwest sample only, as significant correlates of only cigarettes per day: rs4274224, rs4245147 (both dopamine receptor D2 gene), and rs1386493 (tryptophan hydroxylase 2 gene). CONCLUSIONS: The contribution of many genes known to underlie smoking behaviors in NHWs may differ in AIs. IMPACT: Once validated, these variants could be useful in developing more effective cessation strategies.

2.
Hum Mutat ; 2020 Jul 09.
Artigo em Inglês | MEDLINE | ID: mdl-32643855

RESUMO

We hypothesized that human genes differ by their sensitivity to ultraviolet (UV) exposure. We used somatic mutations detected by genome-wide screens in melanoma and reported in the Catalog Of Somatic Mutations In Cancer. As a measure of UV sensitivity, we used the number of silent mutations generated by C>T transitions in pyrimidine dimers of a given transcript divided by the number of potential sites for this type of mutations in the transcript. We found that human genes varied by UV sensitivity by two orders of magnitude. We noted that the melanoma-associated tumor suppressor gene CDKN2A was among the top five most UV-sensitive genes in the human genome. Melanoma driver genes have a higher UV-sensitivity compared with other genes in the human genome. The difference was more prominent for tumor suppressors compared with oncogene. The results of this study suggest that differential sensitivity of human transcripts to UV light may explain melanoma specificity of some driver genes. Practical significance of the study relates to the fact that differences in UV sensitivity among human genes need to be taken into consideration whereas predicting melanoma-associated genes by the number of somatic mutations detected in a given gene.

3.
Carcinogenesis ; 41(10): 1353-1362, 2020 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-32681635

RESUMO

We hypothesized that a joint analysis of cancer risk-associated single-nucleotide polymorphism (SNP) and somatic mutations in tumor samples can predict functional and potentially causal SNPs from GWASs. We used mutations reported in the Catalog of Somatic Mutations in Cancer (COSMIC). Confirmed somatic mutations were subdivided into two groups: (1) mutations reported as SNPs, which we call mutational/SNPs and (2) somatic mutations that are not reported as SNPs, which we call mutational/noSNPs. It is generally accepted that the number of times a somatic mutation is reported in COSMIC correlates with its selective advantage to tumors, with more frequently reported mutations being more functional and providing a stronger selective advantage to the tumor cell. We found that mutations reported ≥10 times in COSMIC-frequent mutational/SNPs (fmSNPs) are likely to be functional. We identified 12 cancer risk-associated SNPs reported in the Catalog of published GWASs at least 10 times as confirmed somatic mutations and therefore deemed to be functional. Additionally, we have identified 42 SNPs that are tightly linked (R2 ≥ 0.8) to SNPs reported in the Catalog of published GWASs as cancer risk associated and that are also reported as fmSNPs. As a result, 54 candidate functional/potentially causal cancer risk associated SNPs were identified. We found that fmSNPs are more likely to be located in evolutionarily conserved regions compared with cancer risk associated SNPs that are not fmSNPs. We also found that fmSNPs also underwent positive selection, which can explain why they exist as population polymorphisms.

4.
Cancer Epidemiol Biomarkers Prev ; 29(7): 1423-1429, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32277007

RESUMO

BACKGROUND: A substantial proportion of cancer driver genes (CDG) are also cancer predisposition genes. However, the associations between genetic variants in lung CDGs and the susceptibility to lung cancer have rarely been investigated. METHODS: We selected expression-related single-nucleotide polymorphisms (eSNP) and nonsynonymous variants of lung CDGs, and tested their associations with lung cancer risk in two large-scale genome-wide association studies (20,871 cases and 15,971 controls of European descent). Conditional and joint association analysis was performed to identify independent risk variants. The associations of independent risk variants with somatic alterations in lung CDGs or recurrently altered pathways were investigated using data from The Cancer Genome Atlas (TCGA) project. RESULTS: We identified seven independent SNPs in five lung CDGs that were consistently associated with lung cancer risk in discovery (P < 0.001) and validation (P < 0.05) stages. Among these loci, rs78062588 in TPM3 (1q21.3) was a new lung cancer susceptibility locus (OR = 0.86, P = 1.65 × 10-6). Subgroup analysis by histologic types further identified nine lung CDGs. Analysis of somatic alterations found that in lung adenocarcinomas, rs78062588[C] allele (TPM3 in 1q21.3) was associated with elevated somatic copy number of TPM3 (OR = 1.16, P = 0.02). In lung adenocarcinomas, rs1611182 (HLA-A in 6p22.1) was associated with truncation mutations of the transcriptional misregulation in cancer pathway (OR = 0.66, P = 1.76 × 10-3). CONCLUSIONS: Genetic variants can regulate functions of lung CDGs and influence lung cancer susceptibility. IMPACT: Our findings might help unravel biological mechanisms underlying lung cancer susceptibility.

5.
Cancer Genet ; 231-232: 67-79, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30803560

RESUMO

BACKGROUND: Usually, genes with a higher-than-expected number of somatic mutations in tumor samples are assumed to be cancer related. We identified genes with a fewer-than-expected number of somatic mutations - "untouchable genes". METHODS: To predict the expected number of somatic mutations, we used a linear regression model with the number of mutations in the gene as an outcome, and gene characteristics, including gene size, nucleotide composition, level of evolutionary conservation, expression level and others, as predictors. Analysis of residuals from the regression model was used to compare the observed and predicted number of mutations. RESULTS: We have identified 19 genes with a less-than-expected number of loss-off-function (nonsense, frameshift or pathogenic missense) mutations - i.e., untouchable genes. The number of silent or neutral missense mutations in untouchable genes was equal or higher than the expected number. Many mucins, including MUC16, MUC17, MUC6, MUC5AC, MUC5B, and MUC12, are untouchable. We hypothesized that untouchable mucins help tumor cells to avoid immune response by providing a protective coat that prevents direct contact between effector immune cells, e.g., cytotoxic T-cells, and tumor cells. Survival analysis of available TCGA data demonstrated that overall survival of patients with low (below the median) expression of untouchable mucins was better compared to patients with high expression of untouchable mucins. Aside from mucins, we have identified a number of other untouchable genes. CONCLUSIONS: Untouchable genes may be ideal targets for cancer treatment since suppression of untouchable genes is expected to inhibit survival of tumor cells.


Assuntos
Genes Neoplásicos , Genoma Humano , Neoplasias/genética , Neoplasias/terapia , Códon sem Sentido/genética , Mutação da Fase de Leitura/genética , Humanos , Modelos Lineares , Mutação com Perda de Função/genética , Mucinas/genética , Mutação de Sentido Incorreto/genética , Análise de Sobrevida
6.
BMC Bioinformatics ; 19(1): 430, 2018 Nov 19.
Artigo em Inglês | MEDLINE | ID: mdl-30453881

RESUMO

BACKGROUND: Because driver mutations provide selective advantage to the mutant clone, they tend to occur at a higher frequency in tumor samples compared to selectively neutral (passenger) mutations. However, mutation frequency alone is insufficient to identify cancer genes because mutability is influenced by many gene characteristics, such as size, nucleotide composition, etc. The goal of this study was to identify gene characteristics associated with the frequency of somatic mutations in the gene in tumor samples. RESULTS: We used data on somatic mutations detected by genome wide screens from the Catalog of Somatic Mutations in Cancer (COSMIC). Gene size, nucleotide composition, expression level of the gene, relative replication time in the cell cycle, level of evolutionary conservation and other gene characteristics (totaling 11) were used as predictors of the number of somatic mutations. We applied stepwise multiple linear regression to predict the number of mutations per gene. Because missense, nonsense, and frameshift mutations are associated with different sets of gene characteristics, they were modeled separately. Gene characteristics explain 88% of the variation in the number of missense, 40% of nonsense, and 23% of frameshift mutations. Comparisons of the observed and expected numbers of mutations identified genes with a higher than expected number of mutations- positive outliers. Many of these are known driver genes. A number of novel candidate driver genes was also identified. CONCLUSIONS: By comparing the observed and predicted number of mutations in a gene, we have identified known cancer-associated genes as well as 111 novel cancer associated genes. We also showed that adding the number of silent mutations per gene reported by genome/exome wide screens across all cancer type (COSMIC data) as a predictor substantially exceeds predicting accuracy of the most popular cancer gene predicting tool - MutsigCV.


Assuntos
Códon sem Sentido , Mutação da Fase de Leitura , Mutação de Sentido Incorreto , Proteínas de Neoplasias/genética , Neoplasias/genética , Humanos , Taxa de Mutação
7.
PLoS One ; 13(1): e0189498, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-29293537

RESUMO

Gene-level analysis of ImmunoChip or genome-wide association studies (GWAS) data has not been previously reported for systemic sclerosis (SSc, scleroderma). The objective of this study was to analyze genetic susceptibility loci in SSc at the gene level and to determine if the detected associations were shared in African-American and White populations, using data from ImmunoChip and GWAS genotyping studies. The White sample included 1833 cases and 3466 controls (956 cases and 2741 controls from the US and 877 cases and 725 controls from Spain) and the African American sample, 291 cases and 260 controls. In both Whites and African Americans, we performed a gene-level analysis that integrates association statistics in a gene possibly harboring multiple SNPs with weak effect on disease risk, using Versatile Gene-based Association Study (VEGAS) software. The SNP-level analysis was performed using PLINK v.1.07. We identified 4 novel candidate genes (STAT1, FCGR2C, NIPSNAP3B, and SCT) significantly associated and 4 genes (SERBP1, PINX1, TMEM175 and EXOC2) suggestively associated with SSc in the gene level analysis in White patients. As an exploratory analysis we compared the results on Whites with those from African Americans. Of previously established susceptibility genes identified in Whites, only TNFAIP3 was significant at the nominal level (p = 6.13x10-3) in African Americans in the gene-level analysis of the ImmunoChip data. Among the top suggestive novel genes identified in Whites based on the ImmunoChip data, FCGR2C and PINX1 were only nominally significant in African Americans (p = 0.016 and p = 0.028, respectively), while among the top novel genes identified in the gene-level analysis in African Americans, UNC5C (p = 5.57x10-4) and CLEC16A (p = 0.0463) were also nominally significant in Whites. We also present the gene-level analysis of SSc clinical and autoantibody phenotypes among Whites. Our findings need to be validated by independent studies, particularly due to the limited sample size of African Americans.


Assuntos
Grupo com Ancestrais do Continente Africano/genética , Grupo com Ancestrais do Continente Europeu/genética , Estudo de Associação Genômica Ampla , Escleroderma Sistêmico/genética , Humanos , Polimorfismo de Nucleotídeo Único
8.
Int J Mol Sci ; 18(11)2017 Oct 25.
Artigo em Inglês | MEDLINE | ID: mdl-29068415

RESUMO

Lung cancer (LC) screening will be more efficient if it is applied to a well-defined high-risk population. Characteristics including metabolic byproducts may be taken into account to access LC risk more precisely. Breath examination provides a non-invasive method to monitor metabolic byproducts. However, the association between volatile organic compounds (VOCs) in exhaled breath and LC risk or LC risk factors is not studied. Exhaled breath samples from 122 healthy persons, who were given routine annual exam from December 2015 to December 2016, were analyzed using thermal desorption coupled with gas chromatography mass spectrometry (TD-GC-MS). Smoking characteristics, air quality, and other risk factors for lung cancer were collected. Univariate and multivariate analyses were used to evaluate the relationship between VOCs and LC risk factors. 7, 7, 11, and 27 VOCs were correlated with smoking status, smoking intensity, years of smoking, and depth of inhalation, respectively. Exhaled VOCs are related to smoking and might have a potential to evaluate LC risk more precisely. Both an assessment of temporal stability and testing in a prospective study are needed to establish the performance of VOCs such as 2,5-dimethylfuranm and 4-methyloctane as lung cancer risk biomarkers.


Assuntos
Testes Respiratórios/métodos , Detecção Precoce de Câncer/métodos , Neoplasias Pulmonares/diagnóstico , Fumar/efeitos adversos , Compostos Orgânicos Voláteis/análise , Adulto , Idoso , Feminino , Furanos/análise , Furanos/metabolismo , Cromatografia Gasosa-Espectrometria de Massas/métodos , Humanos , Neoplasias Pulmonares/química , Neoplasias Pulmonares/etiologia , Masculino , Pessoa de Meia-Idade , Octanos/análise , Octanos/metabolismo , Fumar/metabolismo , Compostos Orgânicos Voláteis/metabolismo
9.
Hum Mol Genet ; 26(8): 1465-1471, 2017 04 15.
Artigo em Inglês | MEDLINE | ID: mdl-28334950

RESUMO

Genome-wide association studies (GWASs) identified over 500 single nucleotide polymorphisms (SNPs) influencing cancer risk. It is logical to expect the cancer-associated genes to cluster in pathways directly involved in carcinogenesis, e.g. cell cycle. Nevertheless, analyses of the GWAS-detected cancer risk genes usually show no or weak enrichment by known cancer genes.We hypothesized that GWAS-detected cancer risk-associated genes function as upstream regulators of the genes directly involved in carcinogenesis. We have analyzed four common cancers: breast, colon, lung, and prostate. To identify downstream targets of GWAS-detected cancer risk genes we used MedScan, which is a text mining tool offered by PathwayStudio. We also used data on protein/protein interactions reported by BioGRID database. Among all identified targets we have selected common downstream targets. A gene was considered a common downstream target if it was a downstream target for at least three GWAS-detected genes for a given cancer type. Common downstream targets were identified separately for each cancer type. We found that common downstream targets for all four cancer types were enriched by cell cycle genes, more specifically, the genes involved in G1/S transition. Common downstream targets for bipolar disorder, Crohn's disease, and type 2 diabetes did not show G1/S transition enrichment.The results of this analysis suggest that many cancer risk genes function as upstream regulators of the genes directly involved in G1/S transition and exert their risk effects by reducing threshold for G1/S transition, elevating the background level of cell proliferation and cancer risk.


Assuntos
Carcinogênese/genética , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Proteínas de Neoplasias/genética , Neoplasias da Mama/genética , Neoplasias da Mama/patologia , Neoplasias do Colo/genética , Neoplasias do Colo/patologia , Feminino , Pontos de Checagem da Fase G1 do Ciclo Celular/genética , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/patologia , Masculino , Polimorfismo de Nucleotídeo Único/genética , Neoplasias da Próstata/genética , Neoplasias da Próstata/patologia
10.
Arthritis Res Ther ; 18: 20, 2016 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-26792595

RESUMO

BACKGROUND: Systemic sclerosis (SSc)-related interstitial lung disease (ILD) has phenotypic similarities to lung involvement in idiopathic interstitial pneumonia (IIP). We aimed to assess whether genetic susceptibility loci recently identified in the large IIP genome-wide association studies (GWASs) were also risk loci for SSc overall or severity of ILD in SSc. METHODS: A total of 2571 SSc patients and 4500 healthy controls were investigated from the US discovery GWAS and additional US replication cohorts. Thirteen IIP-related selected single nucleotide polymorphisms (SNPs) were genotyped and analyzed for their association with SSc. RESULTS: We found an association of SSc with the SNP rs6793295 in the LRRC34 gene (OR = 1.14, CI 95 % 1.03 to 1.25, p value = 0.009) and rs11191865 in the OBFC1 gene (OR = 1.09, CI 95 % 1.00 to 1.19, p value = 0.043) in the discovery cohort. Additionally, rs7934606 in MUC2 (OR = 1.24, CI 95 % 1.01 to 1.52, p value = 0.037) was associated with SSc-ILD defined by imaging. However, these associations failed to replicate in the validation cohort. Furthermore, SNPs rs2076295 in DSP (ß = -2.29, CI 95 % -3.85 to -0.74, p value = 0.004) rs17690703 in SPPL2C (ß = 2.04, CI 95 % 0.21 to 3.88, p value = 0.029) and rs1981997 in MAPT (ß = 2.26, CI 95 % 0.35 to 4.17, p value = 0.02) were associated with percent predicted forced vital capacity (FVC%) even after adjusting for the anti-topoisomerase (ATA)-positive subset. However, these associations also did not replicate in the validation cohort. CONCLUSIONS: Our results add new evidence that SSc and SSc-related ILD are genetically distinct from IIP, although they share phenotypic similarities.


Assuntos
Grupo com Ancestrais do Continente Europeu/genética , Loci Gênicos/genética , Predisposição Genética para Doença/genética , Pneumonias Intersticiais Idiopáticas/genética , Escleroderma Sistêmico/genética , Adulto , Idoso , Estudos de Casos e Controles , Estudos de Coortes , Feminino , Humanos , Pneumonias Intersticiais Idiopáticas/diagnóstico , Masculino , Pessoa de Meia-Idade , Fatores de Risco , Escleroderma Sistêmico/diagnóstico
11.
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
12.
PLoS Genet ; 11(7): e1005371, 2015 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-26201053

RESUMO

Genome-wide association studies (GWAS) have generated sufficient data to assess the role of selection in shaping allelic diversity of disease-associated SNPs. Negative selection against disease risk variants is expected to reduce their frequencies making them overrepresented in the group of minor (<50%) alleles. Indeed, we found that the overall proportion of risk alleles was higher among alleles with frequency <50% (minor alleles) compared to that in the group of major alleles. We hypothesized that negative selection may have different effects on environment (or lifestyle)-dependent versus environment (or lifestyle)-independent diseases. We used an environment/lifestyle index (ELI) to assess influence of environmental/lifestyle factors on disease etiology. ELI was defined as the number of publications mentioning "environment" or "lifestyle" AND disease per 1,000 disease-mentioning publications. We found that the frequency distributions of the risk alleles for the diseases with strong environmental/lifestyle components follow the distribution expected under a selectively neutral model, while frequency distributions of the risk alleles for the diseases with weak environmental/lifestyle influences is shifted to the lower values indicating effects of negative selection. We hypothesized that previously selectively neutral variants become risk alleles when environment changes. The hypothesis of ancestrally neutral, currently disadvantageous risk-associated alleles predicts that the distribution of risk alleles for the environment/lifestyle dependent diseases will follow a neutral model since natural selection has not had enough time to influence allele frequencies. The results of our analysis suggest that prediction of SNP functionality based on the level of evolutionary conservation may not be useful for SNPs associated with environment/lifestyle dependent diseases.


Assuntos
Exposição Ambiental/efeitos adversos , Frequência do Gene/genética , Predisposição Genética para Doença , Seleção Genética/genética , Alelos , Evolução Biológica , Genoma Humano/genética , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Estilo de Vida , Polimorfismo de Nucleotídeo Único
13.
Hum Genet ; 133(12): 1477-86, 2014 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-25273843

RESUMO

Successful independent replication is the most direct approach for distinguishing real genotype-disease associations from false discoveries in genome-wide association studies (GWAS). Selecting SNPs for replication has been primarily based on P values from the discovery stage, although additional characteristics of SNPs may be used to improve replication success. We used disease-associated SNPs from more than 2,000 published GWASs to identify predictors of SNP reproducibility. SNP reproducibility was defined as a proportion of successful replications among all replication attempts. The study reporting association for the first time was considered to be discovery and all consequent studies targeting the same phenotype replications. We found that -Log(P), where P is a P value from the discovery study, is the strongest predictor of the SNP reproducibility. Other significant predictors include type of the SNP (e.g., missense vs intronic SNPs) and minor allele frequency. Features of the genes linked to the disease-associated SNP also predict SNP reproducibility. Based on empirically defined rules, we developed a reproducibility score (RS) to predict SNP reproducibility independently of -Log(P). We used data from two lung cancer GWAS studies as well as recently reported disease-associated SNPs to validate RS. Minus Log(P) outperforms RS when the very top SNPs are selected, while RS works better with relaxed selection criteria. In conclusion, we propose an empirical model to predict SNP reproducibility, which can be used to select SNPs for validation and prioritization.


Assuntos
Estudo de Associação Genômica Ampla , Polimorfismo de Nucleotídeo Único , Frequência do Gene , Predisposição Genética para Doença , Genótipo , Humanos , Neoplasias Pulmonares/genética , Fases de Leitura Aberta , Reprodutibilidade dos Testes
14.
PLoS One ; 9(4): e93430, 2014.
Artigo em Inglês | MEDLINE | ID: mdl-24705368

RESUMO

In this study, we developed a method for modeling the progression and detection of lung cancer based on the smoking behavior at an individual level. The model allows obtaining the characteristics of lung cancer in a population at the time of diagnosis. Lung cancer data from Surveillance, Epidemiology and End Results (SEER) database collected between 2004 and 2008 were used to fit the lung cancer progression and detection model. The fitted model combined with a smoking based carcinogenesis model was used to predict the distribution of age, gender, tumor size, disease stage and smoking status at diagnosis and the results were validated against independent data from the SEER database collected from 1988 to 1999. The model accurately predicted the gender distribution and median age of LC patients of diagnosis, and reasonably predicted the joint tumor size and disease stage distribution.


Assuntos
Neoplasias Pulmonares/diagnóstico , Neoplasias Pulmonares/etiologia , Neoplasias Pulmonares/patologia , Modelos Teóricos , Fumar , Idoso , Idoso de 80 Anos ou mais , Progressão da Doença , Detecção Precoce de Câncer , Feminino , Humanos , Neoplasias Pulmonares/epidemiologia , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Fatores de Risco , Programa de SEER , Fumar/efeitos adversos , Fumar/epidemiologia
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.
PLoS One ; 8(2): e54561, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-23383301

RESUMO

Evidence from human and animal research indicates that choline metabolic pathways may be activated during a variety of diseases, including cancer. We report results of a case-control study of 2821 lung cancer cases and 2923 controls that assessed associations of choline and betaine dietary intakes with lung cancer. Using multivariable logistic regression analyses, we report a significant association between higher betaine intake and lower lung cancer risk that varied by smoking status. Specifically, no significant association was observed between betaine intake and lung cancer among never-smokers. However, higher betaine intake was significantly associated with reduced lung cancer risk among smokers, and the protective effect was more evident among current than former smokers: for former and current smokers, the ORs (95% CI) of lung cancer for individuals with highest as compared to lowest quartiles of intake were 0.70(0.55-0.88) and 0.51(0.39-0.66) respectively. Significant linear trend of higher betaine intake and lower lung cancer risk was observed among both former (p(trend) = 0.002) and current (p(trend)<0.0001) smokers. A similar protective effect was also observed with choline intake both in overall analysis as well as among current smokers, with p-values for chi-square tests being 0.001 and 0.004 respectively, but the effect was less evident, as no linear trend was observed. Our results suggest that choline and betaine intake, especially higher betaine intake, may be protective against lung cancer through mitigating the adverse effect of smoking.


Assuntos
Betaína/farmacologia , Colina/farmacologia , Dieta , Neoplasias Pulmonares/epidemiologia , Neoplasias Pulmonares/prevenção & controle , Fumar/efeitos adversos , Betaína/metabolismo , Estudos de Casos e Controles , Colina/metabolismo , Humanos , Modelos Logísticos , Neoplasias Pulmonares/etiologia , Razão de Chances , Fatores de Risco , Inquéritos e Questionários , Texas/epidemiologia
17.
Cancer Res ; 73(1): 256-64, 2013 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-23108145

RESUMO

Suboptimal cellular DNA repair capacity (DRC) has been shown to be associated with enhanced cancer risk, but genetic variants affecting the DRC phenotype have not been comprehensively investigated. In this study, with the available DRC phenotype data, we analyzed correlations between the DRC phenotype and genotypes detected by the Illumina 317K platform in 1,774 individuals of European ancestry from a Texas lung cancer genome-wide association study. The discovery phase was followed by a replication in an independent set of 1,374 cases and controls of European ancestry. We applied a generalized linear model with single nucleotide polymorphisms as predictors and DRC (a continuous variable) as the outcome. Covariates of age, sex, pack-years of smoking, DRC assay-related variables, and case-control status of the study participants were adjusted in the model. We validated that reduced DRC was associated with an increased risk of lung cancer in both independent datasets. Several suggestive loci that contributed to the DRC phenotype were defined in ERCC2/XPD, PHACTR2, and DUSP1. In summary, we determined that DRC is an independent risk factor for lung cancer, and we defined several genetic loci contributing to DRC phenotype.


Assuntos
Reparo do DNA/genética , Predisposição Genética para Doença/genética , Neoplasias Pulmonares/genética , Adulto , Idoso , Idoso de 80 Anos ou mais , Feminino , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Fenótipo , Polimorfismo de Nucleotídeo Único , Fatores de Risco
18.
Ann Rheum Dis ; 72(4): 602-7, 2013 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-22896740

RESUMO

INTRODUCTION: A recent genome-wide association study in European systemic sclerosis (SSc) patients identified three loci (PSORS1C1, TNIP1 and RHOB) as novel genetic risk factors for the disease. The aim of this study was to replicate the previously mentioned findings in a large multicentre independent SSc cohort of Caucasian ancestry. METHODS: 4389 SSc patients and 7611 healthy controls from different European countries and the USA were included in the study. Six single nucleotide polymorphisms (SNP): rs342070, rs13021401 (RHOB), rs2233287, rs4958881, rs3792783 (TNIP1) and rs3130573 (PSORS1C1) were analysed. Overall significance was calculated by pooled analysis of all the cohorts. Haplotype analyses and conditional logistic regression analyses were carried out to explore further the genetic structure of the tested loci. RESULTS: Pooled analyses of all the analysed SNPs in TNIP1 revealed significant association with the whole disease (rs2233287 p(MH)=1.94×10(-4), OR 1.19; rs4958881 p(MH)=3.26×10(-5), OR 1.19; rs3792783 p(MH)=2.16×10(-4), OR 1.19). These associations were maintained in all the subgroups considered. PSORS1C1 comparison showed association with the complete set of patients and all the subsets except for the anti-centromere-positive patients. However, the association was dependent on different HLA class II alleles. The variants in the RHOB gene were not associated with SSc or any of its subsets. CONCLUSIONS: These data confirmed the influence of TNIP1 on an increased susceptibility to SSc and reinforced this locus as a common autoimmunity risk factor.


Assuntos
Proteínas de Ligação a DNA/genética , Proteínas/genética , Escleroderma Sistêmico/epidemiologia , Escleroderma Sistêmico/genética , Proteína rhoB de Ligação ao GTP/genética , Europa (Continente)/epidemiologia , Grupo com Ancestrais do Continente Europeu/genética , Grupo com Ancestrais do Continente Europeu/estatística & dados numéricos , Predisposição Genética para Doença/epidemiologia , Predisposição Genética para Doença/genética , Estudo de Associação Genômica Ampla , Haplótipos , Humanos , Polimorfismo de Nucleotídeo Único/genética , Fatores de Risco
19.
PLoS One ; 7(11): e49175, 2012.
Artigo em Inglês | MEDLINE | ID: mdl-23166609

RESUMO

More than 400 cancer genes have been identified in the human genome. The list is not yet complete. Statistical models predicting cancer genes may help with identification of novel cancer gene candidates. We used known prostate cancer (PCa) genes (identified through KnowledgeNet) as a training set to build a binary logistic regression model identifying PCa genes. Internal and external validation of the model was conducted using a validation set (also from KnowledgeNet), permutations, and external data on genes with recurrent prostate tumor mutations. We evaluated a set of 33 gene characteristics as predictors. Sixteen of the original 33 predictors were significant in the model. We found that a typical PCa gene is a prostate-specific transcription factor, kinase, or phosphatase with high interindividual variance of the expression level in adjacent normal prostate tissue and differential expression between normal prostate tissue and primary tumor. PCa genes are likely to have an antiapoptotic effect and to play a role in cell proliferation, angiogenesis, and cell adhesion. Their proteins are likely to be ubiquitinated or sumoylated but not acetylated. A number of novel PCa candidates have been proposed. Functional annotations of novel candidates identified antiapoptosis, regulation of cell proliferation, positive regulation of kinase activity, positive regulation of transferase activity, angiogenesis, positive regulation of cell division, and cell adhesion as top functions. We provide the list of the top 200 predicted PCa genes, which can be used as candidates for experimental validation. The model may be modified to predict genes for other cancer sites.


Assuntos
Genes Neoplásicos/genética , Genoma Humano/genética , Genômica/métodos , Modelos Estatísticos , Neoplasias da Próstata/genética , Humanos , Modelos Logísticos , Masculino , Valor Preditivo dos Testes
20.
J Bioinform Comput Biol ; 10(2): 1241008, 2012 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-22809343

RESUMO

Evolutionary aspects of the genetic architecture of common human diseases remain enigmatic. The results of more than 200 genome-wide association studies published to date were compiled in a catalog (). We used cataloged data to determine whether derived (mutant) alleles are associated with higher risk of human disease more frequently than ancestral alleles. We placed all allelic variants into ten categories of population frequency (0%-100%) in 10% increments. We then analyzed the relationship between allelic frequency, evolutionary status of the polymorphic site (ancestral versus derived), and disease risk status (risk versus protection). Given the same population frequency, derived alleles are more likely to be risk associated than ancestral alleles, as are rarer alleles. The common interpretation of this association is that negative selection prevents fixation of the risk variants. However, disease stratification as early or late onset suggests that weak selection against risk-associated alleles is unlikely a major factor shaping genetic architecture of common diseases. Our results clearly suggest that the duration of existence of an allele in a population is more important. Alleles existing longer tend to show weaker linkage disequilibrium with neighboring alleles, including the causal alleles, and are less likely to tag a SNP-disease association.


Assuntos
Alelos , Predisposição Genética para Doença , Variação Genética/genética , Polimorfismo de Nucleotídeo Único , Evolução Biológica , Frequência do Gene , Genoma Humano , Humanos , Desequilíbrio de Ligação
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