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1.
J Thorac Oncol ; 14(8): 1360-1369, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31009812

RESUMO

INTRODUCTION: Inherited susceptibility to lung cancer risk in never-smokers is poorly understood. The major reason for this gap in knowledge is that this disease is relatively uncommon (except in Asians), making it difficult to assemble an adequate study sample. In this study we conducted a genome-wide association study on the largest, to date, set of European-descent never-smokers with lung cancer. METHODS: We conducted a two-phase (discovery and replication) genome-wide association study in never-smokers of European descent. We further augmented the sample by performing a meta-analysis with never-smokers from the recent OncoArray study, which resulted in a total of 3636 cases and 6295 controls. We also compare our findings with those in smokers with lung cancer. RESULTS: We detected three genome-wide statistically significant single nucleotide polymorphisms rs31490 (odds ratio [OR]: 0.769, 95% confidence interval [CI]: 0.722-0.820; p value 5.31 × 10-16), rs380286 (OR: 0.770, 95% CI: 0.723-0.820; p value 4.32 × 10-16), and rs4975616 (OR: 0.778, 95% CI: 0.730-0.829; p value 1.04 × 10-14). All three mapped to Chromosome 5 CLPTM1L-TERT region, previously shown to be associated with lung cancer risk in smokers and in never-smoker Asian women, and risk of other cancers including breast, ovarian, colorectal, and prostate. CONCLUSIONS: We found that genetic susceptibility to lung cancer in never-smokers is associated to genetic variants with pan-cancer risk effects. The comparison with smokers shows that top variants previously shown to be associated with lung cancer risk only confer risk in the presence of tobacco exposure, underscoring the importance of gene-environment interactions in the etiology of this disease.

2.
Cancer Genet ; 231-232: 67-79, 2019 Feb.
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.

3.
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.

4.
Mol Cancer Res ; 2018 Aug 31.
Artigo em Inglês | MEDLINE | ID: mdl-30171176

RESUMO

Melanoma is the most aggressive type of skin cancer in the United States with an increasing incidence. Melanoma lesions often exhibit high immunogenicity, with infiltrating immune cells playing important roles in regression of tumors occurring spontaneously or caused by therapeutic treatment. Computational and experimental methods have been used to estimate the abundance of immune cells in tumors, but their applications are limited by the requirement of large gene sets or multiple antibodies. Although the prognostic role of immune cells has been appreciated, a systematic investigation of their association with clinical factors, genomic features, prognosis and treatment response in melanoma is still lacking. This study, identifies a 25-gene signature based on RNA-seq data from The Cancer Genome Atlas (TCGA)-Skin Cutaneous Melanoma (TCGA-SKCM) dataset. This signature was used to calculate sample-specific Leukocyte Infiltration Scores (LIS) in six independent melanoma microarray datasets and scores were found to vary substantially between different melanoma lesion sites and molecular subtypes. For metastatic melanoma, LIS was prognostic in all datasets with high LIS being associated with good survival. The current approach provided additional prognostic information over established clinical factors, including age, tumor stage, and gender. In addition, LIS was predictive of patient survival in stage III melanoma, and treatment efficacy of tumor-specific antigen vaccine.Implications: This study identifies a 25-gene signature that effectively estimates the level of immune cell infiltration in melanoma, which provides a robust biomarker for predicting patient prognosis. Mol Cancer Res; 1-11. ©2018 AACR.

6.
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
7.
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
8.
J Robot Surg ; 10(4): 343-346, 2016 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-27263110

RESUMO

While robotic-assisted laparoscopic radical prostatectomy (RALRP) is an effective treatment for localized prostate cancer, the risk of complications in older patients can be a deterrent to surgery. We evaluated the rate of medical complications following RALRP in a national dataset of safety events, and assessed whether age is an independent risk factor for these complications. Retrospective analysis of patients undergoing RALRP between 2009 and 2012 in the prospectively maintained American College of Surgeons National Surgical Quality Improvement (ACS-NSQIP) database was performed. Demographic and comorbid data were collated, medical complications occurring during the 30-day post-operative period were identified. We identified age-related comorbidities, and complications associated with these comorbidities. A binary logistic regression model with age and age-related comorbidities as predictors and specific complication as outcome, was used to evaluate whether age is an independent risk factor for these complications. 12,123 patients underwent RALRP between 2009 and 2012, with a mean age of 62 (22-92). Post-operative medical complications included urinary tract infection (UTI) (1.77 %), deep venous thrombosis (DVT) (0.67 %), pulmonary embolism (PE) (0.45 %), pneumonia (PNA) (0.27 %), myocardial infarction (MI) (0.12 %), and cerebrovascular accident (CVA) (0.01 %). Nine comorbidities were positively correlated with age (p < 0.05). Four medical complications were associated with these age-related comorbidities: MI, CVA, PNA, and UTI. On multivariate analysis, age was an independent risk factor for post-operative PNA (p < 0.05), but not for MI (p = 0.09), UTI (p = 0.3) or CVA (p = 0.2). Patient age was independently associated with post-operative pneumonia only. These data suggest that RALRP can be considered as a treatment option in selected older patients with minimal increased risk for post-operative complications.


Assuntos
Laparoscopia/métodos , Complicações Pós-Operatórias/etiologia , Prostatectomia/métodos , Neoplasias da Próstata/cirurgia , Procedimentos Cirúrgicos Robóticos/métodos , Adulto , Distribuição por Idade , Fatores Etários , Idoso , Idoso de 80 Anos ou mais , Doenças Cardiovasculares/complicações , Hemorragia/complicações , Humanos , Laparoscopia/efeitos adversos , Masculino , Pessoa de Meia-Idade , Segurança do Paciente , Prostatectomia/efeitos adversos , Doença Pulmonar Obstrutiva Crônica/complicações , Melhoria de Qualidade , Estudos Retrospectivos , Procedimentos Cirúrgicos Robóticos/efeitos adversos , Infecções Urinárias/complicações , Adulto Jovem
9.
EBioMedicine ; 7: 85-93, 2016 May.
Artigo em Inglês | MEDLINE | ID: mdl-27322462

RESUMO

BACKGROUND: In the Prostate Cancer Prevention Trial, finasteride selectively suppressed low-grade prostate cancer and significantly reduced the incidence of prostate cancer in men treated with finasteride compared with placebo. However, an apparent increase in high-grade disease was also observed among men randomized to finasteride. We aimed to determine why and hypothesized that there is a grade-dependent response to finasteride. METHODS: From 2007 to 2012, we randomized dynamically by intranet-accessible software 183 men with localized prostate cancer to receive 5mg finasteride or placebo daily in a double-blind study during the 4-6weeks preceding prostatectomy. As the primary end point, the expression of a predefined molecular signature (ERß, UBE2C, SRD5A2, and VEGF) differentiating high- and low-grade tumors in Gleason grade (GG) 3 areas of finasteride-exposed tumors from those in GG3 areas of placebo-exposed tumors, adjusted for Gleason score (GS) at prostatectomy, was compared. We also determined androgen receptor (AR) levels, Ki-67, and cleaved caspase 3 to evaluate the effects of finasteride on the expression of its downstream target, cell proliferation, and apoptosis, respectively. The expression of these markers was also compared across grades between and within treatment groups. Logistic regression was used to assess the expression of markers. FINDINGS: We found that the predetermined molecular signature did not distinguish GG3 from GG4 areas in the placebo group. However, AR expression was significantly lower in the GG4 areas of the finasteride group than in those of the placebo group. Within the finasteride group, AR expression was also lower in GG4 than in GG3 areas, but not significantly. Expression of cleaved caspase 3 was significantly increased in both GG3 and GG4 areas in the finasteride group compared to the placebo group, although it was lower in GG4 than in GG3 areas in both groups. INTERPRETATION: We showed that finasteride's effect on apoptosis and AR expression is tumor grade dependent after short-term intervention. This may explain finasteride's selective suppression of low-grade tumors observed in the PCPT.


Assuntos
Finasterida/administração & dosagem , Neoplasias da Próstata/tratamento farmacológico , Neoplasias da Próstata/patologia , Receptores Androgênicos/metabolismo , Administração Oral , Idoso , Apoptose , Biomarcadores Tumorais/metabolismo , Proliferação de Células/efeitos dos fármacos , Método Duplo-Cego , Finasterida/farmacologia , Humanos , Modelos Logísticos , Masculino , Pessoa de Meia-Idade , Gradação de Tumores , Neoplasias da Próstata/metabolismo , Resultado do Tratamento
10.
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
11.
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
12.
Oncologist ; 20(9): 1011-8, 2015 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-26205736

RESUMO

BACKGROUND: Although genetic profiling of tumors is a potentially powerful tool to predict drug sensitivity and resistance, its routine use has been limited because clinicians are often unfamiliar with interpretation and incorporation of the information into practice. We established a Molecular Tumor Board (MTB) to interpret individual patients' tumor genetic profiles and provide treatment recommendations. PATIENTS AND METHODS: DNA from tumor specimens was sequenced in a Clinical Laboratory Improvement Amendments-certified laboratory to identify coding mutations in a 50-gene panel (n = 34) or a 255-gene panel (n = 1). Cases were evaluated by a multidisciplinary MTB that included pathologists, oncologists, hematologists, basic scientists, and genetic counselors. RESULTS: During the first year, 35 cases were evaluated by the MTB, with 32 presented for recommendations on targeted therapies, and 3 referred for potential germline mutations. In 56.3% of cases, MTB recommended treatment with a targeted agent based on evaluation of tumor genetic profile and treatment history. Four patients (12.5%) were subsequently treated with a MTB-recommended targeted therapy; 3 of the 4 patients remain on therapy, 2 of whom experienced clinical benefit lasting >10 months. CONCLUSION: For the majority of cases evaluated, the MTB was able to provide treatment recommendations based on targetable genetic alterations. The most common reasons that MTB-recommended therapy was not administered stemmed from patient preferences and genetic profiling at either very early or very late stages of disease; lack of drug access was rarely encountered. Increasing awareness of molecular profiling and targeted therapies by both clinicians and patients will improve acceptance and adherence to treatments that could significantly improve outcomes. IMPLICATIONS FOR PRACTICE: Case evaluation by a multidisciplinary Molecular Tumor Board (MTB) is critical to benefit from individualized genetic data and maximize clinical impact. MTB recommendations shaped treatment options for the majority of cases evaluated. In the few patients treated with MTB-recommended therapy, disease outcomes were positive and support genetically informed treatment.


Assuntos
Técnicas de Apoio para a Decisão , Neoplasias/tratamento farmacológico , Neoplasias/genética , Medicina de Precisão/métodos , DNA de Neoplasias/análise , DNA de Neoplasias/genética , Feminino , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Masculino , Pessoa de Meia-Idade , Neoplasias/diagnóstico , Neoplasias/patologia , Patologia Molecular/métodos
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.
Cell Commun Signal ; 12: 61, 2014 Sep 25.
Artigo em Inglês | MEDLINE | ID: mdl-25248616

RESUMO

BACKGROUND: INPP4B and PTEN dual specificity phosphatases are frequently lost during progression of prostate cancer to metastatic disease. We and others have previously shown that loss of INPP4B expression correlates with poor prognosis in multiple malignancies and with metastatic spread in prostate cancer. RESULTS: We demonstrate that de novo expression of INPP4B in highly invasive human prostate carcinoma PC-3 cells suppresses their invasion both in vitro and in vivo. Using global gene expression analysis, we found that INPP4B regulates a number of genes associated with cell adhesion, the extracellular matrix, and the cytoskeleton. Importantly, de novo expressed INPP4B suppressed the proinflammatory chemokine IL-8 and induced PAK6. These genes were regulated in a reciprocal manner following downregulation of INPP4B in the independently derived INPP4B-positive LNCaP prostate cancer cell line. Inhibition of PI3K/Akt pathway, which is highly active in both PC-3 and LNCaP cells, did not reproduce INPP4B mediated suppression of IL-8 mRNA expression in either cell type. In contrast, inhibition of PKC signaling phenocopied INPP4B-mediated inhibitory effect on IL-8 in either prostate cancer cell line. In PC-3 cells, INPP4B overexpression caused a decline in the level of metastases associated BIRC5 protein, phosphorylation of PKC, and expression of the common PKC and IL-8 downstream target, COX-2. Reciprocally, COX-2 expression was increased in LNCaP cells following depletion of endogenous INPP4B. CONCLUSION: Taken together, we discovered that INPP4B is a novel suppressor of oncogenic PKC signaling, further emphasizing the role of INPP4B in maintaining normal physiology of the prostate epithelium and suppressing metastatic potential of prostate tumors.


Assuntos
Monoéster Fosfórico Hidrolases/metabolismo , Neoplasias da Próstata/metabolismo , Neoplasias da Próstata/patologia , Proteína Quinase C/metabolismo , Animais , Linhagem Celular Tumoral , Movimento Celular , Proliferação de Células , Ciclo-Oxigenase 2/metabolismo , Regulação Neoplásica da Expressão Gênica , Células HEK293 , Humanos , Indóis/farmacologia , Proteínas Inibidoras de Apoptose/metabolismo , Interleucina-8/genética , Masculino , Maleimidas/farmacologia , Camundongos SCID , Invasividade Neoplásica , Monoéster Fosfórico Hidrolases/genética , Proteína Quinase C/antagonistas & inibidores , Inibidores de Proteínas Quinases/farmacologia , RNA Interferente Pequeno/genética , Survivina , Quinases Ativadas por p21/genética
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.
Comput Math Methods Med ; 2013: 917502, 2013.
Artigo em Inglês | MEDLINE | ID: mdl-24367394

RESUMO

Predicting disease progression is one of the most challenging problems in prostate cancer research. Adding gene expression data to prediction models that are based on clinical features has been proposed to improve accuracy. In the current study, we applied a logistic regression (LR) model combining clinical features and gene co-expression data to improve the accuracy of the prediction of prostate cancer progression. The top-scoring pair (TSP) method was used to select genes for the model. The proposed models not only preserved the basic properties of the TSP algorithm but also incorporated the clinical features into the prognostic models. Based on the statistical inference with the iterative cross validation, we demonstrated that prediction LR models that included genes selected by the TSP method provided better predictions of prostate cancer progression than those using clinical variables only and/or those that included genes selected by the one-gene-at-a-time approach. Thus, we conclude that TSP selection is a useful tool for feature (and/or gene) selection to use in prognostic models and our model also provides an alternative for predicting prostate cancer progression.


Assuntos
Biologia Computacional , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Modelos Logísticos , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/metabolismo , Algoritmos , Área Sob a Curva , DNA Complementar/metabolismo , Progressão da Doença , Genótipo , Humanos , Masculino , Análise de Sequência com Séries de Oligonucleotídeos , Fenótipo , Probabilidade , Prognóstico
17.
Cancer Epidemiol Biomarkers Prev ; 22(2): 251-60, 2013 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-23221128

RESUMO

BACKGROUND: Genome-wide association studies of European and East Asian populations have identified lung cancer susceptibility loci on chromosomes 5p15.33, 6p22.1-p21.31, and 15q25.1. We investigated whether these regions contain lung cancer susceptibly loci in African-Americans and refined previous association signals by using the reduced linkage disequilibrium observed in African-Americans. METHODS: 1,308 African-American cases and 1,241 African-American controls from 3 centers were genotyped for 760 single-nucleotide polymorphisms (SNP) spanning 3 regions, and additional SNP imputation was carried out. Associations between polymorphisms and lung cancer risk were estimated using logistic regression, stratified by tumor histology where appropriate. RESULTS: The strongest associations were observed on 15q25.1 in/near CHRNA5, including a missense substitution [rs16969968: OR, 1.57; 95% confidence interval (CI), 1.25-1.97; P, 1.1 × 10(-4)) and variants in the 5'-UTR. Associations on 6p22.1-p21.31 were histology specific and included a missense variant in BAT2 associated with squamous cell carcinoma (rs2736158: OR, 0.64; 95% CI, 0.48-0.85; P, 1.82 × 10(-3)). Associations on 5p15.33 were detected near TERT, the strongest of which was rs2735940 (OR, 0.82; 95% CI, 0.73-0.93; P, 1.1 × 10(-3)). This association was stronger among cases with adenocarcinoma (OR, 0.75; 95% CI, 0.65-0.86; P, 8.1 × 10(-5)). CONCLUSIONS: Polymorphisms in 5p15.33, 6p22.1-p21.31, and 15q25.1 are associated with lung cancer in African-Americans. Variants on 5p15.33 are stronger risk factors for adenocarcinoma and variants on 6p21.33 associated only with squamous cell carcinoma. IMPACT: Results implicate the BAT2, TERT, and CHRNA5 genes in the pathogenesis of specific lung cancer histologies.


Assuntos
Afro-Americanos/genética , Biomarcadores Tumorais/genética , Cromossomos Humanos Par 15/genética , Cromossomos Humanos Par 5/genética , Cromossomos Humanos Par 6/genética , Predisposição Genética para Doença , Neoplasias Pulmonares/etiologia , Polimorfismo de Nucleotídeo Único/genética , Adenocarcinoma/etnologia , Adenocarcinoma/etiologia , Adenocarcinoma/patologia , Idoso , Carcinoma de Células Escamosas/etnologia , Carcinoma de Células Escamosas/etiologia , Carcinoma de Células Escamosas/patologia , Estudos de Casos e Controles , Mapeamento Cromossômico , Feminino , Estudo de Associação Genômica Ampla , Humanos , Desequilíbrio de Ligação , Pulmão/metabolismo , Pulmão/patologia , Neoplasias Pulmonares/etnologia , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Proteínas do Tecido Nervoso/genética , Reação em Cadeia da Polimerase , Prognóstico , Proteínas/genética , Receptores Nicotínicos/genética , Fatores de Risco , Carcinoma de Pequenas Células do Pulmão/etnologia , Carcinoma de Pequenas Células do Pulmão/etiologia , Carcinoma de Pequenas Células do Pulmão/patologia , Telomerase/genética
18.
Carcinogenesis ; 34(2): 299-306, 2013 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-23125224

RESUMO

Heterogeneity in age of onset of colorectal cancer in individuals with mutations in DNA mismatch repair genes (Lynch syndrome) suggests the influence of other lifestyle and genetic modifiers. We hypothesized that genes regulating the cell cycle influence the observed heterogeneity as cell cycle-related genes respond to DNA damage by arresting the cell cycle to provide time for repair and induce transcription of genes that facilitate repair. We examined the association of 1456 single nucleotide polymorphisms (SNPs) in 128 cell cycle-related genes and 31 DNA repair-related genes in 485 non-Hispanic white participants with Lynch syndrome to determine whether there are SNPs associated with age of onset of colorectal cancer. Genotyping was performed on an Illumina GoldenGate platform, and data were analyzed using Kaplan-Meier survival analysis, Cox regression analysis and classification and regression tree (CART) methods. Ten SNPs were independently significant in a multivariable Cox proportional hazards regression model after correcting for multiple comparisons (P < 5 × 10(-4)). Furthermore, risk modeling using CART analysis defined combinations of genotypes for these SNPs with which subjects could be classified into low-risk, moderate-risk and high-risk groups that had median ages of colorectal cancer onset of 63, 50 and 42 years, respectively. The age-associated risk of colorectal cancer in the high-risk group was more than four times the risk in the low-risk group (hazard ratio = 4.67, 95% CI = 3.16-6.92). The additional genetic markers identified may help in refining risk groups for more tailored screening and follow-up of non-Hispanic white patients with Lynch syndrome.


Assuntos
Biomarcadores Tumorais/genética , Proteínas de Ciclo Celular/genética , Neoplasias Colorretais/genética , Grupo com Ancestrais do Continente Europeu/genética , Predisposição Genética para Doença , Polimorfismo de Nucleotídeo Único/genética , Adolescente , Adulto , Idade de Início , Idoso , Idoso de 80 Anos ou mais , Neoplasias Colorretais/epidemiologia , Neoplasias Colorretais/patologia , Feminino , Seguimentos , Genótipo , Humanos , Masculino , Pessoa de Meia-Idade , Estadiamento de Neoplasias , Prognóstico , Fatores de Risco , Texas/epidemiologia , Adulto Jovem
19.
Oncotarget ; 3(11): 1428-38, 2012 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-23232035

RESUMO

Studies in European and East Asian populations have identified lung cancer susceptibility loci in nicotinic acetylcholine receptor (nAChR) genes on chromosome 15q25.1 which also appear to influence smoking behaviors. We sought to determine if genetic variation in nAChR genes influences lung cancer susceptibly in African-Americans, and evaluated the association of these cancer susceptibility loci with smoking behavior. A total of 1308 African-Americans with lung cancer and 1241 African-American controls from three centers were genotyped for 378 single nucleotide polymorphisms (SNPs) spanning the sixteen human nAChR genes. Associations between SNPs and the risk of lung cancer were estimated using logistic regression, adjusted for relevant covariates. Seven SNPs in three nAChR genes were significantly associated with lung cancer at a strict Bonferroni-corrected level, including a novel association on chromosome 2 near the promoter of CHRNA1 (rs3755486: OR = 1.40, 95% CI = 1.18-1.67, P = 1.0 x 10-4). Association analysis of an additional 305 imputed SNPs on 2q31.1 supported this association. Publicly available expression data demonstrated that the rs3755486 risk allele correlates with increased CHRNA1 gene expression. Additional SNP associations were observed on 15q25.1 in genes previously associated with lung cancer, including a missense variant in CHRNA5 (rs16969968: OR = 1.60, 95% CI = 1.27-2.01, P = 5.9 x 10-5). Risk alleles on 15q25.1 also correlated with an increased number of cigarettes smoked per day among the controls. These findings identify a novel lung cancer risk locus on 2q31.1 which correlates with CHRNA1 expression and replicate previous associations on 15q25.1 in African-Americans.


Assuntos
Afro-Americanos/genética , Neoplasias Pulmonares/etnologia , Neoplasias Pulmonares/genética , Receptores Nicotínicos/genética , Estudos de Casos e Controles , Feminino , Predisposição Genética para Doença , Estudo de Associação Genômica Ampla , Genótipo , Humanos , Masculino , Polimorfismo de Nucleotídeo Único , Fatores de Risco
20.
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
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