WorldWideScience

Sample records for cancer gene interactions

  1. Gene-Gene and Gene-Environment Interactions in the Etiology of Breast Cancer

    National Research Council Canada - National Science Library

    Adegoke, Olufemi

    2003-01-01

    The objective of this CDA is to evaluate the gene-gene and gene-environment interactions in the etiology of breast cancer in two ongoing case-control studies, the Shanghai Breast Cancer Study (SBCS...

  2. Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

    Science.gov (United States)

    Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

    2017-10-03

    With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

  3. Systematic Search for Gene-Gene Interaction Effect on Prostate Cancer Risk

    Science.gov (United States)

    2013-07-01

    Systematic Search for Gene-Gene Interaction 5a. CONTRACT NUMBER Effect on Prostate Cancer Risk 5b. GRANT NUMBER W81XWH-09-1-0488 5c. PROGRAM...Supported by this grant ) 1. Tao S, Wang Z, Feng J, Hsu FC, Jin G, Kin ST, Zhang Z, Gronberg H, Zheng, SL, Isaacs WB, XU J, Sun J. A Genome-Wide Search for...order interactions among estrogen- metabolism genes in sporadic breast cancer. Am J Hum Genet, 69, 138-47. 48. Marchini, J., Donnelly, P. and Cardon

  4. Gene-gene and gene-environment interactions in prostate, breast and colorectal cancer

    DEFF Research Database (Denmark)

    Kopp, Tine Iskov

    The incidence of cancer in the western world has increased steeply during the last 50 years. For three of the most prevalent cancer types in Denmark, prostate, breast and colorectal cancer (PC, BC and CRC, respectively), only a small fraction (1-15%) of the incidences are caused by highly penetrant...... in alcohol-related BC in postmenopausal women involving a specific polymorphism in PPARG (coding the peroxisome proliferatoractivated receptor (PPARγ)) and its interaction with the aromatase (encoded by CYP19A1) was investigated (Paper V-VI). The Danish prospective “Diet, Cancer and Health” cohort study...... as having strong influence on carcinogenesis. Therefore, very frequent, low effect polymorphisms may have a greater contribution on a population level in combination with environmental factors. Indeed, several dietary and life style factors are now well-established risk factors for different cancer types...

  5. Bayesian logistic regression in detection of gene-steroid interaction for cancer at PDLIM5 locus.

    Science.gov (United States)

    Wang, Ke-Sheng; Owusu, Daniel; Pan, Yue; Xie, Changchun

    2016-06-01

    The PDZ and LIM domain 5 (PDLIM5) gene may play a role in cancer, bipolar disorder, major depression, alcohol dependence and schizophrenia; however, little is known about the interaction effect of steroid and PDLIM5 gene on cancer. This study examined 47 single-nucleotide polymorphisms (SNPs) within the PDLIM5 gene in the Marshfield sample with 716 cancer patients (any diagnosed cancer, excluding minor skin cancer) and 2848 noncancer controls. Multiple logistic regression model in PLINK software was used to examine the association of each SNP with cancer. Bayesian logistic regression in PROC GENMOD in SAS statistical software, ver. 9.4 was used to detect gene- steroid interactions influencing cancer. Single marker analysis using PLINK identified 12 SNPs associated with cancer (Plogistic regression in PROC GENMOD showed that both rs6532496 and rs951613 revealed strong gene-steroid interaction effects (OR=2.18, 95% CI=1.31-3.63 with P = 2.9 × 10⁻³ for rs6532496 and OR=2.07, 95% CI=1.24-3.45 with P = 5.43 × 10⁻³ for rs951613, respectively). Results from Bayesian logistic regression showed stronger interaction effects (OR=2.26, 95% CI=1.2-3.38 for rs6532496 and OR=2.14, 95% CI=1.14-3.2 for rs951613, respectively). All the 12 SNPs associated with cancer revealed significant gene-steroid interaction effects (P logistic regression and OR=2.59, 95% CI=1.4-3.97 from Bayesian logistic regression; respectively). This study provides evidence of common genetic variants within the PDLIM5 gene and interactions between PLDIM5 gene polymorphisms and steroid use influencing cancer.

  6. Methodological issues in detecting gene-gene interactions in breast cancer susceptibility: a population-based study in Ontario

    Directory of Open Access Journals (Sweden)

    Onay Venus

    2007-08-01

    Full Text Available Abstract Background There is growing evidence that gene-gene interactions are ubiquitous in determining the susceptibility to common human diseases. The investigation of such gene-gene interactions presents new statistical challenges for studies with relatively small sample sizes as the number of potential interactions in the genome can be large. Breast cancer provides a useful paradigm to study genetically complex diseases because commonly occurring single nucleotide polymorphisms (SNPs may additively or synergistically disturb the system-wide communication of the cellular processes leading to cancer development. Methods In this study, we systematically studied SNP-SNP interactions among 19 SNPs from 18 key genes involved in major cancer pathways in a sample of 398 breast cancer cases and 372 controls from Ontario. We discuss the methodological issues associated with the detection of SNP-SNP interactions in this dataset by applying and comparing three commonly used methods: the logistic regression model, classification and regression trees (CART, and the multifactor dimensionality reduction (MDR method. Results Our analyses show evidence for several simple (two-way and complex (multi-way SNP-SNP interactions associated with breast cancer. For example, all three methods identified XPD-[Lys751Gln]*IL10-[G(-1082A] as the most significant two-way interaction. CART and MDR identified the same critical SNPs participating in complex interactions. Our results suggest that the use of multiple statistical approaches (or an integrated approach rather than a single methodology could be the best strategy to elucidate complex gene interactions that have generally very different patterns. Conclusion The strategy used here has the potential to identify complex biological relationships among breast cancer genes and processes. This will lead to the discovery of novel biological information, which will improve breast cancer risk management.

  7. Genome-wide search for gene-gene interactions in colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Shuo Jiao

    Full Text Available Genome-wide association studies (GWAS have successfully identified a number of single-nucleotide polymorphisms (SNPs associated with colorectal cancer (CRC risk. However, these susceptibility loci known today explain only a small fraction of the genetic risk. Gene-gene interaction (GxG is considered to be one source of the missing heritability. To address this, we performed a genome-wide search for pair-wise GxG associated with CRC risk using 8,380 cases and 10,558 controls in the discovery phase and 2,527 cases and 2,658 controls in the replication phase. We developed a simple, but powerful method for testing interaction, which we term the Average Risk Due to Interaction (ARDI. With this method, we conducted a genome-wide search to identify SNPs showing evidence for GxG with previously identified CRC susceptibility loci from 14 independent regions. We also conducted a genome-wide search for GxG using the marginal association screening and examining interaction among SNPs that pass the screening threshold (p<10(-4. For the known locus rs10795668 (10p14, we found an interacting SNP rs367615 (5q21 with replication p = 0.01 and combined p = 4.19×10(-8. Among the top marginal SNPs after LD pruning (n = 163, we identified an interaction between rs1571218 (20p12.3 and rs10879357 (12q21.1 (nominal combined p = 2.51×10(-6; Bonferroni adjusted p = 0.03. Our study represents the first comprehensive search for GxG in CRC, and our results may provide new insight into the genetic etiology of CRC.

  8. Interaction between alcohol dehydrogenase II gene, alcohol consumption, and risk for breast cancer

    OpenAIRE

    St?rmer, T; Wang-Gohrke, S; Arndt, V; Boeing, H; Kong, X; Kreienberg, R; Brenner, H

    2002-01-01

    MaeIII Restriction Fragment Length Polymorphism in exon 3 of the alcohol dehydrogenase II was assessed in serum from 467 randomly selected German women and 278 women with invasive breast cancer to evaluate the interaction between a polymorphism of the alcohol dehydrogenase II gene, alcohol consumption and risk for breast cancer. In both groups, usual consumption of different alcoholic beverages was asked for using semiquantitative food frequency questionnaires. We used multivariable logistic ...

  9. Quantitative Chemical-Genetic Interaction Map Connects Gene Alterations to Drug Responses | Office of Cancer Genomics

    Science.gov (United States)

    In a recent Cancer Discovery report, CTD2 researchers at the University of California in San Francisco developed a new quantitative chemical-genetic interaction mapping approach to evaluate drug sensitivity or resistance in isogenic cell lines. Performing a high-throughput screen with isogenic cell lines allowed the researchers to explore the impact of a panel of emerging and established drugs on cells overexpressing a single cancer-associated gene in isolation.

  10. HSD3B and gene-gene interactions in a pathway-based analysis of genetic susceptibility to bladder cancer.

    Directory of Open Access Journals (Sweden)

    Angeline S Andrew

    Full Text Available Bladder cancer is the 4(th most common cancer among men in the U.S. We analyzed variant genotypes hypothesized to modify major biological processes involved in bladder carcinogenesis, including hormone regulation, apoptosis, DNA repair, immune surveillance, metabolism, proliferation, and telomere maintenance. Logistic regression was used to assess the relationship between genetic variation affecting these processes and susceptibility in 563 genotyped urothelial cell carcinoma cases and 863 controls enrolled in a case-control study of incident bladder cancer conducted in New Hampshire, U.S. We evaluated gene-gene interactions using Multifactor Dimensionality Reduction (MDR and Statistical Epistasis Network analysis. The 3'UTR flanking variant form of the hormone regulation gene HSD3B2 was associated with increased bladder cancer risk in the New Hampshire population (adjusted OR 1.85 95%CI 1.31-2.62. This finding was successfully replicated in the Texas Bladder Cancer Study with 957 controls, 497 cases (adjusted OR 3.66 95%CI 1.06-12.63. The effect of this prevalent SNP was stronger among males (OR 2.13 95%CI 1.40-3.25 than females (OR 1.56 95%CI 0.83-2.95, (SNP-gender interaction P = 0.048. We also identified a SNP-SNP interaction between T-cell activation related genes GATA3 and CD81 (interaction P = 0.0003. The fact that bladder cancer incidence is 3-4 times higher in males suggests the involvement of hormone levels. This biologic process-based analysis suggests candidate susceptibility markers and supports the theory that disrupted hormone regulation plays a role in bladder carcinogenesis.

  11. Genome-wide diet-gene interaction analyses for risk of colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Jane C Figueiredo

    2014-04-01

    Full Text Available Dietary factors, including meat, fruits, vegetables and fiber, are associated with colorectal cancer; however, there is limited information as to whether these dietary factors interact with genetic variants to modify risk of colorectal cancer. We tested interactions between these dietary factors and approximately 2.7 million genetic variants for colorectal cancer risk among 9,287 cases and 9,117 controls from ten studies. We used logistic regression to investigate multiplicative gene-diet interactions, as well as our recently developed Cocktail method that involves a screening step based on marginal associations and gene-diet correlations and a testing step for multiplicative interactions, while correcting for multiple testing using weighted hypothesis testing. Per quartile increment in the intake of red and processed meat were associated with statistically significant increased risks of colorectal cancer and vegetable, fruit and fiber intake with lower risks. From the case-control analysis, we detected a significant interaction between rs4143094 (10p14/near GATA3 and processed meat consumption (OR = 1.17; p = 8.7E-09, which was consistently observed across studies (p heterogeneity = 0.78. The risk of colorectal cancer associated with processed meat was increased among individuals with the rs4143094-TG and -TT genotypes (OR = 1.20 and OR = 1.39, respectively and null among those with the GG genotype (OR = 1.03. Our results identify a novel gene-diet interaction with processed meat for colorectal cancer, highlighting that diet may modify the effect of genetic variants on disease risk, which may have important implications for prevention.

  12. Gene-environment interaction involving recently identified colorectal cancer susceptibility loci

    Science.gov (United States)

    Kantor, Elizabeth D.; Hutter, Carolyn M.; Minnier, Jessica; Berndt, Sonja I.; Brenner, Hermann; Caan, Bette J.; Campbell, Peter T.; Carlson, Christopher S.; Casey, Graham; Chan, Andrew T.; Chang-Claude, Jenny; Chanock, Stephen J.; Cotterchio, Michelle; Du, Mengmeng; Duggan, David; Fuchs, Charles S.; Giovannucci, Edward L.; Gong, Jian; Harrison, Tabitha A.; Hayes, Richard B.; Henderson, Brian E.; Hoffmeister, Michael; Hopper, John L.; Jenkins, Mark A.; Jiao, Shuo; Kolonel, Laurence N.; Le Marchand, Loic; Lemire, Mathieu; Ma, Jing; Newcomb, Polly A.; Ochs-Balcom, Heather M.; Pflugeisen, Bethann M.; Potter, John D.; Rudolph, Anja; Schoen, Robert E.; Seminara, Daniela; Slattery, Martha L.; Stelling, Deanna L.; Thomas, Fridtjof; Thornquist, Mark; Ulrich, Cornelia M.; Warnick, Greg S.; Zanke, Brent W.; Peters, Ulrike; Hsu, Li; White, Emily

    2014-01-01

    BACKGROUND Genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) that are associated with risk of colorectal cancer (CRC). Prior research has evaluated the presence of gene-environment interaction involving the first 10 identified susceptibility loci, but little work has been conducted on interaction involving SNPs at recently identified susceptibility loci, including: rs10911251, rs6691170, rs6687758, rs11903757, rs10936599, rs647161, rs1321311, rs719725, rs1665650, rs3824999, rs7136702, rs11169552, rs59336, rs3217810, rs4925386, and rs2423279. METHODS Data on 9160 cases and 9280 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and Colon Cancer Family Registry (CCFR) were used to evaluate the presence of interaction involving the above-listed SNPs and sex, body mass index (BMI), alcohol consumption, smoking, aspirin use, post-menopausal hormone (PMH) use, as well as intake of dietary calcium, dietary fiber, dietary folate, red meat, processed meat, fruit, and vegetables. Interaction was evaluated using a fixed-effects meta-analysis of an efficient Empirical Bayes estimator, and permutation was used to account for multiple comparisons. RESULTS None of the permutation-adjusted p-values reached statistical significance. CONCLUSIONS The associations between recently identified genetic susceptibility loci and CRC are not strongly modified by sex, BMI, alcohol, smoking, aspirin, PMH use, and various dietary factors. IMPACT Results suggest no evidence of strong gene-environment interactions involving the recently identified 16 susceptibility loci for CRC taken one at a time. PMID:24994789

  13. Identification of New Genetic Susceptibility Loci for Breast Cancer Through Consideration of Gene-Environment Interactions

    Science.gov (United States)

    Schoeps, Anja; Rudolph, Anja; Seibold, Petra; Dunning, Alison M.; Milne, Roger L.; Bojesen, Stig E.; Swerdlow, Anthony; Andrulis, Irene; Brenner, Hermann; Behrens, Sabine; Orr, Nicholas; Jones, Michael; Ashworth, Alan; Li, Jingmei; Cramp, Helen; Connley, Dan; Czene, Kamila; Darabi, Hatef; Chanock, Stephen J.; Lissowska, Jolanta; Figueroa, Jonine D.; Knight, Julia; Glendon, Gord; Mulligan, Anna M.; Dumont, Martine; Severi, Gianluca; Baglietto, Laura; Olson, Janet; Vachon, Celine; Purrington, Kristen; Moisse, Matthieu; Neven, Patrick; Wildiers, Hans; Spurdle, Amanda; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Hamann, Ute; Ko, Yon-Dschun; Dieffenbach, Aida K.; Arndt, Volker; Stegmaier, Christa; Malats, Núria; Arias Perez, JoséI.; Benítez, Javier; Flyger, Henrik; Nordestgaard, Børge G.; Truong, Théresè; Cordina-Duverger, Emilie; Menegaux, Florence; Silva, Isabel dos Santos; Fletcher, Olivia; Johnson, Nichola; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Braaf, Linde; Atsma, Femke; van den Broek, Alexandra J.; Makalic, Enes; Schmidt, Daniel F.; Southey, Melissa C.; Cox, Angela; Simard, Jacques; Giles, Graham G.; Lambrechts, Diether; Mannermaa, Arto; Brauch, Hiltrud; Guénel, Pascal; Peto, Julian; Fasching, Peter A.; Hopper, John; Flesch-Janys, Dieter; Couch, Fergus; Chenevix-Trench, Georgia; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Schmidt, Marjanka K.; Hall, Per; Easton, Douglas F.; Chang-Claude, Jenny

    2014-01-01

    Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G × E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10−07), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m2 (OR = 1.26, 95% CI 1.15–1.38) but not in women with a BMI of 30 kg/m2 or higher (OR = 0.89, 95% CI 0.72–1.11, P for interaction = 3.2 × 10−05). Our findings confirm comparable power of the recent methods for detecting G × E interaction and the utility of using G × E interaction analyses to identify new susceptibility loci. PMID:24248812

  14. Multiple Gene-Environment Interactions on the Angiogenesis Gene-Pathway Impact Rectal Cancer Risk and Survival

    Directory of Open Access Journals (Sweden)

    Noha Sharafeldin

    2017-09-01

    Full Text Available Characterization of gene-environment interactions (GEIs in cancer is limited. We aimed at identifying GEIs in rectal cancer focusing on a relevant biologic process involving the angiogenesis pathway and relevant environmental exposures: cigarette smoking, alcohol consumption, and animal protein intake. We analyzed data from 747 rectal cancer cases and 956 controls from the Diet, Activity and Lifestyle as a Risk Factor for Rectal Cancer study. We applied a 3-step analysis approach: first, we searched for interactions among single nucleotide polymorphisms on the pathway genes; second, we searched for interactions among the genes, both steps using Logic regression; third, we examined the GEIs significant at the 5% level using logistic regression for cancer risk and Cox proportional hazards models for survival. Permutation-based test was used for multiple testing adjustment. We identified 8 significant GEIs associated with risk among 6 genes adjusting for multiple testing: TNF (OR = 1.85, 95% CI: 1.10, 3.11, TLR4 (OR = 2.34, 95% CI: 1.38, 3.98, and EGR2 (OR = 2.23, 95% CI: 1.04, 4.78 with smoking; IGF1R (OR = 1.69, 95% CI: 1.04, 2.72, TLR4 (OR = 2.10, 95% CI: 1.22, 3.60 and EGR2 (OR = 2.12, 95% CI: 1.01, 4.46 with alcohol; and PDGFB (OR = 1.75, 95% CI: 1.04, 2.92 and MMP1 (OR = 2.44, 95% CI: 1.24, 4.81 with protein. Five GEIs were associated with survival at the 5% significance level but not after multiple testing adjustment: CXCR1 (HR = 2.06, 95% CI: 1.13, 3.75 with smoking; and KDR (HR = 4.36, 95% CI: 1.62, 11.73, TLR2 (HR = 9.06, 95% CI: 1.14, 72.11, EGR2 (HR = 2.45, 95% CI: 1.42, 4.22, and EGFR (HR = 6.33, 95% CI: 1.95, 20.54 with protein. GEIs between angiogenesis genes and smoking, alcohol, and animal protein impact rectal cancer risk. Our results support the importance of considering the biologic hypothesis to characterize GEIs associated with cancer outcomes.

  15. Gene-diet-interactions in folate-mediated one-carbon metabolism modify colon cancer risk.

    Science.gov (United States)

    Liu, Amy Y; Scherer, Dominique; Poole, Elizabeth; Potter, John D; Curtin, Karen; Makar, Karen; Slattery, Martha L; Caan, Bette J; Ulrich, Cornelia M

    2013-04-01

    The importance of folate-mediated one-carbon metabolism (FOCM) in colorectal carcinogenesis is emphasized by observations that high dietary folate intake is associated with decreased risk of colon cancer (CC) and its precursors. Additionally, polymorphisms in FOCM-related genes have been repeatedly associated with risk, supporting a causal relationship between folate and colorectal carcinogenesis. We investigated ten candidate polymorphisms with defined or probable functional impact in eight FOCM-related genes (SHMT1, DHFR, DNMT1, MTHFD1, MTHFR, MTRR, TCN2, and TDG) in 1609 CC cases and 1974 controls for association with CC risk and for interaction with dietary factors. No polymorphism was statistically significantly associated with overall risk of CC. However, statistically significant interactions modifying CC risk were observed for DNMT1 I311V with dietary folate, methionine, vitamin B2 , and vitamin B12 intake and for MTRR I22M with dietary folate, a predefined one-carbon dietary pattern, and vitamin B6 intake. We observed statistically significant gene-diet interactions with five additional polymorphisms. Our results provide evidence that FOCM-related dietary intakes modify the association between CC risk and FOCM allelic variants. These findings add to observations showing that folate-related gene-nutrient interactions play an important role in modifying the risk of CC. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  16. Gene-environment interactions in cancer epidemiology: a National Cancer Institute Think Tank report.

    Science.gov (United States)

    Hutter, Carolyn M; Mechanic, Leah E; Chatterjee, Nilanjan; Kraft, Peter; Gillanders, Elizabeth M

    2013-11-01

    Cancer risk is determined by a complex interplay of genetic and environmental factors. Genome-wide association studies (GWAS) have identified hundreds of common (minor allele frequency [MAF] > 0.05) and less common (0.01 Think Tank" on January 10-11, 2012. The objective of the Think Tank was to facilitate discussions on (1) the state of the science, (2) the goals of G × E interaction studies in cancer epidemiology, and (3) opportunities for developing novel study designs and analysis tools. This report summarizes the Think Tank discussion, with a focus on contemporary approaches to the analysis of G × E interactions. Selecting the appropriate methods requires first identifying the relevant scientific question and rationale, with an important distinction made between analyses aiming to characterize the joint effects of putative or established genetic and environmental factors and analyses aiming to discover novel risk factors or novel interaction effects. Other discussion items include measurement error, statistical power, significance, and replication. Additional designs, exposure assessments, and analytical approaches need to be considered as we move from the current small number of success stories to a fuller understanding of the interplay of genetic and environmental factors. © 2013 WILEY PERIODICALS, INC.

  17. The Cumulative Effect of Gene-Gene and Gene-Environment Interactions on the Risk of Prostate Cancer in Chinese Men

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    Ming Liu

    2016-01-01

    Full Text Available Prostate cancer (PCa is a multifactorial disease involving complex genetic and environmental factors interactions. Gene-gene and gene-environment interactions associated with PCa in Chinese men are less studied. We explored the association between 36 SNPs and PCa in 574 subjects from northern China. Body mass index (BMI, smoking, and alcohol consumption were determined through self-administered questionnaires in 134 PCa patients. Then gene-gene and gene-environment interactions among the PCa-associated SNPs were analyzed using the generalized multifactor dimensionality reduction (GMDR and logistic regression methods. Allelic and genotypic association analyses showed that six variants were associated with PCa and the cumulative effect suggested men who carried any combination of 1, 2, or ≥3 risk genotypes had a gradually increased PCa risk (odds ratios (ORs = 1.79–4.41. GMDR analysis identified the best gene-gene interaction model with scores of 10 for both the cross-validation consistency and sign tests. For gene-environment interactions, rs6983561 CC and rs16901966 GG in individuals with a BMI ≥ 28 had ORs of 7.66 (p = 0.032 and 5.33 (p = 0.046, respectively. rs7679673 CC + CA and rs12653946 TT in individuals that smoked had ORs of 2.77 (p = 0.007 and 3.11 (p = 0.024, respectively. rs7679673 CC in individuals that consumed alcohol had an OR of 4.37 (p = 0.041. These results suggest that polymorphisms, either individually or by interacting with other genes or environmental factors, contribute to an increased risk of PCa.

  18. Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups

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    S. Pamela K. Shiao

    2018-02-01

    Full Text Available For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene–environment interactions and predictors of colorectal cancer (CRC by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black. We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls (p < 0.05, on MTHFR C677T, MTR A2756G, MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05 except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike’s information criterion and leave-one-out cross validation methods. Body mass index (BMI and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene–environment interactions in the prevention of CRC.

  19. Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

    NARCIS (Netherlands)

    Nickels, S.; Truong, T.; Hein, R.; Stevens, K.; Buck, K.; Behrens, S.; Eilber, U.; Schmidt, M.; Haberle, L.; Vrieling, A.; Gaudet, M.; Figueroa, J.; Schoof, N.; Spurdle, A.B.; Rudolph, A.; Fasching, P.A.; Hopper, J.L.; Makalic, E.; Schmidt, D.F.; Southey, M.C.; Beckmann, M.W.; Ekici, A.B.; Fletcher, O.; Gibson, L.; Idos, S. Silva; Peto, J.; Humphreys, M.K.; Wang, J; Cordina-Duverger, E.; Menegaux, F.; Nordestgaard, B.G.; Bojesen, S.E.; Lanng, C.; Anton-Culver, H.; Ziogas, A.; Bernstein, L.; Clarke, C.A.; Brenner, H.; Muller, H.; Arndt, V.; Stegmaier, C.; Brauch, H.; Bruning, T.; Harth, V.; Genica, N.; Mannermaa, A.; Kataja, V.; Kosma, V.M.; Hartikainen, J.M.; Lambrechts, D.; Smeets, D.; Neven, P.; Paridaens, R.; Flesch-Janys, D.; Obi, N.; Wang-Gohrke, S.; Couch, F.J.; Olson, J.E.; Vachon, C.M.; Giles, G.G.; Severi, G.; Baglietto, L.; Offit, K.; John, E.M.; Miron, A.; Andrulis, I.L.; Knight, J.A.; Glendon, G.; Mulligan, A.M.; Chanock, S.J.; Lissowska, J.; Liu, J.; Cox, A; Cramp, H.; Connley, D.; Balasubramanian, S.; Dunning, A.M.; Shah, M.; Trentham-Dietz, A.; Newcomb, P.; Titus, L.; Egan, K.; Cahoon, E.K.; Rajaraman, P.; Sigurdson, A.J.; Doody, M.M.; Guenel, P.; Pharoah, P.D.; Schmidt, M.K.; Hall, P.; Easton, D.F.; Garcia-Closas, M.; Milne, R.L.; Chang-Claude, J.; et al.,

    2013-01-01

    Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer.

  20. Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

    Science.gov (United States)

    Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

    2018-02-16

    For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p relation to gene-environment interactions in the prevention of CRC.

  1. Impact of Maspin Polymorphism rs2289520 G/C and Its Interaction with Gene to Gene, Alcohol Consumption Increase Susceptibility to Oral Cancer Occurrence.

    Science.gov (United States)

    Yang, Po-Yu; Miao, Nae-Fang; Lin, Chiao-Wen; Chou, Ying-Erh; Yang, Shun-Fa; Huang, Hui-Chuan; Chang, Hsiu-Ju; Tsai, Hsiu-Ting

    2016-01-01

    The purpose of this study was to identify gene polymorphisms of mammary serine protease inhibitor (Maspin) specific to patients with oral cancer susceptibility and clinicopathological status. Three single-nucleotide polymorphisms (SNPs) of the Maspin gene from 741 patients with oral cancer and 601 non-cancer controls were analyzed by real-time PCR. The participants with G/G homozygotes or with G/C heterozygotes of Maspin rs2289520 polymorphism had a 2.07-fold (p = 0.01) and a 2.01-fold (p = 0.02) risk of developing oral cancer compared to those with C/C homozygotes. Moreover, gene-gene interaction increased the risk of oral cancer susceptibility among subjects expose to oral cancer related risk factors, including areca, alcohol, and tobacco consumption. G allele of Maspin rs2289520 polymorphism may be a factor that increases the susceptibility to oral cancer. The interactions of gene to oral cancer-related environmental risk factors have a synergetic effect that can further enhance oral cancer development.

  2. Personalized Nutrition-Genes, Diet, and Related Interactive Parameters as Predictors of Cancer in Multiethnic Colorectal Cancer Families.

    Science.gov (United States)

    Shiao, S Pamela K; Grayson, James; Lie, Amanda; Yu, Chong Ho

    2018-06-20

    To personalize nutrition, the purpose of this study was to examine five key genes in the folate metabolism pathway, and dietary parameters and related interactive parameters as predictors of colorectal cancer (CRC) by measuring the healthy eating index (HEI) in multiethnic families. The five genes included methylenetetrahydrofolate reductase ( MTHFR ) 677 and 1298, methionine synthase ( MTR ) 2756, methionine synthase reductase ( MTRR 66), and dihydrofolate reductase ( DHFR ) 19bp , and they were used to compute a total gene mutation score. We included 53 families, 53 CRC patients and 53 paired family friend members of diverse population groups in Southern California. We measured multidimensional data using the ensemble bootstrap forest method to identify variables of importance within domains of genetic, demographic, and dietary parameters to achieve dimension reduction. We then constructed predictive generalized regression (GR) modeling with a supervised machine learning validation procedure with the target variable (cancer status) being specified to validate the results to allow enhanced prediction and reproducibility. The results showed that the CRC group had increased total gene mutation scores compared to the family members ( p < 0.05). Using the Akaike's information criterion and Leave-One-Out cross validation GR methods, the HEI was interactive with thiamine (vitamin B1), which is a new finding for the literature. The natural food sources for thiamine include whole grains, legumes, and some meats and fish which HEI scoring included as part of healthy portions (versus limiting portions on salt, saturated fat and empty calories). Additional predictors included age, as well as gender and the interaction of MTHFR 677 with overweight status (measured by body mass index) in predicting CRC, with the cancer group having more men and overweight cases. The HEI score was significant when split at the median score of 77 into greater or less scores, confirmed through

  3. Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors

    DEFF Research Database (Denmark)

    Nickels, Stefan; Truong, Thérèse; Hein, Rebecca

    2013-01-01

    Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cance...

  4. Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

    Science.gov (United States)

    To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.

  5. Biomarker Identification for Prostate Cancer and Lymph Node Metastasis from Microarray Data and Protein Interaction Network Using Gene Prioritization Method

    Directory of Open Access Journals (Sweden)

    Carlos Roberto Arias

    2012-01-01

    Full Text Available Finding a genetic disease-related gene is not a trivial task. Therefore, computational methods are needed to present clues to the biomedical community to explore genes that are more likely to be related to a specific disease as biomarker. We present biomarker identification problem using gene prioritization method called gene prioritization from microarray data based on shortest paths, extended with structural and biological properties and edge flux using voting scheme (GP-MIDAS-VXEF. The method is based on finding relevant interactions on protein interaction networks, then scoring the genes using shortest paths and topological analysis, integrating the results using a voting scheme and a biological boosting. We applied two experiments, one is prostate primary and normal samples and the other is prostate primary tumor with and without lymph nodes metastasis. We used 137 truly prostate cancer genes as benchmark. In the first experiment, GP-MIDAS-VXEF outperforms all the other state-of-the-art methods in the benchmark by retrieving the truest related genes from the candidate set in the top 50 scores found. We applied the same technique to infer the significant biomarkers in prostate cancer with lymph nodes metastasis which is not established well.

  6. Oxidative balance and colon and rectal cancer: interaction of lifestyle factors and genes.

    Science.gov (United States)

    Slattery, Martha L; Lundgreen, Abbie; Welbourn, Bill; Wolff, Roger K; Corcoran, Christopher

    2012-06-01

    Pro-oxidant and anti-oxidant genetic and lifestyle factors can contribute to an individual's level of oxidative stress. We hypothesize that diet, lifestyle and genetic factors work together to influence colon and rectal cancer through an oxidative balance mechanism. We evaluated nine markers for eosinophil peroxidase (EPX), two for myeloperoxidase (MPO), four for hypoxia-inducible factor-1A (HIFIA), and 16 for inducible nitric oxide synthase (NOS2A) in conjunction with dietary antioxidants, aspirin/NSAID use, and cigarette smoking. We used data from population-based case-control studies (colon cancer n=1555 cases, 1956 controls; rectal cancer n=754 cases, 959 controls). Only NOS2A rs2297518 was associated with colon cancer (OR 0.86 95% CI 0.74, 0.99) and EPX rs2302313 and MPO rs2243828 were associated with rectal cancer (OR 0.75 95% CI 0.59, 0.96; OR 0.81 95% CI 0.67, 0.99 respectively) for main effects. However, after adjustment for multiple comparisons we observed the following significant interactions for colon cancer: NOS2A and lutein, EPX and aspirin/NSAID use, and NOS2A (4 SNPs) and cigarette smoking. For rectal cancer we observed the following interactions after adjustment for multiple comparisons: HIF1A and vitamin E, NOS2A (3SNPs) with calcium; MPO with lutein; HIF1A with lycopene; NOS2A with selenium; EPX and NOS2A with aspirin/NSAID use; HIF1A, MPO, and NOS2A (3 SNPs) with cigarette smoking. We observed significant interaction between a composite oxidative balance score and a polygenic model for both colon (p interaction 0.0008) and rectal cancer (p=0.0018). These results suggest the need to comprehensively evaluate interactions to assess the contribution of risk from both environmental and genetic factors. Copyright © 2012 Elsevier B.V. All rights reserved.

  7. Assessment of Multifactor Gene-Environment Interactions and Ovarian Cancer Risk

    DEFF Research Database (Denmark)

    Usset, Joseph L; Raghavan, Rama; Tyrer, Jonathan P

    2016-01-01

    and non-obese women. METHODS: We considered interactions between 11,441 SNPs within 80 candidate genes related to hormone biosynthesis and metabolism and insulin-like growth factors with six hormone-related factors (oral contraceptive use, parity, endometriosis, tubal ligation, hormone replacement therapy...... Future work is needed to develop powerful statistical methods able to detect these complex interactions. IMPACT: Assessment of multifactor interaction is feasible, and, here, suggests that the relationship between genetic variants within candidate genes and hormone-related risk factors may vary EOC...

  8. Assessing SNP-SNP interactions among DNA repair, modification and metabolism related pathway genes in breast cancer susceptibility.

    Directory of Open Access Journals (Sweden)

    Yadav Sapkota

    Full Text Available Genome-wide association studies (GWASs have identified low-penetrance common variants (i.e., single nucleotide polymorphisms, SNPs associated with breast cancer susceptibility. Although GWASs are primarily focused on single-locus effects, gene-gene interactions (i.e., epistasis are also assumed to contribute to the genetic risks for complex diseases including breast cancer. While it has been hypothesized that moderately ranked (P value based weak single-locus effects in GWASs could potentially harbor valuable information for evaluating epistasis, we lack systematic efforts to investigate SNPs showing consistent associations with weak statistical significance across independent discovery and replication stages. The objectives of this study were i to select SNPs showing single-locus effects with weak statistical significance for breast cancer in a GWAS and/or candidate-gene studies; ii to replicate these SNPs in an independent set of breast cancer cases and controls; and iii to explore their potential SNP-SNP interactions contributing to breast cancer susceptibility. A total of 17 SNPs related to DNA repair, modification and metabolism pathway genes were selected since these pathways offer a priori knowledge for potential epistatic interactions and an overall role in breast carcinogenesis. The study design included predominantly Caucasian women (2,795 cases and 4,505 controls from Alberta, Canada. We observed two two-way SNP-SNP interactions (APEX1-rs1130409 and RPAP1-rs2297381; MLH1-rs1799977 and MDM2-rs769412 in logistic regression that conferred elevated risks for breast cancer (P(interaction<7.3 × 10(-3. Logic regression identified an interaction involving four SNPs (MBD2-rs4041245, MLH1-rs1799977, MDM2-rs769412, BRCA2-rs1799943 (P(permutation = 2.4 × 10(-3. SNPs involved in SNP-SNP interactions also showed single-locus effects with weak statistical significance, while BRCA2-rs1799943 showed stronger statistical significance (P

  9. Identification of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions

    DEFF Research Database (Denmark)

    Schoeps, Anja; Rudolph, Anja; Seibold, Petra

    2014-01-01

    recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714......,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three...... in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 × 10(-07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8...

  10. High Frequency of Interactions between Lung Cancer Susceptibility Genes in the Mouse : Mapping of Sluc5 to Sluc14

    NARCIS (Netherlands)

    Fijneman, Remond J.A.; Jansen, Ritsert C.; Valk, Martin A. van der; Demant, Peter

    1998-01-01

    Although several genes that cause monogenic familial cancer syndromes have been identified, susceptibility to sporadic cancer remains unresolved. Animal experiments have demonstrated multigenic control of tumor susceptibility. Recently, we described four mouse lung cancer susceptibility (Sluc) loci,

  11. Multiple analytical approaches reveal distinct gene-environment interactions in smokers and non smokers in lung cancer.

    Directory of Open Access Journals (Sweden)

    Rakhshan Ihsan

    Full Text Available Complex disease such as cancer results from interactions of multiple genetic and environmental factors. Studying these factors singularly cannot explain the underlying pathogenetic mechanism of the disease. Multi-analytical approach, including logistic regression (LR, classification and regression tree (CART and multifactor dimensionality reduction (MDR, was applied in 188 lung cancer cases and 290 controls to explore high order interactions among xenobiotic metabolizing genes and environmental risk factors. Smoking was identified as the predominant risk factor by all three analytical approaches. Individually, CYP1A1*2A polymorphism was significantly associated with increased lung cancer risk (OR = 1.69;95%CI = 1.11-2.59,p = 0.01, whereas EPHX1 Tyr113His and SULT1A1 Arg213His conferred reduced risk (OR = 0.40;95%CI = 0.25-0.65,p<0.001 and OR = 0.51;95%CI = 0.33-0.78,p = 0.002 respectively. In smokers, EPHX1 Tyr113His and SULT1A1 Arg213His polymorphisms reduced the risk of lung cancer, whereas CYP1A1*2A, CYP1A1*2C and GSTP1 Ile105Val imparted increased risk in non-smokers only. While exploring non-linear interactions through CART analysis, smokers carrying the combination of EPHX1 113TC (Tyr/His, SULT1A1 213GG (Arg/Arg or AA (His/His and GSTM1 null genotypes showed the highest risk for lung cancer (OR = 3.73;95%CI = 1.33-10.55,p = 0.006, whereas combined effect of CYP1A1*2A 6235CC or TC, SULT1A1 213GG (Arg/Arg and betel quid chewing showed maximum risk in non-smokers (OR = 2.93;95%CI = 1.15-7.51,p = 0.01. MDR analysis identified two distinct predictor models for the risk of lung cancer in smokers (tobacco chewing, EPHX1 Tyr113His, and SULT1A1 Arg213His and non-smokers (CYP1A1*2A, GSTP1 Ile105Val and SULT1A1 Arg213His with testing balance accuracy (TBA of 0.6436 and 0.6677 respectively. Interaction entropy interpretations of MDR results showed non-additive interactions of tobacco chewing with

  12. Case-only gene-environment interaction between ALAD tagSNPs and occupational lead exposure in prostate cancer.

    Science.gov (United States)

    Neslund-Dudas, Christine; Levin, Albert M; Rundle, Andrew; Beebe-Dimmer, Jennifer; Bock, Cathryn H; Nock, Nora L; Jankowski, Michelle; Datta, Indrani; Krajenta, Richard; Dou, Q Ping; Mitra, Bharati; Tang, Deliang; Rybicki, Benjamin A

    2014-05-01

    Black men have historically had higher blood lead levels than white men in the U.S. and have the highest incidence of prostate cancer in the world. Inorganic lead has been classified as a probable human carcinogen. Lead (Pb) inhibits delta-aminolevulinic acid dehydratase (ALAD), a gene recently implicated in other genitourinary cancers. The ALAD enzyme is involved in the second step of heme biosynthesis and is an endogenous inhibitor of the 26S proteasome, a master system for protein degradation and a current target of cancer therapy. Using a case-only study design, we assessed potential gene-environment (G × E) interactions between lifetime occupational Pb exposure and 11 tagSNPs within ALAD in black (N = 260) and white (N = 343) prostate cancer cases. Two ALAD tagSNPs in high linkage disequilibrium showed significant interaction with high Pb exposure among black cases (rs818684 interaction odds ratio or IOR = 2.73, 95% CI 1.43-5.22, P = 0.002; rs818689 IOR = 2.20, 95% CI 1.15-4.21, P = 0.017) and an additional tagSNP, rs2761016, showed G × E interaction with low Pb exposure (IOR = 2.08, 95% CI 1.13-3.84, P = 0.019). Further, the variant allele of rs818684 was associated with a higher Gleason grade in those with high Pb exposure among both blacks (OR 3.96, 95% CI 1.01-15.46, P = 0.048) and whites (OR 2.95, 95% CI 1.18-7.39, P = 0.020). Genetic variation in ALAD may modify associations between Pb and prostate cancer. Additional studies of ALAD, Pb, and prostate cancer are warranted and should include black men. Prostate 74:637-646, 2014. © 2014 Wiley Periodicals, Inc. © 2014 Wiley Periodicals, Inc.

  13. Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors.

    Directory of Open Access Journals (Sweden)

    Stefan Nickels

    Full Text Available Various common genetic susceptibility loci have been identified for breast cancer; however, it is unclear how they combine with lifestyle/environmental risk factors to influence risk. We undertook an international collaborative study to assess gene-environment interaction for risk of breast cancer. Data from 24 studies of the Breast Cancer Association Consortium were pooled. Using up to 34,793 invasive breast cancers and 41,099 controls, we examined whether the relative risks associated with 23 single nucleotide polymorphisms were modified by 10 established environmental risk factors (age at menarche, parity, breastfeeding, body mass index, height, oral contraceptive use, menopausal hormone therapy use, alcohol consumption, cigarette smoking, physical activity in women of European ancestry. We used logistic regression models stratified by study and adjusted for age and performed likelihood ratio tests to assess gene-environment interactions. All statistical tests were two-sided. We replicated previously reported potential interactions between LSP1-rs3817198 and parity (Pinteraction = 2.4 × 10(-6 and between CASP8-rs17468277 and alcohol consumption (Pinteraction = 3.1 × 10(-4. Overall, the per-allele odds ratio (95% confidence interval for LSP1-rs3817198 was 1.08 (1.01-1.16 in nulliparous women and ranged from 1.03 (0.96-1.10 in parous women with one birth to 1.26 (1.16-1.37 in women with at least four births. For CASP8-rs17468277, the per-allele OR was 0.91 (0.85-0.98 in those with an alcohol intake of <20 g/day and 1.45 (1.14-1.85 in those who drank ≥ 20 g/day. Additionally, interaction was found between 1p11.2-rs11249433 and ever being parous (Pinteraction = 5.3 × 10(-5, with a per-allele OR of 1.14 (1.11-1.17 in parous women and 0.98 (0.92-1.05 in nulliparous women. These data provide first strong evidence that the risk of breast cancer associated with some common genetic variants may vary with environmental risk factors.

  14. Glutathione S-transferase P1, gene-gene interaction, and lung cancer susceptibility in the Chinese population: An updated meta-analysis and review

    Directory of Open Access Journals (Sweden)

    Xue-Ming Li

    2015-01-01

    Full Text Available Aim of Study: To assess the impact of glutathione S-transferase P1 (GSTP1 Ile105Val polymorphism on the risk of lung cancer in the Chinese population, an updated meta-analysis and review was performed. Materials and Methods: Relevant studies were identified from PubMed, Springer Link, Ovid, Chinese Wanfang Data Knowledge Service Platform, Chinese National Knowledge Infrastructure, and Chinese Biology Medicine published through January 22, 2015. The odds ratios (ORs and 95% confidence intervals (CIs were calculated to estimate the strength of the associations. Results: A total of 13 case-control studies, including 2026 lung cancer cases and 2451 controls, were included in this meta-analysis. Overall, significantly increased lung cancer risk was associated with the variant genotypes of GSTP1 polymorphism in the Chinese population (GG vs. AA: OR = 1.36, 95% CI = 1.01-1.84. In subgroup analyses stratified by geographic area and source of controls, the significant results were found in population-based studies (GG vs. AA: OR = 1.62, 95% CI: 1.13-2.31; GG vs. AG: OR = 1.49, 95% CI: 1.03-2.16; GG vs. AA + AG: OR = 1.55, 95% CI: 1.12-2.26. A gene-gene interaction analysis showed that there was an interaction for individuals with combination of GSTM1 (or GSTT1 null genotype and GSTP1 (AG + GG mutant genotype for lung cancer risk in Chinese. Conclusion: This meta-analysis suggests that GSTP1 Ile105Val polymorphism may increase the risk of lung cancer in the Chinese population.

  15. An epistatic interaction between the PAX8 and STK17B genes in papillary thyroid cancer susceptibility.

    Directory of Open Access Journals (Sweden)

    Iñigo Landa

    Full Text Available Papillary Thyroid Cancer (PTC is a heterogeneous and complex disease; susceptibility to PTC is influenced by the joint effects of multiple common, low-penetrance genes, although relatively few have been identified to date. Here we applied a rigorous combined approach to assess both the individual and epistatic contributions of genetic factors to PTC susceptibility, based on one of the largest series of thyroid cancer cases described to date. In addition to identifying the involvement of TSHR variation in classic PTC, our pioneer study of epistasis revealed a significant interaction between variants in STK17B and PAX8. The interaction was detected by MD-MBR (p = 0.00010 and confirmed by other methods, and then replicated in a second independent series of patients (MD-MBR p = 0.017. Furthermore, we demonstrated an inverse correlation between expression of PAX8 and STK17B in a set of cell lines derived from human thyroid carcinomas. Overall, our work sheds additional light on the genetic basis of thyroid cancer susceptibility, and suggests a new direction for the exploration of the inherited genetic contribution to disease using association studies.

  16. A Multiple Interaction Analysis Reveals ADRB3 as a Potential Candidate for Gallbladder Cancer Predisposition via a Complex Interaction with Other Candidate Gene Variations

    Directory of Open Access Journals (Sweden)

    Rajani Rai

    2015-11-01

    Full Text Available Gallbladder cancer is the most common and a highly aggressive biliary tract malignancy with a dismal outcome. The pathogenesis of the disease is multifactorial, comprising the combined effect of multiple genetic variations of mild consequence along with numerous dietary and environmental risk factors. Previously, we demonstrated the association of several candidate gene variations with GBC risk. In this study, we aimed to identify the combination of gene variants and their possible interactions contributing towards genetic susceptibility of GBC. Here, we performed Multifactor-Dimensionality Reduction (MDR and Classification and Regression Tree Analysis (CRT to investigate the gene–gene interactions and the combined effect of 14 SNPs in nine genes (DR4 (rs20576, rs6557634; FAS (rs2234767; FASL (rs763110; DCC (rs2229080, rs4078288, rs7504990, rs714; PSCA (rs2294008, rs2978974; ADRA2A (rs1801253; ADRB1 (rs1800544; ADRB3 (rs4994; CYP17 (rs2486758 involved in various signaling pathways. Genotyping was accomplished by PCR-RFLP or Taqman allelic discrimination assays. SPSS software version 16.0 and MDR software version 2.0 were used for all the statistical analysis. Single locus investigation demonstrated significant association of DR4 (rs20576, rs6557634, DCC (rs714, rs2229080, rs4078288 and ADRB3 (rs4994 polymorphisms with GBC risk. MDR analysis revealed ADRB3 (rs4994 to be crucial candidate in GBC susceptibility that may act either alone (p < 0.0001, CVC = 10/10 or in combination with DCC (rs714 and rs2229080, p < 0.0001, CVC = 9/10. Our CRT results are in agreement with the above findings. Further, in-silico results of studied SNPs advocated their role in splicing, transcriptional and/or protein coding regulation. Overall, our result suggested complex interactions amongst the studied SNPs and ADRB3 rs4994 as candidate influencing GBC susceptibility.

  17. Gene-Environment Interaction and Breast Cancer on Long Island, NY

    National Research Council Canada - National Science Library

    Teitelbaum, Susan

    2006-01-01

    ...), a large population-based, case-control study of the environment and breast cancer. Participants completed an in-person interviewer-administered interview, donated blood and urine samples, and had home environment samples...

  18. Gene-Environment Interaction and Breast Cancer on Long Island, NY

    Science.gov (United States)

    2008-05-01

    Dietary flavonoid intake and breast cancer survival among women on Long Island. Cancer Epidemiol Biomarkers Prev. 2007 Nov;16(11):2285-92...Kuklenyik, Z., Needham, L.L., Calafat, A.M., 2005. Automated on-line column-switching HPLC -MS/MS method with peak focusing for the determination of...action. Environ Health Perspect 110:917–921. Rybak ME, Parker DL, Pfeiffer CM. 2006. Determination of Urinary Phytoestrogens by HPLC -MS/MS: A Comparison

  19. Gene-environment interactions involving functional variants

    DEFF Research Database (Denmark)

    Barrdahl, Myrto; Rudolph, Anja; Hopper, John L

    2017-01-01

    .36, 95% CI: 1.16-1.59, pint  = 1.9 × 10(-5) ) in relation to ER- disease risk. The remaining two gene-environment interactions were also identified in relation to ER- breast cancer risk and were found between 3p21-rs6796502 and age at menarche (ORint  = 1.26, 95% CI: 1.12-1.43, pint =1.8 × 10...... epidemiological breast cancer risk factors in relation to breast cancer. Analyses were conducted on up to 58,573 subjects (26,968 cases and 31,605 controls) from the Breast Cancer Association Consortium, in one of the largest studies of its kind. Analyses were carried out separately for estrogen receptor (ER......) positive (ER+) and ER negative (ER-) disease. The Bayesian False Discovery Probability (BFDP) was computed to assess the noteworthiness of the results. Four potential gene-environment interactions were identified as noteworthy (BFDP 

  20. Prioritizing genes associated with prostate cancer development

    International Nuclear Information System (INIS)

    Gorlov, Ivan P; Logothetis, Christopher J; Sircar, Kanishka; Zhao, Hongya; Maity, Sankar N; Navone, Nora M; Gorlova, Olga Y; Troncoso, Patricia; Pettaway, Curtis A; Byun, Jin Young

    2010-01-01

    The genetic control of prostate cancer development is poorly understood. Large numbers of gene-expression datasets on different aspects of prostate tumorigenesis are available. We used these data to identify and prioritize candidate genes associated with the development of prostate cancer and bone metastases. Our working hypothesis was that combining meta-analyses on different but overlapping steps of prostate tumorigenesis will improve identification of genes associated with prostate cancer development. A Z score-based meta-analysis of gene-expression data was used to identify candidate genes associated with prostate cancer development. To put together different datasets, we conducted a meta-analysis on 3 levels that follow the natural history of prostate cancer development. For experimental verification of candidates, we used in silico validation as well as in-house gene-expression data. Genes with experimental evidence of an association with prostate cancer development were overrepresented among our top candidates. The meta-analysis also identified a considerable number of novel candidate genes with no published evidence of a role in prostate cancer development. Functional annotation identified cytoskeleton, cell adhesion, extracellular matrix, and cell motility as the top functions associated with prostate cancer development. We identified 10 genes--CDC2, CCNA2, IGF1, EGR1, SRF, CTGF, CCL2, CAV1, SMAD4, and AURKA--that form hubs of the interaction network and therefore are likely to be primary drivers of prostate cancer development. By using this large 3-level meta-analysis of the gene-expression data to identify candidate genes associated with prostate cancer development, we have generated a list of candidate genes that may be a useful resource for researchers studying the molecular mechanisms underlying prostate cancer development

  1. Introduction: Cancer Gene Networks.

    Science.gov (United States)

    Clarke, Robert

    2017-01-01

    Constructing, evaluating, and interpreting gene networks generally sits within the broader field of systems biology, which continues to emerge rapidly, particular with respect to its application to understanding the complexity of signaling in the context of cancer biology. For the purposes of this volume, we take a broad definition of systems biology. Considering an organism or disease within an organism as a system, systems biology is the study of the integrated and coordinated interactions of the network(s) of genes, their variants both natural and mutated (e.g., polymorphisms, rearrangements, alternate splicing, mutations), their proteins and isoforms, and the organic and inorganic molecules with which they interact, to execute the biochemical reactions (e.g., as enzymes, substrates, products) that reflect the function of that system. Central to systems biology, and perhaps the only approach that can effectively manage the complexity of such systems, is the building of quantitative multiscale predictive models. The predictions of the models can vary substantially depending on the nature of the model and its inputoutput relationships. For example, a model may predict the outcome of a specific molecular reaction(s), a cellular phenotype (e.g., alive, dead, growth arrest, proliferation, and motility), a change in the respective prevalence of cell or subpopulations, a patient or patient subgroup outcome(s). Such models necessarily require computers. Computational modeling can be thought of as using machine learning and related tools to integrate the very high dimensional data generated from modern, high throughput omics technologies including genomics (next generation sequencing), transcriptomics (gene expression microarrays; RNAseq), metabolomics and proteomics (ultra high performance liquid chromatography, mass spectrometry), and "subomic" technologies to study the kinome, methylome, and others. Mathematical modeling can be thought of as the use of ordinary

  2. Insights into significant pathways and gene interaction networks underlying breast cancer cell line MCF-7 treated with 17β-estradiol (E2).

    Science.gov (United States)

    Huan, Jinliang; Wang, Lishan; Xing, Li; Qin, Xianju; Feng, Lingbin; Pan, Xiaofeng; Zhu, Ling

    2014-01-01

    Estrogens are known to regulate the proliferation of breast cancer cells and to alter their cytoarchitectural and phenotypic properties, but the gene networks and pathways by which estrogenic hormones regulate these events are only partially understood. We used global gene expression profiling by Affymetrix GeneChip microarray analysis, with KEGG pathway enrichment, PPI network construction, module analysis and text mining methods to identify patterns and time courses of genes that are either stimulated or inhibited by estradiol (E2) in estrogen receptor (ER)-positive MCF-7 human breast cancer cells. Of the genes queried on the Affymetrix Human Genome U133 plus 2.0 microarray, we identified 628 (12h), 852 (24h) and 880 (48 h) differentially expressed genes (DEGs) that showed a robust pattern of regulation by E2. From pathway enrichment analysis, we found out the changes of metabolic pathways of E2 treated samples at each time point. At 12h time point, the changes of metabolic pathways were mainly focused on pathways in cancer, focal adhesion, and chemokine signaling pathway. At 24h time point, the changes were mainly enriched in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction and calcium signaling pathway. At 48 h time point, the significant pathways were pathways in cancer, regulation of actin cytoskeleton, cell adhesion molecules (CAMs), axon guidance and ErbB signaling pathway. Of interest, our PPI network analysis and module analysis found that E2 treatment induced enhancement of PRSS23 at the three time points and PRSS23 was in the central position of each module. Text mining results showed that the important genes of DEGs have relationship with signal pathways, such as ERbB pathway (AREG), Wnt pathway (NDP), MAPK pathway (NTRK3, TH), IP3 pathway (TRA@) and some transcript factors (TCF4, MAF). Our studies highlight the diverse gene networks and metabolic and cell regulatory pathways through which E2 operates to achieve its

  3. Integration of multiple networks and pathways identifies cancer driver genes in pan-cancer analysis.

    Science.gov (United States)

    Cava, Claudia; Bertoli, Gloria; Colaprico, Antonio; Olsen, Catharina; Bontempi, Gianluca; Castiglioni, Isabella

    2018-01-06

    Modern high-throughput genomic technologies represent a comprehensive hallmark of molecular changes in pan-cancer studies. Although different cancer gene signatures have been revealed, the mechanism of tumourigenesis has yet to be completely understood. Pathways and networks are important tools to explain the role of genes in functional genomic studies. However, few methods consider the functional non-equal roles of genes in pathways and the complex gene-gene interactions in a network. We present a novel method in pan-cancer analysis that identifies de-regulated genes with a functional role by integrating pathway and network data. A pan-cancer analysis of 7158 tumour/normal samples from 16 cancer types identified 895 genes with a central role in pathways and de-regulated in cancer. Comparing our approach with 15 current tools that identify cancer driver genes, we found that 35.6% of the 895 genes identified by our method have been found as cancer driver genes with at least 2/15 tools. Finally, we applied a machine learning algorithm on 16 independent GEO cancer datasets to validate the diagnostic role of cancer driver genes for each cancer. We obtained a list of the top-ten cancer driver genes for each cancer considered in this study. Our analysis 1) confirmed that there are several known cancer driver genes in common among different types of cancer, 2) highlighted that cancer driver genes are able to regulate crucial pathways.

  4. The interaction effects of pri-let-7a-1 rs10739971 with PGC and ERCC6 gene polymorphisms in gastric cancer and atrophic gastritis.

    Directory of Open Access Journals (Sweden)

    Qian Xu

    Full Text Available BACKGROUND: The aim of this study was to investigate the interaction effects of pri-let-7a-1 rs10739971 with pepsinogen C (PGC and excision repair cross complementing group 6 (ERCC6 gene polymorphisms and its association with the risks of gastric cancer and atrophic gastritis. We hoped to identify miRNA polymorphism or a combination of several polymorphisms that could serve as biomarkers for predicting the risk of gastric cancer and its precancerous diseases. METHODS: Sequenom MassARRAY platform method was used to detect polymorphisms of pri-let-7a-1 rs10739971 G → A, PGC rs4711690 C → G, PGC rs6458238 G → A, PGC rs9471643 G → C, and ERCC6 rs1917799 in 471 gastric cancer patients, 645 atrophic gastritis patients and 717 controls. RESULTS: An interaction effect of pri-let-7a-1 rs10739971 polymorphism with ERCC6 rs1917799 polymorphism was observed for the risk of gastric cancer (P interaction = 0.026; and interaction effects of pri-let-7a-1 rs10739971 polymorphism with PGC rs6458238 polymorphism (P interaction = 0.012 and PGC rs9471643 polymorphism (P interaction = 0.039 were observed for the risk of atrophic gastritis. CONCLUSION: The combination of pri-let-7a-1 rs10739971 polymorphism and ERCC6 and PGC polymorphisms could provide a greater prediction potential than a single polymorphism on its own. Large-scale studies and molecular mechanism research are needed to confirm our findings.

  5. Folate intake, alcohol consumption, and the methylenetetrahydrofolate reductase (MTHFR C677T gene polymorphism: influence on prostate cancer risk and interactions

    Directory of Open Access Journals (Sweden)

    Lindsay C Kobayashi

    2012-08-01

    Full Text Available Purpose: Folate is essential to DNA methylation and synthesis and may have a complex dualistic role in prostate cancer. Alcohol use may increase risk and epigenetic factors may interact with lifestyle exposures. We aimed to characterize the independent and joint effects of folate intake, alcohol consumption, and the MTHFR C677T gene polymorphism on prostate cancer risk, while accounting for intakes of vitamins B2, B6, B12, methionine, total energy, and confounders.Methods: A case-control study was conducted at Kingston General Hospital of 80 incident primary prostate cancer cases and 334 urology clinic controls, all with normal age-specific PSA levels (to exclude latent prostate cancers. Participants completed a questionnaire on folate and alcohol intakes and potential confounders prior to knowledge of diagnosis, eliminating recall bias, and blood was drawn for MTHFR genotyping. Joint effects of exposures were assessed using unconditional logistic regression and significance of multiplicative and additive interactions using general linear models.Results: Folate, vitamins B2, B6, B12, methionine, and the CT and TT genotypes were not associated with prostate cancer risk. The highest tertile of lifetime alcohol consumption was associated with increased risk (OR=2.08; 95% CI: 1.12-3.86. Consumption of >5 alcoholic drinks/week was associated with increased prostate cancer risk among men with low folate intake (OR=2.38; 95% CI: 1.01-5.57 and higher risk among those with the CC MTHFR genotype (OR=4.43; 95% CI: 1.15-17.05. Increased risk was also apparent for weekly alcohol consumption when accounting for the multiplicative interaction between folate intake and MTHFR C677T genotype (OR=3.22; 95% CI: 1.36-7.59.Conclusion: Alcohol consumption is associated with increased prostate cancer risk, and this association is stronger among men with low folate intake, with the CC MTHFR genotype, and when accounting for the joint effect of folate intake and MTHFR C

  6. Folate intake, alcohol consumption, and the methylenetetrahydrofolate reductase (MTHFR) C677T gene polymorphism: influence on prostate cancer risk and interactions

    International Nuclear Information System (INIS)

    Kobayashi, Lindsay C.; Limburg, Heather; Miao, Qun; Woolcott, Christy; Bedard, Leanne L.; Massey, Thomas E.; Aronson, Kristan J.

    2012-01-01

    Purpose: Folate is essential to DNA methylation and synthesis and may have a complex dualistic role in prostate cancer. Alcohol use may increase risk and epigenetic factors may interact with lifestyle exposures. We aimed to characterize the independent and joint effects of folate intake, alcohol consumption, and the MTHFR C677T gene polymorphism on prostate cancer risk, while accounting for intakes of vitamins B 2 , B 6 , B 12 , methionine, total energy, and confounders. Methods: A case-control study was conducted at Kingston General Hospital of 80 incident primary prostate cancer cases and 334 urology clinic controls, all with normal age-specific PSA levels (to exclude latent prostate cancers). Participants completed a questionnaire on folate and alcohol intakes and potential confounders prior to knowledge of diagnosis, eliminating recall bias, and blood was drawn for MTHFR genotyping. Joint effects of exposures were assessed using unconditional logistic regression and significance of multiplicative and additive interactions using general linear models. Results: Folate, vitamins B 2 , B 6 , B 12 , methionine, and the CT and TT genotypes were not associated with prostate cancer risk. The highest tertile of lifetime alcohol consumption was associated with increased risk (OR = 2.08; 95% CI: 1.12–3.86). Consumption of >5 alcoholic drinks per week was associated with increased prostate cancer risk among men with low folate intake (OR = 2.38; 95% CI: 1.01–5.57), and higher risk among those with the CC MTHFR genotype (OR = 4.43; 95% CI: 1.15–17.05). Increased risk was also apparent for average weekly alcohol consumption when accounting for the multiplicative interaction between folate intake and MTHFR C677T genotype (OR = 3.22; 95% CI: 1.36–7.59). Conclusion: Alcohol consumption is associated with increased prostate cancer risk, and this association is stronger among men with low folate intake, with the CC MTHFR genotype, and when accounting for the joint effect

  7. Metabolic Phase I (CYPs) and Phase II (GSTs) Gene Polymorphisms and Their Interaction with Environmental Factors in Nasopharyngeal Cancer from the Ethnic Population of Northeast India.

    Science.gov (United States)

    Singh, Seram Anil; Ghosh, Sankar Kumar

    2017-09-26

    Multiple genetic and environmental factors and their interaction are believed to contribute in the pathogenesis of Nasopharyngeal Cancer (NPC). We investigate the role of Metabolic Phase I (CYPs) and Phase II (GSTs) gene polymorphisms, gene-gene and gene-environmental interaction in modulating the susceptibility to NPC in Northeast India. To determine the association of metabolic gene polymorphisms and environmental habits, 123 cases and 189 controls blood/swab samples were used for PCR and confirmed by Sanger sequencing. Analysis for GSTM1 and GSTT1 gene polymorphism was done by multiplex PCR. The T3801C in the 3'- flanking region of CYP1A1 gene was detected by PCR-RFLP method. The Logistic regression analysis was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI). The GSTM1 null genotype alone (OR = 2.76) was significantly associated with NPC risk (P < 0.0001). The combinations of GSTM1 null and GSTT1 null genotypes also higher, 3.77 fold (P < 0.0001), risk of NPC, while GSTM1 null genotype along with CYP1A1 T3801C TC + CC genotype had 3.22 (P = 0.001) fold risk. The most remarkable risk was seen among individual carrying GSTM1 null, GSTT1 null genotypes and CYP1A1 T3801C TC + CC genotypes (OR = 5.71, P = 0.001). Further; analyses demonstrate an enhanced risk of NPC in smoked meat (OR = 5.56, P < 0.0001) and fermented fish consumers (OR = 5.73, P < 0.0001) carrying GSTM1 null genotype. An elevated risk of NPC was noted in smokers (OR = 12.67, P < 0.0001) and chewers (OR = 5.68, P < 0.0001) with GSTM1 null genotype. However, smokers had the highest risk of NPC among individuals carrying GSTT1 null genotype (OR = 4.46, P = 0.001) or CYP1A1 T3801C TC + CC genotype (OR = 7.13, P < 0.0001). The association of null genotypes and mutations of metabolic neutralizing genes along with the environmental habits (tobacco smokers and chewers, smoke meat, fermented fishes) can be used as a possible biomarker for

  8. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    NARCIS (Netherlands)

    Rudolph, Anja; Milne, Roger L.; Truong, Thérèse; Knight, Julia A.; Seibold, Petra; Flesch-Janys, Dieter; Behrens, Sabine; Eilber, Ursula; Bolla, Manjeet K.; Wang, Qin; Dennis, Joe; Dunning, Alison M.; Shah, Mitul; Munday, Hannah R.; Darabi, Hatef; Eriksson, Mikael; Brand, Judith S.; Olson, Janet; Vachon, Celine M.; Hallberg, Emily; Castelao, J. Esteban; Carracedo, Angel; Torres, Maria; Li, Jingmei; Humphreys, Keith; Cordina-Duverger, Emilie; Menegaux, Florence; Flyger, Henrik; Nordestgaard, Børge G.; Nielsen, Sune F.; Yesilyurt, Betul T.; Floris, Giuseppe; Leunen, Karin; Engelhardt, Ellen G.; Broeks, Annegien; Rutgers, Emiel J.; Glendon, Gord; Mulligan, Anna Marie; Cross, Simon; Reed, Malcolm; Gonzalez-Neira, Anna; Arias Perez, José Ignacio; Provenzano, Elena; Apicella, Carmel; Southey, Melissa C.; Spurdle, Amanda; Häberle, Lothar; Beckmann, Matthias W.; Ekici, Arif B.; Dieffenbach, Aida Karina; Arndt, Volker; Stegmaier, Christa; McLean, Catriona; Baglietto, Laura; Chanock, Stephen J.; Lissowska, Jolanta; Sherman, Mark E.; Brüning, Thomas; Hamann, Ute; Ko, Yon-Dschun; Orr, Nick; Schoemaker, Minouk; Ashworth, Alan; Kosma, Veli-Matti; Kataja, Vesa; Hartikainen, Jaana M.; Mannermaa, Arto; Swerdlow, Anthony; Giles, Graham G.; Brenner, Hermann; Fasching, Peter A.; Chenevix-Trench, Georgia; Hopper, John; Benítez, Javier; Cox, Angela; Andrulis, Irene L.; Lambrechts, Diether; Gago-Dominguez, Manuela; Couch, Fergus; Czene, Kamila; Bojesen, Stig E.; Easton, Doug F.; Schmidt, Marjanka K.; Guénel, Pascal; Hall, Per; Pharoah, Paul D. P.; Garcia-Closas, Montserrat; Chang-Claude, Jenny

    2015-01-01

    A large genotyping project within the Breast Cancer Association Consortium (BCAC) recently identified 41 associations between single nucleotide polymorphisms (SNPs) and overall breast cancer (BC) risk. We investigated whether the effects of these 41 SNPs, as well as six SNPs associated with estrogen

  9. Meta-analysis of Cancer Gene Profiling Data.

    Science.gov (United States)

    Roy, Janine; Winter, Christof; Schroeder, Michael

    2016-01-01

    The simultaneous measurement of thousands of genes gives the opportunity to personalize and improve cancer therapy. In addition, the integration of meta-data such as protein-protein interaction (PPI) information into the analyses helps in the identification and prioritization of genes from these screens. Here, we describe a computational approach that identifies genes prognostic for outcome by combining gene profiling data from any source with a network of known relationships between genes.

  10. Gene therapy for prostate cancer.

    LENUS (Irish Health Repository)

    Tangney, Mark

    2012-01-31

    Cancer remains a leading cause of morbidity and mortality. Despite advances in understanding, detection, and treatment, it accounts for almost one-fourth of all deaths per year in Western countries. Prostate cancer is currently the most commonly diagnosed noncutaneous cancer in men in Europe and the United States, accounting for 15% of all cancers in men. As life expectancy of individuals increases, it is expected that there will also be an increase in the incidence and mortality of prostate cancer. Prostate cancer may be inoperable at initial presentation, unresponsive to chemotherapy and radiotherapy, or recur following appropriate treatment. At the time of presentation, patients may already have metastases in their tissues. Preventing tumor recurrence requires systemic therapy; however, current modalities are limited by toxicity or lack of efficacy. For patients with such metastatic cancers, the development of alternative therapies is essential. Gene therapy is a realistic prospect for the treatment of prostate and other cancers, and involves the delivery of genetic information to the patient to facilitate the production of therapeutic proteins. Therapeutics can act directly (eg, by inducing tumor cells to produce cytotoxic agents) or indirectly by upregulating the immune system to efficiently target tumor cells or by destroying the tumor\\'s vasculature. However, technological difficulties must be addressed before an efficient and safe gene medicine is achieved (primarily by developing a means of delivering genes to the target cells or tissue safely and efficiently). A wealth of research has been carried out over the past 20 years, involving various strategies for the treatment of prostate cancer at preclinical and clinical trial levels. The therapeutic efficacy observed with many of these approaches in patients indicates that these treatment modalities will serve as an important component of urological malignancy treatment in the clinic, either in isolation or

  11. Expression of PAM50 Genes in Lung Cancer: Evidence that Interactions between Hormone Receptors and HER2/HER3 Contribute to Poor Outcome

    Directory of Open Access Journals (Sweden)

    Jill M. Siegfried

    2015-11-01

    Full Text Available Non–small cell lung cancers (NSCLCs frequently express estrogen receptor (ER β, and estrogen signaling is active in many lung tumors. We investigated the ability of genes contained in the prediction analysis of microarray 50 (PAM50 breast cancer risk predictor gene signature to provide prognostic information in NSCLC. Supervised principal component analysis of mRNA expression data was used to evaluate the ability of the PAM50 panel to provide prognostic information in a stage I NSCLC cohort, in an all-stage NSCLC cohort, and in The Cancer Genome Atlas data. Immunohistochemistry was used to determine status of ERβ and other proteins in lung tumor tissue. Associations with prognosis were observed in the stage I cohort. Cross-validation identified seven genes that, when analyzed together, consistently showed survival associations. In pathway analysis, the seven-gene panel described one network containing the ER and progesterone receptor, as well as human epidermal growth factor receptor (HER2/HER3 and neuregulin-1. NSCLC cases also showed a significant association between ERβ and HER2 protein expression. Cases positive for HER2 expression were more likely to express HER3, and ERβ-positive cases were less likely to be both HER2 and HER3 negative. Prognostic ability of genes in the PAM50 panel was verified in an ERβ-positive cohort representing all NSCLC stages. In The Cancer Genome Atlas data sets, the PAM50 gene set was prognostic in both adenocarcinoma and squamous cell carcinoma, whereas the seven-gene panel was prognostic only in squamous cell carcinoma. Genes in the PAM50 panel, including those linking ER and HER2, identify lung cancer patients at risk for poor outcome, especially among ERβ-positive cases and squamous cell carcinoma.

  12. Polymorphisms in ATP-binding cassette transporter genes and interaction with diet and life style factors in relation to colorectal cancer in a Danish prospective case-cohort study

    DEFF Research Database (Denmark)

    Kopp, Tine Iskov; Andersen, Vibeke; Tjonneland, Anne

    2015-01-01

    to assess whether polymorphisms in ABCB1, ABCC2 and ABCG2 were associated with risk of colorectal cancer (CRC) and to investigate gene-environment (dietary factors, smoking and use of non-steroidal anti-inflammatory drugs) and gene-gene interactions between previously studied polymorphisms in IL1B and IL10......The ATP-binding cassette (ABC) transporter family transports various molecules across the enterocytes in the gut protecting the intestine against potentially harmful substances. Moreover, ABC transporters are involved in mucosal immune defence through interaction with cytokines. The study aimed...... of the polymorphisms were associated with CRC, but ABCB1 and ABCG2 haplotypes were associated with risk of CRC. ABCB1/rs1045642 interacted with intake of cereals and fiber (p-Value for interaction (Pint) = 0.001 and 0.01, respectively). In a three-way analysis, both ABCB1/rs1045642 and ABCG2/rs2231137 in combination...

  13. Protein-Protein Interactions (PPI) reagents: | Office of Cancer Genomics

    Science.gov (United States)

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below.

  14. Protein-Protein Interaction Reagents | Office of Cancer Genomics

    Science.gov (United States)

    The CTD2 Center at Emory University has a library of genes used to study protein-protein interactions in mammalian cells. These genes are cloned in different mammalian expression vectors. A list of available cancer-associated genes can be accessed below. Emory_CTD^2_PPI_Reagents.xlsx Contact: Haian Fu

  15. Gene expression in colorectal cancer

    DEFF Research Database (Denmark)

    Birkenkamp-Demtroder, Karin; Christensen, Lise Lotte; Olesen, Sanne Harder

    2002-01-01

    Understanding molecular alterations in colorectal cancer (CRC) is needed to define new biomarkers and treatment targets. We used oligonucleotide microarrays to monitor gene expression of about 6,800 known genes and 35,000 expressed sequence tags (ESTs) on five pools (four to six samples in each...... pool) of total RNA from left-sided sporadic colorectal carcinomas. We compared normal tissue to carcinoma tissue from Dukes' stages A-D (noninvasive to distant metastasis) and identified 908 known genes and 4,155 ESTs that changed remarkably from normal to tumor tissue. Based on intensive filtering 226...

  16. IGF-Regulated Genes in Prostate Cancer

    National Research Council Canada - National Science Library

    Roberts, Charles

    2003-01-01

    We hypothesized that genes that are differentially expressed as a result of the decreased IGF-I receptor gene expression seen in metastatic prostate cancer contribute to prostate cancer progression...

  17. IGF-Regulated Genes in Prostate Cancer

    National Research Council Canada - National Science Library

    Roberts, Charles T., Jr

    2005-01-01

    We hypothesized that genes that are differentially expressed as a result of the decreased IGF-I receptor gene expression seen in metastatic prostate cancer contribute to prostate cancer progression...

  18. Gene therapy for lung cancer.

    Science.gov (United States)

    Toloza, Eric M; Morse, Michael A; Lyerly, H Kim

    2006-09-01

    Lung cancer patients suffer a 15% overall survival despite advances in chemotherapy, radiation therapy, and surgery. This unacceptably low survival rate is due to the usual finding of advanced disease at diagnosis. However, multimodality strategies using conventional therapies only minimally improve survival rates even in early stages of lung cancer. Attempts to improve survival in advanced disease using various combinations of platinum-based chemotherapy have demonstrated that no regimen is superior, suggesting a therapeutic plateau and the need for novel, more specific, and less toxic therapeutic strategies. Over the past three decades, the genetic etiology of cancer has been gradually delineated, albeit not yet completely. Understanding the molecular events that occur during the multistep process of bronchogenic carcinogenesis may make these tasks more surmountable. During these same three decades, techniques have been developed which allow transfer of functional genes into mammalian cells. For example, blockade of activated tumor-promoting oncogenes or replacement of inactivated tumor-suppressing or apoptosis-promoting genes can be achieved by gene therapy. This article will discuss the therapeutic implications of these molecular changes associated with bronchogenic carcinomas and will then review the status of gene therapies for treatment of lung cancer. (c) 2006 Wiley-Liss, Inc.

  19. Interactions among genes, tumor biology and the environment in cancer health disparities: examining the evidence on a national and global scale.

    Science.gov (United States)

    Wallace, Tiffany A; Martin, Damali N; Ambs, Stefan

    2011-08-01

    Cancer incidence and mortality rates show great variations across nations and between population groups. These variations are largely explained by differences in age distribution, diet and lifestyle, access to health care, cultural barriers and exposure to carcinogens and pathogens. Cancers caused by infections are significantly more common in developing than developed countries, and they overproportionally affect immigrant populations in the USA and other countries. The global pattern of cancer is not stagnant. Instead, it is dynamic because of fluctuations in the age distribution of populations, improvements in cancer prevention and early detection in affluent countries and rapid changes in diet and lifestyle in parts of the world. For example, increased smoking rates have caused tobacco-induced cancers to rise in various Asian countries, whereas reduced smoking rates have caused these cancers to plateau or even begin to decline in Western Europe and North America. Some population groups experience a disproportionally high cancer burden. In the USA and the Caribbean, cancer incidence and mortality rates are excessively high in populations of African ancestry when compared with other population groups. The causes of this disparity are multifaceted and may include tumor biological and genetic factors and their interaction with the environment. In this review, we will discuss the magnitude and causes of global cancer health disparities and will, with a focus on African-Americans and selected cancer sites, evaluate the evidence that genetic and tumor biological factors contribute to existing cancer incidence and outcome differences among population groups in the USA.

  20. Duplicability of self-interacting human genes.

    LENUS (Irish Health Repository)

    Pérez-Bercoff, Asa

    2010-01-01

    BACKGROUND: There is increasing interest in the evolution of protein-protein interactions because this should ultimately be informative of the patterns of evolution of new protein functions within the cell. One model proposes that the evolution of new protein-protein interactions and protein complexes proceeds through the duplication of self-interacting genes. This model is supported by data from yeast. We examined the relationship between gene duplication and self-interaction in the human genome. RESULTS: We investigated the patterns of self-interaction and duplication among 34808 interactions encoded by 8881 human genes, and show that self-interacting proteins are encoded by genes with higher duplicability than genes whose proteins lack this type of interaction. We show that this result is robust against the system used to define duplicate genes. Finally we compared the presence of self-interactions amongst proteins whose genes have duplicated either through whole-genome duplication (WGD) or small-scale duplication (SSD), and show that the former tend to have more interactions in general. After controlling for age differences between the two sets of duplicates this result can be explained by the time since the gene duplication. CONCLUSIONS: Genes encoding self-interacting proteins tend to have higher duplicability than proteins lacking self-interactions. Moreover these duplicate genes have more often arisen through whole-genome rather than small-scale duplication. Finally, self-interacting WGD genes tend to have more interaction partners in general in the PIN, which can be explained by their overall greater age. This work adds to our growing knowledge of the importance of contextual factors in gene duplicability.

  1. SNP-SNP interactions of three new pri-miRNAs with the target gene PGC and multidimensional analysis of H. pylori in the gastric cancer/atrophic gastritis risk in a Chinese population.

    Science.gov (United States)

    Xu, Qian; Wu, Ye-Feng; Li, Ying; He, Cai-Yun; Sun, Li-Ping; Liu, Jing-Wei; Yuan, Yuan

    2016-04-26

    Gastric cancer (GC) is a multistep complex disease involving multiple genes, and gene-gene interactions have a greater effect than a single gene in determining cancer susceptibility. This study aimed to explore the interaction of the let-7e rs8111742, miR-365b rs121224, and miR-4795 rs1002765 single nucleotide polymorphisms (SNPs) with SNPs of the predicted target gene PGC and Helicobacter pylori status in GC and atrophic gastritis (AG) risk. Three miRNA SNPs and seven PGC SNPs were detected in 2448 cases using the Sequenom MassArray platform. Two pairwise combinations of miRNA and PGC SNPs were associated with increased AG risk (let-7e rs8111742 - PGC rs6458238 and miR-4795 rs1002765 - PGC rs9471643). Singly, miR-365b rs121224 and PGC rs6912200 had no effect individually but in combination they demonstrated an epistatic interaction associated with AG risk. Similarly, let-7e rs8111742 and miR-4795 rs1002765 SNPs interacted with H. pylori infection to increase GC risk (rs8111742: Pinteraction = 0.024; rs1002765: Pinteraction = 0.031, respectively). A three-dimensional interaction analysis found miR-4795 rs1002765, PGC rs9471643, and H. pylori infection positively interacted to increase AG risk (Pinteraction = 0.027). Also, let-7e rs8111742, PGC rs6458238, and H. pylori infection positively interacted to increase GC risk (Pinteraction = 0.036). Furthermore, both of these three-dimensional interactions had a dosage-effect correspondence (Ptrend < 0.001) and were verified by MDR. In conclusion, the miRNAs SNPs (let-7e rs8111742 and miR-4795 rs1002765) might have more superior efficiency when combined with PGC SNPs and/or H. pylori for GC or AG risk than a single SNP on its own.

  2. Drug Interactions in Childhood Cancer

    Science.gov (United States)

    Haidar, Cyrine; Jeha, Sima

    2016-01-01

    Children with cancer are increasingly benefiting from novel therapeutic strategies and advances in supportive care, as reflected in improvements in both their survival and quality of life. However, the continuous emergence of new oncology drugs and supportive care agents has also increased the possibility of deleterious drug interactions and healthcare providers need to practice extreme caution when combining medications. In this review, we discuss the most common interactions of chemotherapeutic agents with supportive care drugs such as anticonvulsants, antiemetics, uric acid–lowering agents, acid suppressants, antimicrobials, and pain management medications in pediatric oncology patients. As chemotherapy agents interact not only with medications but also with foods and herbal supplements that patients receive during the course of their treatment, we also briefly review such interactions and provide recommendations to avoid unwanted and potentially fatal interactions in children with cancer. PMID:20869315

  3. Investigation of gene-environment interactions between 47 newly identified breast cancer susceptibility loci and environmental risk factors

    DEFF Research Database (Denmark)

    Rudolph, Anja; Milne, Roger L; Truong, Thérèse

    2015-01-01

    and overall BC risk was stronger for women who had had four or more pregnancies (OR = 0.85, p = 2.0 × 10(-4) ), and absent in women who had had just one (OR = 0.96, p = 0.19, pint = 6.1 × 10(-4) ). SNP rs11242675 was inversely associated with overall BC risk in never/former smokers (OR = 0.93, p = 2.8 × 10......(-5) ), but no association was observed in current smokers (OR = 1.07, p = 0.14, pint = 3.4 × 10(-4) ). In conclusion, recently identified BC susceptibility loci are not strongly modified by established risk factors and the observed potential interactions require confirmation in independent studies....

  4. Prostate Cancer Epigenetics: A Review on Gene Regulation

    Directory of Open Access Journals (Sweden)

    Lena Diaw

    2007-01-01

    Full Text Available Prostate cancer is the most common cancer in men in western countries, and its incidence is increasing steadily worldwide. Molecular changes including both genetic and epigenetic events underlying the development and progression of this disease are still not well understood. Epigenetic events are involved in gene regulation and occur through different mechanisms such as DNA methylation and histone modifi cations. Both DNA methylation and histone modifi cations affect gene regulation and play important roles either independently or by interaction in tumor initiation and progression. This review will discuss the genes associated with epigenetic alterations in prostate cancer progression: their regulation and importance as possible markers for the disease.

  5. A genetic ensemble approach for gene-gene interaction identification

    Directory of Open Access Journals (Sweden)

    Ho Joshua WK

    2010-10-01

    Full Text Available Abstract Background It has now become clear that gene-gene interactions and gene-environment interactions are ubiquitous and fundamental mechanisms for the development of complex diseases. Though a considerable effort has been put into developing statistical models and algorithmic strategies for identifying such interactions, the accurate identification of those genetic interactions has been proven to be very challenging. Methods In this paper, we propose a new approach for identifying such gene-gene and gene-environment interactions underlying complex diseases. This is a hybrid algorithm and it combines genetic algorithm (GA and an ensemble of classifiers (called genetic ensemble. Using this approach, the original problem of SNP interaction identification is converted into a data mining problem of combinatorial feature selection. By collecting various single nucleotide polymorphisms (SNP subsets as well as environmental factors generated in multiple GA runs, patterns of gene-gene and gene-environment interactions can be extracted using a simple combinatorial ranking method. Also considered in this study is the idea of combining identification results obtained from multiple algorithms. A novel formula based on pairwise double fault is designed to quantify the degree of complementarity. Conclusions Our simulation study demonstrates that the proposed genetic ensemble algorithm has comparable identification power to Multifactor Dimensionality Reduction (MDR and is slightly better than Polymorphism Interaction Analysis (PIA, which are the two most popular methods for gene-gene interaction identification. More importantly, the identification results generated by using our genetic ensemble algorithm are highly complementary to those obtained by PIA and MDR. Experimental results from our simulation studies and real world data application also confirm the effectiveness of the proposed genetic ensemble algorithm, as well as the potential benefits of

  6. Text mining in cancer gene and pathway prioritization.

    Science.gov (United States)

    Luo, Yuan; Riedlinger, Gregory; Szolovits, Peter

    2014-01-01

    Prioritization of cancer implicated genes has received growing attention as an effective way to reduce wet lab cost by computational analysis that ranks candidate genes according to the likelihood that experimental verifications will succeed. A multitude of gene prioritization tools have been developed, each integrating different data sources covering gene sequences, differential expressions, function annotations, gene regulations, protein domains, protein interactions, and pathways. This review places existing gene prioritization tools against the backdrop of an integrative Omic hierarchy view toward cancer and focuses on the analysis of their text mining components. We explain the relatively slow progress of text mining in gene prioritization, identify several challenges to current text mining methods, and highlight a few directions where more effective text mining algorithms may improve the overall prioritization task and where prioritizing the pathways may be more desirable than prioritizing only genes.

  7. A Partial Least Square Approach for Modeling Gene-gene and Gene-environment Interactions When Multiple Markers Are Genotyped

    Science.gov (United States)

    Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C.

    2008-01-01

    Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense SNPs in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches: the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey’s 1-df model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women’s Health Initiative (WHI), this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with BMI. PMID:18615621

  8. Gene panel testing for inherited cancer risk.

    Science.gov (United States)

    Hall, Michael J; Forman, Andrea D; Pilarski, Robert; Wiesner, Georgia; Giri, Veda N

    2014-09-01

    Next-generation sequencing technologies have ushered in the capability to assess multiple genes in parallel for genetic alterations that may contribute to inherited risk for cancers in families. Thus, gene panel testing is now an option in the setting of genetic counseling and testing for cancer risk. This article describes the many gene panel testing options clinically available to assess inherited cancer susceptibility, the potential advantages and challenges associated with various types of panels, clinical scenarios in which gene panels may be particularly useful in cancer risk assessment, and testing and counseling considerations. Given the potential issues for patients and their families, gene panel testing for inherited cancer risk is recommended to be offered in conjunction or consultation with an experienced cancer genetic specialist, such as a certified genetic counselor or geneticist, as an integral part of the testing process. Copyright © 2014 by the National Comprehensive Cancer Network.

  9. Double-Bottom Chaotic Map Particle Swarm Optimization Based on Chi-Square Test to Determine Gene-Gene Interactions

    Science.gov (United States)

    Yang, Cheng-Hong; Chang, Hsueh-Wei

    2014-01-01

    Gene-gene interaction studies focus on the investigation of the association between the single nucleotide polymorphisms (SNPs) of genes for disease susceptibility. Statistical methods are widely used to search for a good model of gene-gene interaction for disease analysis, and the previously determined models have successfully explained the effects between SNPs and diseases. However, the huge numbers of potential combinations of SNP genotypes limit the use of statistical methods for analysing high-order interaction, and finding an available high-order model of gene-gene interaction remains a challenge. In this study, an improved particle swarm optimization with double-bottom chaotic maps (DBM-PSO) was applied to assist statistical methods in the analysis of associated variations to disease susceptibility. A big data set was simulated using the published genotype frequencies of 26 SNPs amongst eight genes for breast cancer. Results showed that the proposed DBM-PSO successfully determined two- to six-order models of gene-gene interaction for the risk association with breast cancer (odds ratio > 1.0; P value <0.05). Analysis results supported that the proposed DBM-PSO can identify good models and provide higher chi-square values than conventional PSO. This study indicates that DBM-PSO is a robust and precise algorithm for determination of gene-gene interaction models for breast cancer. PMID:24895547

  10. CCDB: a curated database of genes involved in cervix cancer.

    Science.gov (United States)

    Agarwal, Subhash M; Raghav, Dhwani; Singh, Harinder; Raghava, G P S

    2011-01-01

    The Cervical Cancer gene DataBase (CCDB, http://crdd.osdd.net/raghava/ccdb) is a manually curated catalog of experimentally validated genes that are thought, or are known to be involved in the different stages of cervical carcinogenesis. In spite of the large women population that is presently affected from this malignancy still at present, no database exists that catalogs information on genes associated with cervical cancer. Therefore, we have compiled 537 genes in CCDB that are linked with cervical cancer causation processes such as methylation, gene amplification, mutation, polymorphism and change in expression level, as evident from published literature. Each record contains details related to gene like architecture (exon-intron structure), location, function, sequences (mRNA/CDS/protein), ontology, interacting partners, homology to other eukaryotic genomes, structure and links to other public databases, thus augmenting CCDB with external data. Also, manually curated literature references have been provided to support the inclusion of the gene in the database and establish its association with cervix cancer. In addition, CCDB provides information on microRNA altered in cervical cancer as well as search facility for querying, several browse options and an online tool for sequence similarity search, thereby providing researchers with easy access to the latest information on genes involved in cervix cancer.

  11. Artificial neural network-based exploration of gene-nutrient interactions in folate and xenobiotic metabolic pathways that modulate susceptibility to breast cancer.

    Science.gov (United States)

    Naushad, Shaik Mohammad; Ramaiah, M Janaki; Pavithrakumari, Manickam; Jayapriya, Jaganathan; Hussain, Tajamul; Alrokayan, Salman A; Gottumukkala, Suryanarayana Raju; Digumarti, Raghunadharao; Kutala, Vijay Kumar

    2016-04-15

    In the current study, an artificial neural network (ANN)-based breast cancer prediction model was developed from the data of folate and xenobiotic pathway genetic polymorphisms along with the nutritional and demographic variables to investigate how micronutrients modulate susceptibility to breast cancer. The developed ANN model explained 94.2% variability in breast cancer prediction. Fixed effect models of folate (400 μg/day) and B12 (6 μg/day) showed 33.3% and 11.3% risk reduction, respectively. Multifactor dimensionality reduction analysis showed the following interactions in responders to folate: RFC1 G80A × MTHFR C677T (primary), COMT H108L × CYP1A1 m2 (secondary), MTR A2756G (tertiary). The interactions among responders to B12 were RFC1G80A × cSHMT C1420T and CYP1A1 m2 × CYP1A1 m4. ANN simulations revealed that increased folate might restore ER and PR expression and reduce the promoter CpG island methylation of extra cellular superoxide dismutase and BRCA1. Dietary intake of folate appears to confer protection against breast cancer through its modulating effects on ER and PR expression and methylation of EC-SOD and BRCA1. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. Progress in Gene Therapy for Prostate Cancer

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Kamran A.; Davis, Brian J. [Department of Radiation Oncology, Mayo Clinic, Rochester, MN (United States); Wilson, Torrence M. [Department of Urology, Mayo Clinic, Rochester, MN (United States); Wiseman, Gregory A. [Division of Nuclear Medicine, Mayo Clinic, Rochester, MN (United States); Federspiel, Mark J. [Department of Molecular Medicine, Mayo Clinic, Rochester, MN (United States); Morris, John C., E-mail: davis.brian@mayo.edu [Division of Endocrinology, Mayo Clinic, Rochester, MN (United States)

    2012-11-19

    Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.

  13. Progress in Gene Therapy for Prostate Cancer

    International Nuclear Information System (INIS)

    Ahmed, Kamran A.; Davis, Brian J.; Wilson, Torrence M.; Wiseman, Gregory A.; Federspiel, Mark J.; Morris, John C.

    2012-01-01

    Gene therapy has held promise to correct various disease processes. Prostate cancer represents the second leading cause of cancer death in American men. A number of clinical trials involving gene therapy for the treatment of prostate cancer have been reported. The ability to efficiently transduce tumors with effective levels of therapeutic genes has been identified as a fundamental barrier to effective cancer gene therapy. The approach utilizing gene therapy in prostate cancer patients at our institution attempts to address this deficiency. The sodium-iodide symporter (NIS) is responsible for the ability of the thyroid gland to transport and concentrate iodide. The characteristics of the NIS gene suggest that it could represent an ideal therapeutic gene for cancer therapy. Published results from Mayo Clinic researchers have indicated several important successes with the use of the NIS gene and prostate gene therapy. Studies have demonstrated that transfer of the human NIS gene into prostate cancer using adenovirus vectors in vitro and in vivo results in efficient uptake of radioactive iodine and significant tumor growth delay with prolongation of survival. Preclinical successes have culminated in the opening of a phase I trial for patients with advanced prostate disease which is currently accruing patients. Further study will reveal the clinical promise of NIS gene therapy in the treatment of prostate as well as other malignancies.

  14. Novel interactions between vertebrate Hox genes

    NARCIS (Netherlands)

    Hooiveld, MHW; Morgan, R; Rieden, PID; Houtzager, E; Pannese, M; Damen, K; Boncinelli, E; Durston, AJ

    1999-01-01

    Understanding why metazoan Hox/HOM-C genes are expressed in spatiotemporal sequences showing colinearity with their genomic sequence is a central challenge in developmental biology. Here, we studied the consequences of ectopically expressing Hox genes to investigate whether Hox-Hox interactions

  15. Cancer suicide gene therapy: a patent review.

    Science.gov (United States)

    Navarro, Saúl Abenhamar; Carrillo, Esmeralda; Griñán-Lisón, Carmen; Martín, Ana; Perán, Macarena; Marchal, Juan Antonio; Boulaiz, Houria

    2016-09-01

    Cancer is considered the second leading cause of death worldwide despite the progress made in early detection and advances in classical therapies. Advancing in the fight against cancer requires the development of novel strategies, and the suicide gene transfer to tumor cells is providing new possibilities for cancer therapy. In this manuscript, authors present an overview of suicide gene systems and the latest innovations done to enhance cancer suicide gene therapy strategies by i) improving vectors for targeted gene delivery using tissue specific promoter and receptors; ii) modification of the tropism; and iii) combining suicide genes and/or classical therapies for cancer. Finally, the authors highlight the main challenges to be addressed in the future. Even if many efforts are needed for suicide gene therapy to be a real alternative for cancer treatment, we believe that the significant progress made in the knowledge of cancer biology and characterization of cancer stem cells accompanied by the development of novel targeted vectors will enhance the effectiveness of this type of therapeutic strategy. Moreover, combined with current treatments, suicide gene therapy will improve the clinical outcome of patients with cancer in the future.

  16. Polymorphisms in genes involved in the inflammatory response and interaction with NSAID use or smoking in relation to lung cancer risk in a prospective study

    DEFF Research Database (Denmark)

    Vogel, Ulla; Christensen, Jane; Wallin, Håkan

    2007-01-01

    polymorphism and factors, which modify an inflammatory response, such as smoking status, duration, and intensity, and use of NSAID. The functional SNPs IL-1B T-31C, IL6 G-174C, IL8 T-251A, IL10 C-592T, COX2 C8473T, COX2 A-1195G and PPARgamma2 Pro(12)Ala were included. A case-cohort study including 428 lung...... cases. There was interaction between IL-1B T-31C, COX-2 A-1195G and PPARgamma2 Pro(12)Ala and NSAID use in relation to lung cancer risk. For the two latter, NSAID use was only associated with a lower cancer risk among homozygous wild type allele carriers. p for interaction was 3x10(-6) for COX-2 A-1195G...... and 9x10(-5) for PPARgamma2 Pro(12)Ala. The results suggest that NSAID use may modify risk of lung cancer differently depending on the genotype. Udgivelsesdato: 2008-Mar-1...

  17. Polymorphisms in genes involved in the inflammatory response and interaction with NSAID use or smoking in relation to lung cancer risk in a prospective study

    DEFF Research Database (Denmark)

    Vogel, Ulla; Christensen, Jane; Wallin, Håkan

    2008-01-01

    polymorphism and factors, which modify an inflammatory response, such as smoking status, duration, and intensity, and use of NSAID. The functional SNPs IL-1B T-31C, IL6 G-174C, IL8 T-251A, IL10 C-592T, COX2 C8473T, COX2 A-1195G and PPARgamma2 Pro(12)Ala were included. A case-cohort study including 428 lung...... cases. There was interaction between IL-1B T-31C, COX-2 A-1195G and PPARgamma2 Pro(12)Ala and NSAID use in relation to lung cancer risk. For the two latter, NSAID use was only associated with a lower cancer risk among homozygous wild type allele carriers. p for interaction was 3 x 10(-6) for COX-2 A......-1195G and 9 x 10(-5) for PPARgamma2 Pro(12)Ala. The results suggest that NSAID use may modify risk of lung cancer differently depending on the genotype....

  18. Polymorphisms in genes related to activation or detoxification of carcinogens might interact with smoking to increase renal cancer risk: Results from The Netherlands Cohort Study on diet and cancer

    NARCIS (Netherlands)

    Smits, K.M.; Schouten, L.J.; Dijk, B.A.C. van; Houwelingen, K. van; Hulsbergen-Kaa, C.A. van de; Kiemeney, L.A.L.M.; Houwelingen, K. van; Goldbohm, R.A.; Oosterwijk, E.; Brandt, P.A. van den

    2008-01-01

    Metabolic gene polymorphisms have previously been suggested as risk factors for renal cell carcinoma (RCC). These polymorphisms are involved in activation or detoxification of carcinogens in cigarette smoke which is another RCC risk factor. We evaluated gene-environment interactions between CYP1A1,

  19. Endocrine aspects of cancer gene therapy.

    Science.gov (United States)

    Barzon, Luisa; Boscaro, Marco; Palù, Giorgio

    2004-02-01

    The field of cancer gene therapy is in continuous expansion, and technology is quickly moving ahead as far as gene targeting and regulation of gene expression are concerned. This review focuses on the endocrine aspects of gene therapy, including the possibility to exploit hormone and hormone receptor functions for regulating therapeutic gene expression, the use of endocrine-specific genes as new therapeutic tools, the effects of viral vector delivery and transgene expression on the endocrine system, and the endocrine response to viral vector delivery. Present ethical concerns of gene therapy and the risk of germ cell transduction are also discussed, along with potential lines of innovation to improve cell and gene targeting.

  20. Human cancer protein-protein interaction network: a structural perspective.

    Directory of Open Access Journals (Sweden)

    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  1. Association of Allelic Interaction of Single Nucleotide Polymorphisms of Influx and Efflux Transporters Genes With Nonhematologic Adverse Events of Docetaxel in Breast Cancer Patients.

    Science.gov (United States)

    Jabir, Rafid Salim; Ho, Gwo Fuang; Annuar, Muhammad Azrif Bin Ahmad; Stanslas, Johnson

    2018-05-04

    Nonhematologic adverse events (AEs) of docetaxel constitute an extra burden in the treatment of cancer patients and necessitate either a dose reduction or an outright switch of docetaxel for other regimens. These AEs are frequently associated with genetic polymorphisms of genes encoding for proteins involved docetaxel disposition. Therefore, we investigated that association in Malaysian breast cancer patients. A total of 110 Malaysian breast cancer patients were enrolled in the present study, and their blood samples were investigated for different single nucleotide polymorphisms using polymerase chain reaction restriction fragment length polymorphism. AEs were evaluated using the Common Terminology Criteria for Adverse Events, version 4.0. Fatigue, nausea, oral mucositis, and vomiting were the most common nonhematologic AEs. Rash was associated with heterozygous and mutant genotypes of ABCB1 3435C>T (P A/T reported more fatigue than those carrying the heterozygous genotype GA (P T polymorphism could be a potential predictive biomarker of docetaxel-induced rash, and homozygous wild-type ABCB1 2677G>A/T might predict for a greater risk of fatigue. In addition, the concurrent presence of specific alleles could be predictive of vomiting, nausea, and oral mucositis. Copyright © 2018 Elsevier Inc. All rights reserved.

  2. Comparative modeling and docking studies of p16ink4/Cyclin D1/Rb pathway genes in lung cancer revealed functionally interactive residue of RB1 and its functional partner E2F1

    Directory of Open Access Journals (Sweden)

    e Zahra Syeda Naqsh

    2013-01-01

    Full Text Available Abstract Background Lung cancer is the major cause of mortality worldwide. Major signalling pathways that could play significant role in lung cancer therapy include (1 Growth promoting pathways (Epidermal Growth Factor Receptor/Ras/ PhosphatidylInositol 3-Kinase (2 Growth inhibitory pathways (p53/Rb/P14ARF, STK11 (3 Apoptotic pathways (Bcl-2/Bax/Fas/FasL. Insilico strategy was implemented to solve the mystery behind selected lung cancer pathway by applying comparative modeling and molecular docking studies. Results YASARA [v 12.4.1] was utilized to predict structural models of P16-INK4 and RB1 genes using template 4ELJ-A and 1MX6-B respectively. WHAT CHECK evaluation tool demonstrated overall quality of predicted P16-INK4 and RB1 with Z-score of −0.132 and −0.007 respectively which showed a strong indication of reliable structure prediction. Protein-protein interactions were explored by utilizing STRING server, illustrated that CDK4 and E2F1 showed strong interaction with P16-INK4 and RB1 based on confidence score of 0.999 and 0.999 respectively. In order to facilitate a comprehensive understanding of the complex interactions between candidate genes with their functional interactors, GRAMM-X server was used. Protein-protein docking investigation of P16-INK4 revealed four ionic bonds illustrating Arg47, Arg80,Cys72 and Met1 residues as actively participating in interactions with CDK4 while docking results of RB1 showed four hydrogen bonds involving Glu864, Ser567, Asp36 and Arg861 residues which interact strongly with its respective functional interactor E2F1. Conclusion This research may provide a basis for understanding biological insights of P16-INK4 and RB1 proteins which will be helpful in future to design a suitable drug to inhibit the disease pathogenesis as we have determined the interacting amino acids which can be targeted in order to design a ligand in-vitro to propose a drug for clinical trials. Protein -protein docking of

  3. Network graph analysis of gene-gene interactions in genome-wide association study data.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2012-12-01

    Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  4. Methylated genes as new cancer biomarkers.

    LENUS (Irish Health Repository)

    Duffy, M J

    2012-02-01

    Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested that measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2 for predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene methylation need to be standardised, simplified and evaluated in external quality assurance programmes. It is concluded that methylated genes have the potential to provide a new generation of cancer biomarkers.

  5. The prediction of candidate genes for cervix related cancer through gene ontology and graph theoretical approach.

    Science.gov (United States)

    Hindumathi, V; Kranthi, T; Rao, S B; Manimaran, P

    2014-06-01

    With rapidly changing technology, prediction of candidate genes has become an indispensable task in recent years mainly in the field of biological research. The empirical methods for candidate gene prioritization that succors to explore the potential pathway between genetic determinants and complex diseases are highly cumbersome and labor intensive. In such a scenario predicting potential targets for a disease state through in silico approaches are of researcher's interest. The prodigious availability of protein interaction data coupled with gene annotation renders an ease in the accurate determination of disease specific candidate genes. In our work we have prioritized the cervix related cancer candidate genes by employing Csaba Ortutay and his co-workers approach of identifying the candidate genes through graph theoretical centrality measures and gene ontology. With the advantage of the human protein interaction data, cervical cancer gene sets and the ontological terms, we were able to predict 15 novel candidates for cervical carcinogenesis. The disease relevance of the anticipated candidate genes was corroborated through a literature survey. Also the presence of the drugs for these candidates was detected through Therapeutic Target Database (TTD) and DrugMap Central (DMC) which affirms that they may be endowed as potential drug targets for cervical cancer.

  6. SNP-SNP interactions in breast cancer susceptibility

    International Nuclear Information System (INIS)

    Onay, Venüs Ümmiye; Ozcelik, Hilmi; Briollais, Laurent; Knight, Julia A; Shi, Ellen; Wang, Yuanyuan; Wells, Sean; Li, Hong; Rajendram, Isaac; Andrulis, Irene L

    2006-01-01

    Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2) are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs) are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination. In an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR) principle. None of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP) interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082)A]), cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val]), cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln]), and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val]) pathways. The importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their biological interactions through SNPs have not been described

  7. SNP-SNP interactions in breast cancer susceptibility

    Directory of Open Access Journals (Sweden)

    Wang Yuanyuan

    2006-05-01

    Full Text Available Abstract Background Breast cancer predisposition genes identified to date (e.g., BRCA1 and BRCA2 are responsible for less than 5% of all breast cancer cases. Many studies have shown that the cancer risks associated with individual commonly occurring single nucleotide polymorphisms (SNPs are incremental. However, polygenic models suggest that multiple commonly occurring low to modestly penetrant SNPs of cancer related genes might have a greater effect on a disease when considered in combination. Methods In an attempt to identify the breast cancer risk conferred by SNP interactions, we have studied 19 SNPs from genes involved in major cancer related pathways. All SNPs were genotyped by TaqMan 5'nuclease assay. The association between the case-control status and each individual SNP, measured by the odds ratio and its corresponding 95% confidence interval, was estimated using unconditional logistic regression models. At the second stage, two-way interactions were investigated using multivariate logistic models. The robustness of the interactions, which were observed among SNPs with stronger functional evidence, was assessed using a bootstrap approach, and correction for multiple testing based on the false discovery rate (FDR principle. Results None of these SNPs contributed to breast cancer risk individually. However, we have demonstrated evidence for gene-gene (SNP-SNP interaction among these SNPs, which were associated with increased breast cancer risk. Our study suggests cross talk between the SNPs of the DNA repair and immune system (XPD-[Lys751Gln] and IL10-[G(-1082A], cell cycle and estrogen metabolism (CCND1-[Pro241Pro] and COMT-[Met108/158Val], cell cycle and DNA repair (BARD1-[Pro24Ser] and XPD-[Lys751Gln], and within carcinogen metabolism (GSTP1-[Ile105Val] and COMT-[Met108/158Val] pathways. Conclusion The importance of these pathways and their communication in breast cancer predisposition has been emphasized previously, but their

  8. A Classification Framework Applied to Cancer Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Hussein Hijazi

    2013-01-01

    Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

  9. P-MartCancer-Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets.

    Science.gov (United States)

    Webb-Robertson, Bobbie-Jo M; Bramer, Lisa M; Jensen, Jeffrey L; Kobold, Markus A; Stratton, Kelly G; White, Amanda M; Rodland, Karin D

    2017-11-01

    P-MartCancer is an interactive web-based software environment that enables statistical analyses of peptide or protein data, quantitated from mass spectrometry-based global proteomics experiments, without requiring in-depth knowledge of statistical programming. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification, and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access and the capability to analyze multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium at the peptide, gene, and protein levels. P-MartCancer is deployed as a web service (https://pmart.labworks.org/cptac.html), alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/). Cancer Res; 77(21); e47-50. ©2017 AACR . ©2017 American Association for Cancer Research.

  10. PTH Gene Polymorphism and Breast Cancer Risk in Kazakhstan

    Directory of Open Access Journals (Sweden)

    Nurgul Sikhayeva

    2014-12-01

    Full Text Available Introduction. Breast cancer is the most common type of cancer among women. In Kazakhstan, breast cancer holds first place among causes of women death caused by cancer in the 45-55 year age group . Many studies have shown that the risk of acquiring breast cancer may be related to the level of calcium in the blood serum. One of the important regulators of calcium metabolism in the body is the parathyroid hormone. Single nucleotide polymorphisms in the gene encoding the parathyroid hormone (PTH are associated with breast cancer development risk, and may modify the associative interaction between the levels of calcium intake and breast cancer. Experimental studies have shown that PTH gene has a carcinogenic effect. At least three studies showed a weak positive correlation between the risk of acquiring breast cancer and primary hyperparathyroidism, a state with high levels of PTH and often high levels of calcium. The aim of this investigation was to evaluate potential association between PTH gene polymorphism and breast cancer risk among Kazakhstani women.Methods. Female breast cancer patients (n = 429 and matched control women (n = 373 were recruited into a case – control study,. Genomic DNA was extracted from peripheral venous blood of study participants using Wizard® Genomic DNA Purification Kit (Promega, USA. Detection of PTH gene polymorphism (rs1459015 was done by means of the TaqMan® SNP Genotyping Assay of real-time PCR. Statistical analysis was conducted using SPSS 19.0.Results. PTH gene alleles were in Hardy–Weinberg equilibrium (p > 0.05. Distribution was 59% CC, 35% CT, 6% TT in the group with breast cancer and 50% CC, 43% CT, 6% TT in the control group. Total difference (between the group with breast cancer and the control group in allele frequencies for PTH polymorphism was not significant (p > 0.05. No association was found between rs1459015 TT and breast cancer risk (OR = 1.039; 95%, CI 0.740 - 1.297; p = 0.893.Conclusion. We

  11. Gene Delivery for Metastatic Prostate Cancer Cells

    National Research Council Canada - National Science Library

    Pang, Shen

    2001-01-01

    .... Enhanced by the bystander effect, the specific expression of the DTA gene causes significant cell death in prostate cancer cell cultures, with very low background cell eradication in control cell lines...

  12. Inflammatory Gene Polymorphisms in Lung Cancer Susceptibility.

    Science.gov (United States)

    Eaton, Keith D; Romine, Perrin E; Goodman, Gary E; Thornquist, Mark D; Barnett, Matt J; Petersdorf, Effie W

    2018-05-01

    Chronic inflammation has been implicated in carcinogenesis, with increasing evidence of its role in lung cancer. We aimed to evaluate the role of genetic polymorphisms in inflammation-related genes in the risk for development of lung cancer. A nested case-control study design was used, and 625 cases and 625 well-matched controls were selected from participants in the β-Carotene and Retinol Efficacy Trial, which is a large, prospective lung cancer chemoprevention trial. The association between lung cancer incidence and survival and 23 polymorphisms descriptive of 11 inflammation-related genes (interferon gamma gene [IFNG], interleukin 10 gene [IL10], interleukin 1 alpha gene [IL1A], interleukin 1 beta gene [IL1B], interleukin 2 gene [IL2], interleukin 4 receptor gene [IL4R], interleukin 4 gene [IL4], interleukin 6 gene [IL6], prostaglandin-endoperoxide synthase 2 gene [PTGS2] (also known as COX2), transforming growth factor beta 1 gene [TGFB1], and tumor necrosis factor alpha gene [TNFA]) was evaluated. Of the 23 polymorphisms, two were associated with risk for lung cancer. Compared with individuals with the wild-type (CC) variant, individuals carrying the minor allele variants of the IL-1β-511C>T promoter polymorphism (rs16944) (CT and TT) had decreased odds of lung cancer (OR = 0.74, [95% confidence interval (CI): 0.58-0.94] and OR = 0.71 [95% CI: 0.50-1.01], respectively, p = 0.03). Similar results were observed for the IL-1β-1464 C>G promoter polymorphism (rs1143623), with presence of the minor variants CG and CC having decreased odds of lung cancer (OR = 0.75 [95% CI: 0.59-0.95] and OR = 0.69 [95% CI: 0.46-1.03], respectively, p = 0.03). Survival was not influenced by genotype. This study provides further evidence that IL1B promoter polymorphisms may modulate the risk for development of lung cancer. Copyright © 2018 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

  13. Interactions between diet, lifestyle and IL10, IL1B, and PTGS2/COX-2 gene polymorphisms in relation to risk of colorectal cancer in a prospective Danish case-cohort study.

    Directory of Open Access Journals (Sweden)

    Vibeke Andersen

    Full Text Available BACKGROUND & AIMS: Diet contributes to colorectal cancer development and may be potentially modified. We wanted to identify the biological mechanisms underlying colorectal carcinogenesis by assessment of diet-gene interactions. METHODS: The polymorphisms IL10 C-592A (rs1800872, C-rs3024505-T, IL1b C-3737T (rs4848306, G-1464C (rs1143623, T-31C (rs1143627 and PTGS2 (encoding COX-2 A-1195G (rs689466, G-765C (rs20417, and T8473C (rs5275 were assessed in relation to risk of colorectal cancer (CRC and interaction with diet (red meat, fish, fibre, cereals, fruit and vegetables and lifestyle (non-steroid-anti-inflammatory drug use and smoking status was assessed in a nested case-cohort study of nine hundred and seventy CRC cases and 1789 randomly selected participants from a prospective study of 57,053 persons. RESULTS: IL1b C-3737T, G-1464C and PTGS2 T8473C variant genotypes were associated with risk of CRC compared to the homozygous wildtype genotype (IRR=0.81, 95%CI: 0.68-0.97, p=0.02, and IRR=1.22, 95%CI: 1.04-1.44, p=0.02, IRR=0.75, 95%CI: 0.57-0.99, p=0.04, respectively. Interactions were found between diet and IL10 rs3024505 (P-value for interaction (P(int; meat=0.04, fish=0.007, fibre=0.0008, vegetables=0.0005, C-592A (P(int; fibre=0.025, IL1b C-3737T (Pint; vegetables=0.030, NSAID use=0.040 and PTGS2 genotypes G-765C (P(int; meat=0.006, fibre=0.0003, fruit 0.004, and T8473C (P(int; meat 0.049, fruit=0.03 and A-1195G (P(int; meat 0.038, fibre 0.040, fruit=0.059, vegetables=0.025, and current smoking=0.046. CONCLUSIONS: Genetically determined low COX-2 and high IL-1β activity were associated with increased risk of CRC in this northern Caucasian cohort. Furthermore, interactions were found between IL10, IL1b, and PTGS2 and diet and lifestyle factors in relation to CRC. The present study demonstrates that gene-environment interactions may identify genes and environmental factors involved in colorectal carcinogenesis.

  14. Identifying candidate driver genes by integrative ovarian cancer genomics data

    Science.gov (United States)

    Lu, Xinguo; Lu, Jibo

    2017-08-01

    Integrative analysis of molecular mechanics underlying cancer can distinguish interactions that cannot be revealed based on one kind of data for the appropriate diagnosis and treatment of cancer patients. Tumor samples exhibit heterogeneity in omics data, such as somatic mutations, Copy Number Variations CNVs), gene expression profiles and so on. In this paper we combined gene co-expression modules and mutation modulators separately in tumor patients to obtain the candidate driver genes for resistant and sensitive tumor from the heterogeneous data. The final list of modulators identified are well known in biological processes associated with ovarian cancer, such as CCL17, CACTIN, CCL16, CCL22, APOB, KDF1, CCL11, HNF1B, LRG1, MED1 and so on, which can help to facilitate the discovery of biomarkers, molecular diagnostics, and drug discovery.

  15. GSNFS: Gene subnetwork biomarker identification of lung cancer expression data.

    Science.gov (United States)

    Doungpan, Narumol; Engchuan, Worrawat; Chan, Jonathan H; Meechai, Asawin

    2016-12-05

    Gene expression has been used to identify disease gene biomarkers, but there are ongoing challenges. Single gene or gene-set biomarkers are inadequate to provide sufficient understanding of complex disease mechanisms and the relationship among those genes. Network-based methods have thus been considered for inferring the interaction within a group of genes to further study the disease mechanism. Recently, the Gene-Network-based Feature Set (GNFS), which is capable of handling case-control and multiclass expression for gene biomarker identification, has been proposed, partly taking into account of network topology. However, its performance relies on a greedy search for building subnetworks and thus requires further improvement. In this work, we establish a new approach named Gene Sub-Network-based Feature Selection (GSNFS) by implementing the GNFS framework with two proposed searching and scoring algorithms, namely gene-set-based (GS) search and parent-node-based (PN) search, to identify subnetworks. An additional dataset is used to validate the results. The two proposed searching algorithms of the GSNFS method for subnetwork expansion are concerned with the degree of connectivity and the scoring scheme for building subnetworks and their topology. For each iteration of expansion, the neighbour genes of a current subnetwork, whose expression data improved the overall subnetwork score, is recruited. While the GS search calculated the subnetwork score using an activity score of a current subnetwork and the gene expression values of its neighbours, the PN search uses the expression value of the corresponding parent of each neighbour gene. Four lung cancer expression datasets were used for subnetwork identification. In addition, using pathway data and protein-protein interaction as network data in order to consider the interaction among significant genes were discussed. Classification was performed to compare the performance of the identified gene subnetworks with three

  16. The bystander effect of cancer gene therapy

    International Nuclear Information System (INIS)

    Lumniczky, K.; Safrany, G.

    2008-01-01

    Cancer gene therapy is a new, promising therapeutic agent. In the clinic, it should be used in combination with existing modalities, such as tumour irradiation. First, we summarise the most important fields of cancer gene therapy: gene directed enzyme pro-drug therapy; the activation of an anti-tumour immune attack; restoration of the wild type p53 status; the application of new, replication competent and oncolytic viral vectors; tumour specific, as well as radiation- and hypoxia-induced gene expression. Special emphasizes are put on the combined effect of these modalities with local tumour irradiation. Using the available vector systems, only a small portion of the cancer cells will contain the therapeutic genes under therapeutic situations. Bystander cell killing might contribute to the success of various gene therapy protocols. We summarise the evidences that lethal bystander effects may occur during cancer gene therapy. Bystander effects are especially important in the gene directed enzyme pro-drug therapy. There, bystander cell killing might have different routes: cell communication through gap junction intercellular contacts; release of toxic metabolites into the neighbourhood or to larger distances; phagocytosis of apoptotic bodies; and the activation of the immune system. Bystander cell killing can be enhanced by the introduction of gap junction proteins into the cells, by further activating the immune system with immune-stimulatory molecules, or by introducing genes into the cells that help the transfer of cytotoxic genes and / or metabolites into the bystander cells. In conclusion, there should be additional improvements in cancer gene therapy for the more efficient clinical application. (orig.)

  17. The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

    Directory of Open Access Journals (Sweden)

    Frank eEmmert-Streib

    2014-02-01

    Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

  18. Theranostic Imaging of Cancer Gene Therapy.

    Science.gov (United States)

    Sekar, Thillai V; Paulmurugan, Ramasamy

    2016-01-01

    Gene-directed enzyme prodrug therapy (GDEPT) is a promising therapeutic approach for treating cancers of various phenotypes. This strategy is independent of various other chemotherapeutic drugs used for treating cancers where the drugs are mainly designed to target endogenous cellular mechanisms, which are different in various cancer subtypes. In GDEPT an external enzyme, which is different from the cellular proteins, is expressed to convert the injected prodrug in to a toxic metabolite, that normally kill cancer cells express this protein. Theranostic imaging is an approach used to directly monitor the expression of these gene therapy enzymes while evaluating therapeutic effect. We recently developed a dual-GDEPT system where we combined mutant human herpes simplex thymidine kinase (HSV1sr39TK) and E. coli nitroreductase (NTR) enzyme, to improve therapeutic efficiency of cancer gene therapy by simultaneously injecting two prodrugs at a lower dose. In this approach we use two different prodrugs such as ganciclovir (GCV) and CB1954 to target two different cellular mechanisms to kill cancer cells. The developed dual GDEPT system was highly efficacious than that of either of the system used independently. In this chapter, we describe the complete protocol involved for in vitro and in vivo imaging of therapeutic cancer gene therapy evaluation.

  19. Gene-based interaction analysis shows GABAergic genes interacting with parenting in adolescent depressive symptoms

    NARCIS (Netherlands)

    Van Assche, Evelien; Moons, Tim; Cinar, Ozan; Viechtbauer, Wolfgang; Oldehinkel, Albertine J.; Van Leeuwen, Karla; Verschueren, Karine; Colpin, Hilde; Lambrechts, Diether; Van den Noortgate, Wim; Goossens, Luc; Claes, Stephan; van Winkel, Ruud

    2017-01-01

    BACKGROUND: Most gene-environment interaction studies (G × E) have focused on single candidate genes. This approach is criticized for its expectations of large effect sizes and occurrence of spurious results. We describe an approach that accounts for the polygenic nature of most psychiatric

  20. Gene-Lifestyle Interactions in Obesity.

    Science.gov (United States)

    van Vliet-Ostaptchouk, Jana V; Snieder, Harold; Lagou, Vasiliki

    2012-01-01

    Obesity is a complex multifaceted disease resulting from interactions between genetics and lifestyle. The proportion of phenotypic variance ascribed to genetic variance is 0.4 to 0.7 for obesity and recent years have seen considerable success in identifying disease-susceptibility variants. Although with the advent of genome-wide association studies the list of genetic variants predisposing to obesity has significantly increased the identified variants only explain a fraction of disease heritability. Studies of gene-environment interactions can provide more insight into the biological mechanisms involved in obesity despite the challenges associated with such designs. Epigenetic changes that affect gene function without DNA sequence modifications may be a key factor explaining interindividual differences in obesity, with both genetic and environmental factors influencing the epigenome. Disentangling the relative contributions of genetic, environmental and epigenetic marks to the establishment of obesity is a major challenge given the complex interplay between these determinants.

  1. Finding gene-environment interactions for Phobias

    OpenAIRE

    Gregory, Alice M.; Lau, Jennifer Y. F.; Eley, Thalia C.

    2008-01-01

    Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G × E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G × Es for phobias. In addition to the careful concep...

  2. Gene expression analysis identifies global gene dosage sensitivity in cancer

    DEFF Research Database (Denmark)

    Fehrmann, Rudolf S. N.; Karjalainen, Juha M.; Krajewska, Malgorzata

    2015-01-01

    Many cancer-associated somatic copy number alterations (SCNAs) are known. Currently, one of the challenges is to identify the molecular downstream effects of these variants. Although several SCNAs are known to change gene expression levels, it is not clear whether each individual SCNA affects gen...

  3. Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

    Directory of Open Access Journals (Sweden)

    Sungyoung Lee

    2012-12-01

    Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  4. A model of gene-gene and gene-environment interactions and its implications for targeting environmental interventions by genotype

    Directory of Open Access Journals (Sweden)

    Wallace Helen M

    2006-10-01

    Full Text Available Abstract Background The potential public health benefits of targeting environmental interventions by genotype depend on the environmental and genetic contributions to the variance of common diseases, and the magnitude of any gene-environment interaction. In the absence of prior knowledge of all risk factors, twin, family and environmental data may help to define the potential limits of these benefits in a given population. However, a general methodology to analyze twin data is required because of the potential importance of gene-gene interactions (epistasis, gene-environment interactions, and conditions that break the 'equal environments' assumption for monozygotic and dizygotic twins. Method A new model for gene-gene and gene-environment interactions is developed that abandons the assumptions of the classical twin study, including Fisher's (1918 assumption that genes act as risk factors for common traits in a manner necessarily dominated by an additive polygenic term. Provided there are no confounders, the model can be used to implement a top-down approach to quantifying the potential utility of genetic prediction and prevention, using twin, family and environmental data. The results describe a solution space for each disease or trait, which may or may not include the classical twin study result. Each point in the solution space corresponds to a different model of genotypic risk and gene-environment interaction. Conclusion The results show that the potential for reducing the incidence of common diseases using environmental interventions targeted by genotype may be limited, except in special cases. The model also confirms that the importance of an individual's genotype in determining their risk of complex diseases tends to be exaggerated by the classical twin studies method, owing to the 'equal environments' assumption and the assumption of no gene-environment interaction. In addition, if phenotypes are genetically robust, because of epistasis

  5. DDPC: Dragon database of genes associated with prostate cancer

    KAUST Repository

    Maqungo, Monique

    2010-09-29

    Prostate cancer (PC) is one of the most commonly diagnosed cancers in men. PC is relatively difficult to diagnose due to a lack of clear early symptoms. Extensive research of PC has led to the availability of a large amount of data on PC. Several hundred genes are implicated in different stages of PC, which may help in developing diagnostic methods or even cures. In spite of this accumulated information, effective diagnostics and treatments remain evasive. We have developed Dragon Database of Genes associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise require tedious computational analyses, (ii) it integrates data on molecular interactions, pathways, gene ontologies, gene regulation at molecular level, predicted transcription factor binding sites on promoters of PC implicated genes and transcription factors that correspond to these binding sites and (iii) it contains DrugBank data on drugs associated with PC. We believe this resource will serve as a source of useful information for research on PC. DDPC is freely accessible for academic and non-profit users via http://apps.sanbi.ac.za/ddpc/ and http://cbrc .kaust.edu.sa/ddpc/. The Author(s) 2010.

  6. Dietary methyl donors, methyl metabolizing enzymes, and epigenetic regulators: Diet-gene interactions and promoter CpG island hypermethylation in colorectal cancer

    NARCIS (Netherlands)

    Vogel, S. de; Wouters, K.A.D.; Gottschalk, R.W.H.; Schooten, F.J. van; Goeij, A.F.P.M. de; Bruïne, A.P. de; Goldbohm, R.A.; Brandt, P.A. van den; Engeland, M. van; Weijenberg, M.P.

    2011-01-01

    Dietary methyl donors might influence DNA methylation during carcinogenesis of colorectal cancer (CRC). Among 609 CRC cases and 1,663 subcohort members of the Netherlands Cohort Study on diet and cancer (n = 120,852), we estimated CRC risk according to methyl donor intake across genotypes of folate

  7. Methylated genes as new cancer biomarkers

    DEFF Research Database (Denmark)

    Brunner, Nils; Duffy, M.J; Napieralski, R.

    2009-01-01

    Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested that meas......Aberrant hypermethylation of promoter regions in specific genes is a key event in the formation and progression of cancer. In at least some situations, these aberrant alterations occur early in the formation of malignancy and appear to be tumour specific. Multiple reports have suggested...... that measurement of the methylation status of the promoter regions of specific genes can aid early detection of cancer, determine prognosis and predict therapy responses. Promising DNA methylation biomarkers include the use of methylated GSTP1 for aiding the early diagnosis of prostate cancer, methylated PITX2...... for predicting outcome in lymph node-negative breast cancer patients and methylated MGMT in predicting benefit from alkylating agents in patients with glioblastomas. However, prior to clinical utilisation, these findings require validation in prospective clinical studies. Furthermore, assays for measuring gene...

  8. FGF receptor genes and breast cancer susceptibility

    DEFF Research Database (Denmark)

    Agarwal, D; Pineda, S; Michailidou, K

    2014-01-01

    Background:Breast cancer is one of the most common malignancies in women. Genome-wide association studies have identified FGFR2 as a breast cancer susceptibility gene. Common variation in other fibroblast growth factor (FGF) receptors might also modify risk. We tested this hypothesis by studying...... genotyped single-nucleotide polymorphisms (SNPs) and imputed SNPs in FGFR1, FGFR3, FGFR4 and FGFRL1 in the Breast Cancer Association Consortium.Methods:Data were combined from 49 studies, including 53 835 cases and 50 156 controls, of which 89 050 (46 450 cases and 42 600 controls) were of European ancestry......, 12 893 (6269 cases and 6624 controls) of Asian and 2048 (1116 cases and 932 controls) of African ancestry. Associations with risk of breast cancer, overall and by disease sub-type, were assessed using unconditional logistic regression.Results:Little evidence of association with breast cancer risk...

  9. Finding gene-environment interactions for phobias.

    Science.gov (United States)

    Gregory, Alice M; Lau, Jennifer Y F; Eley, Thalia C

    2008-03-01

    Phobias are common disorders causing a great deal of suffering. Studies of gene-environment interaction (G x E) have revealed much about the complex processes underlying the development of various psychiatric disorders but have told us little about phobias. This article describes what is already known about genetic and environmental influences upon phobias and suggests how this information can be used to optimise the chances of discovering G x Es for phobias. In addition to the careful conceptualisation of new studies, it is suggested that data already collected should be re-analysed in light of increased understanding of processes influencing phobias.

  10. Clinical adenoviral gene therapy for prostate cancer

    Czech Academy of Sciences Publication Activity Database

    Schenk, E.; Essand, M.; Bangma, Ch. H.; Barber, Ch.; Behr, J.-P.; Briggs, S.; Carlisle, R.; Cheng, W.-S.; Danielsson, A.; Dautzenberg, I. J. C.; Dzojic, H.; Erbacher, P.; Fisher, K.; Frazier, A.; Georgopoulos, L. J.; Hoeben, R.; Kochanek, S.; Koppers-Lalic, D.; Kraaij, R.; Kreppel, F.; Lindholm, L.; Magnusson, M.; Maitland, N.; Neuberg, P.; Nilsson, B.; Ogris, M.; Remy, J.-S.; Scaife, M.; Schooten, E.; Seymour, L.; Totterman, T.; Uil, T. G.; Ulbrich, Karel; Veldhoven-Zweistra, J. L. M.; de Vrij, J.; van Weerden, W.; Wagner, E.; Willemsen, R.

    2010-01-01

    Roč. 21, č. 7 (2010), s. 807-813 ISSN 1043-0342 EU Projects: European Commission(XE) 512087 - GIANT Keywords : adenovirus * gene delivery * prostate cancer Subject RIV: CD - Macromolecular Chemistry Impact factor: 4.829, year: 2010

  11. Gene expression in early stage cervical cancer

    NARCIS (Netherlands)

    Biewenga, Petra; Buist, Marrije R.; Moerland, Perry D.; van Thernaat, Emiel Ver Loren; van Kampen, Antoine H. C.; ten Kate, Fiebo J. W.; Baas, Frank

    2008-01-01

    Objective. Pelvic lymph node metastases are the main prognostic factor for survival in early stage cervical cancer, yet accurate detection methods before surgery are lacking. In this study, we examined whether gene expression profiling can predict the presence of lymph node metastasis in early stage

  12. Gene expression patterns combined with network analysis identify hub genes associated with bladder cancer.

    Science.gov (United States)

    Bi, Dongbin; Ning, Hao; Liu, Shuai; Que, Xinxiang; Ding, Kejia

    2015-06-01

    To explore molecular mechanisms of bladder cancer (BC), network strategy was used to find biomarkers for early detection and diagnosis. The differentially expressed genes (DEGs) between bladder carcinoma patients and normal subjects were screened using empirical Bayes method of the linear models for microarray data package. Co-expression networks were constructed by differentially co-expressed genes and links. Regulatory impact factors (RIF) metric was used to identify critical transcription factors (TFs). The protein-protein interaction (PPI) networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and clusters were obtained through molecular complex detection (MCODE) algorithm. Centralities analyses for complex networks were performed based on degree, stress and betweenness. Enrichment analyses were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Co-expression networks and TFs (based on expression data of global DEGs and DEGs in different stages and grades) were identified. Hub genes of complex networks, such as UBE2C, ACTA2, FABP4, CKS2, FN1 and TOP2A, were also obtained according to analysis of degree. In gene enrichment analyses of global DEGs, cell adhesion, proteinaceous extracellular matrix and extracellular matrix structural constituent were top three GO terms. ECM-receptor interaction, focal adhesion, and cell cycle were significant pathways. Our results provide some potential underlying biomarkers of BC. However, further validation is required and deep studies are needed to elucidate the pathogenesis of BC. Copyright © 2015 Elsevier Ltd. All rights reserved.

  13. A partial least-square approach for modeling gene-gene and gene-environment interactions when multiple markers are genotyped.

    Science.gov (United States)

    Wang, Tao; Ho, Gloria; Ye, Kenny; Strickler, Howard; Elston, Robert C

    2009-01-01

    Genetic association studies achieve an unprecedented level of resolution in mapping disease genes by genotyping dense single nucleotype polymorphisms (SNPs) in a gene region. Meanwhile, these studies require new powerful statistical tools that can optimally handle a large amount of information provided by genotype data. A question that arises is how to model interactions between two genes. Simply modeling all possible interactions between the SNPs in two gene regions is not desirable because a greatly increased number of degrees of freedom can be involved in the test statistic. We introduce an approach to reduce the genotype dimension in modeling interactions. The genotype compression of this approach is built upon the information on both the trait and the cross-locus gametic disequilibrium between SNPs in two interacting genes, in such a way as to parsimoniously model the interactions without loss of useful information in the process of dimension reduction. As a result, it improves power to detect association in the presence of gene-gene interactions. This approach can be similarly applied for modeling gene-environment interactions. We compare this method with other approaches, the corresponding test without modeling any interaction, that based on a saturated interaction model, that based on principal component analysis, and that based on Tukey's one-degree-of-freedom model. Our simulations suggest that this new approach has superior power to that of the other methods. In an application to endometrial cancer case-control data from the Women's Health Initiative, this approach detected AKT1 and AKT2 as being significantly associated with endometrial cancer susceptibility by taking into account their interactions with body mass index.

  14. Nonviral Delivery Systems For Cancer Gene Therapy: Strategies And Challenges.

    Science.gov (United States)

    Shim, Gayong; Kim, Dongyoon; Le, Quoc-Viet; Park, Gyu Thae; Kwon, Taekhyun; Oh, Yu-Kyoung

    2018-01-19

    Gene therapy has been receiving widespread attention due to its unique advantage in regulating the expression of specific target genes. In the field of cancer gene therapy, modulation of gene expression has been shown to decrease oncogenic factors in cancer cells or increase immune responses against cancer. Due to the macromolecular size and highly negative physicochemical features of plasmid DNA, efficient delivery systems are an essential ingredient for successful gene therapy. To date, a variety of nanostructures and materials have been studied as nonviral gene delivery systems. In this review, we will cover nonviral delivery strategies for cancer gene therapy, with a focus on target cancer genes and delivery materials. Moreover, we will address current challenges and perspectives for nonviral delivery-based cancer gene therapeutics. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  15. Research progress in machine learning methods for gene-gene interaction detection.

    Science.gov (United States)

    Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu

    2018-03-20

    Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.

  16. Environmental and genetic interactions in human cancer

    International Nuclear Information System (INIS)

    Paterson, M.C.

    Humans, depending upon their genetic make-up, differ in their susceptibility to the cancer-causing effects of extrinsic agents. Clinical and laboratory studies on the hereditary disorder, ataxia telangiectasia (AT) show that persons afflicted with this are cancer-prone and unusually sensitive to conventional radiotherapy. Their skin cells, when cultured, are hypersensitive to killing by ionizing radiation, being defective in the enzymatic repair of radiation-induced damange to the genetic material, deoxyribonucleic acid (DNA). This molecular finding implicates DNA damage and its imperfect repair as an early step in the induction of human cancer by radiation and other carcinogens. The parents of AT patients are clincally normal but their cultured cells are often moderately radiosensitive. The increased radiosensitivity of cultured cells offers a means of identifying a presumed cancer-prone subpopulation that should avoid undue exposure to certain carcinogens. The radioresponse of cells from patients with other cancer-associated genetic disorders and persons suspected of being genetically predisposed to radiation-induced cancer has also been measured. Increased cell killing by γ-rays appears in the complex genetic disease, tuberous sclerosis. Cells from cancer-stricken members of a leukemia-prone family are also radiosensitive, as are cells from one patient with radiation-associated breast cancer. These radiobiological data, taken together, strongly suggest that genetic factors can interact with extrinsic agents and thereby play a greater causative role in the development of common cancers in man than previously thought. (L.L.)

  17. Systematically characterizing and prioritizing chemosensitivity related gene based on Gene Ontology and protein interaction network

    Directory of Open Access Journals (Sweden)

    Chen Xin

    2012-10-01

    Full Text Available Abstract Background The identification of genes that predict in vitro cellular chemosensitivity of cancer cells is of great importance. Chemosensitivity related genes (CRGs have been widely utilized to guide clinical and cancer chemotherapy decisions. In addition, CRGs potentially share functional characteristics and network features in protein interaction networks (PPIN. Methods In this study, we proposed a method to identify CRGs based on Gene Ontology (GO and PPIN. Firstly, we documented 150 pairs of drug-CCRG (curated chemosensitivity related gene from 492 published papers. Secondly, we characterized CCRGs from the perspective of GO and PPIN. Thirdly, we prioritized CRGs based on CCRGs’ GO and network characteristics. Lastly, we evaluated the performance of the proposed method. Results We found that CCRG enriched GO terms were most often related to chemosensitivity and exhibited higher similarity scores compared to randomly selected genes. Moreover, CCRGs played key roles in maintaining the connectivity and controlling the information flow of PPINs. We then prioritized CRGs using CCRG enriched GO terms and CCRG network characteristics in order to obtain a database of predicted drug-CRGs that included 53 CRGs, 32 of which have been reported to affect susceptibility to drugs. Our proposed method identifies a greater number of drug-CCRGs, and drug-CCRGs are much more significantly enriched in predicted drug-CRGs, compared to a method based on the correlation of gene expression and drug activity. The mean area under ROC curve (AUC for our method is 65.2%, whereas that for the traditional method is 55.2%. Conclusions Our method not only identifies CRGs with expression patterns strongly correlated with drug activity, but also identifies CRGs in which expression is weakly correlated with drug activity. This study provides the framework for the identification of signatures that predict in vitro cellular chemosensitivity and offers a valuable

  18. Behavioral science and the study of gene-nutrition and gene-physical activity interactions in obesity research.

    Science.gov (United States)

    Faith, Myles S

    2008-12-01

    This report summarizes emerging opportunities for behavioral science to help advance the field of gene-environment and gene-behavior interactions, based on presentations at The National Cancer Institute (NCI) Workshop, "Gene-Nutrition and Gene-Physical Activity Interactions in the Etiology of Obesity." Three opportunities are highlighted: (i) designing potent behavioral "challenges" in experiments, (ii) determining viable behavioral phenotypes for genetics studies, and (iii) identifying specific measures of the environment or environmental exposures. Additional points are underscored, including the need to incorporate novel findings from neuroimaging studies regarding motivation and drive for eating and physical activity. Advances in behavioral science theory and methods can play an important role in advancing understanding of gene-brain-behavior relationships in obesity onset.

  19. Interactions between epigenetics and metabolism in cancers

    International Nuclear Information System (INIS)

    Yun, Jihye; Johnson, Jared L.; Hanigan, Christin L.; Locasale, Jason W.

    2012-01-01

    Cancer progression is accompanied by widespread transcriptional changes and metabolic alterations. While it is widely accepted that the origin of cancer can be traced to the mutations that accumulate over time, relatively recent evidence favors a similarly fundamental role for alterations in the epigenome during tumorigenesis. Changes in epigenetics that arise from post-translational modifications of histones and DNA are exploited by cancer cells to upregulate and/or downregulate the expression levels of oncogenes and tumor suppressors, respectively. Although the mechanisms behind these modifications, in particular how they lead to gene silencing and activation, are still being understood, most of the enzymatic machinery of epigenetics require metabolites as substrates or cofactors. As a result, their activities can be influenced by the metabolic state of the cell. The purpose of this review is to give an overview of cancer epigenetics and metabolism and provide examples of where they converge.

  20. Interactions between epigenetics and metabolism in cancers

    Directory of Open Access Journals (Sweden)

    Jihye eYun

    2012-11-01

    Full Text Available Cancer progression is accompanied by widespread transcriptional changes and metabolic alterations. Although it is widely accepted that the origin of cancer can be traced to the mutations that accumulate over time, relatively recent evidence favors a similarly fundamental role for alterations in the epigenome during tumorigenesis. Changes in epigenetics that arise from post-translational modifications of histones and DNA, are exploited by cancer cells to upregulate and/or downregulate the expression levels of oncogenes and tumor suppressors, respectively. Although the mechanisms behind these modifications, in particular how they lead to gene silencing and activation, are still being understood, many enzymes that carry out post-translational modifications that alter epigenetics require metabolites as substrates or cofactors. As a result, their activities can be influenced by the metabolic state of the cell. The purpose of this review is to give an overview of cancer epigenetics and metabolism and provide examples of where they converge.

  1. Gene-particulate matter-health interactions

    International Nuclear Information System (INIS)

    Kleeberger, Steven R.; Ohtsuka, Yoshinori

    2005-01-01

    Inter-individual variation in human responses to air pollutants suggests that some subpopulations are at increased risk to the detrimental effects of pollutant exposure. Extrinsic factors such as previous exposure and nutritional status may influence individual susceptibility. Intrinsic (host) factors that determine susceptibility include age, gender, and pre-existing disease (e.g., asthma), and it is becoming clear that genetic background also contributes to individual susceptibility. Environmental exposures to particulates and genetic factors associated with disease risk likely interact in a complex fashion that varies from one population and one individual to another. The relationships between genetic background and disease risk and severity are often evaluated through traditional family-based linkage studies and positional cloning techniques. However, case-control studies based on association of disease or disease subphenotypes with candidate genes have advantages over family pedigree studies for complex disease phenotypes. This is based in part on continued development of quantitative analysis and the discovery and availability of simple sequence repeats and single nucleotide polymorphisms. Linkage analyses with genetically standardized animal models also provide a useful tool to identify genetic determinants of responses to environmental pollutants. These approaches have identified significant susceptibility quantitative trait loci on mouse chromosomes 1, 6, 11, and 17. Physical mapping and comparative mapping between human and mouse genomes will yield candidate susceptibility genes that may be tested by association studies in human subjects. Human studies and mouse modeling will provide important insight to understanding genetic factors that contribute to differential susceptibility to air pollutants

  2. Gene-gene interactions and gene polymorphisms of VEGFA and EG-VEGF gene systems in recurrent pregnancy loss.

    Science.gov (United States)

    Su, Mei-Tsz; Lin, Sheng-Hsiang; Chen, Yi-Chi; Kuo, Pao-Lin

    2014-06-01

    Both vascular endothelial growth factor A (VEGFA) and endocrine gland-derived vascular endothelial growth factor (EG-VEGF) systems play major roles in angiogenesis. A body of evidence suggests VEGFs regulate critical processes during pregnancy and have been associated with recurrent pregnancy loss (RPL). However, little information is available regarding the interaction of these two major major angiogenesis-related systems in early human pregnancy. This study was conducted to investigate the association of gene polymorphisms and gene-gene interaction among genes in VEGFA and EG-VEGF systems and idiopathic RPL. A total of 98 women with history of idiopathic RPL and 142 controls were included, and 5 functional SNPs selected from VEGFA, KDR, EG-VEGF (PROK1), PROKR1 and PROKR2 were genotyped. We used multifactor dimensionality reduction (MDR) analysis to choose a best model and evaluate gene-gene interactions. Ingenuity pathways analysis (IPA) was introduced to explore possible complex interactions. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL (P<0.01). The MDR test revealed that the KDR (Q472H) polymorphism was the best loci to be associated with RPL (P=0.02). IPA revealed EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3 signaling pathways. Two receptor gene polymorphisms [KDR (Q472H) and PROKR2 (V331M)] were significantly associated with idiopathic RPL. EG-VEGF and VEGFA systems shared several canonical signaling pathways that may contribute to gene-gene interactions, including the Akt, IL-8, EGFR, MAPK, SRC, VHL, HIF-1A and STAT3.

  3. Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3

    Directory of Open Access Journals (Sweden)

    Lund Eiliv

    2009-07-01

    Full Text Available Abstract Background Gonadotropin releasing hormone (GNRH1 triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3. Methods We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs were genotyped and used to identify haplotype-tagging SNPs (htSNPS in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II, European Prospective Investigation on Cancer and Nutrition (EPIC, Multiethnic Cohort (MEC, Nurses' Health Study (NHS, and Women's Health Study (WHS. Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone were also measured in 4713 study subjects. Results Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. Conclusion Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians.

  4. Genetic polymorphisms of the GNRH1 and GNRHR genes and risk of breast cancer in the National Cancer Institute Breast and Prostate Cancer Cohort Consortium (BPC3)

    International Nuclear Information System (INIS)

    Canzian, Federico; Calle, Eugenia E; Chanock, Stephen; Clavel-Chapelon, Francoise; Dossus, Laure; Feigelson, Heather Spencer; Haiman, Christopher A; Hankinson, Susan E; Hoover, Robert; Hunter, David J; Isaacs, Claudine; Kaaks, Rudolf; Lenner, Per; Lund, Eiliv; Overvad, Kim; Palli, Domenico; Pearce, Celeste Leigh; Quiros, Jose R; Riboli, Elio; Stram, Daniel O; Thomas, Gilles; Thun, Michael J; Cox, David G; Trichopoulos, Dimitrios; Gils, Carla H van; Ziegler, Regina G; Henderson, Katherine D; Henderson, Brian E; Berg, Christine; Bingham, Sheila; Boeing, Heiner; Buring, Julie

    2009-01-01

    Gonadotropin releasing hormone (GNRH1) triggers the release of follicle stimulating hormone and luteinizing hormone from the pituitary. Genetic variants in the gene encoding GNRH1 or its receptor may influence breast cancer risk by modulating production of ovarian steroid hormones. We studied the association between breast cancer risk and polymorphisms in genes that code for GNRH1 and its receptor (GNRHR) in the large National Cancer Institute Breast and Prostate Cancer Cohort Consortium (NCI-BPC3). We sequenced exons of GNRH1 and GNRHR in 95 invasive breast cancer cases. Resulting single nucleotide polymorphisms (SNPs) were genotyped and used to identify haplotype-tagging SNPs (htSNPS) in a panel of 349 healthy women. The htSNPs were genotyped in 5,603 invasive breast cancer cases and 7,480 controls from the Cancer Prevention Study-II (CPS-II), European Prospective Investigation on Cancer and Nutrition (EPIC), Multiethnic Cohort (MEC), Nurses' Health Study (NHS), and Women's Health Study (WHS). Circulating levels of sex steroids (androstenedione, estradiol, estrone and testosterone) were also measured in 4713 study subjects. Breast cancer risk was not associated with any polymorphism or haplotype in the GNRH1 and GNRHR genes, nor were there any statistically significant interactions with known breast cancer risk factors. Polymorphisms in these two genes were not strongly associated with circulating hormone levels. Common variants of the GNRH1 and GNRHR genes are not associated with risk of invasive breast cancer in Caucasians

  5. Discovery of cancer common and specific driver gene sets

    Science.gov (United States)

    2017-01-01

    Abstract Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found. PMID:28168295

  6. Evaluation of candidate stromal epithelial cross-talk genes identifies association between risk of serous ovarian cancer and TERT, a cancer susceptibility "hot-spot"

    DEFF Research Database (Denmark)

    Johnatty, Sharon E; Beesley, Jonathan; Chen, Xiaoqing

    2010-01-01

    We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes...

  7. Evaluation of candidate stromal epithelial cross-talk genes identifies association between risk of serous ovarian cancer and TERT, a cancer susceptibility "hot-spot"

    DEFF Research Database (Denmark)

    Johnatty, Sharon E; Beesley, Jonathan; Chen, Xiaoqing

    2010-01-01

    We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs) in 173 genes in...

  8. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Science.gov (United States)

    Naderi, Elnaz; Mostafaei, Mehdi; Pourshams, Akram

    2014-01-01

    Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches. PMID:24895587

  9. Network of microRNAs-mRNAs Interactions in Pancreatic Cancer

    Directory of Open Access Journals (Sweden)

    Elnaz Naderi

    2014-01-01

    Full Text Available Background. MicroRNAs are small RNA molecules that regulate the expression of certain genes through interaction with mRNA targets and are mainly involved in human cancer. This study was conducted to make the network of miRNAs-mRNAs interactions in pancreatic cancer as the fourth leading cause of cancer death. Methods. 56 miRNAs that were exclusively expressed and 1176 genes that were downregulated or silenced in pancreas cancer were extracted from beforehand investigations. MiRNA–mRNA interactions data analysis and related networks were explored using MAGIA tool and Cytoscape 3 software. Functional annotations of candidate genes in pancreatic cancer were identified by DAVID annotation tool. Results. This network is made of 217 nodes for mRNA, 15 nodes for miRNA, and 241 edges that show 241 regulations between 15 miRNAs and 217 target genes. The miR-24 was the most significantly powerful miRNA that regulated series of important genes. ACVR2B, GFRA1, and MTHFR were significant target genes were that downregulated. Conclusion. Although the collected previous data seems to be a treasure trove, there was no study simultaneous to analysis of miRNAs and mRNAs interaction. Network of miRNA-mRNA interactions will help to corroborate experimental remarks and could be used to refine miRNA target predictions for developing new therapeutic approaches.

  10. A review for detecting gene-gene interactions using machine learning methods in genetic epidemiology.

    Science.gov (United States)

    Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed

    2013-01-01

    Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  11. A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer

    Directory of Open Access Journals (Sweden)

    Mary Qu Yang

    Full Text Available Clear cell renal cell carcinoma (ccRCC is the most common and most aggressive form of renal cell cancer (RCC. The incidence of RCC has increased steadily in recent years. The pathogenesis of renal cell cancer remains poorly understood. Many of the tumor suppressor genes, oncogenes, and dysregulated pathways in ccRCC need to be revealed for improvement of the overall clinical outlook of the disease. Here, we developed a systems biology approach to prioritize the somatic mutated genes that lead to dysregulation of pathways in ccRCC. The method integrated multi-layer information to infer causative mutations and disease genes. First, we identified differential gene modules in ccRCC by coupling transcriptome and protein-protein interactions. Each of these modules consisted of interacting genes that were involved in similar biological processes and their combined expression alterations were significantly associated with disease type. Then, subsequent gene module-based eQTL analysis revealed somatic mutated genes that had driven the expression alterations of differential gene modules. Our study yielded a list of candidate disease genes, including several known ccRCC causative genes such as BAP1 and PBRM1, as well as novel genes such as NOD2, RRM1, CSRNP1, SLC4A2, TTLL1 and CNTN1. The differential gene modules and their driver genes revealed by our study provided a new perspective for understanding the molecular mechanisms underlying the disease. Moreover, we validated the results in independent ccRCC patient datasets. Our study provided a new method for prioritizing disease genes and pathways. Keywords: ccRCC, Causative mutation, Pathways, Protein-protein interaction, Gene module, eQTL

  12. Expression of KLK2 gene in prostate cancer

    Directory of Open Access Journals (Sweden)

    Sajad Shafai

    2018-01-01

    Conclusion: The expression of KLK2 gene in people with prostate cancer is the higher than the healthy person; finally, according to the results, it could be mentioned that the KLK2 gene considered as a useful factor in prostate cancer, whose expression is associated with progression and development of the prostate cancer.

  13. Human synthetic lethal inference as potential anti-cancer target gene detection

    Directory of Open Access Journals (Sweden)

    Solé Ricard V

    2009-12-01

    Full Text Available Abstract Background Two genes are called synthetic lethal (SL if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases as well as on existent approved drugs (DrugBank database supports our selection of cancer-therapy candidates. Conclusions Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.

  14. Identification of human disease genes from interactome network using graphlet interaction.

    Directory of Open Access Journals (Sweden)

    Xiao-Dong Wang

    Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

  15. Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

    Science.gov (United States)

    Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

    2014-01-01

    Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

  16. xSyn: A Software Tool for Identifying Sophisticated 3-Way Interactions From Cancer Expression Data

    Directory of Open Access Journals (Sweden)

    Baishali Bandyopadhyay

    2017-08-01

    Full Text Available Background: Constructing gene co-expression networks from cancer expression data is important for investigating the genetic mechanisms underlying cancer. However, correlation coefficients or linear regression models are not able to model sophisticated relationships among gene expression profiles. Here, we address the 3-way interaction that 2 genes’ expression levels are clustered in different space locations under the control of a third gene’s expression levels. Results: We present xSyn, a software tool for identifying such 3-way interactions from cancer gene expression data based on an optimization procedure involving the usage of UPGMA (Unweighted Pair Group Method with Arithmetic Mean and synergy. The effectiveness is demonstrated by application to 2 real gene expression data sets. Conclusions: xSyn is a useful tool for decoding the complex relationships among gene expression profiles. xSyn is available at http://www.bdxconsult.com/xSyn.html .

  17. Hormonal Involvement in Breast Cancer Gene Amplification

    Science.gov (United States)

    2010-10-01

    been shown to induce DN A amplification in yeast (Gopalakrishnan et al., 2001; Nguy en et al., 2001; Green et al., 2006) an d increased Cdt1 results in...re-replication in human cells (Dorn et al., 2008). The N- terminus of Cdt1 is important for re-replication, perhaps through interactions with PCNA...evolution of a cancer genome. Genome Res. (Epub. Dec. 3, 2008). Harris TD, Buzby PR, Babcock H, Beer E, Bowers J, Bras lavsky I, Causey M

  18. In silico analysis of SNPs of SYK gene Involved in Oral Cancer

    Directory of Open Access Journals (Sweden)

    Sarita Swain

    2017-12-01

    Full Text Available Oral cancer is the sixth most common cancer in the world. Oral cancer is the cancer of the oral cavity and pharynx, including cancer of the lip, tongue, salivary glands, gum, floor and other areas of the mouth. The aim of the study is to identify SNPs using dbSNP and predict the effect of mutation using Predict SNP. The association of genes is done by STRING. The disease and drugs associated with the genes are obtained from Webgestalt. The prediction of binding site is done by CASTp. The interaction of ligand and protein is done by using Autodock and Visualised through Discovery studio, pymol, Ligplot. From this report we found that oral cancer differs from person to person based on their genes and genetic interactions and expressions which recommend the clinicians to go for personalized medicine rather that generalized medicine for the patients with oral cancer. Seeking the importance of genetic background of oral cancer patients further studies can be done by mining of non-synonymous SNPs associated with genes for causing oral cancer.

  19. Suicide genes or p53 gene and p53 target genes as targets for cancer gene therapy by ionizing radiation

    International Nuclear Information System (INIS)

    Liu Bing; Chinese Academy of Sciences, Beijing; Zhang Hong

    2005-01-01

    Radiotherapy has some disadvantages due to the severe side-effect on the normal tissues at a curative dose of ionizing radiation (IR). Similarly, as a new developing approach, gene therapy also has some disadvantages, such as lack of specificity for tumors, limited expression of therapeutic gene, potential biological risk. To certain extent, above problems would be solved by the suicide genes or p53 gene and its target genes therapies targeted by ionizing radiation. This strategy not only makes up the disadvantage from radiotherapy or gene therapy alone, but also promotes success rate on the base of lower dose. By present, there have been several vectors measuring up to be reaching clinical trials. This review focused on the development of the cancer gene therapy through suicide genes or p53 and its target genes mediated by IR. (authors)

  20. FunGeneNet: a web tool to estimate enrichment of functional interactions in experimental gene sets.

    Science.gov (United States)

    Tiys, Evgeny S; Ivanisenko, Timofey V; Demenkov, Pavel S; Ivanisenko, Vladimir A

    2018-02-09

    Estimation of functional connectivity in gene sets derived from genome-wide or other biological experiments is one of the essential tasks of bioinformatics. A promising approach for solving this problem is to compare gene networks built using experimental gene sets with random networks. One of the resources that make such an analysis possible is CrossTalkZ, which uses the FunCoup database. However, existing methods, including CrossTalkZ, do not take into account individual types of interactions, such as protein/protein interactions, expression regulation, transport regulation, catalytic reactions, etc., but rather work with generalized types characterizing the existence of any connection between network members. We developed the online tool FunGeneNet, which utilizes the ANDSystem and STRING to reconstruct gene networks using experimental gene sets and to estimate their difference from random networks. To compare the reconstructed networks with random ones, the node permutation algorithm implemented in CrossTalkZ was taken as a basis. To study the FunGeneNet applicability, the functional connectivity analysis of networks constructed for gene sets involved in the Gene Ontology biological processes was conducted. We showed that the method sensitivity exceeds 0.8 at a specificity of 0.95. We found that the significance level of the difference between gene networks of biological processes and random networks is determined by the type of connections considered between objects. At the same time, the highest reliability is achieved for the generalized form of connections that takes into account all the individual types of connections. By taking examples of the thyroid cancer networks and the apoptosis network, it is demonstrated that key participants in these processes are involved in the interactions of those types by which these networks differ from random ones. FunGeneNet is a web tool aimed at proving the functionality of networks in a wide range of sizes of

  1. Evolutionary Origins of Cancer Driver Genes and Implications for Cancer Prognosis.

    Science.gov (United States)

    Chu, Xin-Yi; Jiang, Ling-Han; Zhou, Xiong-Hui; Cui, Ze-Jia; Zhang, Hong-Yu

    2017-07-14

    The cancer atavistic theory suggests that carcinogenesis is a reverse evolution process. It is thus of great interest to explore the evolutionary origins of cancer driver genes and the relevant mechanisms underlying the carcinogenesis. Moreover, the evolutionary features of cancer driver genes could be helpful in selecting cancer biomarkers from high-throughput data. In this study, through analyzing the cancer endogenous molecular networks, we revealed that the subnetwork originating from eukaryota could control the unlimited proliferation of cancer cells, and the subnetwork originating from eumetazoa could recapitulate the other hallmarks of cancer. In addition, investigations based on multiple datasets revealed that cancer driver genes were enriched in genes originating from eukaryota, opisthokonta, and eumetazoa. These results have important implications for enhancing the robustness of cancer prognosis models through selecting the gene signatures by the gene age information.

  2. New genes linked to lung cancer susceptibility in Asian women

    Science.gov (United States)

    An international group of scientists has identified three genes that predispose Asian women who have never smoked to lung cancer. The discovery of specific genetic variations, which have not previously been associated with lung cancer risk in other popul

  3. Animal models of gene-environment interactions in schizophrenia.

    Science.gov (United States)

    Ayhan, Yavuz; Sawa, Akira; Ross, Christopher A; Pletnikov, Mikhail V

    2009-12-07

    The pathogenesis of schizophrenia and related mental illnesses likely involves multiple interactions between susceptibility genes of small effects and environmental factors. Gene-environment interactions occur across different stages of neurodevelopment to produce heterogeneous clinical and pathological manifestations of the disease. The main obstacle for mechanistic studies of gene-environment interplay has been the paucity of appropriate experimental systems for elucidating the molecular pathways that mediate gene-environment interactions relevant to schizophrenia. Recent advances in psychiatric genetics and a plethora of experimental data from animal studies allow us to suggest a new approach to gene-environment interactions in schizophrenia. We propose that animal models based on identified genetic mutations and measurable environment factors will help advance studies of the molecular mechanisms of gene-environment interplay.

  4. Sperm competition, immunity, selfish genes and cancer.

    Science.gov (United States)

    Lewis, Z; Price, T A R; Wedell, N

    2008-10-01

    Sperm competition is widespread and has played an important role in shaping male reproductive characters such as testis size and numbers of sperm produced, and this is reflected in the rapid evolution of many reproductive genes. Additionally, sperm competition has been implicated in the rapid evolution of seminal fluids. However, our understanding of the molecular basis of many traits thought to be important in sperm competition is rudimentary. Furthermore, links between sperm competition and a range of issues not directly related to reproduction are only just beginning to be explored. These include associations between sperm competition and selfish genes, immunity and diseases such as cancer.We briefly review these topics and suggest areas we consider worthy of additional research.

  5. Cancer gene therapy with targeted adenoviruses.

    Science.gov (United States)

    Bachtarzi, Houria; Stevenson, Mark; Fisher, Kerry

    2008-11-01

    Clinical experience with adenovirus vectors has highlighted the need for improved delivery and targeting. This manuscript aims to provide an overview of the techniques currently under development for improving adenovirus delivery to malignant cells in vivo. Primary research articles reporting improvements in adenoviral gene delivery are described. Strategies include genetic modification of viral coat proteins, non-genetic modifications including polymer encapsulation approaches and pharmacological interventions. Reprogramming adenovirus tropism in vitro has been convincingly demonstrated using a range of genetic and physical strategies. These studies have provided new insights into our understanding of virology and the field is progressing. However, there are still some limitations that need special consideration before adenovirus-targeted cancer gene therapy emerges as a routine treatment in the clinical setting.

  6. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Science.gov (United States)

    Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

    2014-01-01

    The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  7. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Chihyun Park

    Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  8. A Novel Functional Screen for New Breast Cancer Genes

    National Research Council Canada - National Science Library

    King, Mary-Claire; Welcsh, Piri L

    2005-01-01

    Genetic instability is a hallmark of tumor development. Mechanisms for maintenance of genomic stability are heterogeneous and identification of the genes responsible a critical goal of cancer biologists...

  9. Predictability of Genetic Interactions from Functional Gene Modules

    Directory of Open Access Journals (Sweden)

    Jonathan H. Young

    2017-02-01

    Full Text Available Characterizing genetic interactions is crucial to understanding cellular and organismal response to gene-level perturbations. Such knowledge can inform the selection of candidate disease therapy targets, yet experimentally determining whether genes interact is technically nontrivial and time-consuming. High-fidelity prediction of different classes of genetic interactions in multiple organisms would substantially alleviate this experimental burden. Under the hypothesis that functionally related genes tend to share common genetic interaction partners, we evaluate a computational approach to predict genetic interactions in Homo sapiens, Drosophila melanogaster, and Saccharomyces cerevisiae. By leveraging knowledge of functional relationships between genes, we cross-validate predictions on known genetic interactions and observe high predictive power of multiple classes of genetic interactions in all three organisms. Additionally, our method suggests high-confidence candidate interaction pairs that can be directly experimentally tested. A web application is provided for users to query genes for predicted novel genetic interaction partners. Finally, by subsampling the known yeast genetic interaction network, we found that novel genetic interactions are predictable even when knowledge of currently known interactions is minimal.

  10. Association of -330 interleukin-2 gene polymorphism with oral cancer.

    Science.gov (United States)

    Singh, Prithvi Kumar; Kumar, Vijay; Ahmad, Mohammad Kaleem; Gupta, Rajni; Mahdi, Abbas Ali; Jain, Amita; Bogra, Jaishri; Chandra, Girish

    2017-12-01

    Cytokines play an important role in the development of cancer. Several single-nucleotide polymorphisms (SNPs) of cytokine genes have been reported to be associated with the development and severity of inflammatory diseases and cancer predisposition. This study was undertaken to evaluate a possible association of interleukin 2 (IL-2) (- 330A>C) gene polymorphisms with the susceptibility to oral cancer. The SNP in IL-2 (-330A>C) gene was genotyped in 300 oral cancer patients and in similar number of healthy volunteers by polymerase chain reaction (PCR)-restriction fragment length polymorphism and the association of the gene with the disease was evaluated. IL-2 (-330A>C) gene polymorphism was significantly associated with oral cancer whereas it was neither associated with clinicopathological status nor with cancer pain. The AC heterozygous genotype was significantly associated with oral cancer patients as compared to controls [odds ratio (OR): 3.0; confidence interval (CI): 2.14-4.20; Poral cancer (OR: 1.80; CI: 1.39-2.33; PC) gene polymorphism was also associated with oral cancer in tobacco smokers and chewers. Our results showed that oral cancer patients had significantly higher frequency of AA genotype but significantly lower frequency of AC genotype and C allele compared to controls. The IL-2 AC genotype and C allele of IL-2 (-330A>C) gene polymorphisms could be potential protective factors and might reduce the risk of oral cancer in Indian population.

  11. Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

    Directory of Open Access Journals (Sweden)

    Hua-Sheng Chiu

    2018-04-01

    Full Text Available Summary: Long noncoding RNAs (lncRNAs are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes by modeling their effects on the activity of transcription factors, RNA-binding proteins, and microRNAs in 5,185 TCGA tumors and 1,019 ENCODE assays. Our predictions included hundreds of candidate onco- and tumor-suppressor lncRNAs (cancer lncRNAs whose somatic alterations account for the dysregulation of dozens of cancer genes and pathways in each of 14 tumor contexts. To demonstrate proof of concept, we showed that perturbations targeting OIP5-AS1 (an inferred tumor suppressor and TUG1 and WT1-AS (inferred onco-lncRNAs dysregulated cancer genes and altered proliferation of breast and gynecologic cancer cells. Our analysis indicates that, although most lncRNAs are dysregulated in a tumor-specific manner, some, including OIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergistically dysregulate cancer pathways in multiple tumor contexts. : Chiu et al. present a pan-cancer analysis of lncRNA regulatory interactions. They suggest that the dysregulation of hundreds of lncRNAs target and alter the expression of cancer genes and pathways in each tumor context. This implies that hundreds of lncRNAs can alter tumor phenotypes in each tumor context. Keywords: lncRNA, regulation, modulation, cancer gene, pan-cancer, noncoding RNA, microRNA, RNA-binding proteins, interactome

  12. Nanoparticles for cancer gene therapy: Recent advances, challenges, and strategies.

    Science.gov (United States)

    Wang, Kui; Kievit, Forrest M; Zhang, Miqin

    2016-12-01

    Compared to conventional treatments, gene therapy offers a variety of advantages for cancer treatment including high potency and specificity, low off-target toxicity, and delivery of multiple genes that concurrently target cancer tumorigenesis, recurrence, and drug resistance. In the past decades, gene therapy has undergone remarkable progress, and is now poised to become a first line therapy for cancer. Among various gene delivery systems, nanoparticles have attracted much attention because of their desirable characteristics including low toxicity profiles, well-controlled and high gene delivery efficiency, and multi-functionalities. This review provides an overview on gene therapeutics and gene delivery technologies, and highlight recent advances, challenges and insights into the design and the utility of nanoparticles in gene therapy for cancer treatment. Copyright © 2016. Published by Elsevier Ltd.

  13. Modeling mechanical interactions between cancerous mammary acini

    Science.gov (United States)

    Wang, Jeffrey; Liphardt, Jan; Rycroft, Chris

    2015-03-01

    The rules and mechanical forces governing cell motility and interactions with the extracellular matrix of a tissue are often critical for understanding the mechanisms by which breast cancer is able to spread through the breast tissue and eventually metastasize. Ex vivo experimentation has demonstrated the the formation of long collagen fibers through collagen gels between the cancerous mammary acini responsible for milk production, providing a fiber scaffolding along which cancer cells can disorganize. We present a minimal mechanical model that serves as a potential explanation for the formation of these collagen fibers and the resultant motion. Our working hypothesis is that cancerous cells induce this fiber formation by pulling on the gel and taking advantage of the specific mechanical properties of collagen. To model this system, we employ a new Eulerian, fixed grid simulation method to model the collagen as a nonlinear viscoelastic material subject to various forces coupled with a multi-agent model to describe individual cancer cells. We find that these phenomena can be explained two simple ideas: cells pull collagen radially inwards and move towards the tension gradient of the collagen gel, while being exposed to standard adhesive and collision forces.

  14. Environmental confounding in gene-environment interaction studies.

    Science.gov (United States)

    Vanderweele, Tyler J; Ko, Yi-An; Mukherjee, Bhramar

    2013-07-01

    We show that, in the presence of uncontrolled environmental confounding, joint tests for the presence of a main genetic effect and gene-environment interaction will be biased if the genetic and environmental factors are correlated, even if there is no effect of either the genetic factor or the environmental factor on the disease. When environmental confounding is ignored, such tests will in fact reject the joint null of no genetic effect with a probability that tends to 1 as the sample size increases. This problem with the joint test vanishes under gene-environment independence, but it still persists if estimating the gene-environment interaction parameter itself is of interest. Uncontrolled environmental confounding will bias estimates of gene-environment interaction parameters even under gene-environment independence, but it will not do so if the unmeasured confounding variable itself does not interact with the genetic factor. Under gene-environment independence, if the interaction parameter without controlling for the environmental confounder is nonzero, then there is gene-environment interaction either between the genetic factor and the environmental factor of interest or between the genetic factor and the unmeasured environmental confounder. We evaluate several recently proposed joint tests in a simulation study and discuss the implications of these results for the conduct of gene-environment interaction studies.

  15. The development of genes associated with radiosensitivity of cervical cancer

    International Nuclear Information System (INIS)

    Li Hongyan; Chen Zhihua; He Guifang

    2007-01-01

    It has a good application prospect to predict effects of radiotherapy by examining radiosensitivity of patients with cervical cancers before their radiotherapy. Prediction of tumor cell radiosensitivity according to their level of gene expression and gene therapy to reverse radio-resistance prior to radiation on cervical cancers are heated researches on tumor therapy. The expression of some proliferation-related genes, apoptosis-related genes and hypoxia-related genes can inerease the radiosensitivity of cervical cancer. Microarray technology may have more direct applications to the study of biological pathway contributing to radiation resistance and may lead to development of alternative treatment modalities. (authors)

  16. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  17. Gene-Environment Interaction in Parkinson's Disease

    DEFF Research Database (Denmark)

    Chuang, Yu-Hsuan; Lill, Christina M; Lee, Pei-Chen

    2016-01-01

    BACKGROUND AND PURPOSE: Drinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2...

  18. Personalizing gene therapy in gastric cancer.

    Science.gov (United States)

    Vogiatzi, P; Cassone, M; Claudio, P P

    2006-11-01

    Gene therapy was proposed many decades ago as a more straightforward and definitive way of curing human diseases, but only recently technical advancements and improved knowledge have allowed its active development as a broad and promising research field. After the first successes in the cure of genetic and infectious diseases, it has been actively investigated as a means to decrease the burden and suffering generated by cancer. The field of gastric cancer is witnessing an impressive flourishing of studies testing the possibilities and actual efficacy of the many different strategies employed in gene therapy, and overall results seem to be two-sided: while original ideas and innovative protocols are providing extremely interesting contributions with great potential, more advanced-phase studies concluded so far have fallen short of expectations regarding efficacy, although invariably demonstrating little or no toxicity. An overview of the major efforts in this field is provided here, and a critical discussion is presented on the single strategies undertaken and on the overall balance between potentiality and pitfalls. Copyright 2006 Prous Science. All rights reserved.

  19. Can gene fusions serve for fingerprints of radiogenic cancers?

    International Nuclear Information System (INIS)

    Nakamura, Nori

    2016-01-01

    It has been recognized that malignancies in blood cells often bear specific chromosome translocations or gene fusions. In recent years, the presence of fusion genes became to be known also among solid cancers as driver mutations. However, representative solid cancers bearing specific gene fusions are limited to cancers of thyroid, prostate, and sarcomas among which only thyroid cancer risk is known to be related to radiation exposures. On the other hand, it is extremely rare to find recurrent reciprocal translocations among common cancers such as in the lung, stomach, breast, and colon, which form a major component of radiation risks. It is therefore unlikely that radiation increases the risk of cancer by inducing specific translocations (gene fusions) but more likely through induction of mutations (including deletions). Although gene fusions could play a role in radiation carcinogenesis, it does not seem good enough to serve for a radiation fingerprint. (author)

  20. Distinct gene expression profiles in ovarian cancer linked to Lynch syndrome

    DEFF Research Database (Denmark)

    Jönsson, Jenny-Maria; Bartuma, Katarina; Dominguez-Valentin, Mev

    2014-01-01

    Ovarian cancer linked to Lynch syndrome represents a rare subset that typically presents at young age as early-stage tumors with an overrepresentation of endometrioid and clear cell histologies. We investigated the molecular profiles of Lynch syndrome-associated and sporadic ovarian cancer...... with the aim to identify key discriminators and central tumorigenic mechanisms in hereditary ovarian cancer. Global gene expression profiling using whole-genome c-DNA-mediated Annealing, Selection, extension, and Ligation was applied to 48 histopathologically matched Lynch syndrome-associated and sporadic...... ovarian cancers. Lynch syndrome-associated and sporadic ovarian cancers differed by 349 significantly deregulated genes, including PTPRH, BIRC3, SHH and TNFRSF6B. The genes involved were predominantly linked to cell growth, proliferation, and cell-to-cell signaling and interaction. When stratified...

  1. Screening for interaction effects in gene expression data.

    Directory of Open Access Journals (Sweden)

    Peter J Castaldi

    Full Text Available Expression quantitative trait (eQTL studies are a powerful tool for identifying genetic variants that affect levels of messenger RNA. Since gene expression is controlled by a complex network of gene-regulating factors, one way to identify these factors is to search for interaction effects between genetic variants and mRNA levels of transcription factors (TFs and their respective target genes. However, identification of interaction effects in gene expression data pose a variety of methodological challenges, and it has become clear that such analyses should be conducted and interpreted with caution. Investigating the validity and interpretability of several interaction tests when screening for eQTL SNPs whose effect on the target gene expression is modified by the expression level of a transcription factor, we characterized two important methodological issues. First, we stress the scale-dependency of interaction effects and highlight that commonly applied transformation of gene expression data can induce or remove interactions, making interpretation of results more challenging. We then demonstrate that, in the setting of moderate to strong interaction effects on the order of what may be reasonably expected for eQTL studies, standard interaction screening can be biased due to heteroscedasticity induced by true interactions. Using simulation and real data analysis, we outline a set of reasonable minimum conditions and sample size requirements for reliable detection of variant-by-environment and variant-by-TF interactions using the heteroscedasticity consistent covariance-based approach.

  2. Identification of Constrained Cancer Driver Genes Based on Mutation Timing

    Science.gov (United States)

    Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko

    2015-01-01

    Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148

  3. The role of gene-gene interaction in the prediction of criminal behavior.

    Science.gov (United States)

    Boutwell, Brian B; Menard, Scott; Barnes, J C; Beaver, Kevin M; Armstrong, Todd A; Boisvert, Danielle

    2014-04-01

    A host of research has examined the possibility that environmental risk factors might condition the influence of genes on various outcomes. Less research, however, has been aimed at exploring the possibility that genetic factors might interact to impact the emergence of human traits. Even fewer studies exist examining the interaction of genes in the prediction of behavioral outcomes. The current study expands this body of research by testing the interaction between genes involved in neural transmission. Our findings suggest that certain dopamine genes interact to increase the odds of criminogenic outcomes in a national sample of Americans. Copyright © 2014 Elsevier Inc. All rights reserved.

  4. Identifying Cancer Driver Genes Using Replication-Incompetent Retroviral Vectors

    Directory of Open Access Journals (Sweden)

    Victor M. Bii

    2016-10-01

    Full Text Available Identifying novel genes that drive tumor metastasis and drug resistance has significant potential to improve patient outcomes. High-throughput sequencing approaches have identified cancer genes, but distinguishing driver genes from passengers remains challenging. Insertional mutagenesis screens using replication-incompetent retroviral vectors have emerged as a powerful tool to identify cancer genes. Unlike replicating retroviruses and transposons, replication-incompetent retroviral vectors lack additional mutagenesis events that can complicate the identification of driver mutations from passenger mutations. They can also be used for almost any human cancer due to the broad tropism of the vectors. Replication-incompetent retroviral vectors have the ability to dysregulate nearby cancer genes via several mechanisms including enhancer-mediated activation of gene promoters. The integrated provirus acts as a unique molecular tag for nearby candidate driver genes which can be rapidly identified using well established methods that utilize next generation sequencing and bioinformatics programs. Recently, retroviral vector screens have been used to efficiently identify candidate driver genes in prostate, breast, liver and pancreatic cancers. Validated driver genes can be potential therapeutic targets and biomarkers. In this review, we describe the emergence of retroviral insertional mutagenesis screens using replication-incompetent retroviral vectors as a novel tool to identify cancer driver genes in different cancer types.

  5. Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

    Science.gov (United States)

    Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

    2013-01-01

    The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

  6. Interactions between Diet, Lifestyle and IL10, IL1B, and PTGS2/COX-2 Gene Polymorphisms in Relation to Risk of Colorectal Cancer in a Prospective Danish Case-Cohort Study

    DEFF Research Database (Denmark)

    Andersen, Vibeke; Holst, René; Kopp, Tine Iskov

    2013-01-01

    Genetically determined low COX-2 and high IL-1β activity were associated with increased risk of CRC in this northern Caucasian cohort. Furthermore, interactions were found between IL10, IL1b, and PTGS2 and diet and lifestyle factors in relation to CRC. The present study demonstrates that gene...

  7. Gene Expression Correlation for Cancer Diagnosis: A Pilot Study

    Directory of Open Access Journals (Sweden)

    Binbing Ling

    2014-01-01

    Full Text Available Poor prognosis for late-stage, high-grade, and recurrent cancers has been motivating cancer researchers to search for more efficient biomarkers to identify the onset of cancer. Recent advances in constructing and dynamically analyzing biomolecular networks for different types of cancer have provided a promising novel strategy to detect tumorigenesis and metastasis. The observation of different biomolecular networks associated with normal and cancerous states led us to hypothesize that correlations for gene expressions could serve as valid indicators of early cancer development. In this pilot study, we tested our hypothesis by examining whether the mRNA expressions of three randomly selected cancer-related genes PIK3C3, PIM3, and PTEN were correlated during cancer progression and the correlation coefficients could be used for cancer diagnosis. Strong correlations (0.68≤r≤1.0 were observed between PIK3C3 and PIM3 in breast cancer, between PIK3C3 and PTEN in breast and ovary cancers, and between PIM3 and PTEN in breast, kidney, liver, and thyroid cancers during disease progression, implicating that the correlations for cancer network gene expressions could serve as a supplement to current clinical biomarkers, such as cancer antigens, for early cancer diagnosis.

  8. Identifying Novel Candidate Genes Related to Apoptosis from a Protein-Protein Interaction Network

    Directory of Open Access Journals (Sweden)

    Baoman Wang

    2015-01-01

    Full Text Available Apoptosis is the process of programmed cell death (PCD that occurs in multicellular organisms. This process of normal cell death is required to maintain the balance of homeostasis. In addition, some diseases, such as obesity, cancer, and neurodegenerative diseases, can be cured through apoptosis, which produces few side effects. An effective comprehension of the mechanisms underlying apoptosis will be helpful to prevent and treat some diseases. The identification of genes related to apoptosis is essential to uncover its underlying mechanisms. In this study, a computational method was proposed to identify novel candidate genes related to apoptosis. First, protein-protein interaction information was used to construct a weighted graph. Second, a shortest path algorithm was applied to the graph to search for new candidate genes. Finally, the obtained genes were filtered by a permutation test. As a result, 26 genes were obtained, and we discuss their likelihood of being novel apoptosis-related genes by collecting evidence from published literature.

  9. Targeted cancer gene therapy : the flexibility of adenoviral gene therapy vectors

    NARCIS (Netherlands)

    Rots, MG; Curiel, DT; Gerritsen, WR; Haisma, HJ

    2003-01-01

    Recombinant adenoviral vectors are promising reagents for therapeutic interventions in humans, including gene therapy for biologically complex diseases like cancer and cardiovascular diseases. In this regard, the major advantage of adenoviral vectors is their superior in vivo gene transfer

  10. Towards prostate cancer gene therapy: Development of a chlorotoxin-targeted nanovector for toxic (melittin) gene delivery.

    Science.gov (United States)

    Tarokh, Zahra; Naderi-Manesh, Hossein; Nazari, Mahboobeh

    2017-03-01

    Prostate cancer is the second leading cause of death due to cancer in men. Owing to shortcomings in the current treatments, other therapies are being considered. Toxic gene delivery is one of the most effective methods for cancer therapy. Cationic polymers are able to form stable nanoparticles via interaction with nucleic acids electrostatically. Branched polyethylenimine that contains amine groups has notable buffering capacity and the ability to escape from endosome through the proton sponge effect. However, the cytotoxicity of this polymer is high, and modification is one of the applicable strategies to overcome this problem. In this study, PEI was targeted with chlorotoxin (CTX) via N-succinimidyl 3-(2-pyridyldithio) propionate (SPDP) cross-linker. CTX can bind specifically to matrix metalloproteinase-2 that is overexpressed in certain cancers. Melittin as the major component of bee venom has been reported to have anti-cancer activity. This was thus selected to deliver to PC3 cell line. Flow cytometry analysis revealed that transfection efficiency of targeted nanoparticles is significantly higher compared to non-targeted nanoparticles. Targeted nanoparticles carrying the melittin gene also decreased cell viability of PC3 cells significantly while no toxic effects were observed on NIH3T3 cell line. Therefore, CTX-targeted nanoparticles carrying the melittin gene could serve as an appropriate gene delivery system for prostate and other MMP-2 positive cancer cells. Copyright © 2016 Elsevier B.V. All rights reserved.

  11. Association of MTHFR gene polymorphisms with breast cancer survival

    International Nuclear Information System (INIS)

    Martin, Damali N; Boersma, Brenda J; Howe, Tiffany M; Goodman, Julie E; Mechanic, Leah E; Chanock, Stephen J; Ambs, Stefan

    2006-01-01

    Two functional single nucleotide polymorphisms (SNPs) in the 5,10-methylenetetrahydrofolate reductase (MTHFR) gene, C677T and A1298C, lead to decreased enzyme activity and affect chemosensitivity of tumor cells. We investigated whether these MTHFR SNPs were associated with breast cancer survival in African-American and Caucasian women. African-American (n = 143) and Caucasian (n = 105) women, who had incident breast cancer with surgery, were recruited between 1993 and 2003 from the greater Baltimore area, Maryland, USA. Kaplan-Meier survival and multivariate Cox proportional hazards regression analyses were used to examine the relationship between MTHFR SNPs and disease-specific survival. We observed opposite effects of the MTHFR polymorphisms A1298C and C677T on breast cancer survival. Carriers of the variant allele at codon 1298 (A/C or C/C) had reduced survival when compared to homozygous carriers of the common A allele [Hazard ratio (HR) = 2.05; 95% confidence interval (CI), 1.05–4.00]. In contrast, breast cancer patients with the variant allele at codon 677 (C/T or T/T) had improved survival, albeit not statistically significant, when compared to individuals with the common C/C genotype (HR = 0.65; 95% CI, 0.31–1.35). The effects were stronger in patients with estrogen receptor-negative tumors (HR = 2.70; 95% CI, 1.17–6.23 for A/C or C/C versus A/A at codon 1298; HR = 0.36; 95% CI, 0.12–1.04 for C/T or T/T versus C/C at codon 677). Interactions between the two MTHFR genotypes and race/ethnicity on breast cancer survival were also observed (A1298C, p interaction = 0.088; C677T, p interaction = 0.026). We found that the MTHFR SNPs, C677T and A1298C, were associated with breast cancer survival. The variant alleles had opposite effects on disease outcome in the study population. Race/ethnicity modified the association between the two SNPs and breast cancer survival

  12. A stochastic model for identifying differential gene pair co-expression patterns in prostate cancer progression

    Directory of Open Access Journals (Sweden)

    Mao Yu

    2009-07-01

    this research, several gene interaction networks inferred could provide clues for the mechanism of prostate cancer progression. Conclusion The SIG method reliably identifies cancer progression correlated gene pairs, and performs well both in gene pair ontology analysis and in pathway enrichment analysis. This method provides an effective means of understanding the molecular mechanism of carcinogenesis by appropriately tracking down the process of cancer progression.

  13. ANALYSES ON DIFFERENTIALLY EXPRESSED GENES ASSOCIATED WITH HUMAN BREAST CANCER

    Institute of Scientific and Technical Information of China (English)

    MENG Xu-li; DING Xiao-wen; XU Xiao-hong

    2006-01-01

    Objective: To investigate the molecular etiology of breast cancer by way of studying the differential expression and initial function of the related genes in the occurrence and development of breast cancer. Methods: Two hundred and eighty-eight human tumor related genes were chosen for preparation of the oligochips probe. mRNA was extracted from 16 breast cancer tissues and the corresponding normal breast tissues, and cDNA probe was prepared through reverse-transcription and hybridized with the gene chip. A laser focused fluorescent scanner was used to scan the chip. The different gene expressions were thereafter automatically compared and analyzed between the two sample groups. Cy3/Cy5>3.5 meant significant up-regulation. Cy3/Cy5<0.25 meant significant down-regulation. Results: The comparison between the breast cancer tissues and their corresponding normal tissues showed that 84 genes had differential expression in the Chip. Among the differently expressed genes, there were 4 genes with significant down-regulation and 6 with significant up-regulation. Compared with normal breast tissues, differentially expressed genes did partially exist in the breast cancer tissues. Conclusion: Changes in multi-gene expression regulations take place during the occurrence and development of breast cancer; and the research on related genes can help understanding the mechanism of tumor occurrence.

  14. Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Bing Jiang

    2017-01-01

    Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

  15. Gene × Smoking Interactions on Human Brain Gene Expression: Finding Common Mechanisms in Adolescents and Adults

    Science.gov (United States)

    Wolock, Samuel L.; Yates, Andrew; Petrill, Stephen A.; Bohland, Jason W.; Blair, Clancy; Li, Ning; Machiraju, Raghu; Huang, Kun; Bartlett, Christopher W.

    2013-01-01

    Background: Numerous studies have examined gene × environment interactions (G × E) in cognitive and behavioral domains. However, these studies have been limited in that they have not been able to directly assess differential patterns of gene expression in the human brain. Here, we assessed G × E interactions using two publically available datasets…

  16. Approaches to diagnose DNA mismatch repair gene defects in cancer

    DEFF Research Database (Denmark)

    Peña-Diaz, Javier; Rasmussen, Lene Juel

    2016-01-01

    development was first observed in colorectal cancer patients that carried inactivating germline mutations in MMR genes and the disease was named as hereditary non-polyposis colorectal cancer (HNPCC). Currently, a growing list of cancers is found to be MMR defective and HNPCC has been renamed Lynch syndrome...

  17. Gene-gene, gene-environment, gene-nutrient interactions and single nucleotide polymorphisms of inflammatory cytokines.

    Science.gov (United States)

    Nadeem, Amina; Mumtaz, Sadaf; Naveed, Abdul Khaliq; Aslam, Muhammad; Siddiqui, Arif; Lodhi, Ghulam Mustafa; Ahmad, Tausif

    2015-05-15

    Inflammation plays a significant role in the etiology of type 2 diabetes mellitus (T2DM). The rise in the pro-inflammatory cytokines is the essential step in glucotoxicity and lipotoxicity induced mitochondrial injury, oxidative stress and beta cell apoptosis in T2DM. Among the recognized markers are interleukin (IL)-6, IL-1, IL-10, IL-18, tissue necrosis factor-alpha (TNF-α), C-reactive protein, resistin, adiponectin, tissue plasminogen activator, fibrinogen and heptoglobins. Diabetes mellitus has firm genetic and very strong environmental influence; exhibiting a polygenic mode of inheritance. Many single nucleotide polymorphisms (SNPs) in various genes including those of pro and anti-inflammatory cytokines have been reported as a risk for T2DM. Not all the SNPs have been confirmed by unifying results in different studies and wide variations have been reported in various ethnic groups. The inter-ethnic variations can be explained by the fact that gene expression may be regulated by gene-gene, gene-environment and gene-nutrient interactions. This review highlights the impact of these interactions on determining the role of single nucleotide polymorphism of IL-6, TNF-α, resistin and adiponectin in pathogenesis of T2DM.

  18. Gene-physical activity interactions and their impact on diabetes

    DEFF Research Database (Denmark)

    Oskari Kilpeläinen, Tuomas; Franks, Paul W

    2014-01-01

    to an equal bout of physical activity. Individuals with specific genetic profiles are also expected to be more responsive to the beneficial effects of physical activity in the prevention of type 2 diabetes. Identification of such gene-physical activity interactions could give new insights into the biological...... the reader to the recent advances in the genetics of type 2 diabetes, summarize the current evidence on gene-physical activity interactions in relation to type 2 diabetes, and outline how information on gene-physical activity interactions might help improve the prevention and treatment of type 2 diabetes....... Finally, we will discuss the existing and emerging strategies that might enhance our ability to identify and exploit gene-physical activity interactions in the etiology of type 2 diabetes. © 2014 S. Karger AG, Basel....

  19. Rrp1b, a new candidate susceptibility gene for breast cancer progression and metastasis.

    Directory of Open Access Journals (Sweden)

    Nigel P S Crawford

    2007-11-01

    Full Text Available A novel candidate metastasis modifier, ribosomal RNA processing 1 homolog B (Rrp1b, was identified through two independent approaches. First, yeast two-hybrid, immunoprecipitation, and functional assays demonstrated a physical and functional interaction between Rrp1b and the previous identified metastasis modifier Sipa1. In parallel, using mouse and human metastasis gene expression data it was observed that extracellular matrix (ECM genes are common components of metastasis predictive signatures, suggesting that ECM genes are either important markers or causal factors in metastasis. To investigate the relationship between ECM genes and poor prognosis in breast cancer, expression quantitative trait locus analysis of polyoma middle-T transgene-induced mammary tumor was performed. ECM gene expression was found to be consistently associated with Rrp1b expression. In vitro expression of Rrp1b significantly altered ECM gene expression, tumor growth, and dissemination in metastasis assays. Furthermore, a gene signature induced by ectopic expression of Rrp1b in tumor cells predicted survival in a human breast cancer gene expression dataset. Finally, constitutional polymorphism within RRP1B was found to be significantly associated with tumor progression in two independent breast cancer cohorts. These data suggest that RRP1B may be a novel susceptibility gene for breast cancer progression and metastasis.

  20. P-MartCancer–Interactive Online Software to Enable Analysis of Shotgun Cancer Proteomic Datasets

    Energy Technology Data Exchange (ETDEWEB)

    Webb-Robertson, Bobbie-Jo M.; Bramer, Lisa M.; Jensen, Jeffrey L.; Kobold, Markus A.; Stratton, Kelly G.; White, Amanda M.; Rodland, Karin D.

    2017-10-31

    P-MartCancer is a new interactive web-based software environment that enables biomedical and biological scientists to perform in-depth analyses of global proteomics data without requiring direct interaction with the data or with statistical software. P-MartCancer offers a series of statistical modules associated with quality assessment, peptide and protein statistics, protein quantification and exploratory data analyses driven by the user via customized workflows and interactive visualization. Currently, P-MartCancer offers access to multiple cancer proteomic datasets generated through the Clinical Proteomics Tumor Analysis Consortium (CPTAC) at the peptide, gene and protein levels. P-MartCancer is deployed using Azure technologies (http://pmart.labworks.org/cptac.html), the web-service is alternatively available via Docker Hub (https://hub.docker.com/r/pnnl/pmart-web/) and many statistical functions can be utilized directly from an R package available on GitHub (https://github.com/pmartR).

  1. Detection of Gene Interactions Based on Syntactic Relations

    Directory of Open Access Journals (Sweden)

    Mi-Young Kim

    2008-01-01

    Full Text Available Interactions between proteins and genes are considered essential in the description of biomolecular phenomena, and networks of interactions are applied in a system's biology approach. Recently, many studies have sought to extract information from biomolecular text using natural language processing technology. Previous studies have asserted that linguistic information is useful for improving the detection of gene interactions. In particular, syntactic relations among linguistic information are good for detecting gene interactions. However, previous systems give a reasonably good precision but poor recall. To improve recall without sacrificing precision, this paper proposes a three-phase method for detecting gene interactions based on syntactic relations. In the first phase, we retrieve syntactic encapsulation categories for each candidate agent and target. In the second phase, we construct a verb list that indicates the nature of the interaction between pairs of genes. In the last phase, we determine direction rules to detect which of two genes is the agent or target. Even without biomolecular knowledge, our method performs reasonably well using a small training dataset. While the first phase contributes to improve recall, the second and third phases contribute to improve precision. In the experimental results using ICML 05 Workshop on Learning Language in Logic (LLL05 data, our proposed method gave an F-measure of 67.2% for the test data, significantly outperforming previous methods. We also describe the contribution of each phase to the performance.

  2. Cell-ECM Interactions During Cancer Invasion

    Science.gov (United States)

    Jiang, Yi

    The extracellular matrix (ECM), a fibrous material that forms a network in a tissue, significantly affects many aspects of cellular behavior, including cell movement and proliferation. Transgenic mouse tumor studies indicate that excess collagen, a major component of ECM, enhances tumor formation and invasiveness. Clinically, tumor associated collagen signatures are strong markers for breast cancer survival. However, the underlying mechanisms are unclear since the properties of ECM are complex, with diverse structural and mechanical properties depending on various biophysical parameters. We have developed a three-dimensional elastic fiber network model, and parameterized it with in vitro collagen mechanics. Using this model, we study ECM remodeling as a result of local deformation and cell migration through the ECM as a network percolation problem. We have also developed a three-dimensional, multiscale model of cell migration and interaction with ECM. Our model reproduces quantitative single cell migration experiments. This model is a first step toward a fully biomechanical cell-matrix interaction model and may shed light on tumor associated collagen signatures in breast cancer. This work was partially supported by NIH-U01CA143069.

  3. PREFACE: Physics approaches to protein interactions and gene regulation Physics approaches to protein interactions and gene regulation

    Science.gov (United States)

    Nussinov, Ruth; Panchenko, Anna R.; Przytycka, Teresa

    2011-06-01

    nor sufficient for transcription factor activity. Transcription regulation is a complex and still not fully understood process involving, in addition to protein-DNA binding, other factors such as epigenetic modifications and three-dimensional DNA organization. In this issue, Levens and Benham discuss another important mechanism which is likely to contribute to overall gene regulation—changes of DNA secondary structure in response to supercoiling-induced stress. Pointing out that DNA is "more than a cipher", they argue that the DNA structural transitions driven by negative supercoiling may have profound consequences for the cell and have to be accounted for in detailed models. There is considerable progress in physical modeling of DNA dynamics in response to stress. Such efforts, supported by experimental data, will bring us closer to an understanding of the role of supercoiling in gene regulation. Large-scale biomolecular interaction networks not only provide a system-level view of cellular processes, but are also increasingly used to model communications between molecules. The lack of sufficient biochemical data and the gigantic scale of the network prevented detailed modeling of network dynamics and have stimulated the development of simplified models such as the information flow approach described by Kim et al in this issue. Importantly, despite their simplicity, such models proved to be extremely useful for identifying network modules, essential nodes, and molecular pathways which are dysregulated in complex diseases such as cancer. Finally, moving from studies of single cells towards populations, one has to recognize the heterogeneity present within a population of cells. In the context of protein abundance, such cell-to-cell variation within clonal populations of cells, referred to as expression noise, has recently become a focus of intense cross-disciplinary research. Concerted efforts of experimentalists, physicists and mathematicians have brought us closer

  4. Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium

    Directory of Open Access Journals (Sweden)

    Dhir Rajiv

    2004-08-01

    Full Text Available Abstract Background Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. Results Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using

  5. Altered interactions between unicellular and multicellular genes drive hallmarks of transformation in a diverse range of solid tumors.

    Science.gov (United States)

    Trigos, Anna S; Pearson, Richard B; Papenfuss, Anthony T; Goode, David L

    2017-06-13

    Tumors of distinct tissues of origin and genetic makeup display common hallmark cellular phenotypes, including sustained proliferation, suppression of cell death, and altered metabolism. These phenotypic commonalities have been proposed to stem from disruption of conserved regulatory mechanisms evolved during the transition to multicellularity to control fundamental cellular processes such as growth and replication. Dating the evolutionary emergence of human genes through phylostratigraphy uncovered close association between gene age and expression level in RNA sequencing data from The Cancer Genome Atlas for seven solid cancers. Genes conserved with unicellular organisms were strongly up-regulated, whereas genes of metazoan origin were primarily inactivated. These patterns were most consistent for processes known to be important in cancer, implicating both selection and active regulation during malignant transformation. The coordinated expression of strongly interacting multicellularity and unicellularity processes was lost in tumors. This separation of unicellular and multicellular functions appeared to be mediated by 12 highly connected genes, marking them as important general drivers of tumorigenesis. Our findings suggest common principles closely tied to the evolutionary history of genes underlie convergent changes at the cellular process level across a range of solid cancers. We propose altered activity of genes at the interfaces between multicellular and unicellular regions of human gene regulatory networks activate primitive transcriptional programs, driving common hallmark features of cancer. Manipulation of cross-talk between biological processes of different evolutionary origins may thus present powerful and broadly applicable treatment strategies for cancer.

  6. The Candidate Cancer Gene Database: a database of cancer driver genes from forward genetic screens in mice.

    Science.gov (United States)

    Abbott, Kenneth L; Nyre, Erik T; Abrahante, Juan; Ho, Yen-Yi; Isaksson Vogel, Rachel; Starr, Timothy K

    2015-01-01

    Identification of cancer driver gene mutations is crucial for advancing cancer therapeutics. Due to the overwhelming number of passenger mutations in the human tumor genome, it is difficult to pinpoint causative driver genes. Using transposon mutagenesis in mice many laboratories have conducted forward genetic screens and identified thousands of candidate driver genes that are highly relevant to human cancer. Unfortunately, this information is difficult to access and utilize because it is scattered across multiple publications using different mouse genome builds and strength metrics. To improve access to these findings and facilitate meta-analyses, we developed the Candidate Cancer Gene Database (CCGD, http://ccgd-starrlab.oit.umn.edu/). The CCGD is a manually curated database containing a unified description of all identified candidate driver genes and the genomic location of transposon common insertion sites (CISs) from all currently published transposon-based screens. To demonstrate relevance to human cancer, we performed a modified gene set enrichment analysis using KEGG pathways and show that human cancer pathways are highly enriched in the database. We also used hierarchical clustering to identify pathways enriched in blood cancers compared to solid cancers. The CCGD is a novel resource available to scientists interested in the identification of genetic drivers of cancer. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. Case-only study of interactions between metabolic enzymes and smoking in colorectal cancer

    International Nuclear Information System (INIS)

    Fan, Chunhong; Jin, Mingjuan; Chen, Kun; Zhang, Yongjing; Zhang, Shuangshuang; Liu, Bing

    2007-01-01

    Gene-gene and gene-environment interactions involved in the metabolism of carcinogens may increase the risk of cancer. Our objective was to measure the interactions between common polymorphisms of P450 (CYP1A2, CYP1B1, CYP2E1), GSTM1 and T1, SULT1A1 and cigarette smoking in colorectal cancer (CRC). A case-only design was conducted in a Chinese population including 207 patients with sporadic CRC. Unconditional logistic regression analysis was performed adjusting for age, gender, alcohol consumption, and cigarette smoking. The interaction odds ratio (COR) for the gene-gene interaction between CYP1B1 1294G and SULT1A1 638A allele was 2.68 (95% CI: 1.16–6.26). The results of the gene-environment analyses revealed that an interaction existed between cigarette smoking and the CYP1B1 1294G allele for CRC (COR = 2.62, 95%CI: 1.01–6.72), the COR for the interaction of CYP1B1 1294G and smoking history > 35 pack-years was 3.47 (95%CI: 1.12–10.80). No other significant gene-gene and gene-environment interactions were observed. Our results showed that the interaction between polymorphisms in CYP1B1 1294G and SULT1A1*2 may play a significant role on CRC in the Chinese population. Also, it is suggested that the association between cigarette smoking and CRC could be differentiated by the CYP1B1 1294G allele

  8. Gene Signature in Sessile Serrated Polyps Identifies Colon Cancer Subtype

    Science.gov (United States)

    Kanth, Priyanka; Bronner, Mary P.; Boucher, Kenneth M.; Burt, Randall W.; Neklason, Deborah W.; Hagedorn, Curt H.; Delker, Don A.

    2016-01-01

    Sessile serrated colon adenoma/polyps (SSA/Ps) are found during routine screening colonoscopy and may account for 20–30% of colon cancers. However, differentiating SSA/Ps from hyperplastic polyps (HP) with little risk of cancer is challenging and complementary molecular markers are needed. Additionally, the molecular mechanisms of colon cancer development from SSA/Ps are poorly understood. RNA sequencing was performed on 21 SSA/Ps, 10 HPs, 10 adenomas, 21 uninvolved colon and 20 control colon specimens. Differential expression and leave-one-out cross validation methods were used to define a unique gene signature of SSA/Ps. Our SSA/P gene signature was evaluated in colon cancer RNA-Seq data from The Cancer Genome Atlas (TCGA) to identify a subtype of colon cancers that may develop from SSA/Ps. A total of 1422 differentially expressed genes were found in SSA/Ps relative to controls. Serrated polyposis syndrome (n=12) and sporadic SSA/Ps (n=9) exhibited almost complete (96%) gene overlap. A 51-gene panel in SSA/P showed similar expression in a subset of TCGA colon cancers with high microsatellite instability (MSI-H). A smaller seven-gene panel showed high sensitivity and specificity in identifying BRAF mutant, CpG island methylator phenotype high (CIMP-H) and MLH1 silenced colon cancers. We describe a unique gene signature in SSA/Ps that identifies a subset of colon cancers likely to develop through the serrated pathway. These gene panels may be utilized for improved differentiation of SSA/Ps from HPs and provide insights into novel molecular pathways altered in colon cancer arising from the serrated pathway. PMID:27026680

  9. Id-1 gene and gene products as therapeutic targets for treatment of breast cancer and other types of carcinoma

    Science.gov (United States)

    Desprez, Pierre-Yves; Campisi, Judith

    2014-08-19

    A method for treatment of breast cancer and other types of cancer. The method comprises targeting and modulating Id-1 gene expression, if any, for the Id-1 gene, or gene products in breast or other epithelial cancers in a patient by delivering products that modulate Id-1 gene expression. When expressed, Id-1 gene is a prognostic indicator that cancer cells are invasive and metastatic.

  10. A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology

    Directory of Open Access Journals (Sweden)

    Ching Lee Koo

    2013-01-01

    Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.

  11. A kernel regression approach to gene-gene interaction detection for case-control studies.

    Science.gov (United States)

    Larson, Nicholas B; Schaid, Daniel J

    2013-11-01

    Gene-gene interactions are increasingly being addressed as a potentially important contributor to the variability of complex traits. Consequently, attentions have moved beyond single locus analysis of association to more complex genetic models. Although several single-marker approaches toward interaction analysis have been developed, such methods suffer from very high testing dimensionality and do not take advantage of existing information, notably the definition of genes as functional units. Here, we propose a comprehensive family of gene-level score tests for identifying genetic elements of disease risk, in particular pairwise gene-gene interactions. Using kernel machine methods, we devise score-based variance component tests under a generalized linear mixed model framework. We conducted simulations based upon coalescent genetic models to evaluate the performance of our approach under a variety of disease models. These simulations indicate that our methods are generally higher powered than alternative gene-level approaches and at worst competitive with exhaustive SNP-level (where SNP is single-nucleotide polymorphism) analyses. Furthermore, we observe that simulated epistatic effects resulted in significant marginal testing results for the involved genes regardless of whether or not true main effects were present. We detail the benefits of our methods and discuss potential genome-wide analysis strategies for gene-gene interaction analysis in a case-control study design. © 2013 WILEY PERIODICALS, INC.

  12. RET is a potential tumor suppressor gene in colorectal cancer

    Science.gov (United States)

    Luo, Yanxin; Tsuchiya, Karen D.; Park, Dong Il; Fausel, Rebecca; Kanngurn, Samornmas; Welcsh, Piri; Dzieciatkowski, Slavomir; Wang, Jianping; Grady, William M.

    2012-01-01

    Cancer arises as the consequence of mutations and epigenetic alterations that activate oncogenes and inactivate tumor suppressor genes. Through a genome-wide screen for methylated genes in colon neoplasms, we identified aberrantly methylated RET in colorectal cancer. RET, a transmembrane receptor tyrosine kinase and a receptor for the GDNF-family ligands, was one of the first oncogenes to be identified and has been shown to be an oncogene in thyroid cancer and pheochromocytoma. However, unexpectedly, we found RET is methylated in 27% of colon adenomas and in 63% of colorectal cancers, and now provide evidence that RET has tumor suppressor activity in colon cancer. The aberrant methylation of RET correlates with decreased RET expression, whereas the restoration of RET in colorectal cancer cell lines results in apoptosis. Furthermore, in support of a tumor suppressor function of RET, mutant RET has also been found in primary colorectal cancer. We now show that these mutations inactivate RET, which is consistent with RET being a tumor suppressor gene in the colon. These findings suggest that the aberrant methylation of RET and the mutational inactivation of RET promote colorectal cancer formation and that RET can serve as a tumor suppressor gene in the colon. Moreover, the increased frequency of methylated RET in colon cancers compared to adenomas suggests RET inactivation is involved in the progression of colon adenomas to cancer. PMID:22751117

  13. Gene × physical activity interactions in obesity

    DEFF Research Database (Denmark)

    Ahmad, Shafqat; Rukh, Gull; Varga, Tibor V

    2013-01-01

    Numerous obesity loci have been identified using genome-wide association studies. A UK study indicated that physical activity may attenuate the cumulative effect of 12 of these loci, but replication studies are lacking. Therefore, we tested whether the aggregate effect of these loci is diminished...... in adults of European ancestry reporting high levels of physical activity. Twelve obesity-susceptibility loci were genotyped or imputed in 111,421 participants. A genetic risk score (GRS) was calculated by summing the BMI-associated alleles of each genetic variant. Physical activity was assessed using self...... combined using meta-analysis weighted by cohort sample size. The meta-analysis yielded a statistically significant GRS × physical activity interaction effect estimate (Pinteraction  = 0.015). However, a statistically significant interaction effect was only apparent in North American cohorts (n = 39...

  14. Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

  15. Optimizing prognosis-related key miRNA-target interactions responsible for cancer metastasis.

    Science.gov (United States)

    Zhao, Hongying; Yuan, Huating; Hu, Jing; Xu, Chaohan; Liao, Gaoming; Yin, Wenkang; Xu, Liwen; Wang, Li; Zhang, Xinxin; Shi, Aiai; Li, Jing; Xiao, Yun

    2017-12-12

    Increasing evidence suggests that the abnormality of microRNAs (miRNAs) and their downstream targets is frequently implicated in the pathogenesis of human cancers, however, the clinical benefit of causal miRNA-target interactions has been seldom studied. Here, we proposed a computational method to optimize prognosis-related key miRNA-target interactions by combining transcriptome and clinical data from thousands of TCGA tumors across 16 cancer types. We obtained a total of 1,956 prognosis-related key miRNA-target interactions between 112 miRNAs and 1,443 their targets. Interestingly, these key target genes are specifically involved in tumor progression-related functions, such as 'cell adhesion' and 'cell migration'. Furthermore, they are most significantly correlated with 'tissue invasion and metastasis', a hallmark of metastasis, in ten distinct types of cancer through the hallmark analysis. These results implicated that the prognosis-related key miRNA-target interactions were highly associated with cancer metastasis. Finally, we observed that the combination of these key miRNA-target interactions allowed to distinguish patients with good prognosis from those with poor prognosis both in most TCGA cancer types and independent validation sets, highlighting their roles in cancer metastasis. We provided a user-friendly database named miRNATarget (freely available at http://biocc.hrbmu.edu.cn/miRNATar/), which provides an overview of the prognosis-related key miRNA-target interactions across 16 cancer types.

  16. Gene expression profiles in stages II and III colon cancers

    DEFF Research Database (Denmark)

    Thorsteinsson, Morten; Kirkeby, Lene T; Hansen, Raino

    2012-01-01

    PURPOSE: A 128-gene signature has been proposed to predict outcome in patients with stages II and III colorectal cancers. In the present study, we aimed to reproduce and validate the 128-gene signature in external and independent material. METHODS: Gene expression data from the original material...... were retrieved from the Gene Expression Omnibus (GEO) (n¿=¿111) in addition to a Danish data set (n¿=¿37). All patients had stages II and III colon cancers. A Prediction Analysis of Microarray classifier, based on the 128-gene signature and the original training set of stage I (n¿=¿65) and stage IV (n...... correctly predicted as stage IV-like, and the remaining patients were predicted as stage I-like and unclassifiable, respectively. Stage II patients could not be stratified. CONCLUSIONS: The 128-gene signature showed reproducibility in stage III colon cancer, but could not predict recurrence in stage II...

  17. Combining many interaction networks to predict gene function and analyze gene lists.

    Science.gov (United States)

    Mostafavi, Sara; Morris, Quaid

    2012-05-01

    In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  18. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

    Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

  19. Genetic variation in selenoprotein genes, lifestyle, and risk of colon and rectal cancer.

    Directory of Open Access Journals (Sweden)

    Martha L Slattery

    Full Text Available BACKGROUND: Associations between selenium and cancer have directed attention to role of selenoproteins in the carcinogenic process. METHODS: We used data from two population-based case-control studies of colon (n = 1555 cases, 1956 controls and rectal (n = 754 cases, 959 controls cancer. We evaluated the association between genetic variation in TXNRD1, TXNRD2, TXNRD3, C11orf31 (SelH, SelW, SelN1, SelS, SepX, and SeP15 with colorectal cancer risk. RESULTS: After adjustment for multiple comparisons, several associations were observed. Two SNPs in TXNRD3 were associated with rectal cancer (rs11718498 dominant OR 1.42 95% CI 1.16,1.74 pACT 0.0036 and rs9637365 recessive 0.70 95% CI 0.55,0.90 pACT 0.0208. Four SNPs in SepN1 were associated with rectal cancer (rs11247735 recessive OR 1.30 95% CI 1.04,1.63 pACT 0.0410; rs2072749 GGvsAA OR 0.53 95% CI 0.36,0.80 pACT 0.0159; rs4659382 recessive OR 0.58 95% CI 0.39,0.86 pACT 0.0247; rs718391 dominant OR 0.76 95% CI 0.62,0.94 pACT 0.0300. Interaction between these genes and exposures that could influence these genes showed numerous significant associations after adjustment for multiple comparisons. Two SNPs in TXNRD1 and four SNPs in TXNRD2 interacted with aspirin/NSAID to influence colon cancer; one SNP in TXNRD1, two SNPs in TXNRD2, and one SNP in TXNRD3 interacted with aspirin/NSAIDs to influence rectal cancer. Five SNPs in TXNRD2 and one in SelS, SeP15, and SelW1 interacted with estrogen to modify colon cancer risk; one SNP in SelW1 interacted with estrogen to alter rectal cancer risk. Several SNPs in this candidate pathway influenced survival after diagnosis with colon cancer (SeP15 and SepX1 increased HRR and rectal cancer (SepX1 increased HRR. CONCLUSIONS: Findings support an association between selenoprotein genes and colon and rectal cancer development and survival after diagnosis. Given the interactions observed, it is likely that the impact of cancer susceptibility from genotype is

  20. Analysis of the interaction of extracellular matrix and phenotype of bladder cancer cells

    International Nuclear Information System (INIS)

    Dozmorov, Mikhail G; Kyker, Kimberly D; Saban, Ricardo; Knowlton, Nicholas; Dozmorov, Igor; Centola, Michael B; Hurst, Robert E

    2006-01-01

    The extracellular matrix has a major effect upon the malignant properties of bladder cancer cells both in vitro in 3-dimensional culture and in vivo. Comparing gene expression of several bladder cancer cells lines grown under permissive and suppressive conditions in 3-dimensional growth on cancer-derived and normal-derived basement membrane gels respectively and on plastic in conventional tissue culture provides a model system for investigating the interaction of malignancy and extracellular matrix. Understanding how the extracellular matrix affects the phenotype of bladder cancer cells may provide important clues to identify new markers or targets for therapy. Five bladder cancer cell lines and one immortalized, but non-tumorigenic, urothelial line were grown on Matrigel, a cancer-derived ECM, on SISgel, a normal-derived ECM, and on plastic, where the only ECM is derived from the cells themselves. The transcriptomes were analyzed on an array of 1186 well-annotated cancer derived cDNAs containing most of the major pathways for malignancy. Hypervariable genes expressing more variability across cell lines than a set expressing technical variability were analyzed further. Expression values were clustered, and to identify genes most likely to represent biological factors, statistically over-represented ontologies and transcriptional regulatory elements were identified. Approximately 400 of the 1186 total genes were expressed 2 SD above background. Approximately 100 genes were hypervariable in cells grown on each ECM, but the pattern was different in each case. A core of 20 were identified as hypervariable under all 3 growth conditions, and 33 were hypervariable on both SISgel and Matrigel, but not on plastic. Clustering of the hypervariable genes showed very different patterns for the same 6 cell types on the different ECM. Even when loss of cell cycle regulation was identified, different genes were involved, depending on the ECM. Under the most permissive conditions

  1. Identifying functional cancer-specific miRNA-mRNA interactions in testicular germ cell tumor.

    Science.gov (United States)

    Sedaghat, Nafiseh; Fathy, Mahmood; Modarressi, Mohammad Hossein; Shojaie, Ali

    2016-09-07

    Testicular cancer is the most common cancer in men aged between 15 and 35 and more than 90% of testicular neoplasms are originated at germ cells. Recent research has shown the impact of microRNAs (miRNAs) in different types of cancer, including testicular germ cell tumor (TGCT). MicroRNAs are small non-coding RNAs which affect the development and progression of cancer cells by binding to mRNAs and regulating their expressions. The identification of functional miRNA-mRNA interactions in cancers, i.e. those that alter the expression of genes in cancer cells, can help delineate post-regulatory mechanisms and may lead to new treatments to control the progression of cancer. A number of sequence-based methods have been developed to predict miRNA-mRNA interactions based on the complementarity of sequences. While necessary, sequence complementarity is, however, not sufficient for presence of functional interactions. Alternative methods have thus been developed to refine the sequence-based interactions using concurrent expression profiles of miRNAs and mRNAs. This study aims to find functional cancer-specific miRNA-mRNA interactions in TGCT. To this end, the sequence-based predicted interactions are first refined using an ensemble learning method, based on two well-known methods of learning miRNA-mRNA interactions, namely, TaLasso and GenMiR++. Additional functional analyses were then used to identify a subset of interactions to be most likely functional and specific to TGCT. The final list of 13 miRNA-mRNA interactions can be potential targets for identifying TGCT-specific interactions and future laboratory experiments to develop new therapies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  2. Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2007-10-01

    Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

  3. Cancer gene therapy targeting angiogenesis: An updated Review

    Science.gov (United States)

    Liu, Ching-Chiu; Shen, Zan; Kung, Hsiang-Fu; Lin, Marie CM

    2006-01-01

    Since the relationship between angiogenesis and tumor growth was established by Folkman in 1971, scientists have made efforts exploring the possibilities in treating cancer by targeting angiogenesis. Inhibition of angiogenesis growth factors and administration of angiogenesis inhibitors are the basics of anti-angiogenesis therapy. Transfer of anti-angiogenesis genes has received attention recently not only because of the advancement of recombinant vectors, but also because of the localized and sustained expression of therapeutic gene product inside the tumor after gene transfer. This review provides the up-to-date information about the strategies and the vectors studied in the field of anti-angiogenesis cancer gene therapy. PMID:17109514

  4. Quantitative DNA methylation analysis of candidate genes in cervical cancer.

    Directory of Open Access Journals (Sweden)

    Erin M Siegel

    Full Text Available Aberrant DNA methylation has been observed in cervical cancer; however, most studies have used non-quantitative approaches to measure DNA methylation. The objective of this study was to quantify methylation within a select panel of genes previously identified as targets for epigenetic silencing in cervical cancer and to identify genes with elevated methylation that can distinguish cancer from normal cervical tissues. We identified 49 women with invasive squamous cell cancer of the cervix and 22 women with normal cytology specimens. Bisulfite-modified genomic DNA was amplified and quantitative pyrosequencing completed for 10 genes (APC, CCNA, CDH1, CDH13, WIF1, TIMP3, DAPK1, RARB, FHIT, and SLIT2. A Methylation Index was calculated as the mean percent methylation across all CpG sites analyzed per gene (~4-9 CpG site per sequence. A binary cut-point was defined at >15% methylation. Sensitivity, specificity and area under ROC curve (AUC of methylation in individual genes or a panel was examined. The median methylation index was significantly higher in cases compared to controls in 8 genes, whereas there was no difference in median methylation for 2 genes. Compared to HPV and age, the combination of DNA methylation level of DAPK1, SLIT2, WIF1 and RARB with HPV and age significantly improved the AUC from 0.79 to 0.99 (95% CI: 0.97-1.00, p-value = 0.003. Pyrosequencing analysis confirmed that several genes are common targets for aberrant methylation in cervical cancer and DNA methylation level of four genes appears to increase specificity to identify cancer compared to HPV detection alone. Alterations in DNA methylation of specific genes in cervical cancers, such as DAPK1, RARB, WIF1, and SLIT2, may also occur early in cervical carcinogenesis and should be evaluated.

  5. Gene therapy of cancer and development of therapeutic target gene

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang Min; Kwon, Hee Chung

    1998-04-01

    We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene.

  6. Gene therapy of cancer and development of therapeutic target gene

    International Nuclear Information System (INIS)

    Kim, Chang Min; Kwon, Hee Chung

    1998-04-01

    We applied HSV-tk/GCV strategy to orthotopic rat hepatoma model and showed anticancer effects of hepatoma. The increased expression of Lac Z gene after adenovirus-mediated gene delivery throughout hepatic artery was thought that is increased the possibility of gene therapy for curing hepatoma. With the construction of kGLP-laboratory, it is possible to produce a good quantity and quality of adenovirus in lage-scale production and purification of adenovirus vector. Also, the analysis of hepatoma related genes by PCR-LOH could be used for the diagnosis of patients and the development of therapeutic gene

  7. Relevance of Fusion Genes in Pediatric Cancers: Toward Precision Medicine

    Directory of Open Access Journals (Sweden)

    Célia Dupain

    2017-03-01

    Full Text Available Pediatric cancers differ from adult tumors, especially by their very low mutational rate. Therefore, their etiology could be explained in part by other oncogenic mechanisms such as chromosomal rearrangements, supporting the possible implication of fusion genes in the development of pediatric cancers. Fusion genes result from chromosomal rearrangements leading to the juxtaposition of two genes. Consequently, an abnormal activation of one or both genes is observed. The detection of fusion genes has generated great interest in basic cancer research and in the clinical setting, since these genes can lead to better comprehension of the biological mechanisms of tumorigenesis and they can also be used as therapeutic targets and diagnostic or prognostic biomarkers. In this review, we discuss the molecular mechanisms of fusion genes and their particularities in pediatric cancers, as well as their relevance in murine models and in the clinical setting. We also point out the difficulties encountered in the discovery of fusion genes. Finally, we discuss future perspectives and priorities for finding new innovative therapies in childhood cancer.

  8. Vitamin D receptor gene polymorphisms, dietary promotion of insulin resistance, and colon and rectal cancer.

    Science.gov (United States)

    Murtaugh, Maureen A; Sweeney, Carol; Ma, Khe-Ni; Potter, John D; Caan, Bette J; Wolff, Roger K; Slattery, Martha L

    2006-01-01

    Modifiable risk factors in colorectal cancer etiology and their interactions with genetic susceptibility are of particular interest. Functional vitamin D receptor (VDR) gene polymorphisms may influence carcinogenesis through modification of cell growth, protection from oxidative stress, cell-cell matrix effects, or insulin and insulin-like growth factor pathways. We investigated interactions between foods (dairy products, red and processed meat, and whole and refined grains) and dietary patterns (sucrose-to-fiber ratio and glycemic index) associated with insulin resistance with the FokI polymorphism of the VDR gene and colon and rectal cancer risk. Data (diet, anthropometrics, and lifestyle) and DNA came from case-control studies of colon (1,698 cases and 1,861 controls) and rectal cancer (752 cases and 960 controls) in northern California, Utah, and the Twin Cities metropolitan area, Minnesota (colon cancer study only). Unconditional logistic regression models were adjusted for smoking, race, sex, age, body mass index, physical activity, energy intake, dietary fiber, and calcium. The lowest colon cancer risk was observed with the Ff/ff FokI genotypes and a low sucrose-to-fiber ratio. Rectal cancer risk decreased with greater consumption of dairy products and increased with red or processed meat consumption and the FF genotype. Modifiable dietary risk factors may be differentially important among individuals by VDR genotype and may act through the insulin pathway to affect colon cancer risk and through fat, calcium, or other means to influence rectal cancer risk.

  9. GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature

    Directory of Open Access Journals (Sweden)

    Ning Ye

    2015-01-01

    Full Text Available The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

  10. A deeper look at two concepts of measuring gene-gene interactions: logistic regression and interaction information revisited.

    Science.gov (United States)

    Mielniczuk, Jan; Teisseyre, Paweł

    2018-03-01

    Detection of gene-gene interactions is one of the most important challenges in genome-wide case-control studies. Besides traditional logistic regression analysis, recently the entropy-based methods attracted a significant attention. Among entropy-based methods, interaction information is one of the most promising measures having many desirable properties. Although both logistic regression and interaction information have been used in several genome-wide association studies, the relationship between them has not been thoroughly investigated theoretically. The present paper attempts to fill this gap. We show that although certain connections between the two methods exist, in general they refer two different concepts of dependence and looking for interactions in those two senses leads to different approaches to interaction detection. We introduce ordering between interaction measures and specify conditions for independent and dependent genes under which interaction information is more discriminative measure than logistic regression. Moreover, we show that for so-called perfect distributions those measures are equivalent. The numerical experiments illustrate the theoretical findings indicating that interaction information and its modified version are more universal tools for detecting various types of interaction than logistic regression and linkage disequilibrium measures. © 2017 WILEY PERIODICALS, INC.

  11. DDPC: Dragon database of genes associated with prostate cancer

    KAUST Repository

    Maqungo, Monique; Kaur, Mandeep; Kwofie, Samuel K.; Radovanovic, Aleksandar; Schaefer, Ulf; Schmeier, Sebastian; Oppon, Ekow; Christoffels, Alan; Bajic, Vladimir B.

    2010-01-01

    associated with Prostate Cancer (DDPC) as an integrated knowledgebase of genes experimentally verified as implicated in PC. DDPC is distinctive from other databases in that (i) it provides pre-compiled biomedical text-mining information on PC, which otherwise

  12. Genotype x diet interactions in mice predisposed to mammary cancer: II. Tumors and metastasis

    DEFF Research Database (Denmark)

    Gordon, Ryan R; Hunter, Kent W; Merrill, Michele La

    2008-01-01

    either a very high-fat or a matched-control-fat diet, and we measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL × diet interaction effects. Here we describe......High dietary fat intake and obesity may increase the risk of susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F2 mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F2 mice...... effects of diet on mammary tumor and metastases phenotypes, mapping of tumor/metastasis modifier genes, and the interaction between dietary fat levels and effects of cancer modifiers. Results demonstrate that animals fed a high-fat diet are not only more likely to experience decreased mammary cancer...

  13. Polymorphisms in inflammation pathway genes and endometrial cancer risk

    Science.gov (United States)

    Delahanty, Ryan J.; Xiang, Yong-Bing; Spurdle, Amanda; Beeghly-Fadiel, Alicia; Long, Jirong; Thompson, Deborah; Tomlinson, Ian; Yu, Herbert; Lambrechts, Diether; Dörk, Thilo; Goodman, Marc T.; Zheng, Ying; Salvesen, Helga B.; Bao, Ping-Ping; Amant, Frederic; Beckmann, Matthias W.; Coenegrachts, Lieve; Coosemans, An; Dubrowinskaja, Natalia; Dunning, Alison; Runnebaum, Ingo B.; Easton, Douglas; Ekici, Arif B.; Fasching, Peter A.; Halle, Mari K.; Hein, Alexander; Howarth, Kimberly; Gorman, Maggie; Kaydarova, Dylyara; Krakstad, Camilla; Lose, Felicity; Lu, Lingeng; Lurie, Galina; O’Mara, Tracy; Matsuno, Rayna K.; Pharoah, Paul; Risch, Harvey; Corssen, Madeleine; Trovik, Jone; Turmanov, Nurzhan; Wen, Wanqing; Lu, Wei; Cai, Qiuyin; Zheng, Wei; Shu, Xiao-Ou

    2013-01-01

    Background Experimental and epidemiological evidence have suggested that chronic inflammation may play a critical role in endometrial carcinogenesis. Methods To investigate this hypothesis, a two-stage study was carried out to evaluate single nucleotide polymorphisms (SNPs) in inflammatory pathway genes in association with endometrial cancer risk. In stage 1, 64 candidate pathway genes were identified and 4,542 directly genotyped or imputed SNPs were analyzed among 832 endometrial cancer cases and 2,049 controls, using data from the Shanghai Endometrial Cancer Genetics Study. Linkage disequilibrium of stage 1 SNPs significantly associated with endometrial cancer (PAsian- and European-ancestry samples. Conclusions These findings lend support to the hypothesis that genetic polymorphisms in genes involved in the inflammatory pathway may contribute to genetic susceptibility to endometrial cancer. Impact Statement This study adds to the growing evidence that inflammation plays an important role in endometrial carcinogenesis. PMID:23221126

  14. Intracellular delivery of potential therapeutic genes: prospects in cancer gene therapy.

    Science.gov (United States)

    Bakhtiar, Athirah; Sayyad, Mustak; Rosli, Rozita; Maruyama, Atsushi; Chowdhury, Ezharul H

    2014-01-01

    Conventional therapies for malignant cancer such as chemotherapy and radiotherapy are associated with poor survival rates owing to the development of cellular resistance to cancer drugs and the lack of targetability, resulting in unwanted adverse effects on healthy cells and necessitating the lowering of therapeutic dose with consequential lower efficacy of the treatment. Gene therapy employing different types of viral and non-viral carriers to transport gene(s) of interest and facilitating production of the desirable therapeutic protein(s) has tremendous prospects in cancer treatments due to the high-level of specificity in therapeutic action of the expressed protein(s) with diminished off-target effects, although cancer cell-specific delivery of transgene(s) still poses some challenges to be addressed. Depending on the potential therapeutic target genes, cancer gene therapy could be categorized into tumor suppressor gene replacement therapy, immune gene therapy and enzyme- or prodrug-based therapy. This review would shed light on the current progress of delivery of potentially therapeutic genes into various cancer cells in vitro and animal models utilizing a variety of viral and non-viral vectors.

  15. Increased signaling entropy in cancer requires the scale-free property of protein interaction networks

    Science.gov (United States)

    Teschendorff, Andrew E.; Banerji, Christopher R. S.; Severini, Simone; Kuehn, Reimer; Sollich, Peter

    2015-01-01

    One of the key characteristics of cancer cells is an increased phenotypic plasticity, driven by underlying genetic and epigenetic perturbations. However, at a systems-level it is unclear how these perturbations give rise to the observed increased plasticity. Elucidating such systems-level principles is key for an improved understanding of cancer. Recently, it has been shown that signaling entropy, an overall measure of signaling pathway promiscuity, and computable from integrating a sample's gene expression profile with a protein interaction network, correlates with phenotypic plasticity and is increased in cancer compared to normal tissue. Here we develop a computational framework for studying the effects of network perturbations on signaling entropy. We demonstrate that the increased signaling entropy of cancer is driven by two factors: (i) the scale-free (or near scale-free) topology of the interaction network, and (ii) a subtle positive correlation between differential gene expression and node connectivity. Indeed, we show that if protein interaction networks were random graphs, described by Poisson degree distributions, that cancer would generally not exhibit an increased signaling entropy. In summary, this work exposes a deep connection between cancer, signaling entropy and interaction network topology. PMID:25919796

  16. Insulators form gene loops by interacting with promoters in Drosophila.

    Science.gov (United States)

    Erokhin, Maksim; Davydova, Anna; Kyrchanova, Olga; Parshikov, Alexander; Georgiev, Pavel; Chetverina, Darya

    2011-09-01

    Chromatin insulators are regulatory elements involved in the modulation of enhancer-promoter communication. The 1A2 and Wari insulators are located immediately downstream of the Drosophila yellow and white genes, respectively. Using an assay based on the yeast GAL4 activator, we have found that both insulators are able to interact with their target promoters in transgenic lines, forming gene loops. The existence of an insulator-promoter loop is confirmed by the fact that insulator proteins could be detected on the promoter only in the presence of an insulator in the transgene. The upstream promoter regions, which are required for long-distance stimulation by enhancers, are not essential for promoter-insulator interactions. Both insulators support basal activity of the yellow and white promoters in eyes. Thus, the ability of insulators to interact with promoters might play an important role in the regulation of basal gene transcription.

  17. Prostate Cancer Epigenetics: A Review on Gene Regulation

    OpenAIRE

    Diaw, Lena; Woodson, Karen; Gillespie, John W.

    2007-01-01

    Prostate cancer is the most common cancer in men in western countries, and its incidence is increasing steadily worldwide. Molecular changes including both genetic and epigenetic events underlying the development and progression of this disease are still not well understood. Epigenetic events are involved in gene regulation and occur through different mechanisms such as DNA methylation and histone modifi cations. Both DNA methylation and histone modifi cations affect gene regulation and play ...

  18. Anti-Angiogenic Gene Therapy for Prostate Cancer

    Science.gov (United States)

    2004-04-01

    S. Parvovirus vectors for cancer gene therapy. Expert. Opin. Bid. Ther., 2004, 4: 53-64. Ponnazhagan, S., and Hoover, F. Delivery of DNA to tumor... vaccine with plasmid adjuvants 95h Annual Meeting of the American Society for Cancer Research, Orlando, FL, April 2004. Chaudhuri, T.R., Cao, Z...with recombinant AAV vectors results in sustained expression in a dog model of hemophilia. Gene Ther., 5: 40-49, 1998. 2ś 35. Bohl, D., Bosch, A

  19. EIGER: Electromagnetic Interactions GEneRalized

    International Nuclear Information System (INIS)

    Champagne, N J; Sharpe, R M; Rockway, J W

    2001-01-01

    The EIGER (Electromagnetic Interactions Generalized) modeling suite is a joint development activity by the Lawrence Livermore National Lab, Sandia National Labs, the University of Houston, and the Navy (Space and Naval Warfare Systems Center-San Diego). The effort endeavors to bring the next generation of hybrid, higher-order, full-wave analysis methods into a single integrated framework. The tools are based upon frequency-domain solutions of Maxwell's equations to model scattering and radiation from complex 2D and 3D structures. The framework employs boundary element solutions of integral equation formulations and finite element solutions of the Helmholtz wave equation. A goal is to use higher-order representations to model both the geometry (using higher-order geometric elements) and numerical methods (using higher-order vector basis functions). In addition, a variety of advanced Green's functions and symmetry operators can be applied to efficiently treat geometries containing such features as layered material regions and periodic structures. Each of these methods can be brought to bear simultaneously, on different portions of a complex structure. HPC implementation issues were addressed during the design of the software architecture, so that the same package runs on platforms ranging from serial desktop workstations through advanced HPC architectures. Our current efforts on higher-order modeling and improved solver libraries will be highlighted

  20. Bacteria as vectors for gene therapy of cancer.

    LENUS (Irish Health Repository)

    Baban, Chwanrow K

    2012-01-31

    Anti-cancer therapy faces major challenges, particularly in terms of specificity of treatment. The ideal therapy would eradicate tumor cells selectively with minimum side effects on normal tissue. Gene or cell therapies have emerged as realistic prospects for the treatment of cancer, and involve the delivery of genetic information to a tumor to facilitate the production of therapeutic proteins. However, there is still much to be done before an efficient and safe gene medicine is achieved, primarily developing the means of targeting genes to tumors safely and efficiently. An emerging family of vectors involves bacteria of various genera. It has been shown that bacteria are naturally capable of homing to tumors when systemically administered resulting in high levels of replication locally. Furthermore, invasive species can deliver heterologous genes intra-cellularly for tumor cell expression. Here, we review the use of bacteria as vehicles for gene therapy of cancer, detailing the mechanisms of action and successes at preclinical and clinical levels.

  1. Deregulation of an imprinted gene network in prostate cancer.

    Science.gov (United States)

    Ribarska, Teodora; Goering, Wolfgang; Droop, Johanna; Bastian, Klaus-Marius; Ingenwerth, Marc; Schulz, Wolfgang A

    2014-05-01

    Multiple epigenetic alterations contribute to prostate cancer progression by deregulating gene expression. Epigenetic mechanisms, especially differential DNA methylation at imprinting control regions (termed DMRs), normally ensure the exclusive expression of imprinted genes from one specific parental allele. We therefore wondered to which extent imprinted genes become deregulated in prostate cancer and, if so, whether deregulation is due to altered DNA methylation at DMRs. Therefore, we selected presumptive deregulated imprinted genes from a previously conducted in silico analysis and from the literature and analyzed their expression in prostate cancer tissues by qRT-PCR. We found significantly diminished expression of PLAGL1/ZAC1, MEG3, NDN, CDKN1C, IGF2, and H19, while LIT1 was significantly overexpressed. The PPP1R9A gene, which is imprinted in selected tissues only, was strongly overexpressed, but was expressed biallelically in benign and cancerous prostatic tissues. Expression of many of these genes was strongly correlated, suggesting co-regulation, as in an imprinted gene network (IGN) reported in mice. Deregulation of the network genes also correlated with EZH2 and HOXC6 overexpression. Pyrosequencing analysis of all relevant DMRs revealed generally stable DNA methylation between benign and cancerous prostatic tissues, but frequent hypo- and hyper-methylation was observed at the H19 DMR in both benign and cancerous tissues. Re-expression of the ZAC1 transcription factor induced H19, CDKN1C and IGF2, supporting its function as a nodal regulator of the IGN. Our results indicate that a group of imprinted genes are coordinately deregulated in prostate cancers, independently of DNA methylation changes.

  2. Evidence for plasticity genotypes in a gene-gene-environment interaction : the TRAILS study

    NARCIS (Netherlands)

    Nederhof, E; Bouma, Esther; Riese, Harriette; Laceulle, Odilia; Ormel, J.; Oldehinkel, A.J.

    2010-01-01

    The purpose was to study how functional polymorphisms in the brain derived neurotrophic factor gene (BDNF val66met) and the serotonin transporter gene linked promotor region (5-HTTLPR) interact with childhood adversities in predicting Effortful Control. Effortful Control refers to the ability to

  3. MDM2 SNP309, gene-gene interaction, and tumor susceptibility: an updated meta-analysis

    Directory of Open Access Journals (Sweden)

    Wu Wei

    2011-05-01

    Full Text Available Abstract Background The tumor suppressor gene p53 is involved in multiple cellular pathways including apoptosis, transcriptional control, and cell cycle regulation. In the last decade it has been demonstrated that the single nucleotide polymorphism (SNP at codon 72 of the p53 gene is associated with the risk for development of various neoplasms. MDM2 SNP309 is a single nucleotide T to G polymorphism located in the MDM2 gene promoter. From the time that this well-characterized functional polymorphism was identified, a variety of case-control studies have been published that investigate the possible association between MDM2 SNP309 and cancer risk. However, the results of the published studies, as well as the subsequent meta-analyses, remain contradictory. Methods To investigate whether currently published epidemiological studies can clarify the potential interaction between MDM2 SNP309 and the functional genetic variant in p53 codon72 (Arg72Pro and p53 mutation status, we performed a meta-analysis of the risk estimate on 27,813 cases with various tumor types and 30,295 controls. Results The data we reviewed indicated that variant homozygote 309GG and heterozygote 309TG were associated with a significant increased risk of all tumor types (homozygote comparison: odds ratio (OR = 1.25, 95% confidence interval (CI = 1.13-1.37; heterozygote comparison: OR = 1.10, 95% CI = 1.03-1.17. We also found that the combination of GG and Pro/Pro, TG and Pro/Pro, GG and Arg/Arg significantly increased the risk of cancer (OR = 3.38, 95% CI = 1.77-6.47; OR = 1.88, 95% CI = 1.26-2.81; OR = 1.96, 95% CI = 1.01-3.78, respectively. In a stratified analysis by tumor location, we also found a significant increased risk in brain, liver, stomach and uterus cancer (OR = 1.47, 95% CI = 1.06-2.03; OR = 2.24, 95%CI = 1.57-3.18; OR = 1.54, 95%CI = 1.04-2.29; OR = 1.34, 95%CI = 1.07-1.29, respectively. However, no association was seen between MDM2 SNP309 and tumor susceptibility

  4. Gene-Environment Interactions in Severe Mental Illness

    Directory of Open Access Journals (Sweden)

    Rudolf eUher

    2014-05-01

    Full Text Available Severe mental illness is a broad category that includes schizophrenia, bipolar disorder and severe depression. Both genetic disposition and environmental exposures play important roles in the development of severe mental illness. Multiple lines of evidence suggest that the roles of genetic and environmental depend on each other. Gene-environment interactions may underlie the paradox of strong environmental factors for highly heritable disorders, the low estimates of shared environmental influences in twin studies of severe mental illness and the heritability gap between twin and molecular heritability estimates. Sons and daughters of parents with severe mental illness are more vulnerable to the effects of prenatal and postnatal environmental exposures, suggesting that the expression of genetic liability depends on environment. In the last decade, gene-environment interactions involving specific molecular variants in candidate genes have been identified. Replicated findings include an interaction between a polymorphism in the AKT1 gene and cannabis use in the development of psychosis and an interaction between the length polymorphism of the serotonin transporter gene and childhood maltreatment in the development of persistent depressive disorder. Bipolar disorder has been underinvestigated, with only a single study showing an interaction between a functional polymorphism in BDNF and stressful life events triggering bipolar depressive episodes. The first systematic search for gene-environment interactions has found that a polymorphism in CTNNA3 may sensitise the developing brain to the pathogenic effect of cytomegalovirus in utero, leading to schizophrenia in adulthood. Strategies for genome-wide investigations will likely include coordination between epidemiological and genetic research efforts, systematic assessment of multiple environmental factors in large samples, and prioritization of genetic variants.

  5. miRNA-Processing Gene Methylation and Cancer Risk.

    Science.gov (United States)

    Joyce, Brian T; Zheng, Yinan; Zhang, Zhou; Liu, Lei; Kocherginsky, Masha; Murphy, Robert; Achenbach, Chad J; Musa, Jonah; Wehbe, Firas; Just, Allan; Shen, Jincheng; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A; Hou, Lifang

    2018-05-01

    Background: Dysregulation of miRNA and methylation levels are epigenetic hallmarks of cancer, potentially linked via miRNA-processing genes. Studies have found genetic alterations to miRNA-processing genes in cancer cells and human population studies. Our objective was to prospectively examine changes in DNA methylation of miRNA-processing genes and their associations with cancer risk. Methods: We examined cohort data from the Department of Veterans' Affairs Normative Aging Study. Participants were assessed every 3 to 5 years starting in 1999 through 2013 including questionnaires, medical record review, and blood collection. Blood from 686 consenting participants was analyzed using the Illumina 450K BeadChip array to measure methylation at CpG sites throughout the genome. We selected 19 genes based on a literature review, with 519 corresponding CpG sites. We then used Cox proportional hazards models to examine associations with cancer incidence, and generalized estimating equations to examine associations with cancer prevalence. Associations at false discovery rate time to cancer development (positively for cg06751583, inversely for cg23230564 and cg21034183), whereas methylation of one CpG site ( DROSHA : cg16131300) was positively associated with cancer prevalence. Conclusions: DNA methylation of DROSHA , a key miRNA-processing gene, and TNRC6B may play a role in early carcinogenesis. Impact: Changes in miRNA processing may exert multiple effects on cancer development, including protecting against it via altered global miRNAs, and may be a useful early detection biomarker of cancer. Cancer Epidemiol Biomarkers Prev; 27(5); 550-7. ©2018 AACR . ©2018 American Association for Cancer Research.

  6. Phase I metabolic genes and risk of lung cancer: multiple polymorphisms and mRNA expression.

    Directory of Open Access Journals (Sweden)

    Melissa Rotunno

    2009-05-01

    Full Text Available Polymorphisms in genes coding for enzymes that activate tobacco lung carcinogens may generate inter-individual differences in lung cancer risk. Previous studies had limited sample sizes, poor exposure characterization, and a few single nucleotide polymorphisms (SNPs tested in candidate genes. We analyzed 25 SNPs (some previously untested in 2101 primary lung cancer cases and 2120 population controls from the Environment And Genetics in Lung cancer Etiology (EAGLE study from six phase I metabolic genes, including cytochrome P450s, microsomal epoxide hydrolase, and myeloperoxidase. We evaluated the main genotype effects and genotype-smoking interactions in lung cancer risk overall and in the major histology subtypes. We tested the combined effect of multiple SNPs on lung cancer risk and on gene expression. Findings were prioritized based on significance thresholds and consistency across different analyses, and accounted for multiple testing and prior knowledge. Two haplotypes in EPHX1 were significantly associated with lung cancer risk in the overall population. In addition, CYP1B1 and CYP2A6 polymorphisms were inversely associated with adenocarcinoma and squamous cell carcinoma risk, respectively. Moreover, the association between CYP1A1 rs2606345 genotype and lung cancer was significantly modified by intensity of cigarette smoking, suggesting an underlying dose-response mechanism. Finally, increasing number of variants at CYP1A1/A2 genes revealed significant protection in never smokers and risk in ever smokers. Results were supported by differential gene expression in non-tumor lung tissue samples with down-regulation of CYP1A1 in never smokers and up-regulation in smokers from CYP1A1/A2 SNPs. The significant haplotype associations emphasize that the effect of multiple SNPs may be important despite null single SNP-associations, and warrants consideration in genome-wide association studies (GWAS. Our findings emphasize the necessity of post

  7. Transcriptome analysis of recurrently deregulated genes across multiple cancers identifies new pan-cancer biomarkers

    DEFF Research Database (Denmark)

    Kaczkowski, Bogumil; Tanaka, Yuji; Kawaji, Hideya

    2016-01-01

    Genes that are commonly deregulated in cancer are clinically attractive as candidate pan-diagnostic markers and therapeutic targets. To globally identify such targets, we compared Cap Analysis of Gene Expression (CAGE) profiles from 225 different cancer cell lines and 339 corresponding primary cell...

  8. Haplotype analysis of common variants in the BRCA1 gene and risk of sporadic breast cancer

    International Nuclear Information System (INIS)

    Cox, David G; Kraft, Peter; Hankinson, Susan E; Hunter, David J

    2005-01-01

    Truncation mutations in the BRCA1 gene cause a substantial increase in risk of breast cancer. However, these mutations are rare in the general population and account for little of the overall incidence of sporadic breast cancer. We used whole-gene resequencing data to select haplotype tagging single nucleotide polymorphisms, and examined the association between common haplotypes of BRCA1 and breast cancer in a nested case-control study in the Nurses' Health Study (1323 cases and 1910 controls). One haplotype was associated with a slight increase in risk (odds ratio 1.18, 95% confidence interval 1.02–1.37). A significant interaction (P = 0.05) was seen between this haplotype, positive family history of breast cancer, and breast cancer risk. Although not statistically significant, similar interactions were observed with age at diagnosis and with menopausal status at diagnosis; risk tended to be higher among younger, pre-menopausal women. We have described a haplotype in the BRCA1 gene that was associated with an approximately 20% increase in risk of sporadic breast cancer in the general population. However, the functional variant(s) responsible for the association are unclear

  9. VarWalker: personalized mutation network analysis of putative cancer genes from next-generation sequencing data.

    Science.gov (United States)

    Jia, Peilin; Zhao, Zhongming

    2014-02-01

    A major challenge in interpreting the large volume of mutation data identified by next-generation sequencing (NGS) is to distinguish driver mutations from neutral passenger mutations to facilitate the identification of targetable genes and new drugs. Current approaches are primarily based on mutation frequencies of single-genes, which lack the power to detect infrequently mutated driver genes and ignore functional interconnection and regulation among cancer genes. We propose a novel mutation network method, VarWalker, to prioritize driver genes in large scale cancer mutation data. VarWalker fits generalized additive models for each sample based on sample-specific mutation profiles and builds on the joint frequency of both mutation genes and their close interactors. These interactors are selected and optimized using the Random Walk with Restart algorithm in a protein-protein interaction network. We applied the method in >300 tumor genomes in two large-scale NGS benchmark datasets: 183 lung adenocarcinoma samples and 121 melanoma samples. In each cancer, we derived a consensus mutation subnetwork containing significantly enriched consensus cancer genes and cancer-related functional pathways. These cancer-specific mutation networks were then validated using independent datasets for each cancer. Importantly, VarWalker prioritizes well-known, infrequently mutated genes, which are shown to interact with highly recurrently mutated genes yet have been ignored by conventional single-gene-based approaches. Utilizing VarWalker, we demonstrated that network-assisted approaches can be effectively adapted to facilitate the detection of cancer driver genes in NGS data.

  10. A Search for Gene Fusions/Translocations in Breast Cancer

    Science.gov (United States)

    2013-11-01

    2008). The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349. Palanisamy, N., Ateeq, B., Kalyana-Sundaram...census of human cancer genes. Nat Rev Cancer 4, 177–183. [2] Santarius T, Shipley J, Brewer D, Stratton MR, and Cooper CS (2010). A census of amplified

  11. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool.

    Science.gov (United States)

    Chen, Edward Y; Tan, Christopher M; Kou, Yan; Duan, Qiaonan; Wang, Zichen; Meirelles, Gabriela Vaz; Clark, Neil R; Ma'ayan, Avi

    2013-04-15

    System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.

  12. Hereditary Ovarian Cancer: Not Only BRCA 1 and 2 Genes

    Directory of Open Access Journals (Sweden)

    Angela Toss

    2015-01-01

    Full Text Available More than one-fifth of ovarian tumors have hereditary susceptibility and, in about 65–85% of these cases, the genetic abnormality is a germline mutation in BRCA genes. Nevertheless, several other suppressor genes and oncogenes have been associated with hereditary ovarian cancers, including the mismatch repair (MMR genes in Lynch syndrome, the tumor suppressor gene, TP53, in the Li-Fraumeni syndrome, and several other genes involved in the double-strand breaks repair system, such as CHEK2, RAD51, BRIP1, and PALB2. The study of genetic discriminators and deregulated pathways involved in hereditary ovarian syndromes is relevant for the future development of molecular diagnostic strategies and targeted therapeutic approaches. The recent development and implementation of next-generation sequencing technologies have provided the opportunity to simultaneously analyze multiple cancer susceptibility genes, reduce the delay and costs, and optimize the molecular diagnosis of hereditary tumors. Particularly, the identification of mutations in ovarian cancer susceptibility genes in healthy women may result in a more personalized cancer risk management with tailored clinical and radiological surveillance, chemopreventive approaches, and/or prophylactic surgeries. On the other hand, for ovarian cancer patients, the identification of mutations may provide potential targets for biologic agents and guide treatment decision-making.

  13. Identification of candidate new cancer susceptibility genes using yeast genomics

    International Nuclear Information System (INIS)

    Brown, M.; Brown, J.A.; Game, J.C.

    2003-01-01

    A large proportion of cancer susceptibility syndromes are the result of mutations in genes in DNA repair or in cell-cycle checkpoints in response to DNA damage, such as ataxia telangiectasia (AT), Fanconi's anemia (FA), Bloom's syndrome (BS), Nijmegen breakage syndrome (NBS), and xeroderma pigmentosum (XP). Mutations in these genes often cause gross chromosomal instability leading to an increased mutation rate of all genes including those directly responsible for cancer. We have proposed that because the orthologs of these genes in budding yeast, S. cerevisiae, confer protection against killing by DNA damaging agents it should be possible to identify new cancer susceptibility genes by identifying yeast genes whose deletion causes sensitivity to DNA damage. We therefore screened the recently completed collection of individual gene deletion mutants to identify genes that affect sensitivity to DNA-damaging agents. Screening for sensitivity in this obtained up to now with the F98 glioma model othe fact that each deleted gene is replaced by a cassette containing two molecular 'barcodes', or 20-mers, that uniquely identify the strain when DNA from a pool of strains is hybridized to an oligonucleotide array containing the complementary sequences of the barcodes. We performed the screen with UV, IR, H 2 0 2 and other DNA damaging agents. In addition to identifying genes already known to confer resistance to DNA damaging agents we have identified, and individually confirmed, several genes not previously associated with resistance. Several of these are of unknown function. We have also examined the chromosomal stability of selected strains and found that IR sensitive strains often but not always exhibit genomic instability. We are presently constructing a yeast artificial chromosome to globally interrogate all the genes in the deletion pool for their involvement in genomic stability. This work shows that budding yeast is a valuable eukaryotic model organism to identify

  14. A Nonlinear Model for Gene-Based Gene-Environment Interaction

    Directory of Open Access Journals (Sweden)

    Jian Sa

    2016-06-01

    Full Text Available A vast amount of literature has confirmed the role of gene-environment (G×E interaction in the etiology of complex human diseases. Traditional methods are predominantly focused on the analysis of interaction between a single nucleotide polymorphism (SNP and an environmental variable. Given that genes are the functional units, it is crucial to understand how gene effects (rather than single SNP effects are influenced by an environmental variable to affect disease risk. Motivated by the increasing awareness of the power of gene-based association analysis over single variant based approach, in this work, we proposed a sparse principle component regression (sPCR model to understand the gene-based G×E interaction effect on complex disease. We first extracted the sparse principal components for SNPs in a gene, then the effect of each principal component was modeled by a varying-coefficient (VC model. The model can jointly model variants in a gene in which their effects are nonlinearly influenced by an environmental variable. In addition, the varying-coefficient sPCR (VC-sPCR model has nice interpretation property since the sparsity on the principal component loadings can tell the relative importance of the corresponding SNPs in each component. We applied our method to a human birth weight dataset in Thai population. We analyzed 12,005 genes across 22 chromosomes and found one significant interaction effect using the Bonferroni correction method and one suggestive interaction. The model performance was further evaluated through simulation studies. Our model provides a system approach to evaluate gene-based G×E interaction.

  15. Dissecting Tumor-Stromal Interactions in Breast Cancer Bone Metastasis

    Directory of Open Access Journals (Sweden)

    Yibin Kang

    2016-06-01

    Full Text Available Bone metastasis is a frequent occurrence in breast cancer, affecting more than 70% of late stage cancer patients with severe complications such as fracture, bone pain, and hypercalcemia. The pathogenesis of osteolytic bone metastasis depends on cross-communications between tumor cells and various stromal cells residing in the bone microenvironment. Several growth factor signaling pathways, secreted micro RNAs (miRNAs and exosomes are functional mediators of tumor-stromal interactions in bone metastasis. We developed a functional genomic approach to systemically identified molecular pathways utilized by breast cancer cells to engage the bone stroma in order to generate osteolytic bone metastasis. We showed that elevated expression of vascular cell adhesion molecule 1 (VCAM1 in disseminated breast tumor cells mediates the recruitment of pre-osteoclasts and promotes their differentiation to mature osteoclasts during the bone metastasis formation. Transforming growth factor β (TGF-β is released from bone matrix upon bone destruction, and signals to breast cancer to further enhance their malignancy in developing bone metastasis. We furthered identified Jagged1 as a TGF-β target genes in tumor cells that engaged bone stromal cells through the activation of Notch signaling to provide a positive feedback to promote tumor growth and to activate osteoclast differentiation. Substantially change in miRNA expression was observed in osteoclasts during their differentiation and maturation, which can be exploited as circulating biomarkers of emerging bone metastasis and therapeutic targets for the treatment of bone metastasis. Further research in this direction may lead to improved diagnosis and treatment strategies for bone metastasis.

  16. DDEC: Dragon database of genes implicated in esophageal cancer

    KAUST Repository

    Essack, Magbubah

    2009-07-06

    Background: Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data. Description: Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new \\'association hypotheses\\' generated based on the precompiled reports. Conclusion: We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is

  17. DDEC: Dragon database of genes implicated in esophageal cancer

    International Nuclear Information System (INIS)

    Essack, Magbubah; Radovanovic, Aleksandar; Schaefer, Ulf; Schmeier, Sebastian; Seshadri, Sundararajan V; Christoffels, Alan; Kaur, Mandeep; Bajic, Vladimir B

    2009-01-01

    Esophageal cancer ranks eighth in order of cancer occurrence. Its lethality primarily stems from inability to detect the disease during the early organ-confined stage and the lack of effective therapies for advanced-stage disease. Moreover, the understanding of molecular processes involved in esophageal cancer is not complete, hampering the development of efficient diagnostics and therapy. Efforts made by the scientific community to improve the survival rate of esophageal cancer have resulted in a wealth of scattered information that is difficult to find and not easily amendable to data-mining. To reduce this gap and to complement available cancer related bioinformatic resources, we have developed a comprehensive database (Dragon Database of Genes Implicated in Esophageal Cancer) with esophageal cancer related information, as an integrated knowledge database aimed at representing a gateway to esophageal cancer related data. Manually curated 529 genes differentially expressed in EC are contained in the database. We extracted and analyzed the promoter regions of these genes and complemented gene-related information with transcription factors that potentially control them. We further, precompiled text-mined and data-mined reports about each of these genes to allow for easy exploration of information about associations of EC-implicated genes with other human genes and proteins, metabolites and enzymes, toxins, chemicals with pharmacological effects, disease concepts and human anatomy. The resulting database, DDEC, has a useful feature to display potential associations that are rarely reported and thus difficult to identify. Moreover, DDEC enables inspection of potentially new 'association hypotheses' generated based on the precompiled reports. We hope that this resource will serve as a useful complement to the existing public resources and as a good starting point for researchers and physicians interested in EC genetics. DDEC is freely accessible to academic

  18. Vitamin D metabolic pathway genes and pancreatic cancer risk.

    Directory of Open Access Journals (Sweden)

    Hannah Arem

    Full Text Available Evidence on the association between vitamin D status and pancreatic cancer risk is inconsistent. This inconsistency may be partially attributable to variation in vitamin D regulating genes. We selected 11 vitamin D-related genes (GC, DHCR7, CYP2R1, VDR, CYP27B1, CYP24A1, CYP27A1, RXRA, CRP2, CASR and CUBN totaling 213 single nucleotide polymorphisms (SNPs, and examined associations with pancreatic adenocarcinoma. Our study included 3,583 pancreatic cancer cases and 7,053 controls from the genome-wide association studies of pancreatic cancer PanScans-I-III. We used the Adaptive Joint Test and the Adaptive Rank Truncated Product statistic for pathway and gene analyses, and unconditional logistic regression for SNP analyses, adjusting for age, sex, study and population stratification. We examined effect modification by circulating vitamin D concentration (≤50, >50 nmol/L for the most significant SNPs using a subset of cohort cases (n = 713 and controls (n = 878. The vitamin D metabolic pathway was not associated with pancreatic cancer risk (p = 0.830. Of the individual genes, none were associated with pancreatic cancer risk at a significance level of p<0.05. SNPs near the VDR (rs2239186, LRP2 (rs4668123, CYP24A1 (rs2762932, GC (rs2282679, and CUBN (rs1810205 genes were the top SNPs associated with pancreatic cancer (p-values 0.008-0.037, but none were statistically significant after adjusting for multiple comparisons. Associations between these SNPs and pancreatic cancer were not modified by circulating concentrations of vitamin D. These findings do not support an association between vitamin D-related genes and pancreatic cancer risk. Future research should explore other pathways through which vitamin D status might be associated with pancreatic cancer risk.

  19. GOBO: gene expression-based outcome for breast cancer online.

    Directory of Open Access Journals (Sweden)

    Markus Ringnér

    Full Text Available Microarray-based gene expression analysis holds promise of improving prognostication and treatment decisions for breast cancer patients. However, the heterogeneity of breast cancer emphasizes the need for validation of prognostic gene signatures in larger sample sets stratified into relevant subgroups. Here, we describe a multifunctional user-friendly online tool, GOBO (http://co.bmc.lu.se/gobo, allowing a range of different analyses to be performed in an 1881-sample breast tumor data set, and a 51-sample breast cancer cell line set, both generated on Affymetrix U133A microarrays. GOBO supports a wide range of applications including: 1 rapid assessment of gene expression levels in subgroups of breast tumors and cell lines, 2 identification of co-expressed genes for creation of potential metagenes, 3 association with outcome for gene expression levels of single genes, sets of genes, or gene signatures in multiple subgroups of the 1881-sample breast cancer data set. The design and implementation of GOBO facilitate easy incorporation of additional query functions and applications, as well as additional data sets irrespective of tumor type and array platform.

  20. A Critical Perspective On Microarray Breast Cancer Gene Expression Profiling

    NARCIS (Netherlands)

    Sontrop, H.M.J.

    2015-01-01

    Microarrays offer biologists an exciting tool that allows the simultaneous assessment of gene expression levels for thousands of genes at once. At the time of their inception, microarrays were hailed as the new dawn in cancer biology and oncology practice with the hope that within a decade diseases

  1. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Deling Wang

    2018-03-01

    Full Text Available Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS, random forest (RF, and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  2. Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms.

    Science.gov (United States)

    Wang, Deling; Li, Jia-Rui; Zhang, Yu-Hang; Chen, Lei; Huang, Tao; Cai, Yu-Dong

    2018-03-12

    Breast cancer is one of the most common malignancies in women. Patient-derived tumor xenograft (PDX) model is a cutting-edge approach for drug research on breast cancer. However, PDX still exhibits differences from original human tumors, thereby challenging the molecular understanding of tumorigenesis. In particular, gene expression changes after tissues are transplanted from human to mouse model. In this study, we propose a novel computational method by incorporating several machine learning algorithms, including Monte Carlo feature selection (MCFS), random forest (RF), and rough set-based rule learning, to identify genes with significant expression differences between PDX and original human tumors. First, 831 breast tumors, including 657 PDX and 174 human tumors, were collected. Based on MCFS and RF, 32 genes were then identified to be informative for the prediction of PDX and human tumors and can be used to construct a prediction model. The prediction model exhibits a Matthews coefficient correlation value of 0.777. Seven interpretable interactions within the informative gene were detected based on the rough set-based rule learning. Furthermore, the seven interpretable interactions can be well supported by previous experimental studies. Our study not only presents a method for identifying informative genes with differential expression but also provides insights into the mechanism through which gene expression changes after being transplanted from human tumor into mouse model. This work would be helpful for research and drug development for breast cancer.

  3. GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

    Science.gov (United States)

    Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

    2018-01-01

    When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

  4. Osteoblast-Prostate Cancer Cell Interaction in Prostate Cancer Bone Metastases

    National Research Council Canada - National Science Library

    Navone, Nora

    2001-01-01

    .... This suggests that prostate cancer cells interact with cells from the osteoblastic lineage. To understand the molecular bases of prostatic bone metastases, we established two prostate cancer cell lines, MDA PCa 2a and MDA PCa 2b (1...

  5. Inference of gene-phenotype associations via protein-protein interaction and orthology.

    Directory of Open Access Journals (Sweden)

    Panwen Wang

    Full Text Available One of the fundamental goals of genetics is to understand gene functions and their associated phenotypes. To achieve this goal, in this study we developed a computational algorithm that uses orthology and protein-protein interaction information to infer gene-phenotype associations for multiple species. Furthermore, we developed a web server that provides genome-wide phenotype inference for six species: fly, human, mouse, worm, yeast, and zebrafish. We evaluated our inference method by comparing the inferred results with known gene-phenotype associations. The high Area Under the Curve values suggest a significant performance of our method. By applying our method to two human representative diseases, Type 2 Diabetes and Breast Cancer, we demonstrated that our method is able to identify related Gene Ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways. The web server can be used to infer functions and putative phenotypes of a gene along with the candidate genes of a phenotype, and thus aids in disease candidate gene discovery. Our web server is available at http://jjwanglab.org/PhenoPPIOrth.

  6. An Interactive Database of Cocaine-Responsive Gene Expression

    Directory of Open Access Journals (Sweden)

    Willard M. Freeman

    2002-01-01

    Full Text Available The postgenomic era of large-scale gene expression studies is inundating drug abuse researchers and many other scientists with findings related to gene expression. This information is distributed across many different journals, and requires laborious literature searches. Here, we present an interactive database that combines existing information related to cocaine-mediated changes in gene expression in an easy-to-use format. The database is limited to statistically significant changes in mRNA or protein expression after cocaine administration. The Flash-based program is integrated into a Web page, and organizes changes in gene expression based on neuroanatomical region, general function, and gene name. Accompanying each gene is a description of the gene, links to the original publications, and a link to the appropriate OMIM (Online Mendelian Inheritance in Man entry. The nature of this review allows for timely modifications and rapid inclusion of new publications, and should help researchers build second-generation hypotheses on the role of gene expression changes in the physiology and behavior of cocaine abuse. Furthermore, this method of organizing large volumes of scientific information can easily be adapted to assist researchers in fields outside of drug abuse.

  7. Gene expression signatures for colorectal cancer microsatellite status and HNPCC

    DEFF Research Database (Denmark)

    Kruhøffer, M; Jensen, J L; Laiho, P

    2005-01-01

    The majority of microsatellite instable (MSI) colorectal cancers are sporadic, but a subset belongs to the syndrome hereditary non-polyposis colorectal cancer (HNPCC). Microsatellite instability is caused by dysfunction of the mismatch repair (MMR) system that leads to a mutator phenotype, and MSI...... of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated...... is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression...

  8. Inverse gene-for-gene interactions contribute additively to tan spot susceptibility in wheat.

    Science.gov (United States)

    Liu, Zhaohui; Zurn, Jason D; Kariyawasam, Gayan; Faris, Justin D; Shi, Gongjun; Hansen, Jana; Rasmussen, Jack B; Acevedo, Maricelis

    2017-06-01

    Tan spot susceptibility is conferred by multiple interactions of necrotrophic effector and host sensitivity genes. Tan spot of wheat, caused by Pyrenophora tritici-repentis, is an important disease in almost all wheat-growing areas of the world. The disease system is known to involve at least three fungal-produced necrotrophic effectors (NEs) that interact with the corresponding host sensitivity (S) genes in an inverse gene-for-gene manner to induce disease. However, it is unknown if the effects of these NE-S gene interactions contribute additively to the development of tan spot. In this work, we conducted disease evaluations using different races and quantitative trait loci (QTL) analysis in a wheat recombinant inbred line (RIL) population derived from a cross between two susceptible genotypes, LMPG-6 and PI 626573. The two parental lines each harbored a single known NE sensitivity gene with LMPG-6 having the Ptr ToxC sensitivity gene Tsc1 and PI 626573 having the Ptr ToxA sensitivity gene Tsn1. Transgressive segregation was observed in the population for all races. QTL mapping revealed that both loci (Tsn1 and Tsc1) were significantly associated with susceptibility to race 1 isolates, which produce both Ptr ToxA and Ptr ToxC, and the two genes contributed additively to tan spot susceptibility. For isolates of races 2 and 3, which produce only Ptr ToxA and Ptr ToxC, only Tsn1 and Tsc1 were associated with tan spot susceptibility, respectively. This work clearly demonstrates that tan spot susceptibility in this population is due primarily to two NE-S interactions. Breeders should remove both sensitivity genes from wheat lines to obtain high levels of tan spot resistance.

  9. Bacterial Toxins for Oncoleaking Suicidal Cancer Gene Therapy.

    Science.gov (United States)

    Pahle, Jessica; Walther, Wolfgang

    For suicide gene therapy, initially prodrug-converting enzymes (gene-directed enzyme-producing therapy, GDEPT) were employed to intracellularly metabolize non-toxic prodrugs into toxic compounds, leading to the effective suicidal killing of the transfected tumor cells. In this regard, the suicide gene therapy has demonstrated its potential for efficient tumor eradication. Numerous suicide genes of viral or bacterial origin were isolated, characterized, and extensively tested in vitro and in vivo, demonstrating their therapeutic potential even in clinical trials to treat cancers of different entities. Apart from this, growing efforts are made to generate more targeted and more effective suicide gene systems for cancer gene therapy. In this regard, bacterial toxins are an alternative to the classical GDEPT strategy, which add to the broad spectrum of different suicide approaches. In this context, lytic bacterial toxins, such as streptolysin O (SLO) or the claudin-targeted Clostridium perfringens enterotoxin (CPE) represent attractive new types of suicide oncoleaking genes. They permit as pore-forming proteins rapid and also selective toxicity toward a broad range of cancers. In this chapter, we describe the generation and use of SLO as well as of CPE-based gene therapies for the effective tumor cell eradication as promising, novel suicide gene approach particularly for treatment of therapy refractory tumors.

  10. Phylostratigraphic tracking of cancer genes suggests a link to the emergence of multicellularity in metazoa

    Directory of Open Access Journals (Sweden)

    Domazet-Lošo Tomislav

    2010-05-01

    Full Text Available Abstract Background Phylostratigraphy is a method used to correlate the evolutionary origin of founder genes (that is, functional founder protein domains of gene families with particular macroevolutionary transitions. It is based on a model of genome evolution that suggests that the origin of complex phenotypic innovations will be accompanied by the emergence of such founder genes, the descendants of which can still be traced in extant organisms. The origin of multicellularity can be considered to be a macroevolutionary transition, for which new gene functions would have been required. Cancer should be tightly connected to multicellular life since it can be viewed as a malfunction of interaction between cells in a multicellular organism. A phylostratigraphic tracking of the origin of cancer genes should, therefore, also provide insights into the origin of multicellularity. Results We find two strong peaks of the emergence of cancer related protein domains, one at the time of the origin of the first cell and the other around the time of the evolution of the multicellular metazoan organisms. These peaks correlate with two major classes of cancer genes, the 'caretakers', which are involved in general functions that support genome stability and the 'gatekeepers', which are involved in cellular signalling and growth processes. Interestingly, this phylogenetic succession mirrors the ontogenetic succession of tumour progression, where mutations in caretakers are thought to precede mutations in gatekeepers. Conclusions A link between multicellularity and formation of cancer has often been predicted. However, this has not so far been explicitly tested. Although we find that a significant number of protein domains involved in cancer predate the origin of multicellularity, the second peak of cancer protein domain emergence is, indeed, connected to a phylogenetic level where multicellular animals have emerged. The fact that we can find a strong and

  11. Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

    Directory of Open Access Journals (Sweden)

    Dai Hongying

    2013-01-01

    Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

  12. Gene therapy of cancer by vaccines carrying inserted immunostimulatory genes

    Czech Academy of Sciences Publication Activity Database

    Bubeník, Jan

    2007-01-01

    Roč. 53, č. 3 (2007), s. 71-73 ISSN 0015-5500 Grant - others:EU-FP6 NoE Clinigene(XE) 018933; Liga proti rakovině, Praha(CZ) XX Institutional research plan: CEZ:AV0Z50520514 Keywords : gene therapy * immunostimulatory genes * vaccine Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 0.596, year: 2007

  13. Combining Gene Signatures Improves Prediction of Breast Cancer Survival

    Science.gov (United States)

    Zhao, Xi; Naume, Bjørn; Langerød, Anita; Frigessi, Arnoldo; Kristensen, Vessela N.; Børresen-Dale, Anne-Lise; Lingjærde, Ole Christian

    2011-01-01

    Background Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123) and test set (n = 81), respectively. Gene sets from eleven previously published gene signatures are included in the study. Principal Findings To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014). Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001). The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. Conclusion Combining the predictive strength of multiple gene signatures improves prediction of breast

  14. Combining gene signatures improves prediction of breast cancer survival.

    Directory of Open Access Journals (Sweden)

    Xi Zhao

    Full Text Available BACKGROUND: Several gene sets for prediction of breast cancer survival have been derived from whole-genome mRNA expression profiles. Here, we develop a statistical framework to explore whether combination of the information from such sets may improve prediction of recurrence and breast cancer specific death in early-stage breast cancers. Microarray data from two clinically similar cohorts of breast cancer patients are used as training (n = 123 and test set (n = 81, respectively. Gene sets from eleven previously published gene signatures are included in the study. PRINCIPAL FINDINGS: To investigate the relationship between breast cancer survival and gene expression on a particular gene set, a Cox proportional hazards model is applied using partial likelihood regression with an L2 penalty to avoid overfitting and using cross-validation to determine the penalty weight. The fitted models are applied to an independent test set to obtain a predicted risk for each individual and each gene set. Hierarchical clustering of the test individuals on the basis of the vector of predicted risks results in two clusters with distinct clinical characteristics in terms of the distribution of molecular subtypes, ER, PR status, TP53 mutation status and histological grade category, and associated with significantly different survival probabilities (recurrence: p = 0.005; breast cancer death: p = 0.014. Finally, principal components analysis of the gene signatures is used to derive combined predictors used to fit a new Cox model. This model classifies test individuals into two risk groups with distinct survival characteristics (recurrence: p = 0.003; breast cancer death: p = 0.001. The latter classifier outperforms all the individual gene signatures, as well as Cox models based on traditional clinical parameters and the Adjuvant! Online for survival prediction. CONCLUSION: Combining the predictive strength of multiple gene signatures improves

  15. DNMT1-interacting RNAs block gene specific DNA methylation

    Science.gov (United States)

    Di Ruscio, Annalisa; Ebralidze, Alexander K.; Benoukraf, Touati; Amabile, Giovanni; Goff, Loyal A.; Terragni, Joylon; Figueroa, Maria Eugenia; De Figureido Pontes, Lorena Lobo; Alberich-Jorda, Meritxell; Zhang, Pu; Wu, Mengchu; D’Alò, Francesco; Melnick, Ari; Leone, Giuseppe; Ebralidze, Konstantin K.; Pradhan, Sriharsa; Rinn, John L.; Tenen, Daniel G.

    2013-01-01

    Summary DNA methylation was described almost a century ago. However, the rules governing its establishment and maintenance remain elusive. Here, we present data demonstrating that active transcription regulates levels of genomic methylation. We identified a novel RNA arising from the CEBPA gene locus critical in regulating the local DNA methylation profile. This RNA binds to DNMT1 and prevents CEBPA gene locus methylation. Deep sequencing of transcripts associated with DNMT1 combined with genome-scale methylation and expression profiling extended the generality of this finding to numerous gene loci. Collectively, these results delineate the nature of DNMT1-RNA interactions and suggest strategies for gene selective demethylation of therapeutic targets in disease. PMID:24107992

  16. Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

    Directory of Open Access Journals (Sweden)

    Yang X

    2018-03-01

    Full Text Available Xiao Yang,1 Shaoming Zhu,2 Li Li,3 Li Zhang,1 Shu Xian,1 Yanqing Wang,1 Yanxiang Cheng1 1Department of Obstetrics and Gynecology, 2Department of Urology, Renmin Hospital of Wuhan University, 3Department of Pharmacology, Wuhan University Health Science Center, Wuhan, Hubei, People’s Republic of China Background: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. Results: The expression profiles of GDS3592, GSE54388, and GSE66957 were downloaded from the Gene Expression Omnibus (GEO database, which contained 115 samples, including 85 cases of ovarian cancer samples and 30 cases of normal ovarian samples. The three microarray datasets were integrated to obtain differentially expressed genes (DEGs and were deeply analyzed by bioinformatics methods. The gene ontology (GO and Kyoto Encyclopedia of Genes and Genomes (KEGG pathway enrichments of DEGs were performed by DAVID and KOBAS online analyses, respectively. The protein–protein interaction (PPI networks of the DEGs were constructed from the STRING database. A total of 190 DEGs were identified in the three GEO datasets, of which 99 genes were upregulated and 91 genes were downregulated. GO analysis showed that the biological functions of DEGs focused primarily on regulating cell proliferation, adhesion, and differentiation and intracellular signal cascades. The main cellular components include cell membranes, exosomes, the cytoskeleton, and the extracellular matrix. The molecular functions include growth factor activity, protein kinase regulation, DNA binding, and oxygen transport activity. KEGG pathway analysis showed that these DEGs were mainly involved in the Wnt signaling pathway, amino acid metabolism, and the

  17. Gene set analysis of purine and pyrimidine antimetabolites cancer therapies.

    Science.gov (United States)

    Fridley, Brooke L; Batzler, Anthony; Li, Liang; Li, Fang; Matimba, Alice; Jenkins, Gregory D; Ji, Yuan; Wang, Liewei; Weinshilboum, Richard M

    2011-11-01

    Responses to therapies, either with regard to toxicities or efficacy, are expected to involve complex relationships of gene products within the same molecular pathway or functional gene set. Therefore, pathways or gene sets, as opposed to single genes, may better reflect the true underlying biology and may be more appropriate units for analysis of pharmacogenomic studies. Application of such methods to pharmacogenomic studies may enable the detection of more subtle effects of multiple genes in the same pathway that may be missed by assessing each gene individually. A gene set analysis of 3821 gene sets is presented assessing the association between basal messenger RNA expression and drug cytotoxicity using ethnically defined human lymphoblastoid cell lines for two classes of drugs: pyrimidines [gemcitabine (dFdC) and arabinoside] and purines [6-thioguanine and 6-mercaptopurine]. The gene set nucleoside-diphosphatase activity was found to be significantly associated with both dFdC and arabinoside, whereas gene set γ-aminobutyric acid catabolic process was associated with dFdC and 6-thioguanine. These gene sets were significantly associated with the phenotype even after adjusting for multiple testing. In addition, five associated gene sets were found in common between the pyrimidines and two gene sets for the purines (3',5'-cyclic-AMP phosphodiesterase activity and γ-aminobutyric acid catabolic process) with a P value of less than 0.0001. Functional validation was attempted with four genes each in gene sets for thiopurine and pyrimidine antimetabolites. All four genes selected from the pyrimidine gene sets (PSME3, CANT1, ENTPD6, ADRM1) were validated, but only one (PDE4D) was validated for the thiopurine gene sets. In summary, results from the gene set analysis of pyrimidine and purine therapies, used often in the treatment of various cancers, provide novel insight into the relationship between genomic variation and drug response.

  18. Blood lead levels, iron metabolism gene polymorphisms and homocysteine: a gene-environment interaction study.

    Science.gov (United States)

    Kim, Kyoung-Nam; Lee, Mee-Ri; Lim, Youn-Hee; Hong, Yun-Chul

    2017-12-01

    Homocysteine has been causally associated with various adverse health outcomes. Evidence supporting the relationship between lead and homocysteine levels has been accumulating, but most prior studies have not focused on the interaction with genetic polymorphisms. From a community-based prospective cohort, we analysed 386 participants (aged 41-71 years) with information regarding blood lead and plasma homocysteine levels. Blood lead levels were measured between 2001 and 2003, and plasma homocysteine levels were measured in 2007. Interactions of lead levels with 42 genotyped single-nucleotide polymorphisms (SNPs) in five genes ( TF , HFE , CBS , BHMT and MTR ) were assessed via a 2-degree of freedom (df) joint test and a 1-df interaction test. In secondary analyses using imputation, we further assessed 58 imputed SNPs in the TF and MTHFR genes. Blood lead concentrations were positively associated with plasma homocysteine levels (p=0.0276). Six SNPs in the TF and MTR genes were screened using the 2-df joint test, and among them, three SNPs in the TF gene showed interactions with lead with respect to homocysteine levels through the 1-df interaction test (plead levels. Blood lead levels were positively associated with plasma homocysteine levels measured 4-6 years later, and three SNPs in the TF gene modified the association. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  19. Major cancer protein amplifies global gene expression

    Science.gov (United States)

    Scientists may have discovered why a protein called MYC can provoke a variety of cancers. Like many proteins associated with cancer, MYC helps regulate cell growth. A new study carried out by researchers at the National Institutes of Health and colleagues

  20. EXSPRESSION OF MDR-GENES AND MONORESISTANCE GENES IN NON-SMALL-CELL LUNG CANCER

    Directory of Open Access Journals (Sweden)

    E. L. Yumov

    2014-01-01

    Full Text Available We studied the expression of multidrug resistance genes (MDR and monoresistance genes in normal bronchial tissue and tumor tissue of the non-small cell lung cancer (NSCLC after neoadjuvant chemotherapy (NACT (vinorelbine-carboplatine. The study included 30 patients with NSCLC (Т2–4N0–3M0. Normal bronchial tissue, normal lung tissue and tumor tissue collected during surgery following neoadjuvant chemotherapy (NACT served as a material of the study. The expression levels of MDR genes (ABCB1, ABCB2, ABCC1, ABCC2, ABCС5, ABCG1, ABCG2, GSTP and MVP, and monoresistance genes (BRCA1, ERCC1, RRM1, TOP1, TOP2A, TUBB3 and TYMS were estimated by quantitative reverse transcriptase PCR (RT-qPCR. The expression levels of some MDR genes and monoresistance genes (АВСВ1, АВСВ2, ABCG1, ERCC1, GSTP1 and MVP were significantly higher in the bronchi than in tumor tissue. The expression of ABCG1, ABCG2 and ERCC1 genes was higher in patients with T1-2 cancer than in patients with T3-4 cancer. Patients with adenocarcinoma had higher expression of BRCA1, MVP and ABCB1 genes than patients with squamous cell lung cancer. A tendency towards reduction in the expression level of MDR-genes and monoresistance genes was observed in patients with partial tumor regression compared to that observed in patients with stable disease. These findings were consistent with the previous data on reduction in the MDR-gene expression after chemotherapy with a good response in breast cancer patients.

  1. Robust multi-tissue gene panel for cancer detection

    Directory of Open Access Journals (Sweden)

    Talantov Dmitri

    2010-06-01

    Full Text Available Abstract Background We have identified a set of genes whose relative mRNA expression levels in various solid tumors can be used to robustly distinguish cancer from matching normal tissue. Our current feature set consists of 113 gene probes for 104 unique genes, originally identified as differentially expressed in solid primary tumors in microarray data on Affymetrix HG-U133A platform in five tissue types: breast, colon, lung, prostate and ovary. For each dataset, we first identified a set of genes significantly differentially expressed in tumor vs. normal tissue at p-value = 0.05 using an experimentally derived error model. Our common cancer gene panel is the intersection of these sets of significantly dysregulated genes and can distinguish tumors from normal tissue on all these five tissue types. Methods Frozen tumor specimens were obtained from two commercial vendors Clinomics (Pittsfield, MA and Asterand (Detroit, MI. Biotinylated targets were prepared using published methods (Affymetrix, CA and hybridized to Affymetrix U133A GeneChips (Affymetrix, CA. Expression values for each gene were calculated using Affymetrix GeneChip analysis software MAS 5.0. We then used a software package called Genes@Work for differential expression discovery, and SVM light linear kernel for building classification models. Results We validate the predictability of this gene list on several publicly available data sets generated on the same platform. Of note, when analysing the lung cancer data set of Spira et al, using an SVM linear kernel classifier, our gene panel had 94.7% leave-one-out accuracy compared to 87.8% using the gene panel in the original paper. In addition, we performed high-throughput validation on the Dana Farber Cancer Institute GCOD database and several GEO datasets. Conclusions Our result showed the potential for this panel as a robust classification tool for multiple tumor types on the Affymetrix platform, as well as other whole genome arrays

  2. Anti-EGFR immunonanoparticles containing IL12 and salmosin genes for targeted cancer gene therapy.

    Science.gov (United States)

    Kim, Jung Seok; Kang, Seong Jae; Jeong, Hwa Yeon; Kim, Min Woo; Park, Sang Il; Lee, Yeon Kyung; Kim, Hong Sung; Kim, Keun Sik; Park, Yong Serk

    2016-09-01

    Tumor-directed gene delivery is of major interest in the field of cancer gene therapy. Varied functionalizations of non-viral vectors have been suggested to enhance tumor targetability. In the present study, we prepared two different types of anti-EGF receptor (EGFR) immunonanoparticles containing pDNA, neutrally charged liposomes and cationic lipoplexes, for tumor-directed transfection of cancer therapeutic genes. Even though both anti-EGFR immunonanoparticles had a high binding affinity to the EGFR-positive cancer cells, the anti-EGFR immunolipoplex formulation exhibited approximately 100-fold higher transfection to the target cells than anti-EGFR immunoliposomes. The lipoplex formulation also showed a higher transfection to SK-OV-3 tumor xenografts in mice. Thus, IL12 and/or salmosin genes were loaded in the anti-EGFR immunolipoplexes and intravenously administered to mice carrying SK-OV-3 tumors. Co-transfection of IL12 and salmosin genes using anti-EGFR immunolipoplexes significantly reduced tumor growth and pulmonary metastasis. Furthermore, combinatorial treatment with doxorubicin synergistically inhibited tumor growth. These results suggest that anti-EGFR immunolipoplexes containing pDNA encoding therapeutic genes could be utilized as a gene-transfer modality for cancer gene therapy.

  3. Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity

    Directory of Open Access Journals (Sweden)

    Sucheston Lara

    2010-09-01

    Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

  4. Mining disease genes using integrated protein-protein interaction and gene-gene co-regulation information.

    Science.gov (United States)

    Li, Jin; Wang, Limei; Guo, Maozu; Zhang, Ruijie; Dai, Qiguo; Liu, Xiaoyan; Wang, Chunyu; Teng, Zhixia; Xuan, Ping; Zhang, Mingming

    2015-01-01

    In humans, despite the rapid increase in disease-associated gene discovery, a large proportion of disease-associated genes are still unknown. Many network-based approaches have been used to prioritize disease genes. Many networks, such as the protein-protein interaction (PPI), KEGG, and gene co-expression networks, have been used. Expression quantitative trait loci (eQTLs) have been successfully applied for the determination of genes associated with several diseases. In this study, we constructed an eQTL-based gene-gene co-regulation network (GGCRN) and used it to mine for disease genes. We adopted the random walk with restart (RWR) algorithm to mine for genes associated with Alzheimer disease. Compared to the Human Protein Reference Database (HPRD) PPI network alone, the integrated HPRD PPI and GGCRN networks provided faster convergence and revealed new disease-related genes. Therefore, using the RWR algorithm for integrated PPI and GGCRN is an effective method for disease-associated gene mining.

  5. Frequent epigenetic inactivation of Wnt antagonist genes in breast cancer

    Science.gov (United States)

    Suzuki, H; Toyota, M; Caraway, H; Gabrielson, E; Ohmura, T; Fujikane, T; Nishikawa, N; Sogabe, Y; Nojima, M; Sonoda, T; Mori, M; Hirata, K; Imai, K; Shinomura, Y; Baylin, S B; Tokino, T

    2008-01-01

    Although mutation of APC or CTNNB1 (β-catenin) is rare in breast cancer, activation of Wnt signalling is nonetheless thought to play an important role in breast tumorigenesis, and epigenetic silencing of Wnt antagonist genes, including the secreted frizzled-related protein (SFRP) and Dickkopf (DKK) families, has been observed in various tumours. In breast cancer, frequent methylation and silencing of SFRP1 was recently documented; however, altered expression of other Wnt antagonist genes is largely unknown. In the present study, we found frequent methylation of SFRP family genes in breast cancer cell lines (SFRP1, 7 out of 11, 64%; SFRP2, 11 out of 11, 100%; SFRP5, 10 out of 11, 91%) and primary breast tumours (SFRP1, 31 out of 78, 40%; SFRP2, 60 out of 78, 77%; SFRP5, 55 out of 78, 71%). We also observed methylation of DKK1, although less frequently, in cell lines (3 out of 11, 27%) and primary tumours (15 out of 78, 19%). Breast cancer cell lines express various Wnt ligands, and overexpression of SFRPs inhibited cancer cell growth. In addition, overexpression of a β-catenin mutant and depletion of SFRP1 using small interfering RNA synergistically upregulated transcriptional activity of T-cell factor/lymphocyte enhancer factor. Our results confirm the frequent methylation and silencing of Wnt antagonist genes in breast cancer, and suggest that their loss of function contributes to activation of Wnt signalling in breast carcinogenesis. PMID:18283316

  6. Overexpression screens identify conserved dosage chromosome instability genes in yeast and human cancer

    Science.gov (United States)

    Duffy, Supipi; Fam, Hok Khim; Wang, Yi Kan; Styles, Erin B.; Kim, Jung-Hyun; Ang, J. Sidney; Singh, Tejomayee; Larionov, Vladimir; Shah, Sohrab P.; Andrews, Brenda; Boerkoel, Cornelius F.; Hieter, Philip

    2016-01-01

    Somatic copy number amplification and gene overexpression are common features of many cancers. To determine the role of gene overexpression on chromosome instability (CIN), we performed genome-wide screens in the budding yeast for yeast genes that cause CIN when overexpressed, a phenotype we refer to as dosage CIN (dCIN), and identified 245 dCIN genes. This catalog of genes reveals human orthologs known to be recurrently overexpressed and/or amplified in tumors. We show that two genes, TDP1, a tyrosyl-DNA-phosphdiesterase, and TAF12, an RNA polymerase II TATA-box binding factor, cause CIN when overexpressed in human cells. Rhabdomyosarcoma lines with elevated human Tdp1 levels also exhibit CIN that can be partially rescued by siRNA-mediated knockdown of TDP1. Overexpression of dCIN genes represents a genetic vulnerability that could be leveraged for selective killing of cancer cells through targeting of an unlinked synthetic dosage lethal (SDL) partner. Using SDL screens in yeast, we identified a set of genes that when deleted specifically kill cells with high levels of Tdp1. One gene was the histone deacetylase RPD3, for which there are known inhibitors. Both HT1080 cells overexpressing hTDP1 and rhabdomyosarcoma cells with elevated levels of hTdp1 were more sensitive to histone deacetylase inhibitors valproic acid (VPA) and trichostatin A (TSA), recapitulating the SDL interaction in human cells and suggesting VPA and TSA as potential therapeutic agents for tumors with elevated levels of hTdp1. The catalog of dCIN genes presented here provides a candidate list to identify genes that cause CIN when overexpressed in cancer, which can then be leveraged through SDL to selectively target tumors. PMID:27551064

  7. Identification of upstream transcription factors (TFs) for expression signature genes in breast cancer.

    Science.gov (United States)

    Zang, Hongyan; Li, Ning; Pan, Yuling; Hao, Jingguang

    2017-03-01

    Breast cancer is a common malignancy among women with a rising incidence. Our intention was to detect transcription factors (TFs) for deeper understanding of the underlying mechanisms of breast cancer. Integrated analysis of gene expression datasets of breast cancer was performed. Then, functional annotation of differentially expressed genes (DEGs) was conducted, including Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Furthermore, TFs were identified and a global transcriptional regulatory network was constructed. Seven publically available GEO datasets were obtained, and a set of 1196 DEGs were identified (460 up-regulated and 736 down-regulated). Functional annotation results showed that cell cycle was the most significantly enriched pathway, which was consistent with the fact that cell cycle is closely related to various tumors. Fifty-three differentially expressed TFs were identified, and the regulatory networks consisted of 817 TF-target interactions between 46 TFs and 602 DEGs in the context of breast cancer. Top 10 TFs covering the most downstream DEGs were SOX10, NFATC2, ZNF354C, ARID3A, BRCA1, FOXO3, GATA3, ZEB1, HOXA5 and EGR1. The transcriptional regulatory networks could enable a better understanding of regulatory mechanisms of breast cancer pathology and provide an opportunity for the development of potential therapy.

  8. Interaction between common breast cancer susceptibility variants, genetic ancestry, and nongenetic risk factors in Hispanic women.

    Science.gov (United States)

    Fejerman, Laura; Stern, Mariana C; John, Esther M; Torres-Mejía, Gabriela; Hines, Lisa M; Wolff, Roger K; Baumgartner, Kathy B; Giuliano, Anna R; Ziv, Elad; Pérez-Stable, Eliseo J; Slattery, Martha L

    2015-11-01

    Most genetic variants associated with breast cancer risk have been discovered in women of European ancestry, and only a few genome-wide association studies (GWAS) have been conducted in minority groups. This research disparity persists in post-GWAS gene-environment interaction analyses. We tested the interaction between hormonal and lifestyle risk factors for breast cancer, and ten GWAS-identified SNPs among 2,107 Hispanic women with breast cancer and 2,587 unaffected controls, to gain insight into a previously reported gene by ancestry interaction in this population. We estimated genetic ancestry with a set of 104 ancestry-informative markers selected to discriminate between Indigenous American and European ancestry. We used logistic regression models to evaluate main effects and interactions. We found that the rs13387042-2q35(G/A) SNP was associated with breast cancer risk only among postmenopausal women who never used hormone therapy [per A allele OR: 0.94 (95% confidence intervals, 0.74-1.20), 1.20 (0.94-1.53), and 1.49 (1.28-1.75) for current, former, and never hormone therapy users, respectively, Pinteraction 0.002] and premenopausal women who breastfed >12 months [OR: 1.01 (0.72-1.42), 1.19 (0.98-1.45), and 1.69 (1.26-2.26) for never, 12 months breastfeeding, respectively, Pinteraction 0.014]. The correlation between genetic ancestry, hormone replacement therapy use, and breastfeeding behavior partially explained a previously reported interaction between a breast cancer risk variant and genetic ancestry in Hispanic women. These results highlight the importance of understanding the interplay between genetic ancestry, genetics, and nongenetic risk factors and their contribution to breast cancer risk. ©2015 American Association for Cancer Research.

  9. Mapping Interactive Cancer Susceptibility Genes in Prostate Cancer

    Science.gov (United States)

    2007-04-01

    interval within intron 5 of FHIT. Since non- exonic causative mutations are difficult to identify, we employed an approach looking for signatures of...natural selection in this region within human populations to better understand the potential nature of any disease mutation(s). Since non- exonic ...0.523 0.126 CYP3A4 7 98.999-99.026 D7S647 199496 0.79 98.913 195 0.510 0.300 EZH2 7 147.961-147.982 D7S688 199984 0.84 147.981 49 0.478 0.687 PTEN 10

  10. Association of apolipoprotein e gene polymorphisms with blood lipids and their interaction with dietary factors

    DEFF Research Database (Denmark)

    Shatwan, Israa M.; Winther, Kristian Hillert; Ellahi, Basma

    2018-01-01

    of two single nucleotide polymorphisms (SNPs) at LPL, seven tagging SNPs at the APOE gene, and a common APOE haplotype (two SNPs) with blood lipids, and examined the interaction of these SNPs with dietary factors. Methods: The population studied for this investigation included 660 individuals from...... the Prevention of Cancer by Intervention with Selenium (PRECISE) study who supplied baseline data. The findings of the PRECISE study were further replicated using 1238 individuals from the Caerphilly Prospective cohort (CaPS). Dietary intake was assessed using a validated food-frequency questionnaire (FFQ......Background: Several candidate genes have been identified in relation to lipid metabolism, and among these, lipoprotein lipase (LPL) and apolipoprotein E (APOE) gene polymorphisms are major sources of genetically determined variation in lipid concentrations. This study investigated the association...

  11. Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.

    Science.gov (United States)

    Li, Yongsheng; Xu, Juan; Chen, Hong; Zhao, Zheng; Li, Shengli; Bai, Jing; Wu, Aiwei; Jiang, Chunjie; Wang, Yuan; Su, Bin; Li, Xia

    2013-01-01

    DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery. In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome. We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.

  12. Expression of circadian clock genes and proteins in urothelial cancer is related to cancer-associated genes

    International Nuclear Information System (INIS)

    Litlekalsoy, Jorunn; Rostad, Kari; Kalland, Karl-Henning; Hostmark, Jens G.; Laerum, Ole Didrik

    2016-01-01

    The purpose of this study was to evaluate invasive and metastatic potential of urothelial cancer by investigating differential expression of various clock genes/proteins participating in the 24 h circadian rhythms and to compare these gene expressions with transcription of other cancer-associated genes. Twenty seven paired samples of tumour and benign tissue collected from patients who underwent cystectomy were analysed and compared to 15 samples of normal bladder tissue taken from patients who underwent cystoscopy for benign prostate hyperplasia (unrelated donors). Immunohistochemical analyses were made for clock and clock-related proteins. In addition, the gene-expression levels of 22 genes (clock genes, casein kinases, oncogenes, tumour suppressor genes and cytokeratins) were analysed by real-time quantitative PCR (qPCR). Considerable up- or down-regulation and altered cellular distribution of different clock proteins, a reduction of casein kinase1A1 (CSNK1A1) and increase of casein kinase alpha 1 E (CSNK1E) were found. The pattern was significantly correlated with simultaneous up-regulation of stimulatory tumour markers, and a down-regulation of several suppressor genes. The pattern was mainly seen in aneuploid high-grade cancers. Considerable alterations were also found in the neighbouring bladder mucosa. The close correlation between altered expression of various clock genes and common tumour markers in urothelial cancer indicates that disturbed function in the cellular clock work may be an important additional mechanism contributing to cancer progression and malignant behaviour. The online version of this article (doi:10.1186/s12885-016-2580-y) contains supplementary material, which is available to authorized users

  13. Mutation analysis of breast cancer gene BRCA among breast cancer Jordanian females

    International Nuclear Information System (INIS)

    Atoum, Manar F.; Al-Kayed, Sameer A.

    2004-01-01

    To screen mutations of the tumor suppressor breast cancer susceptibility gene 1 (BRCA1) within 3 exons among Jordanian breast cancer females. A total of 135 Jordanian breast cancer females were genetically analyzed by denaturing gradient electrophoresis (DGGE) for mutation detection in 3 BRCA1 exons (2, 11 and 20) between 2000-2002 in Al-Basheer Hospital, Amman, Jordan. Of the studied patients 50 had a family history of breast cancer, 28 had a family history of cancer other than breast cancer, and 57 had no family history of any cancer. Five germline mutations were detected among breast cancer females with a family history of breast cancers (one in exon 2 and 4 mutations in exon 11). Another germline mutation (within exon 11) was detected among breast cancer females with family history of cancer other than breast cancer, and no mutation was detected among breast cancer females with no family history of any cancer or among normal control females. Screening mutations within exon 2, exon 11 and exon 20 showed that most screened mutations were within BRCA1 exon 11 among breast cancer Jordanian families with a family history of breast cancer. (author)

  14. BTG2 Antiproliferative Gene and Prostate Cancer

    National Research Council Canada - National Science Library

    Walden, Paul D

    2008-01-01

    .... During this study we showed that BTG2 protein expression is lost as an early event in prostate carcinogenesis and that prostate cancer cells degrade BTG2 at a greater rate than noncancerous prostate cells...

  15. P53 Gene Mutagenesis in Breast Cancer

    National Research Council Canada - National Science Library

    Sommer, Steve S

    2005-01-01

    .... The central hypothesis of this proposal is that variability in the patterns of p53 mutagensis in breast cancer reflects differences in exposures to different amounts and/or types of diverse environmental mutagens...

  16. Prognostic Gene Expression Profiles in Breast Cancer

    DEFF Research Database (Denmark)

    Sørensen, Kristina Pilekær

    Each year approximately 4,800 Danish women are diagnosed with breast cancer. Several clinical and pathological factors are used as prognostic and predictive markers to categorize the patients into groups of high or low risk. Around 90% of all patients are allocated to the high risk group...... clinical courses, and they may be useful as novel prognostic biomarkers in breast cancer. The aim of the present project was to predict the development of metastasis in lymph node negative breast cancer patients by RNA profiling. We collected and analyzed 82 primary breast tumors from patients who...... and the time of event. Previous findings have shown that high expression of the lncRNA HOTAIR is correlated with poor survival in breast cancer. We validated this finding by demonstrating that high HOTAIR expression in our primary tumors was significantly associated with worse prognosis independent...

  17. Association testing to detect gene-gene interactions on sex chromosomes in trio data

    Directory of Open Access Journals (Sweden)

    Yeonok eLee

    2013-11-01

    Full Text Available Autism Spectrum Disorder (ASD occurs more often among males than females in a 4:1 ratio. Among theories used to explain the causes of ASD, the X chromosome and the Y chromosome theories attribute ASD to X-linked mutation and the male-limited gene expressions on the Y chromosome, respectively. Despite the rationale of the theory, studies have failed to attribute the sex-biased ratio to the significant linkage or association on the regions of interest on X chromosome. We further study the gender biased ratio by examining the possible interaction effects between two genes in the sex chromosomes. We propose a logistic regression model with mixed effects to detect gene-gene interactions on sex chromosomes. We investigated the power and type I error rates of the approach for a range of minor allele frequencies and varying linkage disequilibrium between markers and QTLs. We also evaluated the robustness of the model to population stratification. We applied the model to a trio-family data set with an ASD affected male child to study gene-gene interactions on sex chromosomes.

  18. Risk of metachronous colon cancer following surgery for rectal cancer in mismatch repair gene mutation carriers.

    Science.gov (United States)

    Win, Aung Ko; Parry, Susan; Parry, Bryan; Kalady, Matthew F; Macrae, Finlay A; Ahnen, Dennis J; Young, Graeme P; Lipton, Lara; Winship, Ingrid; Boussioutas, Alex; Young, Joanne P; Buchanan, Daniel D; Arnold, Julie; Le Marchand, Loïc; Newcomb, Polly A; Haile, Robert W; Lindor, Noralane M; Gallinger, Steven; Hopper, John L; Jenkins, Mark A

    2013-06-01

    Despite regular surveillance colonoscopy, the metachronous colorectal cancer risk for mismatch repair (MMR) gene mutation carriers after segmental resection for colon cancer is high and total or subtotal colectomy is the preferred option. However, if the index cancer is in the rectum, management decisions are complicated by considerations of impaired bowel function. We aimed to estimate the risk of metachronous colon cancer for MMR gene mutation carriers who underwent a proctectomy for index rectal cancer. This retrospective cohort study comprised 79 carriers of germline mutation in a MMR gene (18 MLH1, 55 MSH2, 4 MSH6, and 2 PMS2) from the Colon Cancer Family Registry who had had a proctectomy for index rectal cancer. Cumulative risks of metachronous colon cancer were calculated using the Kaplan-Meier method. During median 9 years (range 1-32 years) of observation since the first diagnosis of rectal cancer, 21 carriers (27 %) were diagnosed with metachronous colon cancer (incidence 24.25, 95 % confidence interval [CI] 15.81-37.19 per 1,000 person-years). Cumulative risk of metachronous colon cancer was 19 % (95 % CI 9-31 %) at 10 years, 47 (95 % CI 31-68 %) at 20 years, and 69 % (95 % CI 45-89 %) at 30 years after surgical resection. The frequency of surveillance colonoscopy was 1 colonoscopy per 1.16 years (95 % CI 1.01-1.31 years). The AJCC stages of the metachronous cancers, where available, were 72 % stage I, 22 % stage II, and 6 % stage III. Given the high metachronous colon cancer risk for MMR gene mutation carriers diagnosed with an index rectal cancer, proctocolectomy may need to be considered.

  19. Gene Therapy for Pancreatic Cancer: Specificity, Issues and Hopes.

    Science.gov (United States)

    Rouanet, Marie; Lebrin, Marine; Gross, Fabian; Bournet, Barbara; Cordelier, Pierre; Buscail, Louis

    2017-06-08

    A recent death projection has placed pancreatic ductal adenocarcinoma as the second cause of death by cancer in 2030. The prognosis for pancreatic cancer is very poor and there is a great need for new treatments that can change this poor outcome. Developments of therapeutic innovations in combination with conventional chemotherapy are needed urgently. Among innovative treatments the gene therapy offers a promising avenue. The present review gives an overview of the general strategy of gene therapy as well as the limitations and stakes of the different experimental in vivo models, expression vectors (synthetic and viral), molecular tools (interference RNA, genome editing) and therapeutic genes (tumor suppressor genes, antiangiogenic and pro-apoptotic genes, suicide genes). The latest developments in pancreatic carcinoma gene therapy are described including gene-based tumor cell sensitization to chemotherapy, vaccination and adoptive immunotherapy (chimeric antigen receptor T-cells strategy). Nowadays, there is a specific development of oncolytic virus therapies including oncolytic adenoviruses, herpes virus, parvovirus or reovirus. A summary of all published and on-going phase-1 trials is given. Most of them associate gene therapy and chemotherapy or radiochemotherapy. The first results are encouraging for most of the trials but remain to be confirmed in phase 2 trials.

  20. Hereditary cancer genes are highly susceptible to splicing mutations

    Science.gov (United States)

    Soemedi, Rachel; Maguire, Samantha; Murray, Michael F.; Monaghan, Sean F.

    2018-01-01

    Substitutions that disrupt pre-mRNA splicing are a common cause of genetic disease. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations mapping to the canonical 5′ and 3′ splice sites. However, splicing mutations present in exons and deeper intronic positions are vastly underreported. A recent re-analysis of coding mutations in exon 10 of the Lynch Syndrome gene, MLH1, revealed an extremely high rate (77%) of mutations that lead to defective splicing. This finding is confirmed by extending the sampling to five other exons in the MLH1 gene. Further analysis suggests a more general phenomenon of defective splicing driving Lynch Syndrome. Of the 36 mutations tested, 11 disrupted splicing. Furthermore, analyzing past reports suggest that MLH1 mutations in canonical splice sites also occupy a much higher fraction (36%) of total mutations than expected. When performing a comprehensive analysis of splicing mutations in human disease genes, we found that three main causal genes of Lynch Syndrome, MLH1, MSH2, and PMS2, belonged to a class of 86 disease genes which are enriched for splicing mutations. Other cancer genes were also enriched in the 86 susceptible genes. The enrichment of splicing mutations in hereditary cancers strongly argues for additional priority in interpreting clinical sequencing data in relation to cancer and splicing. PMID:29505604

  1. Hereditary cancer genes are highly susceptible to splicing mutations.

    Directory of Open Access Journals (Sweden)

    Christy L Rhine

    2018-03-01

    Full Text Available Substitutions that disrupt pre-mRNA splicing are a common cause of genetic disease. On average, 13.4% of all hereditary disease alleles are classified as splicing mutations mapping to the canonical 5' and 3' splice sites. However, splicing mutations present in exons and deeper intronic positions are vastly underreported. A recent re-analysis of coding mutations in exon 10 of the Lynch Syndrome gene, MLH1, revealed an extremely high rate (77% of mutations that lead to defective splicing. This finding is confirmed by extending the sampling to five other exons in the MLH1 gene. Further analysis suggests a more general phenomenon of defective splicing driving Lynch Syndrome. Of the 36 mutations tested, 11 disrupted splicing. Furthermore, analyzing past reports suggest that MLH1 mutations in canonical splice sites also occupy a much higher fraction (36% of total mutations than expected. When performing a comprehensive analysis of splicing mutations in human disease genes, we found that three main causal genes of Lynch Syndrome, MLH1, MSH2, and PMS2, belonged to a class of 86 disease genes which are enriched for splicing mutations. Other cancer genes were also enriched in the 86 susceptible genes. The enrichment of splicing mutations in hereditary cancers strongly argues for additional priority in interpreting clinical sequencing data in relation to cancer and splicing.

  2. Random Subspace Aggregation for Cancer Prediction with Gene Expression Profiles

    Directory of Open Access Journals (Sweden)

    Liying Yang

    2016-01-01

    Full Text Available Background. Precisely predicting cancer is crucial for cancer treatment. Gene expression profiles make it possible to analyze patterns between genes and cancers on the genome-wide scale. Gene expression data analysis, however, is confronted with enormous challenges for its characteristics, such as high dimensionality, small sample size, and low Signal-to-Noise Ratio. Results. This paper proposes a method, termed RS_SVM, to predict gene expression profiles via aggregating SVM trained on random subspaces. After choosing gene features through statistical analysis, RS_SVM randomly selects feature subsets to yield random subspaces and training SVM classifiers accordingly and then aggregates SVM classifiers to capture the advantage of ensemble learning. Experiments on eight real gene expression datasets are performed to validate the RS_SVM method. Experimental results show that RS_SVM achieved better classification accuracy and generalization performance in contrast with single SVM, K-nearest neighbor, decision tree, Bagging, AdaBoost, and the state-of-the-art methods. Experiments also explored the effect of subspace size on prediction performance. Conclusions. The proposed RS_SVM method yielded superior performance in analyzing gene expression profiles, which demonstrates that RS_SVM provides a good channel for such biological data.

  3. MIM, a Potential Metastasis Suppressor Gene in Bladder Cancer

    Directory of Open Access Journals (Sweden)

    Young-Goo Lee

    2002-01-01

    Full Text Available Using a modified version of the mRNA differential display technique, five human bladder cancer cell lines from low grade to metastatic were analyzed to identify differences in gene expression. A 316-bp cDNA (C11300 was isolated that was not expressed in the metastatic cell line TccSuP. Sequence analysis revealed that this gene was identical to KIAA 0429, has a 5.3-kb transcript that mapped to 8824.1. The protein is predicted to be 356 amino acids in size and has an actin-binding WH2 domain. Northern blot revealed expression in multiple normal tissues, but none in a metastatic breast cancer cell line (SKBR3 or in metastatic prostatic cancer cell lines (LNCaP, PC3. We have named this gene Missing in Metastasis (MIM and our data suggest that it may be involved in cytoskeletal organization.

  4. A novel approach to simulate gene-environment interactions in complex diseases

    Directory of Open Access Journals (Sweden)

    Nicodemi Mario

    2010-01-01

    Full Text Available Abstract Background Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.. Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS, a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte

  5. Characterization of HPV and host genome interactions in primary head and neck cancers

    Science.gov (United States)

    Parfenov, Michael; Pedamallu, Chandra Sekhar; Gehlenborg, Nils; Freeman, Samuel S.; Danilova, Ludmila; Bristow, Christopher A.; Lee, Semin; Hadjipanayis, Angela G.; Ivanova, Elena V.; Wilkerson, Matthew D.; Protopopov, Alexei; Yang, Lixing; Seth, Sahil; Song, Xingzhi; Tang, Jiabin; Ren, Xiaojia; Zhang, Jianhua; Pantazi, Angeliki; Santoso, Netty; Xu, Andrew W.; Mahadeshwar, Harshad; Wheeler, David A.; Haddad, Robert I.; Jung, Joonil; Ojesina, Akinyemi I.; Issaeva, Natalia; Yarbrough, Wendell G.; Hayes, D. Neil; Grandis, Jennifer R.; El-Naggar, Adel K.; Meyerson, Matthew; Park, Peter J.; Chin, Lynda; Seidman, J. G.; Hammerman, Peter S.; Kucherlapati, Raju; Ally, Adrian; Balasundaram, Miruna; Birol, Inanc; Bowlby, Reanne; Butterfield, Yaron S.N.; Carlsen, Rebecca; Cheng, Dean; Chu, Andy; Dhalla, Noreen; Guin, Ranabir; Holt, Robert A.; Jones, Steven J.M.; Lee, Darlene; Li, Haiyan I.; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Robertson, A. Gordon; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Wong, Tina; Protopopov, Alexei; Santoso, Netty; Lee, Semin; Parfenov, Michael; Zhang, Jianhua; Mahadeshwar, Harshad S.; Tang, Jiabin; Ren, Xiaojia; Seth, Sahil; Haseley, Psalm; Zeng, Dong; Yang, Lixing; Xu, Andrew W.; Song, Xingzhi; Pantazi, Angeliki; Bristow, Christopher; Hadjipanayis, Angela; Seidman, Jonathan; Chin, Lynda; Park, Peter J.; Kucherlapati, Raju; Akbani, Rehan; Casasent, Tod; Liu, Wenbin; Lu, Yiling; Mills, Gordon; Motter, Thomas; Weinstein, John; Diao, Lixia; Wang, Jing; Fan, You Hong; Liu, Jinze; Wang, Kai; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Buda, Elizabeth; Hayes, D. Neil; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Kimes, Patrick K.; Marron, J.S.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Parker, Joel S.; Perou, Charles M.; Prins, Jan F.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Singh, Darshan; Soloway, Mathew G.; Tan, Donghui; Veluvolu, Umadevi; Walter, Vonn; Waring, Scot; Wilkerson, Matthew D.; Wu, Junyuan; Zhao, Ni; Cherniack, Andrew D.; Hammerman, Peter S.; Tward, Aaron D.; Pedamallu, Chandra Sekhar; Saksena, Gordon; Jung, Joonil; Ojesina, Akinyemi I.; Carter, Scott L.; Zack, Travis I.; Schumacher, Steven E.; Beroukhim, Rameen; Freeman, Samuel S.; Meyerson, Matthew; Cho, Juok; Chin, Lynda; Getz, Gad; Noble, Michael S.; DiCara, Daniel; Zhang, Hailei; Heiman, David I.; Gehlenborg, Nils; Voet, Doug; Lin, Pei; Frazer, Scott; Stojanov, Petar; Liu, Yingchun; Zou, Lihua; Kim, Jaegil; Lawrence, Michael S.; Sougnez, Carrie; Lichtenstein, Lee; Cibulskis, Kristian; Lander, Eric; Gabriel, Stacey B.; Muzny, Donna; Doddapaneni, HarshaVardhan; Kovar, Christie; Reid, Jeff; Morton, Donna; Han, Yi; Hale, Walker; Chao, Hsu; Chang, Kyle; Drummond, Jennifer A.; Gibbs, Richard A.; Kakkar, Nipun; Wheeler, David; Xi, Liu; Ciriello, Giovanni; Ladanyi, Marc; Lee, William; Ramirez, Ricardo; Sander, Chris; Shen, Ronglai; Sinha, Rileen; Weinhold, Nils; Taylor, Barry S.; Aksoy, B. Arman; Dresdner, Gideon; Gao, Jianjiong; Gross, Benjamin; Jacobsen, Anders; Reva, Boris; Schultz, Nikolaus; Sumer, S. Onur; Sun, Yichao; Chan, Timothy; Morris, Luc; Stuart, Joshua; Benz, Stephen; Ng, Sam; Benz, Christopher; Yau, Christina; Baylin, Stephen B.; Cope, Leslie; Danilova, Ludmila; Herman, James G.; Bootwalla, Moiz; Maglinte, Dennis T.; Laird, Peter W.; Triche, Timothy; Weisenberger, Daniel J.; Van Den Berg, David J.; Agrawal, Nishant; Bishop, Justin; Boutros, Paul C.; Bruce, Jeff P; Byers, Lauren Averett; Califano, Joseph; Carey, Thomas E.; Chen, Zhong; Cheng, Hui; Chiosea, Simion I.; Cohen, Ezra; Diergaarde, Brenda; Egloff, Ann Marie; El-Naggar, Adel K.; Ferris, Robert L.; Frederick, Mitchell J.; Grandis, Jennifer R.; Guo, Yan; Haddad, Robert I.; Hammerman, Peter S.; Harris, Thomas; Hayes, D. Neil; Hui, Angela BY; Lee, J. Jack; Lippman, Scott M.; Liu, Fei-Fei; McHugh, Jonathan B.; Myers, Jeff; Ng, Patrick Kwok Shing; Perez-Ordonez, Bayardo; Pickering, Curtis R.; Prystowsky, Michael; Romkes, Marjorie; Saleh, Anthony D.; Sartor, Maureen A.; Seethala, Raja; Seiwert, Tanguy Y.; Si, Han; Tward, Aaron D.; Van Waes, Carter; Waggott, Daryl M.; Wiznerowicz, Maciej; Yarbrough, Wendell; Zhang, Jiexin; Zuo, Zhixiang; Burnett, Ken; Crain, Daniel; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candance; Shelton, Troy; Sherman, Mark; Yena, Peggy; Black, Aaron D.; Bowen, Jay; Frick, Jessica; Gastier-Foster, Julie M.; Harper, Hollie A.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Baboud, Julien; Jensen, Mark A.; Kahn, Ari B.; Pihl, Todd D.; Pot, David A.; Srinivasan, Deepak; Walton, Jessica S.; Wan, Yunhu; Burton, Robert; Davidsen, Tanja; Demchok, John A.; Eley, Greg; Ferguson, Martin L.; Shaw, Kenna R. Mills; Ozenberger, Bradley A.; Sheth, Margi; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean Claude; Saller, Charles; Tarvin, Katherine; Chen, Chu; Bollag, Roni; Weinberger, Paul; Golusiński, Wojciech; Golusiński, Paweł; Ibbs, Matthiew; Korski, Konstanty; Mackiewicz, Andrzej; Suchorska, Wiktoria; Szybiak, Bartosz; Wiznerowicz, Maciej; Burnett, Ken; Curley, Erin; Gardner, Johanna; Mallery, David; Penny, Robert; Shelton, Troy; Yena, Peggy; Beard, Christina; Mitchell, Colleen; Sandusky, George; Agrawal, Nishant; Ahn, Julie; Bishop, Justin; Califano, Joseph; Khan, Zubair; Bruce, Jeff P; Hui, Angela BY; Irish, Jonathan; Liu, Fei-Fei; Perez-Ordonez, Bayardo; Waldron, John; Boutros, Paul C.; Waggott, Daryl M.; Myers, Jeff; Lippman, Scott M.; Egea, Sophie; Gomez-Fernandez, Carmen; Herbert, Lynn; Bradford, Carol R.; Carey, Thomas E.; Chepeha, Douglas B.; Haddad, Andrea S.; Jones, Tamara R.; Komarck, Christine M.; Malakh, Mayya; McHugh, Jonathan B.; Moyer, Jeffrey S.; Nguyen, Ariane; Peterson, Lisa A.; Prince, Mark E.; Rozek, Laura S.; Sartor, Maureen A.; Taylor, Evan G.; Walline, Heather M.; Wolf, Gregory T.; Boice, Lori; Chera, Bhishamjit S.; Funkhouser, William K.; Gulley, Margaret L.; Hackman, Trevor G.; Hayes, D. Neil; Hayward, Michele C.; Huang, Mei; Rathmell, W. Kimryn; Salazar, Ashley H.; Shockley, William W.; Shores, Carol G.; Thorne, Leigh; Weissler, Mark C.; Wrenn, Sylvia; Zanation, Adam M.; Chiosea, Simion I.; Diergaarde, Brenda; Egloff, Ann Marie; Ferris, Robert L.; Romkes, Marjorie; Seethala, Raja; Brown, Brandee T.; Guo, Yan; Pham, Michelle; Yarbrough, Wendell G.

    2014-01-01

    Previous studies have established that a subset of head and neck tumors contains human papillomavirus (HPV) sequences and that HPV-driven head and neck cancers display distinct biological and clinical features. HPV is known to drive cancer by the actions of the E6 and E7 oncoproteins, but the molecular architecture of HPV infection and its interaction with the host genome in head and neck cancers have not been comprehensively described. We profiled a cohort of 279 head and neck cancers with next generation RNA and DNA sequencing and show that 35 (12.5%) tumors displayed evidence of high-risk HPV types 16, 33, or 35. Twenty-five cases had integration of the viral genome into one or more locations in the human genome with statistical enrichment for genic regions. Integrations had a marked impact on the human genome and were associated with alterations in DNA copy number, mRNA transcript abundance and splicing, and both inter- and intrachromosomal rearrangements. Many of these events involved genes with documented roles in cancer. Cancers with integrated vs. nonintegrated HPV displayed different patterns of DNA methylation and both human and viral gene expressions. Together, these data provide insight into the mechanisms by which HPV interacts with the human genome beyond expression of viral oncoproteins and suggest that specific integration events are an integral component of viral oncogenesis. PMID:25313082

  6. Undefined familial colorectal cancer and the role of pleiotropism in cancer susceptibility genes.

    Science.gov (United States)

    Dobbins, Sara E; Broderick, Peter; Chubb, Daniel; Kinnersley, Ben; Sherborne, Amy L; Houlston, Richard S

    2016-10-01

    Although family history is a major risk factor for colorectal cancer (CRC) a genetic diagnosis cannot be obtained in over 50 % of familial cases when screened for known CRC cancer susceptibility genes. The genetics of undefined-familial CRC is complex and recent studies have implied additional clinically actionable mutations for CRC in susceptibility genes for other cancers. To clarify the contribution of non-CRC susceptibility genes to undefined-familial CRC we conducted a mutational screen of 114 cancer susceptibility genes in 847 patients with early-onset undefined-familial CRC and 1609 controls by analysing high-coverage exome sequencing data. We implemented American College of Medical Genetics and Genomics standards and guidelines for assigning pathogenicity to variants. Globally across all 114 cancer susceptibility genes no statistically significant enrichment of likely pathogenic variants was shown (6.7 % cases 57/847, 5.3 % controls 85/1609; P = 0.15). Moreover there was no significant enrichment of mutations in genes such as TP53 or BRCA2 which have been proposed for clinical testing in CRC. In conclusion, while we identified genes that may be considered interesting candidates as determinants of CRC risk warranting further research, there is currently scant evidence to support a role for genes other than those responsible for established CRC syndromes in the clinical management of familial CRC.

  7. ETS Gene Fusions as Predictive Biomarkers of Resistance to Radiation Therapy for Prostate Cancer

    Science.gov (United States)

    2016-05-01

    phenotype  in   preclinical  models  of  prostate  cancer,  2)  to  explore  the  mechanism  of  interaction  between   ERG  (the  predominant  ETS...established  this  axis  as  a  potential  therapeutic   target.         15. SUBJECT  TERMS Prostate cancer, ETS gene fusions, ERG , radiation resistance, DNA...interaction  between   ERG   (the   predominant   ETS   gene   fusion   product)   and   the   DNA   repair   protein   DNA-­PK,   and   3)   to

  8. A novel test for gene-ancestry interactions in genome-wide association data.

    Directory of Open Access Journals (Sweden)

    Joanna L Davies

    Full Text Available Genome-wide association study (GWAS data on a disease are increasingly available from multiple related populations. In this scenario, meta-analyses can improve power to detect homogeneous genetic associations, but if there exist ancestry-specific effects, via interactions on genetic background or with a causal effect that co-varies with genetic background, then these will typically be obscured. To address this issue, we have developed a robust statistical method for detecting susceptibility gene-ancestry interactions in multi-cohort GWAS based on closely-related populations. We use the leading principal components of the empirical genotype matrix to cluster individuals into "ancestry groups" and then look for evidence of heterogeneous genetic associations with disease or other trait across these clusters. Robustness is improved when there are multiple cohorts, as the signal from true gene-ancestry interactions can then be distinguished from gene-collection artefacts by comparing the observed interaction effect sizes in collection groups relative to ancestry groups. When applied to colorectal cancer, we identified a missense polymorphism in iron-absorption gene CYBRD1 that associated with disease in individuals of English, but not Scottish, ancestry. The association replicated in two additional, independently-collected data sets. Our method can be used to detect associations between genetic variants and disease that have been obscured by population genetic heterogeneity. It can be readily extended to the identification of genetic interactions on other covariates such as measured environmental exposures. We envisage our methodology being of particular interest to researchers with existing GWAS data, as ancestry groups can be easily defined and thus tested for interactions.

  9. Human cancer cells express Slug-based epithelial-mesenchymal transition gene expression signature obtained in vivo

    International Nuclear Information System (INIS)

    Anastassiou, Dimitris; Rumjantseva, Viktoria; Cheng, Weiyi; Huang, Jianzhong; Canoll, Peter D; Yamashiro, Darrell J; Kandel, Jessica J

    2011-01-01

    The biological mechanisms underlying cancer cell motility and invasiveness remain unclear, although it has been hypothesized that they involve some type of epithelial-mesenchymal transition (EMT). We used xenograft models of human cancer cells in immunocompromised mice, profiling the harvested tumors separately with species-specific probes and computationally analyzing the results. Here we show that human cancer cells express in vivo a precise multi-cancer invasion-associated gene expression signature that prominently includes many EMT markers, among them the transcription factor Slug, fibronectin, and α-SMA. We found that human, but not mouse, cells express the signature and Slug is the only upregulated EMT-inducing transcription factor. The signature is also present in samples from many publicly available cancer gene expression datasets, suggesting that it is produced by the cancer cells themselves in multiple cancer types, including nonepithelial cancers such as neuroblastoma. Furthermore, we found that the presence of the signature in human xenografted cells was associated with a downregulation of adipocyte markers in the mouse tissue adjacent to the invasive tumor, suggesting that the signature is triggered by contextual microenvironmental interactions when the cancer cells encounter adipocytes, as previously reported. The known, precise and consistent gene composition of this cancer mesenchymal transition signature, particularly when combined with simultaneous analysis of the adjacent microenvironment, provides unique opportunities for shedding light on the underlying mechanisms of cancer invasiveness as well as identifying potential diagnostic markers and targets for metastasis-inhibiting therapeutics

  10. Genetic polymorphisms in CYP1A1, GSTM1, GSTP1 and GSTT1 metabolic genes and risk of lung cancer in Asturias

    International Nuclear Information System (INIS)

    López-Cima, M Felicitas; Álvarez-Avellón, Sara M; Pascual, Teresa; Fernández-Somoano, Ana; Tardón, Adonina

    2012-01-01

    Metabolic genes have been associated with the function of metabolizing and detoxifying environmental carcinogens. Polymorphisms present in these genes could lead to changes in their metabolizing and detoxifying ability and thus may contribute to individual susceptibility to different types of cancer. We investigated if the individual and/or combined modifying effects of the CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms are related to the risk of developing lung cancer in relation to tobacco consumption and occupation in Asturias, Northern Spain. A hospital-based case–control study (CAPUA Study) was designed including 789 lung cancer patients and 789 control subjects matched in ethnicity, age, sex, and hospital. Genotypes were determined by PCR or PCR-RFLP. Individual and combination effects were analysed using an unconditional logistic regression adjusting for age, pack-years, family history of any cancer and occupation. No statistically significant main effects were observed for the carcinogen metabolism genes in relation to lung cancer risk. In addition, the analysis did not reveal any significant gene-gene, gene-tobacco smoking or gene-occupational exposure interactions relative to lung cancer susceptibility. Lastly, no significant gene-gene combination effects were observed. These results suggest that genetic polymorphisms in the CYP1A1, GSTM1, GSTT1 and GSTP1 metabolic genes were not significantly associated with lung cancer risk in the current study. The results of the analysis of gene-gene interactions of CYP1A1 MspI T6235C, GSTM1 present/null, GSTT1 present/null and GSTP1 Ile105Val polymorphisms in lung cancer risk indicate that these genes do not interact in lung cancer development

  11. Enrichment of putative PAX8 target genes at serous epithelial ovarian cancer susceptibility loci

    DEFF Research Database (Denmark)

    Kar, Siddhartha P; Adler, Emily; Tyrer, Jonathan

    2017-01-01

    BACKGROUND: Genome-wide association studies (GWAS) have identified 18 loci associated with serous ovarian cancer (SOC) susceptibility but the biological mechanisms driving these findings remain poorly characterised. Germline cancer risk loci may be enriched for target genes of transcription factors...... (TFs) critical to somatic tumorigenesis. METHODS: All 615 TF-target sets from the Molecular Signatures Database were evaluated using gene set enrichment analysis (GSEA) and three GWAS for SOC risk: discovery (2196 cases/4396 controls), replication (7035 cases/21 693 controls; independent from discovery...... to interact with PAX8 in the literature to the PAX8-target set and applying an alternative to GSEA, interval enrichment, further confirmed this association (P=0.006). Fifteen of the 157 genes from this expanded PAX8 pathway were near eight loci associated with SOC risk at P

  12. Selenium nanoparticles: potential in cancer gene and drug delivery.

    Science.gov (United States)

    Maiyo, Fiona; Singh, Moganavelli

    2017-05-01

    In recent decades, colloidal selenium nanoparticles have emerged as exceptional selenium species with reported chemopreventative and therapeutic properties. This has sparked widespread interest in their use as a carrier of therapeutic agents with results displaying synergistic effects of selenium with its therapeutic cargo and improved anticancer activity. Functionalization remains a critical step in selenium nanoparticles' development for application in gene or drug delivery. In this review, we highlight recent developments in the synthesis and functionalization strategies of selenium nanoparticles used in cancer drug and gene delivery systems. We also provide an update of recent preclinical studies utilizing selenium nanoparticles in cancer therapeutics.

  13. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

    Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2011-01-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

  14. Prediction of epigenetically regulated genes in breast cancer cell lines

    Energy Technology Data Exchange (ETDEWEB)

    Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen; Nautiyal, Shivani; Flaucher, Diane; Carlton, Victoria EH; Moorhead, Martin; Lu, Yontao; Gray, Joe W; Faham, Malek; Spellman, Paul; Parvin, Bahram

    2010-05-04

    Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines, which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the

  15. Identification of genes containing expanded purine repeats in the human genome and their apparent protective role against cancer.

    Science.gov (United States)

    Singh, Himanshu Narayan; Rajeswari, Moganty R

    2016-01-01

    Purine repeat sequences present in a gene are unique as they have high propensity to form unusual DNA-triple helix structures. Friedreich's ataxia is the only human disease that is well known to be associated with DNA-triplexes formed by purine repeats. The purpose of this study was to recognize the expanded purine repeats (EPRs) in human genome and find their correlation with cancer pathogenesis. We developed "PuRepeatFinder.pl" algorithm to identify non-overlapping EPRs without pyrimidine interruptions in the human genome and customized for searching repeat lengths, n ≥ 200. A total of 1158 EPRs were identified in the genome which followed Wakeby distribution. Two hundred and ninety-six EPRs were found in geneic regions of 282 genes (EPR-genes). Gene clustering of EPR-genes was done based on their cellular function and a large number of EPR-genes were found to be enzymes/enzyme modulators. Meta-analysis of 282 EPR-genes identified only 63 EPR-genes in association with cancer, mostly in breast, lung, and blood cancers. Protein-protein interaction network analysis of all 282 EPR-genes identified proteins including those in cadherins and VEGF. The two observations, that EPRs can induce mutations under malignant conditions and that identification of some EPR-gene products in vital cell signaling-mediated pathways, together suggest the crucial role of EPRs in carcinogenesis. The new link between EPR-genes and their functionally interacting proteins throws a new dimension in the present understanding of cancer pathogenesis and can help in planning therapeutic strategies. Validation of present results using techniques like NGS is required to establish the role of the EPR genes in cancer pathology.

  16. Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

    Directory of Open Access Journals (Sweden)

    Ueki Masao

    2012-05-01

    Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

  17. Pancreatic Cancer Gene Therapy: From Molecular Targets to Delivery Systems

    Energy Technology Data Exchange (ETDEWEB)

    Fillat, Cristina, E-mail: cristina.fillat@crg.es; Jose, Anabel; Ros, Xavier Bofill-De; Mato-Berciano, Ana; Maliandi, Maria Victoria; Sobrevals, Luciano [Programa Gens i Malaltia, Centre de Regulació Genòmica-CRG, UPF, Parc de Recerca Biomedica de Barcelona-PRBB and Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona (Spain)

    2011-01-18

    The continuous identification of molecular changes deregulating critical pathways in pancreatic tumor cells provides us with a large number of novel candidates to engineer gene-targeted approaches for pancreatic cancer treatment. Targets—both protein coding and non-coding—are being exploited in gene therapy to influence the deregulated pathways to facilitate cytotoxicity, enhance the immune response or sensitize to current treatments. Delivery vehicles based on viral or non-viral systems as well as cellular vectors with tumor homing characteristics are a critical part of the design of gene therapy strategies. The different behavior of tumoral versus non-tumoral cells inspires vector engineering with the generation of tumor selective products that can prevent potential toxic-associated effects. In the current review, a detailed analysis of the different targets, the delivery vectors, the preclinical approaches and a descriptive update on the conducted clinical trials are presented. Moreover, future possibilities in pancreatic cancer treatment by gene therapy strategies are discussed.

  18. Functional modules by relating protein interaction networks and gene expression.

    Science.gov (United States)

    Tornow, Sabine; Mewes, H W

    2003-11-01

    Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

  19. A Gene Expression Classifier of Node-Positive Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Paul F. Meeh

    2009-10-01

    Full Text Available We used digital long serial analysis of gene expression to discover gene expression differences between node-negative and node-positive colorectal tumors and developed a multigene classifier able to discriminate between these two tumor types. We prepared and sequenced long serial analysis of gene expression libraries from one node-negative and one node-positive colorectal tumor, sequenced to a depth of 26,060 unique tags, and identified 262 tags significantly differentially expressed between these two tumors (P < 2 x 10-6. We confirmed the tag-to-gene assignments and differential expression of 31 genes by quantitative real-time polymerase chain reaction, 12 of which were elevated in the node-positive tumor. We analyzed the expression levels of these 12 upregulated genes in a validation panel of 23 additional tumors and developed an optimized seven-gene logistic regression classifier. The classifier discriminated between node-negative and node-positive tumors with 86% sensitivity and 80% specificity. Receiver operating characteristic analysis of the classifier revealed an area under the curve of 0.86. Experimental manipulation of the function of one classification gene, Fibronectin, caused profound effects on invasion and migration of colorectal cancer cells in vitro. These results suggest that the development of node-positive colorectal cancer occurs in part through elevated epithelial FN1 expression and suggest novel strategies for the diagnosis and treatment of advanced disease.

  20. Development of Peptidomimetic Inhibitors of the ERG Gene Fusion Product in Prostate Cancer.

    Science.gov (United States)

    Wang, Xiaoju; Qiao, Yuanyuan; Asangani, Irfan A; Ateeq, Bushra; Poliakov, Anton; Cieślik, Marcin; Pitchiaya, Sethuramasundaram; Chakravarthi, Balabhadrapatruni V S K; Cao, Xuhong; Jing, Xiaojun; Wang, Cynthia X; Apel, Ingrid J; Wang, Rui; Tien, Jean Ching-Yi; Juckette, Kristin M; Yan, Wei; Jiang, Hui; Wang, Shaomeng; Varambally, Sooryanarayana; Chinnaiyan, Arul M

    2017-04-10

    Transcription factors play a key role in the development of diverse cancers, and therapeutically targeting them has remained a challenge. In prostate cancer, the gene encoding the transcription factor ERG is recurrently rearranged and plays a critical role in prostate oncogenesis. Here, we identified a series of peptides that interact specifically with the DNA binding domain of ERG. ERG inhibitory peptides (EIPs) and derived peptidomimetics bound ERG with high affinity and specificity, leading to proteolytic degradation of the ERG protein. The EIPs attenuated ERG-mediated transcription, chromatin recruitment, protein-protein interactions, cell invasion and proliferation, and tumor growth. Thus, peptidomimetic targeting of transcription factor fusion products may provide a promising therapeutic strategy for prostate cancer as well as other malignancies. Copyright © 2017 Elsevier Inc. All rights reserved.

  1. Space-time interactions in childhood cancers

    International Nuclear Information System (INIS)

    Morris, V.

    1990-01-01

    During the last twenty five years, there have been sporadic published reports of cases of childhood leukaemia occurring in clusters. Renewed interest in the topic, following suggests that clusters may occur in the vicinity of nuclear establishments, has prompted this report of an investigation into 418 childhood cancer cases which occurred in the Midlands between 1953 and 1960. There was evidence among some age groups and diagnoses of an unexpectedly high number of close pairs of onsets, and some indication of similar patterns among births of children who later developed cancer. Measles appeared to occur more often in the 2-3 years before the onset of leukaemia in children who were later involved in close pairs than in their matched controls. It is concluded that common infectious diseases of childhood may play a minor role in the development of some cancers. Epidemics of these diseases may then be reflected on a greatly reduced scale in the subsequent distribution of cancer cases. (author)

  2. Notch and VEGF Interactions in Breast Cancer

    National Research Council Canada - National Science Library

    Shawber, Carrie J

    2006-01-01

    The proposal objective is to define Notch and VEGFR-3 in breast cancer. We investigated this relationship in primary endothelial cell cultures, mouse embryos, human breast tumors, and mouse mammary tumor xenografts...

  3. Gene-Gene Interactions in the Folate Metabolic Pathway and the Risk of Conotruncal Heart Defects

    Directory of Open Access Journals (Sweden)

    Philip J. Lupo

    2010-01-01

    Full Text Available Conotruncal and related heart defects (CTRD are common, complex malformations. Although there are few established risk factors, there is evidence that genetic variation in the folate metabolic pathway influences CTRD risk. This study was undertaken to assess the association between inherited (i.e., case and maternal gene-gene interactions in this pathway and the risk of CTRD. Case-parent triads (n=727, ascertained from the Children's Hospital of Philadelphia, were genotyped for ten functional variants of nine folate metabolic genes. Analyses of inherited genotypes were consistent with the previously reported association between MTHFR A1298C and CTRD (adjusted P=.02, but provided no evidence that CTRD was associated with inherited gene-gene interactions. Analyses of the maternal genotypes provided evidence of a MTHFR C677T/CBS 844ins68 interaction and CTRD risk (unadjusted P=.02. This association is consistent with the effects of this genotype combination on folate-homocysteine biochemistry but remains to be confirmed in independent study populations.

  4. Common filaggrin gene mutations and risk of cervical cancer

    DEFF Research Database (Denmark)

    Bager, Peter; Wohlfahrt, Jan; Sørensen, Erik

    2015-01-01

    BACKGROUND: As carriers of filaggrin gene (FLG) mutations may have a compromised cervical mucosal barrier against human papillomavirus infection, our primary objective was to study their risk of cervical cancer. METHODS: We genotyped 586 cervical cancer patients for the two most common FLG...... mutations, R501X and 2282del4, using blood from the Copenhagen Hospital Biobank, Denmark. Controls (n = 8050) were genotyped in previous population-based studies. Information on cervical cancer, mortality and emigration were obtained from national registers. Odds ratios (OR) were estimated by logistic...... and stratification by cancer stage. RESULTS: The primary results showed that FLG mutations were not associated with the risk of cervical cancer (6.3% of cases and 7.7% of controls were carriers; OR adjusted 0.81, 95% CI 0.57-1.14; OR adjusted+ weighted 0.96, 95% CI 0.58-1.57). Among cases, FLG mutations increased...

  5. The relationship between Prostate CAncer gene 3 (PCA3) and prostate cancer significance

    NARCIS (Netherlands)

    van Poppel, Hein; Haese, Alexander; Graefen, Markus; de la Taille, Alexandre; Irani, Jacques; de Reijke, Theo; Remzi, Mesut; Marberger, Michael

    2012-01-01

    OBJECTIVE To evaluate the relationship between Prostate CAncer gene 3 (PCA3) and prostate cancer significance. PATIENTS AND METHODS Clinical data from two multi-centre European open-label, prospective studies evaluating the clinical utility of the PCA3 assay in guiding initial and repeat biopsy

  6. Functional annotation of rare gene aberration drivers of pancreatic cancer | Office of Cancer Genomics

    Science.gov (United States)

    As we enter the era of precision medicine, characterization of cancer genomes will directly influence therapeutic decisions in the clinic. Here we describe a platform enabling functionalization of rare gene mutations through their high-throughput construction, molecular barcoding and delivery to cancer models for in vivo tumour driver screens. We apply these technologies to identify oncogenic drivers of pancreatic ductal adenocarcinoma (PDAC).

  7. Leveraging gene-environment interactions and endotypes for asthma gene discovery

    DEFF Research Database (Denmark)

    Bønnelykke, Klaus; Ober, Carole

    2016-01-01

    , such as childhood asthma with severe exacerbations, and on relevant exposures that are involved in gene-environment interactions (GEIs), such as rhinovirus infections, will improve detection of asthma genes and our understanding of the underlying mechanisms. We will discuss the challenges of considering GEIs......Asthma is a heterogeneous clinical syndrome that includes subtypes of disease with different underlying causes and disease mechanisms. Asthma is caused by a complex interaction between genes and environmental exposures; early-life exposures in particular play an important role. Asthma is also...... heritable, and a number of susceptibility variants have been discovered in genome-wide association studies, although the known risk alleles explain only a small proportion of the heritability. In this review, we present evidence supporting the hypothesis that focusing on more specific asthma phenotypes...

  8. RUNX: a trilogy of cancer genes

    DEFF Research Database (Denmark)

    Lund, Anders H; van Lohuizen, Maarten

    2002-01-01

    The RUNX family of transcription factors plays pivotal roles during normal development and in neoplasias. Recent data involve RUNX3 as an important tumor suppressor in gastric cancers and pose interesting questions about how perturbed levels and interspecific competition among RUNX family members...

  9. The role of S100 genes in breast cancer progression.

    LENUS (Irish Health Repository)

    McKiernan, Eadaoin

    2012-02-01

    The S100 gene family encode low molecular weight proteins implicated in cancer progression. In this study, we analyzed the expression of four S100 genes in one cohort of patients with breast cancer and 16 S100 genes in a second cohort. In both cohorts, the expression of S100A8 and S1009 mRNA level was elevated in high-grade compared to low-grade tumors and in estrogen receptor-negative compared to estrogen receptor-positive tumors. None of the S100 transcripts investigated were significantly associated with the presence of lymph node metastasis. Notably, multiple S100 genes, including S100A1, S100A2, S100A4, S100A6, S100A8, S100A9, S100A10, S100A11, and S100A14 were upregulated in basal-type breast cancers compared to non-basal types. Using Spearman\\'s correlation analysis, several S100 transcripts correlated significantly with each other, the strongest correlation has been found between S100A8 and S100A9 (r = 0.889, P < 0.001, n = 295). Of the 16 S100 transcripts investigated, only S100A11 and S100A14 were significantly associated with patient outcome. Indeed, these two transcripts predicted outcome in the cohort of patients that did not receive systemic adjuvant therapy. Based on our findings, we conclude that the different S100 genes play varying roles in breast cancer progression. Specific S100 genes are potential targets for the treatment of basal-type breast cancers.

  10. The role of S100 genes in breast cancer progression.

    LENUS (Irish Health Repository)

    McKiernan, Eadaoin

    2011-06-01

    The S100 gene family encode low molecular weight proteins implicated in cancer progression. In this study, we analyzed the expression of four S100 genes in one cohort of patients with breast cancer and 16 S100 genes in a second cohort. In both cohorts, the expression of S100A8 and S1009 mRNA level was elevated in high-grade compared to low-grade tumors and in estrogen receptor-negative compared to estrogen receptor-positive tumors. None of the S100 transcripts investigated were significantly associated with the presence of lymph node metastasis. Notably, multiple S100 genes, including S100A1, S100A2, S100A4, S100A6, S100A8, S100A9, S100A10, S100A11, and S100A14 were upregulated in basal-type breast cancers compared to non-basal types. Using Spearman\\'s correlation analysis, several S100 transcripts correlated significantly with each other, the strongest correlation has been found between S100A8 and S100A9 (r = 0.889, P < 0.001, n = 295). Of the 16 S100 transcripts investigated, only S100A11 and S100A14 were significantly associated with patient outcome. Indeed, these two transcripts predicted outcome in the cohort of patients that did not receive systemic adjuvant therapy. Based on our findings, we conclude that the different S100 genes play varying roles in breast cancer progression. Specific S100 genes are potential targets for the treatment of basal-type breast cancers.

  11. Association of Genetic Polymorphism in the Interleukin-8 Gene with Risk of Oral Cancer and Its Correlation with Pain.

    Science.gov (United States)

    Singh, Prithvi Kumar; Chandra, Girish; Bogra, Jaishri; Gupta, Rajni; Kumar, Vijay; Hussain, Syed Rizwan; Jain, Amita; Mahdi, Abbas Ali; Ahmad, Mohammad Kaleem

    2016-02-01

    Oral cancer is a multifactorial disease process and involves complex interactions between gene to gene and gene to environmental factors. Interleukin 8 (IL-8), a pro-inflammatory cytokine, having angiogenic activity with elevated expression in tumor cells, is reported to play an essential role in oral cancer development. This study was conducted with the aim to investigate the role of IL-8 (-A251T) gene polymorphism in susceptibility, progression, and self-reporting pain in oral cancer. The single nucleotide polymorphisms of the IL-8 (-A251T) gene were screened in 300 patients with oral cancer and 300 healthy controls, by polymerase chain reaction-restriction fragment length polymorphism. Genotype and allele frequencies were evaluated by chi-square test and odds ratio (OR) with 95% confidence intervals (CIs) were used to evaluate the strength of associations. The results of the study demonstrated that IL-8 (-A251T) gene polymorphism was significantly associated with susceptibility of oral cancer, whereas its correlation with clinico-pathological status or pain due to oral cancer could not be established. The AT heterozygous (OR 5.31; CI 3.38-8.34; p 0.0001) and AA homozygous (OR 2.89; CI 1.76-4.75; p 0.0001) had a greater risk for oral cancer compared to TT homozygous. Furthermore, significantly increased values of A allele frequencies compared to T allele were observed in all patients (OR 1.56; CI 1.24-1.96; p 0.0002). Tobacco chewing and smoking were also found to influence the development of oral cancer and increased the incidence of pain in oral cancer patients. The findings of this study suggest that the IL-8 (-A251T) gene polymorphism may be associated with increased risk of oral cancer.

  12. Blood Gene Expression Profiling of Breast Cancer Survivors Experiencing Fibrosis

    International Nuclear Information System (INIS)

    Landmark-Hoyvik, Hege; Dumeaux, Vanessa; Reinertsen, Kristin V.; Edvardsen, Hege; Fossa, Sophie D.; Borresen-Dale, Anne-Lise

    2011-01-01

    Purpose: To extend knowledge on the mechanisms and pathways involved in maintenance of radiation-induced fibrosis (RIF) by performing gene expression profiling of whole blood from breast cancer (BC) survivors with and without fibrosis 3-7 years after end of radiotherapy treatment. Methods and Materials: Gene expression profiles from blood were obtained for 254 BC survivors derived from a cohort of survivors, treated with adjuvant radiotherapy for breast cancer 3-7 years earlier. Analyses of transcriptional differences in blood gene expression between BC survivors with fibrosis (n = 31) and BC survivors without fibrosis (n = 223) were performed using R version 2.8.0 and tools from the Bioconductor project. Gene sets extracted through a literature search on fibrosis and breast cancer were subsequently used in gene set enrichment analysis. Results: Substantial differences in blood gene expression between BC survivors with and without fibrosis were observed, and 87 differentially expressed genes were identified through linear analysis. Transforming growth factor-β1 signaling was identified as the most significant gene set, showing a down-regulation of most of the core genes, together with up-regulation of a transcriptional activator of the inhibitor of fibrinolysis, Plasminogen activator inhibitor 1 in the BC survivors with fibrosis. Conclusion: Transforming growth factor-β1 signaling was found down-regulated during the maintenance phase of fibrosis as opposed to the up-regulation reported during the early, initiating phase of fibrosis. Hence, once the fibrotic tissue has developed, the maintenance phase might rather involve a deregulation of fibrinolysis and altered degradation of extracellular matrix components.

  13. Finding biological process modifications in cancer tissues by mining gene expression correlations

    Directory of Open Access Journals (Sweden)

    Storari Sergio

    2006-01-01

    Full Text Available Abstract Background Through the use of DNA microarrays it is now possible to obtain quantitative measurements of the expression of thousands of genes from a biological sample. This technology yields a global view of gene expression that can be used in several ways. Functional insight into expression profiles is routinely obtained by using Gene Ontology terms associated to the cellular genes. In this paper, we deal with functional data mining from expression profiles, proposing a novel approach that studies the correlations between genes and their relations to Gene Ontology (GO. By using this "functional correlations comparison" we explore all possible pairs of genes identifying the affected biological processes by analyzing in a pair-wise manner gene expression patterns and linking correlated pairs with Gene Ontology terms. Results We apply here this "functional correlations comparison" approach to identify the existing correlations in hepatocarcinoma (161 microarray experiments and to reveal functional differences between normal liver and cancer tissues. The number of well-correlated pairs in each GO term highlights several differences in genetic interactions between cancer and normal tissues. We performed a bootstrap analysis in order to compute false detection rates (FDR and confidence limits. Conclusion Experimental results show the main advantage of the applied method: it both picks up general and specific GO terms (in particular it shows a fine resolution in the specific GO terms. The results obtained by this novel method are highly coherent with the ones proposed by other cancer biology studies. But additionally they highlight the most specific and interesting GO terms helping the biologist to focus his/her studies on the most relevant biological processes.

  14. The interaction between informal cancer caregivers and health care professionals

    DEFF Research Database (Denmark)

    Lund, Line; Ross, Lone; Petersen, Morten Aagaard

    2015-01-01

    PURPOSE: In order to meet the caregiving challenges, informal caregivers often need a substantial level of interaction with health care professionals (HCPs). This study investigated to which extent the cancer caregivers' needs regarding the interaction with HCPs are met and the associations betwe...

  15. Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

    Science.gov (United States)

    Ashkani, Jahanshah; Naidoo, Kevin J.

    2016-05-01

    Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

  16. Targeted sequencing of established and candidate colorectal cancer genes in the Colon Cancer Family Registry Cohort.

    Science.gov (United States)

    Raskin, Leon; Guo, Yan; Du, Liping; Clendenning, Mark; Rosty, Christophe; Lindor, Noralane M; Gruber, Stephen B; Buchanan, Daniel D

    2017-11-07

    The underlying genetic cause of colorectal cancer (CRC) can be identified for 5-10% of all cases, while at least 20% of CRC cases are thought to be due to inherited genetic factors. Screening for highly penetrant mutations in genes associated with Mendelian cancer syndromes using next-generation sequencing (NGS) can be prohibitively expensive for studies requiring large samples sizes. The aim of the study was to identify rare single nucleotide variants and small indels in 40 established or candidate CRC susceptibility genes in 1,046 familial CRC cases (including both MSS and MSI-H tumor subtypes) and 1,006 unrelated controls from the Colon Cancer Family Registry Cohort using a robust and cost-effective DNA pooling NGS strategy. We identified 264 variants in 38 genes that were observed only in cases, comprising either very rare (minor allele frequency cancer susceptibility genes BAP1, CDH1, CHEK2, ENG, and MSH3 . For the candidate CRC genes, we identified likely pathogenic variants in the helicase domain of POLQ and in the LRIG1 , SH2B3 , and NOS1 genes and present their clinicopathological characteristics. Using a DNA pooling NGS strategy, we identified novel germline mutations in established CRC susceptibility genes in familial CRC cases. Further studies are required to support the role of POLQ , LRIG1 , SH2B3 and NOS1 as CRC susceptibility genes.

  17. Identification of certain cancer-mediating genes using Gaussian ...

    Indian Academy of Sciences (India)

    2015-09-29

    Sep 29, 2015 ... mance of GFI is compared with 19 exiting cluster validity indices. The results .... Using k-means algorithm on human lung expression data, we have found ... of possible genes that mediate the development of a cancer. In other ...

  18. Songs about Cancer, Gene Expression, and the Biochemistry of Photosynthesis

    Science.gov (United States)

    Heineman, Richard H.

    2018-01-01

    These three biology songs can be used for educational purposes to teach about biochemical concepts. They touch on three different topics: (1) cancer progression and germ cells, (2) gene expression, promoters, and repressors, and (3) electronegativity and the biochemical basis of photosynthesis.

  19. Adenovirus-derived vectors for prostate cancer gene therapy

    Czech Academy of Sciences Publication Activity Database

    de Vrij, J.; Willemsen, R. A.; Lindholm, L.; Hoeben, R. C.; Bangma, Ch. H.; Barber, Ch.; Behr, J.-P.; Briggs, S.; Carlisle, R.; Cheng, W.-S.; Dautzenberg, I. J. C.; de Ridder, C.; Dzojic, H.; Erbacher, P.; Essand, M.; Fisher, K.; Frazier, A.; Georgopoulos, L. J.; Jennings, I.; Kochanek, S.; Koppers-Lalic, D.; Kraaij, R.; Kreppel, F.; Magnusson, M.; Maitland, N.; Neuberg, P.; Nugent, R.; Ogris, M.; Remy, J.-S.; Scaife, M.; Schenk, E.; Schooten, E.; Seymour, L.; Slade, M.; Szyjanowicz, P.; Totterman, T.; Uil, T. G.; Ulbrich, Karel; van der Weel, L.; van Weerden, W.; Wagner, E.; Zuber, G.

    2010-01-01

    Roč. 21, č. 7 (2010), s. 795-805 ISSN 1043-0342 EU Projects: European Commission(XE) 512087 - GIANT Keywords : adenovirus * gene delivery * prostate cancer Subject RIV: CD - Macromolecular Chemistry Impact factor: 4.829, year: 2010

  20. Olaparib Approved for Breast Cancers with BRCA Gene Mutations

    Science.gov (United States)

    The Food and Drug Administration has approved olaparib (Lynparza®) to treat metastatic breast cancers that have inherited mutations in the BRCA1 or BRCA2 genes as well as a companion diagnostic test for selecting candidates for the therapy.

  1. Specifically targeted gene therapy for small-cell lung cancer

    DEFF Research Database (Denmark)

    Christensen, C.L.; Zandi, R.; Gjetting, T.

    2009-01-01

    Small-cell lung cancer (SCLC) is a highly malignant disease with poor prognosis. Hence, there is great demand for new therapies that can replace or supplement the current available treatment regimes. Gene therapy constitutes a promising strategy and relies on the principle of introducing exogenous...

  2. Mutations in the AXIN1 gene in advanced prostate cancer

    DEFF Research Database (Denmark)

    Yardy, George W; Bicknell, David C; Wilding, Jennifer L

    2009-01-01

    The Wnt signalling pathway directs aspects of embryogenesis and is thought to contribute to maintenance of certain stem cell populations. Disruption of the pathway has been observed in many different tumour types. In bowel, stomach, and endometrial cancer, this is usually due to mutation of genes...

  3. Cancer : A reproductive strategy of "ultra-selfish" genes?

    NARCIS (Netherlands)

    Schuiling, GA

    2004-01-01

    A hypothesis is presented in which the process of "malignant transformation" which ultimately results in the rapidly dividing tumor(s)(cells) causing "cancer", is regarded as an evolved reproductive strategy of "ultra-selfish" (proto-)(onco-) genes, already present in the genome, or introduced by a

  4. Cancer: a reproductive strategy of "ultra-selfish" genes?

    Science.gov (United States)

    Schuiling, G A

    2004-01-01

    A hypothesis is presented in which the process of "malignant transformation" which ultimately results in the rapidly dividing tumor(s)(cells) causing "cancer", is regarded as an evolved reproductive strategy of "ultra-selfish" (proto-)(onco-) genes, already present in the genome, or introduced by a virus.

  5. IRGM gene polymorphisms and risk of gastric cancer.

    NARCIS (Netherlands)

    Burada, F.; Plantinga, T.S.; Ioana, M.; Rosentul, D.; Angelescu, C.; Joosten, L.A.B.; Netea, M.G.; Saftoiu, A.

    2012-01-01

    OBJECTIVE: The study aimed to assess the possible association of polymorphisms in the autophagy gene IRGM (rs13361189 and rs4958847) with the risk of gastric cancer. METHODS: A total of 102 patients with gastric adenocarcinoma, 52 with chronic gastritis and 351 healthy controls were included in this

  6. Gene expression analysis of FABP4 in gastric cancer

    Directory of Open Access Journals (Sweden)

    Abdulkarim Yasin Karim

    2016-06-01

    Full Text Available Purpose: Gastric cancer has high incidence and mortality rate in several countries and is still one of the most frequent and lethal disease. In this study, we aimed to determine diagnostic markers in gastric cancer by molecular techniques; include mRNA expression analysis of FABP4 gene. Fatty acid binding protein 4 (FABP4 gene encodes the fatty acid binding protein found in adipocytes. The protein encoded by FABP4 are a family of small, highly conserved, cytoplasmic proteins that bind long-chain fatty acids and other hydrophobic ligands. It is thought that FABPs roles include fatty acid uptake, transport, and metabolism. Material and Methods: Total RNA were extracted from paired tumor and normal tissues of 47 gastric cancer. The mRNA expression level of FABP4 was measured employing semi- quantitative reverse transcription- polymerase chain reaction (RT- PCR. Results: The mRNA expression level of FABP4 was significantly decreased (down- regulated. Conclusion: Down-regulation of FABP4 gene seems to occur at the initial steps of gastric cancer development. In order to confirm the relationship between the gastric tumor and FABP4 gene, further analysis like immunohistochemistry and epigenetc techniques are necessary. [Cukurova Med J 2016; 41(2.000: 248-252

  7. Expression and Function of ETS Genes in Prostate Cancer

    NARCIS (Netherlands)

    D. Gasi (Delila)

    2013-01-01

    markdownabstract__Abstract__ Prostate cancer is a heterogeneous disease that is very common in elderly men in developed countries. Understanding the molecular and biological processes that contribute to tumor development and progressive growth is a challenging task. The fusion of the genes ERG

  8. Roles of the Y chromosome genes in human cancers

    Directory of Open Access Journals (Sweden)

    Tatsuo Kido

    2015-06-01

    Full Text Available Male and female differ genetically by their respective sex chromosome composition, that is, XY as male and XX as female. Although both X and Y chromosomes evolved from the same ancestor pair of autosomes, the Y chromosome harbors male-specific genes, which play pivotal roles in male sex determination, germ cell differentiation, and masculinization of various tissues. Deletions or translocation of the sex-determining gene, SRY, from the Y chromosome causes disorders of sex development (previously termed as an intersex condition with dysgenic gonads. Failure of gonadal development results not only in infertility, but also in increased risks of germ cell tumor (GCT, such as gonadoblastoma and various types of testicular GCT. Recent studies demonstrate that either loss of Y chromosome or ectopic expression of Y chromosome genes is closely associated with various male-biased diseases, including selected somatic cancers. These observations suggest that the Y-linked genes are involved in male health and diseases in more frequently than expected. Although only a small number of protein-coding genes are present in the male-specific region of Y chromosome, the impacts of Y chromosome genes on human diseases are still largely unknown, due to lack of in vivo models and differences between the Y chromosomes of human and rodents. In this review, we highlight the involvement of selected Y chromosome genes in cancer development in men.

  9. Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes.

    Science.gov (United States)

    Biankin, Andrew V; Waddell, Nicola; Kassahn, Karin S; Gingras, Marie-Claude; Muthuswamy, Lakshmi B; Johns, Amber L; Miller, David K; Wilson, Peter J; Patch, Ann-Marie; Wu, Jianmin; Chang, David K; Cowley, Mark J; Gardiner, Brooke B; Song, Sarah; Harliwong, Ivon; Idrisoglu, Senel; Nourse, Craig; Nourbakhsh, Ehsan; Manning, Suzanne; Wani, Shivangi; Gongora, Milena; Pajic, Marina; Scarlett, Christopher J; Gill, Anthony J; Pinho, Andreia V; Rooman, Ilse; Anderson, Matthew; Holmes, Oliver; Leonard, Conrad; Taylor, Darrin; Wood, Scott; Xu, Qinying; Nones, Katia; Fink, J Lynn; Christ, Angelika; Bruxner, Tim; Cloonan, Nicole; Kolle, Gabriel; Newell, Felicity; Pinese, Mark; Mead, R Scott; Humphris, Jeremy L; Kaplan, Warren; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chou, Angela; Chin, Venessa T; Chantrill, Lorraine A; Mawson, Amanda; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Daly, Roger J; Merrett, Neil D; Toon, Christopher; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Kakkar, Nipun; Zhao, Fengmei; Wu, Yuan Qing; Wang, Min; Muzny, Donna M; Fisher, William E; Brunicardi, F Charles; Hodges, Sally E; Reid, Jeffrey G; Drummond, Jennifer; Chang, Kyle; Han, Yi; Lewis, Lora R; Dinh, Huyen; Buhay, Christian J; Beck, Timothy; Timms, Lee; Sam, Michelle; Begley, Kimberly; Brown, Andrew; Pai, Deepa; Panchal, Ami; Buchner, Nicholas; De Borja, Richard; Denroche, Robert E; Yung, Christina K; Serra, Stefano; Onetto, Nicole; Mukhopadhyay, Debabrata; Tsao, Ming-Sound; Shaw, Patricia A; Petersen, Gloria M; Gallinger, Steven; Hruban, Ralph H; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Schulick, Richard D; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Capelli, Paola; Corbo, Vincenzo; Scardoni, Maria; Tortora, Giampaolo; Tempero, Margaret A; Mann, Karen M; Jenkins, Nancy A; Perez-Mancera, Pedro A; Adams, David J; Largaespada, David A; Wessels, Lodewyk F A; Rust, Alistair G; Stein, Lincoln D; Tuveson, David A; Copeland, Neal G; Musgrove, Elizabeth A; Scarpa, Aldo; Eshleman, James R; Hudson, Thomas J; Sutherland, Robert L; Wheeler, David A; Pearson, John V; McPherson, John D; Gibbs, Richard A; Grimmond, Sean M

    2012-11-15

    Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis.

  10. Risk of colorectal cancer for people with a mutation in both a MUTYH and a DNA mismatch repair gene

    Science.gov (United States)

    Win, Aung Ko; Reece, Jeanette C.; Buchanan, Daniel D.; Clendenning, Mark; Young, Joanne P.; Cleary, Sean P.; Kim, Hyeja; Cotterchio, Michelle; Dowty, James G.; MacInnis, Robert J.; Tucker, Katherine M.; Winship, Ingrid M.; Macrae, Finlay A.; Burnett, Terrilea; Le Marchand, Loïc; Casey, Graham; Haile, Robert W.; Newcomb, Polly A.; Thibodeau, Stephen N.; Lindor, Noralane M.; Hopper, John L.; Gallinger, Steven; Jenkins, Mark A.

    2015-01-01

    The base excision repair protein, MUTYH, functionally interacts with the DNA mismatch repair (MMR) system. As genetic testing moves from testing one gene at a time, to gene panel and whole exome next generation sequencing approaches, understanding the risk associated with co-existence of germline mutations in these genes will be important for clinical interpretation and management. From the Colon Cancer Family Registry, we identified 10 carriers who had both a MUTYH mutation (6 with c.1187G>A p.(Gly396Asp), 3 with c.821G>A p.(Arg274Gln), and 1 with c.536A>G p.(Tyr179Cys)) and a MMR gene mutation (3 in MLH1, 6 in MSH2, and 1 in PMS2), 375 carriers of a single (monoallelic) MUTYH mutation alone, and 469 carriers of a MMR gene mutation alone. Of the 10 carriers of both gene mutations, 8 were diagnosed with colorectal cancer. Using a weighted cohort analysis, we estimated that risk of colorectal cancer for carriers of both a MUTYH and a MMR gene mutation was substantially higher than that for carriers of a MUTYH mutation alone [hazard ratio (HR) 21.5, 95 % confidence interval (CI) 9.19–50.1; p colorectal cancer for carriers of a MMR gene mutation alone. Our finding suggests MUTYH mutation testing in MMR gene mutation carriers is not clinically informative. PMID:26202870

  11. Gene interactions and genetics for yield and its attributes in grass ...

    Indian Academy of Sciences (India)

    A. K. PARIHAR

    explaining the manifestation of complex traits such as yield. ... interactions (i, j, l) contributed towards the inheritance of traits in the given crosses. ... Keywords. grass pea; scaling test; gene interactions; gene effects; heritability; Lathyrus sativus.

  12. Systematic enrichment analysis of gene expression profiling studies identifies consensus pathways implicated in colorectal cancer development

    Directory of Open Access Journals (Sweden)

    Jesús Lascorz

    2011-01-01

    Full Text Available Background: A large number of gene expression profiling (GEP studies on colorectal carcinogenesis have been performed but no reliable gene signature has been identified so far due to the lack of reproducibility in the reported genes. There is growing evidence that functionally related genes, rather than individual genes, contribute to the etiology of complex traits. We used, as a novel approach, pathway enrichment tools to define functionally related genes that are consistently up- or down-regulated in colorectal carcinogenesis. Materials and Methods: We started the analysis with 242 unique annotated genes that had been reported by any of three recent meta-analyses covering GEP studies on genes differentially expressed in carcinoma vs normal mucosa. Most of these genes (218, 91.9% had been reported in at least three GEP studies. These 242 genes were submitted to bioinformatic analysis using a total of nine tools to detect enrichment of Gene Ontology (GO categories or Kyoto Encyclopedia of Genes and Genomes (KEGG pathways. As a final consistency criterion the pathway categories had to be enriched by several tools to be taken into consideration. Results: Our pathway-based enrichment analysis identified the categories of ribosomal protein constituents, extracellular matrix receptor interaction, carbonic anhydrase isozymes, and a general category related to inflammation and cellular response as significantly and consistently overrepresented entities. Conclusions: We triaged the genes covered by the published GEP literature on colorectal carcinogenesis and subjected them to multiple enrichment tools in order to identify the consistently enriched gene categories. These turned out to have known functional relationships to cancer development and thus deserve further investigation.

  13. The genetic alteration of retinoblastoma gene in esophageal cancer

    International Nuclear Information System (INIS)

    Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min

    1994-12-01

    Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it's alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author)

  14. The genetic alteration of retinoblastoma gene in esophageal cancer

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jae Il; Shim, Yung Mok; Kim, Chang Min [Korea Cancer Center Hospital of Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1994-12-01

    Retinoblastoma(RB) gene is the prototype of tumor suppressor gene and it`s alteration have been frequently observed in a large number of human tumors. To investigate the role of RB in esophageal cancer, we studied 36 esophageal cancer tissues with Southern blot analysis to detect gross LOH and PCR-SSCP method to find minute LOH and mutation, if any. In the cases with abnormalities, the nucleotide sequence analysis was performed. Allelic loss of chromosome 13q14 occurred in 20 out of 32 informative cases (62.5%) by Southern analysis. Furthermore, PCR-LOH added three positive cases. Mobility shift by PCR-SSCP was observed in one case at exon 22, which showed 1 bp deletion in codon 771 of RB gene resulting in frame shift mutation. Besides, nine PCR-band alteration in tumor tissue compared with normal tissue were observed in exon 14 and 22, but mutation was not found on sequencing analysis suggesting the epigenetic alteration in tumor tissue. Analysis of the clinical data did not show any difference depending upon RB alteration. However, the total incidence of RB gene may play an important role in the development of esophageal cancer. The main genetic alteration of RB gene was deletion detected by Southern blot and one bp deletion leading to frame shift was also observed. 8 figs, 5 tabs. (Author).

  15. Common variants of xeroderma pigmentosum genes and prostate cancer risk.

    Science.gov (United States)

    Mirecka, Aneta; Paszkowska-Szczur, Katarzyna; Scott, Rodney J; Górski, Bohdan; van de Wetering, Thierry; Wokołorczyk, Dominika; Gromowski, Tomasz; Serrano-Fernandez, Pablo; Cybulski, Cezary; Kashyap, Aniruddh; Gupta, Satish; Gołąb, Adam; Słojewski, Marcin; Sikorski, Andrzej; Lubiński, Jan; Dębniak, Tadeusz

    2014-08-10

    The genetic basis of prostate cancer (PC) is complex and appears to involve multiple susceptibility genes. A number of studies have evaluated a possible correlation between several NER gene polymorphisms and PC risk, but most of them evaluated only single SNPs among XP genes and the results remain inconsistent. Out of 94 SNPs located in seven XP genes (XPA-XPG) a total of 15 SNPs were assayed in 720 unselected patients with PC and compared to 1121 healthy adults. An increased risk of disease was associated with the XPD SNP, rs1799793 (Asp312Asn) AG genotype (OR=2.60; p<0.001) and with the AA genotype (OR=531; p<0.0001) compared to the control population. Haplotype analysis of XPD revealed one protective haplotype and four associated with an increased disease risk, which showed that the A allele (XPD rs1799793) appeared to drive the main effect on promoting prostate cancer risk. Polymorphism in XPD gene appears to be associated with the risk of prostate cancer. Copyright © 2014. Published by Elsevier B.V.

  16. Gene expression of circulating tumour cells in breast cancer patients

    Directory of Open Access Journals (Sweden)

    Bölke E

    2009-09-01

    Full Text Available Abstract Background The diagnostic tools to predict the prognosis in patients suffering from breast cancer (BC need further improvements. New technological achievements like the gene profiling of circulating tumour cells (CTC could help identify new prognostic markers in the clinical setting. Furthermore, gene expression patterns of CTC might provide important informations on the mechanisms of tumour cell metastasation. Materials and methods We performed realtime-PCR and multiplex-PCR analyses following immunomagnetic separation of CTC. Peripheral blood (PB samples of 63 patients with breast cancer of various stages were analyzed and compared to a control group of 14 healthy individuals. After reverse-transcription, we performed multiplex PCR using primers for the genes ga733.3, muc-1 and c-erbB2. Mammaglobin1, spdef and c-erbB2 were analyzed applying realtime-PCR. Results ga733.2 overexpression was found in 12.7% of breast cancer cases, muc-1 in 15.9%, mgb1 in 9.1% and spdef in 12.1%. In this study, c-erbB2 did not show any significant correlation to BC, possibly due to a highly ambient expression. Besides single gene analyses, gene profiles were additionally evaluated. Highly significant correlations to BC were found in single gene analyses of ga733.2 and muc-1 and in gene profile analyses of ga733.3*muc-1 and GA7 ga733.3*muc-1*mgb1*spdef. Conclusion Our study reveals that the single genes ga733.3, muc-1 and the gene profiles ga733.3*muc-1 and ga733.3*3muc-1*mgb1*spdef can serve as markers for the detection of CTC in BC. The multigene analyses found highly positive levels in BC patients. Our study indicates that not single gene analyses but subtle patterns of multiple genes lead to rising accuracy and low loss of specificity in detection of breast cancer cases.

  17. GxGrare: gene-gene interaction analysis method for rare variants from high-throughput sequencing data.

    Science.gov (United States)

    Kwon, Minseok; Leem, Sangseob; Yoon, Joon; Park, Taesung

    2018-03-19

    With the rapid advancement of array-based genotyping techniques, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with common complex diseases. However, it has been shown that only a small proportion of the genetic etiology of complex diseases could be explained by the genetic factors identified from GWAS. This missing heritability could possibly be explained by gene-gene interaction (epistasis) and rare variants. There has been an exponential growth of gene-gene interaction analysis for common variants in terms of methodological developments and practical applications. Also, the recent advancement of high-throughput sequencing technologies makes it possible to conduct rare variant analysis. However, little progress has been made in gene-gene interaction analysis for rare variants. Here, we propose GxGrare which is a new gene-gene interaction method for the rare variants in the framework of the multifactor dimensionality reduction (MDR) analysis. The proposed method consists of three steps; 1) collapsing the rare variants, 2) MDR analysis for the collapsed rare variants, and 3) detect top candidate interaction pairs. GxGrare can be used for the detection of not only gene-gene interactions, but also interactions within a single gene. The proposed method is illustrated with 1080 whole exome sequencing data of the Korean population in order to identify causal gene-gene interaction for rare variants for type 2 diabetes. The proposed GxGrare performs well for gene-gene interaction detection with collapsing of rare variants. GxGrare is available at http://bibs.snu.ac.kr/software/gxgrare which contains simulation data and documentation. Supported operating systems include Linux and OS X.

  18. Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk

    Science.gov (United States)

    Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

    2018-01-01

    Background Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Results Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; ptrendcolorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). Methods A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Conclusions Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer. PMID:29464080

  19. Effects of interactions between common genetic variants and alcohol consumption on colorectal cancer risk.

    Science.gov (United States)

    Song, Nan; Shin, Aesun; Oh, Jae Hwan; Kim, Jeongseon

    2018-01-19

    Genome-wide association studies (GWAS) have identified approximately 40 common genetic loci associated with colorectal cancer risk. To investigate possible gene-environment interactions (GEIs) between GWAS-identified single-nucleotide polymorphisms (SNPs) and alcohol consumption with respect to colorectal cancer, a hospital-based case-control study was conducted. Higher levels of alcohol consumption as calculated based on a standardized definition of a drink (1 drink=12.5g of ethanol) were associated with increased risk of colorectal cancer (OR=2.47, 95% CI=1.62-3.76 for heavy drinkers [>50g/day] compared to never drinkers; p trend colorectal cancer associated with the G allele of rs6687758 tended to increase among individuals in the heavier alcohol consumption strata. A statistically significant association between rs6687758 and colorectal cancer risk was observed among moderate alcohol drinkers who consumed between >12.5 and ≤50g of alcohol per day (OR=1.46, 95% CI=1.01-2.11). A total of 2,109 subjects (703 colorectal cancer patients and 1,406 healthy controls) were recruited from the Korean National Cancer Center. For genotyping, 30 GWAS-identified SNPs were selected. A logistic regression model was used to evaluate associations of SNPs and alcohol consumption with colorectal cancer risk. We also tested GEIs between SNPs and alcohol consumption using a logistic model with multiplicative interaction terms. Our results suggest that SNP rs6687758 at 1q41 may interact with alcohol consumption in the etiology of colorectal cancer.

  20. Spatially Uniform ReliefF (SURF for computationally-efficient filtering of gene-gene interactions

    Directory of Open Access Journals (Sweden)

    Greene Casey S

    2009-09-01

    Full Text Available Abstract Background Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be the result of single points of failure but instead likely arise from the joint failure of two or more interacting components. The hope in genome-wide screens is that these points of failure can be linked to single nucleotide polymorphisms (SNPs which confer disease susceptibility. Detecting interacting variants that lead to disease in the absence of single-gene effects is difficult however, and methods to exhaustively analyze sets of these variants for interactions are combinatorial in nature thus making them computationally infeasible. Efficient algorithms which can detect interacting SNPs are needed. ReliefF is one such promising algorithm, although it has low success rate for noisy datasets when the interaction effect is small. ReliefF has been paired with an iterative approach, Tuned ReliefF (TuRF, which improves the estimation of weights in noisy data but does not fundamentally change the underlying ReliefF algorithm. To improve the sensitivity of studies using these methods to detect small effects we introduce Spatially Uniform ReliefF (SURF. Results SURF's ability to detect interactions in this domain is significantly greater than that of ReliefF. Similarly SURF, in combination with the TuRF strategy significantly outperforms TuRF alone for SNP selection under an epistasis model. It is important to note that this success rate increase does not require an increase in algorithmic complexity and allows for increased success rate, even with the removal of a nuisance parameter from the algorithm. Conclusion Researchers performing genetic association studies and aiming to discover gene-gene interactions associated with increased disease susceptibility should use SURF in place of ReliefF. For instance, SURF should be

  1. Chemical-gene interaction networks and causal reasoning for ...

    Science.gov (United States)

    Evaluating the potential human health and ecological risks associated with exposures to complex chemical mixtures in the environment is one of the main challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and biological effects data to evaluate risks associated with chemicals present in the environment. Here, we used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near the North Branch and Chisago wastewater treatment plants (WWTP) in the St. Croix River Basin, MN and WI. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data were also mapped to the assembly models to evaluate the likelihood of a chemical contributing to the observed biological responses using richness and concordance statistics. The prior knowledge approach was able predict the observed biological pathways impacted at one site but not the other. Atrazine was identified as a potential contributor to the observed gene expression responses at a location upstream of the North Branch WTTP. Four chemicals were identified as contributors to the observed biological responses at the effluent and downstream o

  2. Animal model for schizophrenia that reflects gene-environment interactions.

    Science.gov (United States)

    Nagai, Taku; Ibi, Daisuke; Yamada, Kiyofumi

    2011-01-01

    Schizophrenia is a devastating psychiatric disorder that impairs mental and social functioning and affects approximately 1% of the population worldwide. Genetic susceptibility factors for schizophrenia have recently been reported, some of which are known to play a role in neurodevelopment; these include neuregulin-1, dysbindin, and disrupted-in-schizophrenia 1 (DISC1). Moreover, epidemiologic studies suggest that environmental insults, such as prenatal infection and perinatal complication, are involved in the development of schizophrenia. The possible interaction between environment and genetic susceptibility factors, especially during neurodevelopment, is proposed as a promising disease etiology of schizophrenia. Polyriboinosinic-polyribocytidilic acid (polyI : C) is a synthetic analogue of double-stranded RNA that leads to the pronounced but time-limited production of pro-inflammatory cytokines. Maternal immune activation by polyI : C exposure in rodents is known to precipitate a wide spectrum of behavioral, cognitive, and pharmacological abnormalities in adult offspring. Recently, we have reported that neonatal injection of polyI : C in mice results in schizophrenia-like behavioral alterations in adulthood. In this review, we show how gene-environment interactions during neurodevelopment result in phenotypic changes in adulthood by injecting polyI : C into transgenic mice that express a dominant-negative form of human DISC1 (DN-DISC1). Our findings suggest that polyI : C-treated DN-DISC1 mice are a well-validated animal model for schizophrenia that reflects gene-environment interactions.

  3. Expression analysis of cancer-testis genes in prostate cancer reveals candidates for immunotherapy.

    Science.gov (United States)

    Faramarzi, Sepideh; Ghafouri-Fard, Soudeh

    2017-09-01

    Prostate cancer is a prevalent disorder among men with a heterogeneous etiological background. Several molecular events and signaling perturbations have been found in this disorder. Among genes whose expressions have been altered during the prostate cancer development are cancer-testis antigens (CTAs). This group of antigens has limited expression in the normal adult tissues but aberrant expression in cancers. This property provides them the possibility to be used as cancer biomarkers and immunotherapeutic targets. Several CTAs have been shown to be immunogenic in prostate cancer patients and some of the have entered clinical trials. Based on the preliminary data obtained from these trials, it is expected that CTA-based therapeutic options are beneficial for at least a subset of prostate cancer patients.

  4. Molecular and biological interactions in colorectal cancer

    NARCIS (Netherlands)

    Heer, Pieter de

    2007-01-01

    The current thesis discusses the use of molecular and biological tumor markers to predict clinical outcome. By studying several key processes in the develepment of cancer as regulation of cell motility (non-receptor protein tyrosin adesion kinases, FAK, Src and paxillin, Apoptosis (caspase-3

  5. Modeling Gene-Environment Interactions With Quasi-Natural Experiments.

    Science.gov (United States)

    Schmitz, Lauren; Conley, Dalton

    2017-02-01

    This overview develops new empirical models that can effectively document Gene × Environment (G×E) interactions in observational data. Current G×E studies are often unable to support causal inference because they use endogenous measures of the environment or fail to adequately address the nonrandom distribution of genes across environments, confounding estimates. Comprehensive measures of genetic variation are incorporated into quasi-natural experimental designs to exploit exogenous environmental shocks or isolate variation in environmental exposure to avoid potential confounders. In addition, we offer insights from population genetics that improve upon extant approaches to address problems from population stratification. Together, these tools offer a powerful way forward for G×E research on the origin and development of social inequality across the life course. © 2015 Wiley Periodicals, Inc.

  6. Exploring Plant Co-Expression and Gene-Gene Interactions with CORNET 3.0.

    Science.gov (United States)

    Van Bel, Michiel; Coppens, Frederik

    2017-01-01

    Selecting and filtering a reference expression and interaction dataset when studying specific pathways and regulatory interactions can be a very time-consuming and error-prone task. In order to reduce the duplicated efforts required to amass such datasets, we have created the CORNET (CORrelation NETworks) platform which allows for easy access to a wide variety of data types: coexpression data, protein-protein interactions, regulatory interactions, and functional annotations. The CORNET platform outputs its results in either text format or through the Cytoscape framework, which is automatically launched by the CORNET website.CORNET 3.0 is the third iteration of the web platform designed for the user exploration of the coexpression space of plant genomes, with a focus on the model species Arabidopsis thaliana. Here we describe the platform: the tools, data, and best practices when using the platform. We indicate how the platform can be used to infer networks from a set of input genes, such as upregulated genes from an expression experiment. By exploring the network, new target and regulator genes can be discovered, allowing for follow-up experiments and more in-depth study. We also indicate how to avoid common pitfalls when evaluating the networks and how to avoid over interpretation of the results.All CORNET versions are available at http://bioinformatics.psb.ugent.be/cornet/ .

  7. Nanoparticle-mediated delivery of suicide genes in cancer therapy.

    Science.gov (United States)

    Vago, Riccardo; Collico, Veronica; Zuppone, Stefania; Prosperi, Davide; Colombo, Miriam

    2016-09-01

    Conventional chemotherapeutics have been employed in cancer treatment for decades due to their efficacy in killing the malignant cells, but the other side of the coin showed off-target effects, onset of drug resistance and recurrences. To overcome these limitations, different approaches have been investigated and suicide gene therapy has emerged as a promising alternative. This approach consists in the introduction of genetic materials into cancerous cells or the surrounding tissue to cause cell death or retard the growth of the tumor mass. Despite promising results obtained both in vitro and in vivo, this innovative approach has been limited, for long time, to the treatment of localized tumors, due to the suboptimal efficiency in introducing suicide genes into cancer cells. Nanoparticles represent a valuable non-viral delivery system to protect drugs in the bloodstream, to improve biodistribution, and to limit side effects by achieving target selectivity through surface ligands. In this scenario, the real potential of suicide genes can be translated into clinically viable treatments for patients. In the present review, we summarize the recent advances of inorganic nanoparticles as non-viral vectors in terms of therapeutic efficacy, targeting capacity and safety issues. We describe the main suicide genes currently used in therapy, with particular emphasis on toxin-encoding genes of bacterial and plant origin. In addition, we discuss the relevance of molecular targeting and tumor-restricted expression to improve treatment specificity to cancer tissue. Finally, we analyze the main clinical applications, limitations and future perspectives of suicide gene therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. The WSB1 gene is involved in pancreatic cancer progression.

    Directory of Open Access Journals (Sweden)

    Cendrine Archange

    Full Text Available BACKGROUND: Pancreatic cancer cells generate metastases because they can survive the stress imposed by the new environment of the host tissue. To mimic this process, pancreatic cancer cells which are not stressed in standard culture conditions are injected into nude mice. Because they develop xenografts, they should have developed adequate stress response. Characterizing that response might provide new strategies to interfere with pancreatic cancer metastasis. METHODOLOGY/PRINCIPAL FINDINGS: In the human pancreatic cancer cell lines Panc-1, Mia-PaCa2, Capan-1, Capan-2 and BxPC3, we used Affymetrix DNA microarrays to compare the expressions of 22.000 genes in vitro and in the corresponding xenografts. We identified 228 genes overexpressed in xenografts and characterized the implication of one of them, WSB1, in the control of apoptosis and cell proliferation. WSB1 generates 3 alternatively spliced transcripts encoding distinct protein isoforms. In xenografts and in human pancreatic tumors, global expression of WSB1 mRNA is modestly increased whereas isoform 3 is strongly overexpressed and isoforms 1 and 2 are down-regulated. Treating Mia-PaCa2 cells with stress-inducing agents induced similar changes. Whereas retrovirus-forced expression of WSB1 isoforms 1 and 2 promoted cell growth and sensitized the cells to gemcitabine- and doxorubicin-induced apoptosis, WSB1 isoform 3 expression reduced cell proliferation and enhanced resistance to apoptosis, showing that stress-induced modulation of WSB1 alternative splicing increases resistance to apoptosis of pancreatic cancer cells. CONCLUSIONS/SIGNIFICANCE: Data on WSB1 regulation support the hypothesis that activation of stress-response mechanisms helps cancer cells establishing metastases and suggest relevance to cancer development of other genes overexpressed in xenografts.

  9. The Interaction of TXNIP and AFq1 Genes Increases the Susceptibility of Schizophrenia.

    Science.gov (United States)

    Su, Yousong; Ding, Wenhua; Xing, Mengjuan; Qi, Dake; Li, Zezhi; Cui, Donghong

    2017-08-01

    Although previous studies showed the reduced risk of cancer in patients with schizophrenia, whether patients with schizophrenia possess genetic factors that also contribute to tumor suppressor is still unknown. In the present study, based on our previous microarray data, we focused on the tumor suppressor genes TXNIP and AF1q, which differentially expressed in patients with schizophrenia. A total of 413 patients and 578 healthy controls were recruited. We found no significant differences in genotype, allele, or haplotype frequencies at the selected five single nucleotide polymorphisms (SNPs) (rs2236566 and rs7211 in TXNIP gene; rs10749659, rs2140709, and rs3738481 in AF1q gene) between patients with schizophrenia and controls. However, we found the association between the interaction of TXNIP and AF1q with schizophrenia by using the MDR method followed by traditional statistical analysis. The best gene-gene interaction model identified was a three-locus model TXNIP (rs2236566, rs7211)-AF1q (rs2140709). After traditional statistical analysis, we found the high-risk genotype combination was rs2236566 (GG)-rs7211(CC)-rs2140709(CC) (OR = 1.35 [1.03-1.76]). The low-risk genotype combination was rs2236566 (GT)-rs7211(CC)-rs2140709(CC) (OR = 0.67 [0.49-0.91]). Our finding suggested statistically significant role of interaction of TXNIP and AF1q polymorphisms (TXNIP-rs2236566, TXNIP-rs7211, and AF1q-rs2769605) in schizophrenia susceptibility.

  10. A network-based gene expression signature informs prognosis and treatment for colorectal cancer patients.

    Directory of Open Access Journals (Sweden)

    Mingguang Shi

    Full Text Available Several studies have reported gene expression signatures that predict recurrence risk in stage II and III colorectal cancer (CRC patients with minimal gene membership overlap and undefined biological relevance. The goal of this study was to investigate biological themes underlying these signatures, to infer genes of potential mechanistic importance to the CRC recurrence phenotype and to test whether accurate prognostic models can be developed using mechanistically important genes.We investigated eight published CRC gene expression signatures and found no functional convergence in Gene Ontology enrichment analysis. Using a random walk-based approach, we integrated these signatures and publicly available somatic mutation data on a protein-protein interaction network and inferred 487 genes that were plausible candidate molecular underpinnings for the CRC recurrence phenotype. We named the list of 487 genes a NEM signature because it integrated information from Network, Expression, and Mutation. The signature showed significant enrichment in four biological processes closely related to cancer pathophysiology and provided good coverage of known oncogenes, tumor suppressors, and CRC-related signaling pathways. A NEM signature-based Survival Support Vector Machine prognostic model was trained using a microarray gene expression dataset and tested on an independent dataset. The model-based scores showed a 75.7% concordance with the real survival data and separated patients into two groups with significantly different relapse-free survival (p = 0.002. Similar results were obtained with reversed training and testing datasets (p = 0.007. Furthermore, adjuvant chemotherapy was significantly associated with prolonged survival of the high-risk patients (p = 0.006, but not beneficial to the low-risk patients (p = 0.491.The NEM signature not only reflects CRC biology but also informs patient prognosis and treatment response. Thus, the network

  11. Feature genes in metastatic breast cancer identified by MetaDE and SVM classifier methods.

    Science.gov (United States)

    Tuo, Youlin; An, Ning; Zhang, Ming

    2018-03-01

    The aim of the present study was to investigate the feature genes in metastatic breast cancer samples. A total of 5 expression profiles of metastatic breast cancer samples were downloaded from the Gene Expression Omnibus database, which were then analyzed using the MetaQC and MetaDE packages in R language. The feature genes between metastasis and non‑metastasis samples were screened under the threshold of PSVM) classifier training and verification. The accuracy of the SVM classifier was then evaluated using another independent dataset from The Cancer Genome Atlas database. Finally, function and pathway enrichment analyses for genes in the SVM classifier were performed. A total of 541 feature genes were identified between metastatic and non‑metastatic samples. The top 10 genes with the highest betweenness centrality values in the PPI network of feature genes were Nuclear RNA Export Factor 1, cyclin‑dependent kinase 2 (CDK2), myelocytomatosis proto‑oncogene protein (MYC), Cullin 5, SHC Adaptor Protein 1, Clathrin heavy chain, Nucleolin, WD repeat domain 1, proteasome 26S subunit non‑ATPase 2 and telomeric repeat binding factor 2. The cyclin‑dependent kinase inhibitor 1A (CDKN1A), E2F transcription factor 1 (E2F1), and MYC interacted with CDK2. The SVM classifier constructed by the top 30 feature genes was able to distinguish metastatic samples from non‑metastatic samples [correct rate, specificity, positive predictive value and negative predictive value >0.89; sensitivity >0.84; area under the receiver operating characteristic curve (AUROC) >0.96]. The verification of the SVM classifier in an independent dataset (35 metastatic samples and 143 non‑metastatic samples) revealed an accuracy of 94.38% and AUROC of 0.958. Cell cycle associated functions and pathways were the most significant terms of the 30 feature genes. A SVM classifier was constructed to assess the possibility of breast cancer metastasis, which presented high accuracy in several

  12. Methylation of the SPARC gene promoter and its clinical implication in pancreatic cancer

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    Lv Shunli

    2010-03-01

    Full Text Available Abstract Background The secreted protein acidic and rich in cysteine (SPARC plays a pivotal role in regulating cell-matrix interactions and tumor angiogenesis, proliferation, and migration. Detection of SPARC gene methylation may be useful as a tumorigenesis marker for early detection of pancreatic cancer. Methods Methylation of the SPARC gene transcriptional regulation region (TRR was detected using bisulfite-specific (BSP PCR-based sequencing analysis in 40 cases of pancreatic cancer and the adjacent normal tissues, 6 chronic pancreatitis tissues, and 6 normal pancreatic tissues. BSP cloning-based sequencing analysis was also performed in selected cases. Clinicopathological data from the cancer patients were collected and analyzed. Results Analysis of SPARC gene TRR methylation showed two hypermethylation wave peak regions: CpG Region 1 (CpG site 1-7 and CpG Region 2 (CpG site 8-12. Pancreatic tissues have shown methylation in both regions with gradual increases from normal, chronic pancreatitis, and adjacent normal tissues to cancerous tissues. However, Methylation of CpG Region 2 was more sensitive than CpG Region 1 in pancreatic tumorigenesis. Furthermore, the methylation level of CpG Region 2 was associated with increased tumor size and exposure to the risk factors (tobacco smoke and alcohol consumption for developing pancreatic cancer. Conclusion Methylation of the SPARC gene, specifically CpG Region 2, may be an early event during pancreatic tumorigenesis and should be further evaluated as a tumorigenesis marker for early detection of pancreatic cancer.

  13. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

    Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. Characterization of transformation related genes in oral cancer cells.

    Science.gov (United States)

    Chang, D D; Park, N H; Denny, C T; Nelson, S F; Pe, M

    1998-04-16

    A cDNA representational difference analysis (cDNA-RDA) and an arrayed filter technique were used to characterize transformation-related genes in oral cancer. From an initial comparison of normal oral epithelial cells and a human papilloma virus (HPV)-immortalized oral epithelial cell line, we obtained 384 differentially expressed gene fragments and arrayed them on a filter. Two hundred and twelve redundant clones were identified by three rounds of back hybridization. Sequence analysis of the remaining clones revealed 99 unique clones corresponding to 69 genes. The expression of these transformation related gene fragments in three nontumorigenic HPV-immortalized oral epithelial cell lines and three oral cancer cell lines were simultaneously monitored using a cDNA array hybridization. Although there was a considerable cell line-to-cell line variability in the expression of these clones, a reliable prediction of their expression could be made from the cDNA array hybridization. Our study demonstrates the utility of combining cDNA-RDA and arrayed filters in high-throughput gene expression difference analysis. The differentially expressed genes identified in this study should be informative in studying oral epithelial cell carcinogenesis.

  15. Distinct Gene Expression Signatures in Lynch Syndrome and Familial Colorectal Cancer Type X

    DEFF Research Database (Denmark)

    Valentin, Mev; Therkildsen, Christina; Veerla, Srinivas

    2013-01-01

    Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects.......Heredity is estimated to cause at least 20% of colorectal cancer. The hereditary nonpolyposis colorectal cancer subset is divided into Lynch syndrome and familial colorectal cancer type X (FCCTX) based on presence of mismatch repair (MMR) gene defects....

  16. Gene-Diet Interaction and Precision Nutrition in Obesity

    Directory of Open Access Journals (Sweden)

    Yoriko Heianza

    2017-04-01

    Full Text Available The rapid rise of obesity during the past decades has coincided with a profound shift of our living environment, including unhealthy dietary patterns, a sedentary lifestyle, and physical inactivity. Genetic predisposition to obesity may have interacted with such an obesogenic environment in determining the obesity epidemic. Growing studies have found that changes in adiposity and metabolic response to low-calorie weight loss diets might be modified by genetic variants related to obesity, metabolic status and preference to nutrients. This review summarized data from recent studies of gene-diet interactions, and discussed integration of research of metabolomics and gut microbiome, as well as potential application of the findings in precision nutrition.

  17. Modulation of Colorectal Cancer Risk by Polymorphisms in 51Gln/His, 64Ile/Val, and 148Asp/Glu of APEX Gene; 23Gly/Ala of XPA Gene; and 689Ser/Arg of ERCC4 Gene

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    L. Dziki

    2017-01-01

    Full Text Available Polymorphisms in DNA repair genes may affect the activity of the BER (base excision repair and NER (nucleotide excision repair systems. Using DNA isolated from blood taken from patients (n=312 and a control group (n=320 with CRC, we have analyzed the polymorphisms of selected DNA repair genes and we have demonstrated that genotypes 51Gln/His and 148Asp/Glu of APEX gene and 23Gly/Ala of XPA gene may increase the risk of colorectal cancer. At the same time analyzing the gene-gene interactions, we suggest the thesis that the main factor to be considered when analyzing the impact of polymorphisms on the risk of malignant transformation should be intergenic interactions. Moreover, we are suggesting that some polymorphisms may have impact not only on the malignant transformation but also on the stage of the tumor.

  18. Hierarchical clustering of breast cancer methylomes revealed differentially methylated and expressed breast cancer genes.

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    I-Hsuan Lin

    Full Text Available Oncogenic transformation of normal cells often involves epigenetic alterations, including histone modification and DNA methylation. We conducted whole-genome bisulfite sequencing to determine the DNA methylomes of normal breast, fibroadenoma, invasive ductal carcinomas and MCF7. The emergence, disappearance, expansion and contraction of kilobase-sized hypomethylated regions (HMRs and the hypomethylation of the megabase-sized partially methylated domains (PMDs are the major forms of methylation changes observed in breast tumor samples. Hierarchical clustering of HMR revealed tumor-specific hypermethylated clusters and differential methylated enhancers specific to normal or breast cancer cell lines. Joint analysis of gene expression and DNA methylation data of normal breast and breast cancer cells identified differentially methylated and expressed genes associated with breast and/or ovarian cancers in cancer-specific HMR clusters. Furthermore, aberrant patterns of X-chromosome inactivation (XCI was found in breast cancer cell lines as well as breast tumor samples in the TCGA BRCA (breast invasive carcinoma dataset. They were characterized with differentially hypermethylated XIST promoter, reduced expression of XIST, and over-expression of hypomethylated X-linked genes. High expressions of these genes were significantly associated with lower survival rates in breast cancer patients. Comprehensive analysis of the normal and breast tumor methylomes suggests selective targeting of DNA methylation changes during breast cancer progression. The weak causal relationship between DNA methylation and gene expression observed in this study is evident of more complex role of DNA methylation in the regulation of gene expression in human epigenetics that deserves further investigation.

  19. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

  20. You've gotta be lucky: Coverage and the elusive gene-gene interaction.

    Science.gov (United States)

    Reimherr, Matthew; Nicolae, Dan L

    2011-01-01

    Genome-wide association studies (GWAS) have led to a large number of single-SNP association findings, but there has been, so far, no investigation resulting in the discovery of a replicable gene-gene interaction. In this paper, we examine some of the possible explanations for the lack of findings, and argue that coverage of causal variation not only has a large effect on the loss in power, but that the effect is larger than in the single-SNP analyses. We show that the product of linkage disequilibrium measures, r², between causal and tested SNPs offers a good approximation to the loss in efficiency as defined by the ratio of sample sizes that lead to similar power. We also demonstrate that, in addition to the huge search space, the loss in power due to coverage when using commercially available platforms makes the search for gene-gene interactions daunting. © 2010 The Authors Annals of Human Genetics © 2010 Blackwell Publishing Ltd/University College London.

  1. Environment-Gene interaction in common complex diseases: New approaches

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    William A. Toscano, Jr.

    2014-10-01

    Full Text Available Approximately 100,000 different environmental chemicals that are in use as high production volume chemicals confront us in our daily lives. Many of the chemicals we encounter are persistent and have long half-lives in the environment and our bodies. These compounds are referred to as Persistent Organic Pollutants, or POPS. The total environment however is broader than just toxic pollutants. It includes social capital, social economic status, and other factors that are not commonly considered in traditional approaches to studying environment-human interactions. The mechanism of action of environmental agents in altering the human phenotype from health to disease is more complex than once thought. The focus in public health has shifted away from the study of single-gene rare diseases and has given way to the study of multifactorial complex diseases that are common in the population. To understand common complex diseases, we need teams of scientists from different fields working together with common aims. We review some approaches for studying the action of the environment by discussing use-inspired research, and transdisciplinary research approaches. The Genomic era has yielded new tools for study of gene-environment interactions, including genomics, epigenomics, and systems biology. We use environmentally-driven diabetes mellitus type two as an example of environmental epigenomics and disease. The aim of this review is to start the conversation of how the application of advances in biomedical science can be used to advance public health.

  2. Gene-environment interaction and male reproductive function

    Science.gov (United States)

    Axelsson, Jonatan; Bonde, Jens Peter; Giwercman, Yvonne L.; Rylander, Lars; Giwercman, Aleksander

    2010-01-01

    As genetic factors can hardly explain the changes taking place during short time spans, environmental and lifestyle-related factors have been suggested as the causes of time-related deterioration of male reproductive function. However, considering the strong heterogeneity of male fecundity between and within populations, genetic variants might be important determinants of the individual susceptibility to the adverse effects of environment or lifestyle. Although the possible mechanisms of such interplay in relation to the reproductive system are largely unknown, some recent studies have indicated that specific genotypes may confer a larger risk of male reproductive disorders following certain exposures. This paper presents a critical review of animal and human evidence on how genes may modify environmental effects on male reproductive function. Some examples have been found that support this mechanism, but the number of studies is still limited. This type of interaction studies may improve our understanding of normal physiology and help us to identify the risk factors to male reproductive malfunction. We also shortly discuss other aspects of gene-environment interaction specifically associated with the issue of reproduction, namely environmental and lifestyle factors as the cause of sperm DNA damage. It remains to be investigated to what extent such genetic changes, by natural conception or through the use of assisted reproductive techniques, are transmitted to the next generation, thereby causing increased morbidity in the offspring. PMID:20348940

  3. Nuclear Imaging for Assessment of Prostate Cancer Gene Therapy

    Science.gov (United States)

    2007-03-01

    thymidine kinase transfected EL4 cells . Further exploration of Tc-99m conjugated potential HSV1-TK substrates is still undergoing in our laboratory...prostate cancer cells , has been demonstrated the utility for tissue-specific toxic gene therapy for prostate cancer[10, 11]. Therefore, an adenovirus...BJ5183 together with pAdeasy-1, the viral DNA plasmid. The pAdeasy-1 is E1 and E3 deleted, its E1 function can be complemented in 293A cells . The

  4. New genomic structure for prostate cancer specific gene PCA3 within BMCC1: implications for prostate cancer detection and progression.

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    Raymond A Clarke

    Full Text Available The prostate cancer antigen 3 (PCA3/DD3 gene is a highly specific biomarker upregulated in prostate cancer (PCa. In order to understand the importance of PCA3 in PCa we investigated the organization and evolution of the PCA3 gene locus.We have employed cDNA synthesis, RTPCR and DNA sequencing to identify 4 new transcription start sites, 4 polyadenylation sites and 2 new differentially spliced exons in an extended form of PCA3. Primers designed from these novel PCA3 exons greatly improve RT-PCR based discrimination between PCa, PCa metastases and BPH specimens. Comparative genomic analyses demonstrated that PCA3 has only recently evolved in an anti-sense orientation within a second gene, BMCC1/PRUNE2. BMCC1 has been shown previously to interact with RhoA and RhoC, determinants of cellular transformation and metastasis, respectively. Using RT-PCR we demonstrated that the longer BMCC1-1 isoform - like PCA3 - is upregulated in PCa tissues and metastases and in PCa cell lines. Furthermore PCA3 and BMCC1-1 levels are responsive to dihydrotestosterone treatment.Upregulation of two new PCA3 isoforms in PCa tissues improves discrimination between PCa and BPH. The functional relevance of this specificity is now of particular interest given PCA3's overlapping association with a second gene BMCC1, a regulator of Rho signalling. Upregulation of PCA3 and BMCC1 in PCa has potential for improved diagnosis.

  5. A sparse regulatory network of copy-number driven gene expression reveals putative breast cancer oncogenes.

    Science.gov (United States)

    Yuan, Yinyin; Curtis, Christina; Caldas, Carlos; Markowetz, Florian

    2012-01-01

    Copy number aberrations are recognized to be important in cancer as they may localize to regions harboring oncogenes or tumor suppressors. Such genomic alterations mediate phenotypic changes through their impact on expression. Both cis- and transacting alterations are important since they may help to elucidate putative cancer genes. However, amidst numerous passenger genes, trans-effects are less well studied due to the computational difficulty in detecting weak and sparse signals in the data, and yet may influence multiple genes on a global scale. We propose an integrative approach to learn a sparse interaction network of DNA copy-number regions with their downstream transcriptional targets in breast cancer. With respect to goodness of fit on both simulated and real data, the performance of sparse network inference is no worse than other state-of-the-art models but with the advantage of simultaneous feature selection and efficiency. The DNA-RNA interaction network helps to distinguish copy-number driven expression alterations from those that are copy-number independent. Further, our approach yields a quantitative copy-number dependency score, which distinguishes cis- versus trans-effects. When applied to a breast cancer data set, numerous expression profiles were impacted by cis-acting copy-number alterations, including several known oncogenes such as GRB7, ERBB2, and LSM1. Several trans-acting alterations were also identified, impacting genes such as ADAM2 and BAGE, which warrant further investigation. An R package named lol is available from www.markowetzlab.org/software/lol.html.

  6. STAT3 Target Genes Relevant to Human Cancers

    International Nuclear Information System (INIS)

    Carpenter, Richard L.; Lo, Hui-Wen

    2014-01-01

    Since its discovery, the STAT3 transcription factor has been extensively studied for its function as a transcriptional regulator and its role as a mediator of development, normal physiology, and pathology of many diseases, including cancers. These efforts have uncovered an array of genes that can be positively and negatively regulated by STAT3, alone and in cooperation with other transcription factors. Through regulating gene expression, STAT3 has been demonstrated to play a pivotal role in many cellular processes including oncogenesis, tumor growth and progression, and stemness. Interestingly, recent studies suggest that STAT3 may behave as a tumor suppressor by activating expression of genes known to inhibit tumorigenesis. Additional evidence suggested that STAT3 may elicit opposing effects depending on cellular context and tumor types. These mixed results signify the need for a deeper understanding of STAT3, including its upstream regulators, parallel transcription co-regulators, and downstream target genes. To help facilitate fulfilling this unmet need, this review will be primarily focused on STAT3 downstream target genes that have been validated to associate with tumorigenesis and/or malignant biology of human cancers

  7. Identification of new candidate drugs for lung cancer using chemical-chemical interactions, chemical-protein interactions and a K-means clustering algorithm.

    Science.gov (United States)

    Lu, Jing; Chen, Lei; Yin, Jun; Huang, Tao; Bi, Yi; Kong, Xiangyin; Zheng, Mingyue; Cai, Yu-Dong

    2016-01-01

    Lung cancer, characterized by uncontrolled cell growth in the lung tissue, is the leading cause of global cancer deaths. Until now, effective treatment of this disease is limited. Many synthetic compounds have emerged with the advancement of combinatorial chemistry. Identification of effective lung cancer candidate drug compounds among them is a great challenge. Thus, it is necessary to build effective computational methods that can assist us in selecting for potential lung cancer drug compounds. In this study, a computational method was proposed to tackle this problem. The chemical-chemical interactions and chemical-protein interactions were utilized to select candidate drug compounds that have close associations with approved lung cancer drugs and lung cancer-related genes. A permutation test and K-means clustering algorithm were employed to exclude candidate drugs with low possibilities to treat lung cancer. The final analysis suggests that the remaining drug compounds have potential anti-lung cancer activities and most of them have structural dissimilarity with approved drugs for lung cancer.

  8. Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry.

    Directory of Open Access Journals (Sweden)

    Cameron M Scott

    Full Text Available DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.

  9. Inherited variation in circadian rhythm genes and risks of prostate cancer and three other cancer sites in combined cancer consortia.

    Science.gov (United States)

    Gu, Fangyi; Zhang, Han; Hyland, Paula L; Berndt, Sonja; Gapstur, Susan M; Wheeler, William; Ellipse Consortium, The; Amos, Christopher I; Bezieau, Stephane; Bickeböller, Heike; Brenner, Hermann; Brennan, Paul; Chang-Claude, Jenny; Conti, David V; Doherty, Jennifer Anne; Gruber, Stephen B; Harrison, Tabitha A; Hayes, Richard B; Hoffmeister, Michael; Houlston, Richard S; Hung, Rayjean J; Jenkins, Mark A; Kraft, Peter; Lawrenson, Kate; McKay, James; Markt, Sarah; Mucci, Lorelei; Phelan, Catherine M; Qu, Conghui; Risch, Angela; Rossing, Mary Anne; Wichmann, H-Erich; Shi, Jianxin; Schernhammer, Eva; Yu, Kai; Landi, Maria Teresa; Caporaso, Neil E

    2017-11-01

    Circadian disruption has been linked to carcinogenesis in animal models, but the evidence in humans is inconclusive. Genetic variation in circadian rhythm genes provides a tool to investigate such associations. We examined associations of genetic variation in nine core circadian rhythm genes and six melatonin pathway genes with risk of colorectal, lung, ovarian and prostate cancers using data from the Genetic Associations and Mechanisms in Oncology (GAME-ON) network. The major results for prostate cancer were replicated in the Prostate, Lung, Colorectal and Ovarian (PLCO) cancer screening trial, and for colorectal cancer in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). The total number of cancer cases and controls was 15,838/18,159 for colorectal, 14,818/14,227 for prostate, 12,537/17,285 for lung and 4,369/9,123 for ovary. For each cancer site, we conducted gene-based and pathway-based analyses by applying the summary-based Adaptive Rank Truncated Product method (sARTP) on the summary association statistics for each SNP within the candidate gene regions. Aggregate genetic variation in circadian rhythm and melatonin pathways were significantly associated with the risk of prostate cancer in data combining GAME-ON and PLCO, after Bonferroni correction (p pathway  circadian rhythm pathway in GAME-ON (p pathway  = 0.021); this association was not confirmed in GECCO (p pathway  = 0.76) or the combined data (p pathway  = 0.17). No significant association was observed for ovarian and lung cancer. These findings support a potential role for circadian rhythm and melatonin pathways in prostate carcinogenesis. Further functional studies are needed to better understand the underlying biologic mechanisms. © 2017 UICC.

  10. Host pathogen interactions in Helicobacter pylori related gastric cancer

    Science.gov (United States)

    Chmiela, Magdalena; Karwowska, Zuzanna; Gonciarz, Weronika; Allushi, Bujana; Stączek, Paweł

    2017-01-01

    Helicobacter pylori (H. pylori), discovered in 1982, is a microaerophilic, spiral-shaped gram-negative bacterium that is able to colonize the human stomach. Nearly half of the world's population is infected by this pathogen. Its ability to induce gastritis, peptic ulcers, gastric cancer and mucosa-associated lymphoid tissue lymphoma has been confirmed. The susceptibility of an individual to these clinical outcomes is multifactorial and depends on H. pylori virulence, environmental factors, the genetic susceptibility of the host and the reactivity of the host immune system. Despite the host immune response, H. pylori infection can be difficult to eradicate. H. pylori is categorized as a group I carcinogen since this bacterium is responsible for the highest rate of cancer-related deaths worldwide. Early detection of cancer can be lifesaving. The 5-year survival rate for gastric cancer patients diagnosed in the early stages is nearly 90%. Gastric cancer is asymptomatic in the early stages but always progresses over time and begins to cause symptoms when untreated. In 97% of stomach cancer cases, cancer cells metastasize to other organs. H. pylori infection is responsible for nearly 60% of the intestinal-type gastric cancer cases but also influences the development of diffuse gastric cancer. The host genetic susceptibility depends on polymorphisms of genes involved in H. pylori-related inflammation and the cytokine response of gastric epithelial and immune cells. H. pylori strains differ in their ability to induce a deleterious inflammatory response. H. pylori-driven cytokines accelerate the inflammatory response and promote malignancy. Chronic H. pylori infection induces genetic instability in gastric epithelial cells and affects the DNA damage repair systems. Therefore, H. pylori infection should always be considered a pro-cancerous factor. PMID:28321154

  11. Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer

    Science.gov (United States)

    Makondi, Precious Takondwa; Lee, Chia-Hwa; Huang, Chien-Yu; Chu, Chi-Ming; Chang, Yu-Jia

    2018-01-01

    Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC) therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO) database (dataset, GSE86525) was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs). Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID). Protein–protein interaction (PPI) networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING) and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs); the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A), toll-like receptor 4 (TLR4), CD19 molecule (CD19), breast cancer 1, early onset (BRCA1), platelet-derived growth factor subunit A (PDGFA), and matrix metallopeptidase 1 (MMP1) were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4) revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS). The identified genes and pathways

  12. Prediction of novel target genes and pathways involved in bevacizumab-resistant colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Precious Takondwa Makondi

    Full Text Available Bevacizumab combined with cytotoxic chemotherapy is the backbone of metastatic colorectal cancer (mCRC therapy; however, its treatment efficacy is hampered by therapeutic resistance. Therefore, understanding the mechanisms underlying bevacizumab resistance is crucial to increasing the therapeutic efficacy of bevacizumab. The Gene Expression Omnibus (GEO database (dataset, GSE86525 was used to identify the key genes and pathways involved in bevacizumab-resistant mCRC. The GEO2R web tool was used to identify differentially expressed genes (DEGs. Functional and pathway enrichment analyses of the DEGs were performed using the Database for Annotation, Visualization, and Integrated Discovery(DAVID. Protein-protein interaction (PPI networks were established using the Search Tool for the Retrieval of Interacting Genes/Proteins database(STRING and visualized using Cytoscape software. A total of 124 DEGs were obtained, 57 of which upregulated and 67 were downregulated. PPI network analysis showed that seven upregulated genes and nine downregulated genes exhibited high PPI degrees. In the functional enrichment, the DEGs were mainly enriched in negative regulation of phosphate metabolic process and positive regulation of cell cycle process gene ontologies (GOs; the enriched pathways were the phosphoinositide 3-kinase-serine/threonine kinase signaling pathway, bladder cancer, and microRNAs in cancer. Cyclin-dependent kinase inhibitor 1A(CDKN1A, toll-like receptor 4 (TLR4, CD19 molecule (CD19, breast cancer 1, early onset (BRCA1, platelet-derived growth factor subunit A (PDGFA, and matrix metallopeptidase 1 (MMP1 were the DEGs involved in the pathways and the PPIs. The clinical validation of the DEGs in mCRC (TNM clinical stages 3 and 4 revealed that high PDGFA expression levels were associated with poor overall survival, whereas high BRCA1 and MMP1 expression levels were associated with favorable progress free survival(PFS. The identified genes and pathways

  13. Epigenetic changes of DNA repair genes in cancer.

    Science.gov (United States)

    Lahtz, Christoph; Pfeifer, Gerd P

    2011-02-01

    'Every Hour Hurts, The Last One Kills'. That is an old saying about getting old. Every day, thousands of DNA damaging events take place in each cell of our body, but efficient DNA repair systems have evolved to prevent that. However, our DNA repair system and that of most other organisms are not as perfect as that of Deinococcus radiodurans, for example, which is able to repair massive amounts of DNA damage at one time. In many instances, accumulation of DNA damage has been linked to cancer, and genetic deficiencies in specific DNA repair genes are associated with tumor-prone phenotypes. In addition to mutations, which can be either inherited or somatically acquired, epigenetic silencing of DNA repair genes may promote tumorigenesis. This review will summarize current knowledge of the epigenetic inactivation of different DNA repair components in human cancer.

  14. Influence of SNPs in nutrient-sensitive candidate genes and gene-diet interactions on blood lipids

    DEFF Research Database (Denmark)

    Brahe, Lena Kirchner; Angquist, Lars; Larsen, Lesli Hingstrup

    2013-01-01

    Blood lipid response to a given dietary intervention could be determined by the effect of diet, gene variants or gene-diet interactions. The objective of the present study was to investigate whether variants in presumed nutrient-sensitive genes involved in lipid metabolism modified lipid profile ...

  15. Sleep Duration and Depressive Symptoms: A Gene-Environment Interaction

    Science.gov (United States)

    Watson, Nathaniel F.; Harden, Kathryn Paige; Buchwald, Dedra; Vitiello, Michael V.; Pack, Allan I.; Strachan, Eric; Goldberg, Jack

    2014-01-01

    Objective: We used quantitative genetic models to assess whether sleep duration modifies genetic and environmental influences on depressive symptoms. Method: Participants were 1,788 adult twins from 894 same-sex twin pairs (192 male and 412 female monozygotic [MZ] pairs, and 81 male and 209 female dizygotic [DZ] pairs] from the University of Washington Twin Registry. Participants self-reported habitual sleep duration and depressive symptoms. Data were analyzed using quantitative genetic interaction models, which allowed the magnitude of additive genetic, shared environmental, and non-shared environmental influences on depressive symptoms to vary with sleep duration. Results: Within MZ twin pairs, the twin who reported longer sleep duration reported fewer depressive symptoms (ec = -0.17, SE = 0.06, P sleep duration interaction effect on depressive symptoms (a'c = 0.23, SE = 0.08, P sleep duration and depressive symptoms. Among individuals with sleep duration within the normal range (7-8.9 h/night), the total heritability (h2) of depressive symptoms was approximately 27%. However, among individuals with sleep duration within the low (sleep duration extremes (5 h/night: h2 = 53%; 10 h/night: h2 = 49%). Conclusion: Genetic contributions to depressive symptoms increase at both short and long sleep durations. Citation: Watson NF; Harden KP; Buchwald D; Vitiello MV; Pack AI; Stachan E; Goldberg J. Sleep duration and depressive symptoms: a gene-environment interaction. SLEEP 2014;37(2):351-358. PMID:24497663

  16. Random regression models for detection of gene by environment interaction

    Directory of Open Access Journals (Sweden)

    Meuwissen Theo HE

    2007-02-01

    Full Text Available Abstract Two random regression models, where the effect of a putative QTL was regressed on an environmental gradient, are described. The first model estimates the correlation between intercept and slope of the random regression, while the other model restricts this correlation to 1 or -1, which is expected under a bi-allelic QTL model. The random regression models were compared to a model assuming no gene by environment interactions. The comparison was done with regards to the models ability to detect QTL, to position them accurately and to detect possible QTL by environment interactions. A simulation study based on a granddaughter design was conducted, and QTL were assumed, either by assigning an effect independent of the environment or as a linear function of a simulated environmental gradient. It was concluded that the random regression models were suitable for detection of QTL effects, in the presence and absence of interactions with environmental gradients. Fixing the correlation between intercept and slope of the random regression had a positive effect on power when the QTL effects re-ranked between environments.

  17. Leucine zipper, down regulated in cancer-1 gene expression in prostate cancer

    OpenAIRE

    Salemi, Michele; Barone, Nunziata; La Vignera, Sandro; Condorelli, Rosita A.; Recupero, Domenico; Galia, Antonio; Fraggetta, Filippo; Aiello, Anna Maria; Pepe, Pietro; Castiglione, Roberto; Vicari, Enzo; Calogero, Aldo E.

    2016-01-01

    Numerous genetic alterations have been implicated in the development of prostate cancer (PCa). DNA and protein microarrays have enabled the identification of genes associated with apoptosis, which is important in PCa development. Despite the molecular mechanisms are not entirely understood, inhibition of apoptosis is a critical pathophysiological factor that contributes to the onset and progression of PCa. Leucine zipper, down-regulated in cancer 1 (LDOC-1) is a known regulator of the nuclear...

  18. Gene selection for cancer classification with the help of bees.

    Science.gov (United States)

    Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

    2016-08-10

    Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

  19. Locating a Prostate Cancer Susceptibility Gene on the X Chromosome by Linkage Disequilibrium Mapping Using Three Founder Populations in Quebec and Switzerland

    Science.gov (United States)

    2006-09-01

    Gordon PH, Wang Q, Puisieux, A, Foulkes WD and Trifiro M. Polymorphisms and HNPCC: PMS2 -MLH1 protein interactions diminished by ‘single nucleotide...and PMS2 responsible for hereditary nonpolyposis colorectal cancer (HNPCC). Genes Chromosomes Cancer, 44 (2): 123-38, 2005. 120. Soravia C

  20. Integrated bioinformatics analysis reveals key candidate genes and pathways in breast cancer.

    Science.gov (United States)

    Wang, Yuzhi; Zhang, Yi; Huang, Qian; Li, Chengwen

    2018-04-19

    Breast cancer (BC) is the leading malignancy in women worldwide, yet relatively little is known about the genes and signaling pathways involved in BC tumorigenesis and progression. The present study aimed to elucidate potential key candidate genes and pathways in BC. Five gene expression profile data sets (GSE22035, GSE3744, GSE5764, GSE21422 and GSE26910) were downloaded from the Gene Expression Omnibus (GEO) database, which included data from 113 tumorous and 38 adjacent non‑tumorous tissue samples. Differentially expressed genes (DEGs) were identified using t‑tests in the limma R package. These DEGs were subsequently investigated by pathway enrichment analysis and a protein‑protein interaction (PPI) network was constructed. The most significant module from the PPI network was selected for pathway enrichment analysis. In total, 227 DEGs were identified, of which 82 were upregulated and 145 were downregulated. Pathway enrichment analysis results revealed that the upregulated DEGs were mainly enriched in 'cell division', the 'proteinaceous extracellular matrix (ECM)', 'ECM structural constituents' and 'ECM‑receptor interaction', whereas downregulated genes were mainly enriched in 'response to drugs', 'extracellular space', 'transcriptional activator activity' and the 'peroxisome proliferator‑activated receptor signaling pathway'. The PPI network contained 174 nodes and 1,257 edges. DNA topoisomerase 2‑a, baculoviral inhibitor of apoptosis repeat‑containing protein 5, cyclin‑dependent kinase 1, G2/mitotic‑specific cyclin‑B1 and kinetochore protein NDC80 homolog were identified as the top 5 hub genes. Furthermore, the genes in the most significant module were predominantly involved in 'mitotic nuclear division', 'mid‑body', 'protein binding' and 'cell cycle'. In conclusion, the DEGs, relative pathways and hub genes identified in the present study may aid in understanding of the molecular mechanisms underlying BC progression and provide

  1. Identification of novel androgen receptor target genes in prostate cancer

    Directory of Open Access Journals (Sweden)

    Gerald William L

    2007-06-01

    Full Text Available Abstract Background The androgen receptor (AR plays critical roles in both androgen-dependent and castrate-resistant prostate cancer (PCa. However, little is known about AR target genes that mediate the receptor's roles in disease progression. Results Using Chromatin Immunoprecipitation (ChIP Display, we discovered 19 novel loci occupied by the AR in castrate resistant C4-2B PCa cells. Only four of the 19 AR-occupied regions were within 10-kb 5'-flanking regulatory sequences. Three were located up to 4-kb 3' of the nearest gene, eight were intragenic and four were in gene deserts. Whereas the AR occupied the same loci in C4-2B (castrate resistant and LNCaP (androgen-dependent PCa cells, differences between the two cell lines were observed in the response of nearby genes to androgens. Among the genes strongly stimulated by DHT in C4-2B cells – D-dopachrome tautomerase (DDT, Protein kinase C delta (PRKCD, Glutathione S- transferase theta 2 (GSTT2, Transient receptor potential cation channel subfamily V member 3 (TRPV3, and Pyrroline-5-carboxylate reductase 1 (PYCR1 – most were less strongly or hardly stimulated in LNCaP cells. Another AR target gene, ornithine aminotransferase (OAT, was AR-stimulated in a ligand-independent manner, since it was repressed by AR siRNA knockdown, but not stimulated by DHT. We also present evidence for in vivo AR-mediated regulation of several genes identified by ChIP Display. For example, PRKCD and PYCR1, which may contribute to PCa cell growth and survival, are expressed in PCa biopsies from primary tumors before and after ablation and in metastatic lesions in a manner consistent with AR-mediated stimulation. Conclusion AR genomic occupancy is similar between LNCaP and C4-2B cells and is not biased towards 5' gene flanking sequences. The AR transcriptionally regulates less than half the genes nearby AR-occupied regions, usually but not always, in a ligand-dependent manner. Most are stimulated and a few are

  2. Interactions between environmental factors and melatonin receptor type 1A polymorphism in relation to oral cancer susceptibility and clinicopathologic development.

    Directory of Open Access Journals (Sweden)

    Feng-Yan Lin

    Full Text Available The purpose of this study was to explore the combined effect of melatonin receptor type 1A (MTNR1A gene polymorphisms and exposure to environmental carcinogens on the susceptibility and clinicopathological characteristics of oral cancer.Three polymorphisms of the MTNR1A gene from 618 patients with oral cancer and 560 non-cancer controls were analyzed by real-time polymerase chain reaction (PCR. The CTA haplotype of the studied MTNR1A polymorphisms (rs2119882, rs13140012, rs6553010 was related to a higher risk of oral cancer. Moreover, MTNR1A gene polymorphisms exhibited synergistic effects of environmental factors (betel quid and tobacco use on the susceptibility of oral cancer. Finally, oral-cancer patients with betel quid-chewing habit who had T/T allele of MTNR1A rs13140012 were at higher risk for developing an advanced clinical stage and lymph node metastasis.These results support gene-environment interactions of MTNR1A polymorphisms with smoking and betel quid-chewing habits possibly altering oral-cancer susceptibility and metastasis.

  3. Targeted Gene Therapy of Cancer: Second Amendment toward Holistic Therapy.

    Science.gov (United States)

    Barar, Jaleh; Omidi, Yadollah

    2013-01-01

    It seems solid tumors are developing smart organs with specialized cells creating specified bio-territory, the so called "tumor microenvironment (TME)", in which there is reciprocal crosstalk among cancer cells, immune system cells and stromal cells. TME as an intricate milieu also consists of cancer stem cells (CSCs) that can resist against chemotherapies. In solid tumors, metabolism and vascularization appears to be aberrant and tumor interstitial fluid (TIF) functions as physiologic barrier. Thus, chemotherapy, immunotherapy and gene therapy often fail to provide cogent clinical outcomes. It looms that it is the time to accept the fact that initiation of cancer could be generation of another form of life that involves a cluster of thousands of genes, while we have failed to observe all aspects of it. Hence, the current treatment modalities need to be re-visited to cover all key aspects of disease using combination therapy based on the condition of patients. Perhaps personalized cluster of genes need to be simultaneously targeted.

  4. Targeted Gene Therapy of Cancer: Second Amendment toward Holistic Therapy

    Directory of Open Access Journals (Sweden)

    Jaleh Barar

    2013-02-01

    Full Text Available It seems solid tumors are developing smart organs with specialized cells creating specified bio-territory, the so called “tumor microenvironment (TME”, in which there is reciprocal crosstalk among cancer cells, immune system cells and stromal cells. TME as an intricate milieu also consists of cancer stem cells (CSCs that can resist against chemotherapies. In solid tumors, metabolism and vascularization appears to be aberrant and tumor interstitial fluid (TIF functions as physiologic barrier. Thus, chemotherapy, immunotherapy and gene therapy often fail to provide cogent clinical outcomes. It looms that it is the time to accept the fact that initiation of cancer could be generation of another form of life that involves a cluster of thousands of genes, while we have failed to observe all aspects of it. Hence, the current treatment modalities need to be re-visited to cover all key aspects of disease using combination therapy based on the condition of patients. Perhaps personalized cluster of genes need to be simultaneously targeted.

  5. [Gene-gene interaction on central obesity in school-aged children in China].

    Science.gov (United States)

    Fu, L W; Zhang, M X; Wu, L J; Gao, L W; Mi, J

    2017-07-10

    Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms ( FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model ( OR =1.24, 95 %CI : 1.06-1.45, P =0.008; OR =1.26, 95 %CI : 1.11-1.43, P =2.98×10(-4); OR =1.18, 95 % CI : 1.06-1.32, P =0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 ( P =0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the

  6. Screening for common copy-number variants in cancer genes.

    Science.gov (United States)

    Tyson, Jess; Majerus, Tamsin M O; Walker, Susan; Armour, John A L

    2010-12-01

    For most cases of colorectal cancer that arise without a family history of the disease, it is proposed that an appreciable heritable component of predisposition is the result of contributions from many loci. Although progress has been made in identifying single nucleotide variants associated with colorectal cancer risk, the involvement of low-penetrance copy number variants is relatively unexplored. We have used multiplex amplifiable probe hybridization (MAPH) in a fourfold multiplex (QuadMAPH), positioned at an average resolution of one probe per 2 kb, to screen a total of 1.56 Mb of genomic DNA for copy number variants around the genes APC, AXIN1, BRCA1, BRCA2, CTNNB1, HRAS, MLH1, MSH2, and TP53. Two deletion events were detected, one upstream of MLH1 in a control individual and the other in APC in a colorectal cancer patient, but these do not seem to correspond to copy number polymorphisms with measurably high population frequencies. In summary, by means of our QuadMAPH assay, copy number measurement data were of sufficient resolution and accuracy to detect any copy number variants with high probability. However, this study has demonstrated a very low incidence of deletion and duplication variants within intronic and flanking regions of these nine genes, in both control individuals and colorectal cancer patients. Copyright © 2010 Elsevier Inc. All rights reserved.

  7. A systematic study on drug-response associated genes using baseline gene expressions of the Cancer Cell Line Encyclopedia

    Science.gov (United States)

    Liu, Xiaoming; Yang, Jiasheng; Zhang, Yi; Fang, Yun; Wang, Fayou; Wang, Jun; Zheng, Xiaoqi; Yang, Jialiang

    2016-03-01

    We have studied drug-response associated (DRA) gene expressions by applying a systems biology framework to the Cancer Cell Line Encyclopedia data. More than 4,000 genes are inferred to be DRA for at least one drug, while the number of DRA genes for each drug varies dramatically from almost 0 to 1,226. Functional enrichment analysis shows that the DRA genes are significantly enriched in genes associated with cell cycle and plasma membrane. Moreover, there might be two patterns of DRA genes between genders. There are significantly shared DRA genes between male and female for most drugs, while very little DRA genes tend to be shared between the two genders for a few drugs targeting sex-specific cancers (e.g., PD-0332991 for breast cancer and ovarian cancer). Our analyses also show substantial difference for DRA genes between young and old samples, suggesting the necessity of considering the age effects for personalized medicine in cancers. Lastly, differential module and key driver analyses confirm cell cycle related modules as top differential ones for drug sensitivity. The analyses also reveal the role of TSPO, TP53, and many other immune or cell cycle related genes as important key drivers for DRA network modules. These key drivers provide new drug targets to improve the sensitivity of cancer therapy.

  8. Evaluation of candidate stromal epithelial cross-talk genes identifies association between risk of serous ovarian cancer and TERT, a cancer susceptibility "hot-spot".

    Directory of Open Access Journals (Sweden)

    Sharon E Johnatty

    2010-07-01

    Full Text Available We hypothesized that variants in genes expressed as a consequence of interactions between ovarian cancer cells and the host micro-environment could contribute to cancer susceptibility. We therefore used a two-stage approach to evaluate common single nucleotide polymorphisms (SNPs in 173 genes involved in stromal epithelial interactions in the Ovarian Cancer Association Consortium (OCAC. In the discovery stage, cases with epithelial ovarian cancer (n=675 and controls (n=1,162 were genotyped at 1,536 SNPs using an Illumina GoldenGate assay. Based on Positive Predictive Value estimates, three SNPs-PODXL rs1013368, ITGA6 rs13027811, and MMP3 rs522616-were selected for replication using TaqMan genotyping in up to 3,059 serous invasive cases and 8,905 controls from 16 OCAC case-control studies. An additional 18 SNPs with Pper-alleleor=0.5. However genotypes at TERT rs7726159 were associated with ovarian cancer risk in the smaller, five-study replication study (Pper-allele=0.03. Combined analysis of the discovery and replication sets for this TERT SNP showed an increased risk of serous ovarian cancer among non-Hispanic whites [adj. ORper-allele 1.14 (1.04-1.24 p=0.003]. Our study adds to the growing evidence that, like the 8q24 locus, the telomerase reverse transcriptase locus at 5p15.33, is a general cancer susceptibility locus.

  9. Suppression subtractive hybridization identified differentially expressed genes in lung adenocarcinoma: ERGIC3 as a novel lung cancer-related gene

    International Nuclear Information System (INIS)

    Wu, Mingsong; Tu, Tao; Huang, Yunchao; Cao, Yi

    2013-01-01

    To understand the carcinogenesis caused by accumulated genetic and epigenetic alterations and seek novel biomarkers for various cancers, studying differentially expressed genes between cancerous and normal tissues is crucial. In the study, two cDNA libraries of lung cancer were constructed and screened for identification of differentially expressed genes. Two cDNA libraries of differentially expressed genes were constructed using lung adenocarcinoma tissue and adjacent nonmalignant lung tissue by suppression subtractive hybridization. The data of the cDNA libraries were then analyzed and compared using bioinformatics analysis. Levels of mRNA and protein were measured by quantitative real-time polymerase chain reaction (q-RT-PCR) and western blot respectively, as well as expression and localization of proteins were determined by immunostaining. Gene functions were investigated using proliferation and migration assays after gene silencing and gene over-expression. Two libraries of differentially expressed genes were obtained. The forward-subtracted library (FSL) and the reverse-subtracted library (RSL) contained 177 and 59 genes, respectively. Bioinformatic analysis demonstrated that these genes were involved in a wide range of cellular functions. The vast majority of these genes were newly identified to be abnormally expressed in lung cancer. In the first stage of the screening for 16 genes, we compared lung cancer tissues with their adjacent non-malignant tissues at the mRNA level, and found six genes (ERGIC3, DDR1, HSP90B1, SDC1, RPSA, and LPCAT1) from the FSL were significantly up-regulated while two genes (GPX3 and TIMP3) from the RSL were significantly down-regulated (P < 0.05). The ERGIC3 protein was also over-expressed in lung cancer tissues and cultured cells, and expression of ERGIC3 was correlated with the differentiated degree and histological type of lung cancer. The up-regulation of ERGIC3 could promote cellular migration and proliferation in vitro. The

  10. Gene Expression Analyses of HER-2/neu and ESR1 in Patients with Breast Cancer

    Directory of Open Access Journals (Sweden)

    Omid Kheyri Nadergoli

    2017-10-01

    Full Text Available ABSTRACT Background: Her-2 and ESR1 genes, that interact in the cell signaling pathway, are the most important molecular markers of breast cancer, which have been amplified or overexpressed in 30% and 70%, respectively. This study was performed to evaluate the gene expression levels of Her-2 and ESR1 genes in tumor cells and its adjacent normal tissue of breast cancer patients and compared them whit clinical-pathological features. Methods: In total, 80 tissue specimens from 40 patients, with an average age of 48.47 years, were examined by Real-time PCR technique, and ultimately evaluated the expression level of Her-2 and ESR1genes. The data were analyzed by REST 2009 V2.0.13 statistical software. Results: HER2 and ESR1 overexpression was identified in 19 (48% and 12 (30% of 40 patients respectively, which was higher and lower than that recorded in international statistics, respectively. ESR1 overexpression was associated with Stage 3A and lymph node involvement 2 (N2 (P = 0.04 and P = 0.047, respectively. No significant correlation was observed between the expression of HER2 and ESR1 and other clinical-pathological features, however, the relative differences were identified in the expression levels of genes between main group and groups that were classified according to the clinical-pathological features and age. Conclusions: Overexpression of Her-2 and ESR1 genes in the patients of our study are higher and lower than international statistics, respectively, indicating the differences in genetic, environmental and ethnic factors that involved in the developing of breast cancer.

  11. Inactivation of tumor suppressor genes and cancer therapy: An evolutionary game theory approach.

    Science.gov (United States)

    Khadem, Heydar; Kebriaei, Hamed; Veisi, Zahra

    2017-06-01

    Inactivation of alleles in tumor suppressor genes (TSG) is one of the important issues resulting in evolution of cancerous cells. In this paper, the evolution of healthy, one and two missed allele cells is modeled using the concept of evolutionary game theory and replicator dynamics. The proposed model also takes into account the interaction rates of the cells as designing parameters of the system. Different combinations of the equilibrium points of the parameterized nonlinear system is studied and categorized into some cases. In each case, the interaction rates' values are suggested in a way that the equilibrium points of the replicator dynamics are located on an appropriate region of the state space. Based on the suggested interaction rates, it is proved that the system doesn't have any undesirable interior equilibrium point as well. Therefore, the system will converge to the desirable region, where there is a scanty level of cancerous cells. In addition, the proposed conditions for interaction rates guarantee that, when a trajectory of the system reaches the boundaries, then it will stay there forever which is a desirable property since the equilibrium points have been already located on the boundaries, appropriately. The simulation results show the effectiveness of the suggestions in the elimination of the cancerous cells in different scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Radiation Gene-expression Signatures in Primary Breast Cancer Cells.

    Science.gov (United States)

    Minafra, Luigi; Bravatà, Valentina; Cammarata, Francesco P; Russo, Giorgio; Gilardi, Maria C; Forte, Giusi I

    2018-05-01

    In breast cancer (BC) care, radiation therapy (RT) is an efficient treatment to control localized tumor. Radiobiological research is needed to understand molecular differences that affect radiosensitivity of different tumor subtypes and the response variability. The aim of this study was to analyze gene expression profiling (GEP) in primary BC cells following irradiation with doses of 9 Gy and 23 Gy delivered by intraoperative electron radiation therapy (IOERT) in order to define gene signatures of response to high doses of ionizing radiation. We performed GEP by cDNA microarrays and evaluated cell survival after IOERT treatment in primary BC cell cultures. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was performed to validate candidate genes. We showed, for the first time, a 4-gene and a 6-gene signature, as new molecular biomarkers, in two primary BC cell cultures after exposure at 9 Gy and 23 Gy respectively, for which we observed a significantly high survival rate. Gene signatures activated by different doses of ionizing radiation may predict response to RT and contribute to defining a personalized biological-driven treatment plan. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

  13. Laughter, Humor, and Cancer: Delicate Moments and Poignant Interactional Circumstances.

    Science.gov (United States)

    Beach, Wayne A; Prickett, Erin

    2017-07-01

    Conversation analysis is employed to examine transcribed excerpts drawn from a subsample of 75 naturally occurring and video recorded interviews between cancer patients and 30 doctors. Close examination is provided of how cancer patients initiate, and doctors respond, to laughter and humor during oncology interviews. Interactions demonstrate that communication about the disease "cancer" shares qualities similar to other medical areas (e.g., primary care): the tendency for patients to initiate laughter or humor to address troubling and challenging circumstances; and that during moments when patients address personal matters, doctors are not invited and do not reciprocate with shared laughter and humor. Prominent in talk about cancer are various precarious circumstances, awkward and delicate moments mirroring the lived experiences of cancer patients (e.g., when patients attempt to minimize fears, justify that they are well when threatened with sickness, claim normality in the midst of chronic conditions, and take stances that weight loss and gain are not problematic). These examples provide a compelling case that routine cancer care involves many poignant situations managed through laughter and humor. Implications are raised for how quality care might be improved through grounded understandings of laughter, humor, and cancer.

  14. Association of common variants in mismatch repair genes and breast cancer susceptibility: a multigene study

    International Nuclear Information System (INIS)

    Conde, João; Silva, Susana N; Azevedo, Ana P; Teixeira, Valdemar; Pina, Julieta Esperança; Rueff, José; Gaspar, Jorge F

    2009-01-01

    MMR is responsible for the repair of base-base mismatches and insertion/deletion loops. Besides this, MMR is also associated with an anti-recombination function, suppressing homologous recombination. Losses of heterozygosity and/or microsatellite instability have been detected in a large number of skin samples from breast cancer patients, suggesting a potential role of MMR in breast cancer susceptibility. We carried out a hospital-based case-control study in a Caucasian Portuguese population (287 cases and 547 controls) to estimate the susceptibility to non-familial breast cancer associated with some polymorphisms in mismatch repair genes (MSH3, MSH4, MSH6, MLH1, MLH3, PMS1 and MUTYH). Using unconditional logistic regression we found that MLH3 (L844P, G>A) polymorphism GA (Leu/Pro) and AA (Pro/Pro) genotypes were associated with a decreased risk: OR = 0.65 (0.45-0.95) (p = 0.03) and OR = 0.62 (0.41-0.94) (p = 0.03), respectively. Analysis of two-way SNP interaction effects on breast cancer revealed two potential associations to breast cancer susceptibility: MSH3 Ala1045Thr/MSH6 Gly39Glu - AA/TC [OR = 0.43 (0.21-0.83), p = 0.01] associated with a decreased risk; and MSH4 Ala97Thr/MLH3 Leu844Pro - AG/AA [OR = 2.35 (1.23-4.49), p = 0.01], GG/AA [OR = 2.11 (1.12-3,98), p = 0.02], and GG/AG [adjusted OR = 1.88 (1.12-3.15), p = 0.02] all associated with an increased risk for breast cancer. It is possible that some of these common variants in MMR genes contribute significantly to breast cancer susceptibility. However, further studies with a large sample size will be needed to support our results

  15. Signal interaction of Hedgehog/GLI and epidermal growth factor receptor signaling in cancer development

    International Nuclear Information System (INIS)

    Eberl, M.

    2012-01-01

    The subject of this PhD thesis is based on the cooperation of Hedgehog (HH)/GLI with epidermal growth factor receptor (EGFR) signaling synergistically promoting oncogenic transformation and cancer growth. In previous studies we have demonstrated that the HH/GLI and EGFR signaling pathways interact synergistically resulting not only in selective induction of HH/GLI-EGFR target genes, but also in the onset of oncogenic transformation and tumor formation (Kasper, Schnidar et al. 2006; Schnidar, Eberl et al. 2009). However, the molecular key mediators acting downstream of HH/GLI and EGFR signal cooperation were largely unknown and the in vivo evidence for the therapeutic relevance of HH/GLI and EGFR signal cooperation in HH-associated cancers was lacking. During my PhD thesis I could demonstrate that the integration of EGFR and HH/GLI signaling involves activation of RAS/MEK/ERK and JUN/AP1 signaling in response to EGFR activation. Furthermore I succeeded in identifying genes, including stem cell- (SOX2, SOX9), tumor growth- (JUN, TGFA, FGF19) and metastasis-associated genes (SPP1/osteopontin, CXCR4) that showed synergistic transcriptional activation by HH/GLI-EGFR signal integration. Importantly, I could demonstrate that these genes arrange themselves within a stable interdependent signaling network, which is required for in vivo growth of basal cell carcinoma (BCC) and tumor-initiating pancreatic cancer cells. These data validate EGFR signaling as additional drug target in HH/GLI driven cancers and provide new therapeutic strategies based on combined targeting of cooperative HH/GLI-EGFR signaling and selected downstream target genes (Eberl, Klingler et al. 2012). (author) [de

  16. Inferring gene dependency network specific to phenotypic alteration based on gene expression data and clinical information of breast cancer.

    Science.gov (United States)

    Zhou, Xionghui; Liu, Juan

    2014-01-01

    Although many methods have been proposed to reconstruct gene regulatory network, most of them, when applied in the sample-based data, can not reveal the gene regulatory relations underlying the phenotypic change (e.g. normal versus cancer). In this paper, we adopt phenotype as a variable when constructing the gene regulatory network, while former researches either neglected it or only used it to select the differentially expressed genes as the inputs to construct the gene regulatory network. To be specific, we integrate phenotype information with gene expression data to identify the gene dependency pairs by using the method of conditional mutual information. A gene dependency pair (A,B) means that the influence of gene A on the phenotype depends on gene B. All identified gene dependency pairs constitute a directed network underlying the phenotype, namely gene dependency network. By this way, we have constructed gene dependency network of breast cancer from gene expression data along with two different phenotype states (metastasis and non-metastasis). Moreover, we have found the network scale free, indicating that its hub genes with high out-degrees may play critical roles in the network. After functional investigation, these hub genes are found to be biologically significant and specially related to breast cancer, which suggests that our gene dependency network is meaningful. The validity has also been justified by literature investigation. From the network, we have selected 43 discriminative hubs as signature to build the classification model for distinguishing the distant metastasis risks of breast cancer patients, and the result outperforms those classification models with published signatures. In conclusion, we have proposed a promising way to construct the gene regulatory network by using sample-based data, which has been shown to be effective and accurate in uncovering the hidden mechanism of the biological process and identifying the gene signature for

  17. MicroRNA-gene signaling pathways in pancreatic cancer

    Directory of Open Access Journals (Sweden)

    Alexandra Drakaki

    2013-10-01

    Full Text Available Pancreatic cancer is the fourth most frequent cause of cancer-related deaths and is characterized by early metastasis and pronounced resistance to chemotherapy and radiation therapy. Despite extensive esearch efforts, there is not any substantial progress regarding the identification of novel drugs against pancreatic cancer. Although the introduction of the chemotherapeutic agent gemcitabine improved clinical response, the prognosis of these patients remained extremely poor with a 5-year survival rate of 3-5%. Thus, the identification of the novel molecular pathways involved in pancreatic oncogenesis and the development of new and potent therapeutic options are highly desirable. Here, we describe how microRNAs control signaling pathways that are frequently deregulated during pancreatic oncogenesis. In addition, we provide evidence that microRNAs could be potentially used as novel pancreatic cancer therapeutics through reversal of chemotherapy and radiotherapy resistance or regulation of essential molecular pathways. Further studies should integrate the deregulated genes and microRNAs into molecular networks in order to identify the central regulators of pancreatic oncogenesis. Targeting these central regulators could lead to the development of novel targeted therapeutic approaches for pancreatic cancer patients.

  18. Cancer Outlier Analysis Based on Mixture Modeling of Gene Expression Data

    Directory of Open Access Journals (Sweden)

    Keita Mori

    2013-01-01

    Full Text Available Molecular heterogeneity of cancer, partially caused by various chromosomal aberrations or gene mutations, can yield substantial heterogeneity in gene expression profile in cancer samples. To detect cancer-related genes which are active only in a subset of cancer samples or cancer outliers, several methods have been proposed in the context of multiple testing. Such cancer outlier analyses will generally suffer from a serious lack of power, compared with the standard multiple testing setting where common activation of genes across all cancer samples is supposed. In this paper, we consider information sharing across genes and cancer samples, via a parametric normal mixture modeling of gene expression levels of cancer samples across genes after a standardization using the reference, normal sample data. A gene-based statistic for gene selection is developed on the basis of a posterior probability of cancer outlier for each cancer sample. Some efficiency improvement by using our method was demonstrated, even under settings with misspecified, heavy-tailed t-distributions. An application to a real dataset from hematologic malignancies is provided.

  19. Finding cancer genes in copy number data and insertional mutagenesis data

    NARCIS (Netherlands)

    Klijn, C.N.

    2011-01-01

    Cancer is a genetic disease. Step-wise alteration of genes that have a normal function in the cell can lead to the transformation of a healthy cell into a malignant cancer cell. Cancer genes provide several traits to the cell that allow it to become malignant. These traits have been researched for

  20. The Key Genes of Chronic Pancreatitis which Bridge Chronic Pancreatitis and Pancreatic Cancer Can be Therapeutic Targets.

    Science.gov (United States)

    Li, Shuang; Li, Rui; Wang, Heping; Li, Lisha; Li, Huiyu; Li, Yulin

    2018-04-01

    An important question in systems biology is what role the underlying molecular mechanisms play in disease progression. The relationship between chronic pancreatitis and pancreatic cancer needs further exploration in a system view. We constructed the disease network based on gene expression data and protein-protein interaction. We proposed an approach to discover the underlying core network and molecular factors in the progression of pancreatic diseases, which contain stages of chronic pancreatitis and pancreatic cancer. The chronic pancreatitis and pancreatic cancer core network and key factors were revealed and then verified by gene set enrichment analysis of pathways and diseases. The key factors provide the microenvironment for tumor initiation and the change of gene expression level of key factors bridge chronic pancreatitis and pancreatic cancer. Some new candidate genes need further verification by experiments. Transcriptome profiling-based network analysis reveals the importance of chronic pancreatitis genes and pathways in pancreatic cancer development on a system level by computational method and they can be therapeutic targets.

  1. Study of oral clefts: Indication of gene-environment interaction

    Energy Technology Data Exchange (ETDEWEB)

    Hwang, S.J.; Beaty, T.H.; Panny, S. [Johns Hopkins Univ., Baltimore, MD (United States)] [and others

    1994-09-01

    In this study of infants with isolated birth defects, 69 cleft palate-only (CPO) cases, 114 cleft lip with or without palate (CL/P), and 284 controls with non-cleft birth defects (all born in Maryland during 1984-1992) were examined to test for associations among genetic markers and different oral clefts. Modest associations were found between transforming growth factor {alpha} (TGF{alpha}) marker and CPO, as well as that between D17S579 (Mfd188) and CL/P in this study. The association between TGF{alpha} marker and CPO reflects a statistical interaction between mother`s smoking and child`s TGF{alpha} genotype. A significantly higher risk of CPO was found among those reporting maternal smoking during pregnancy and carrying less common TGF{alpha} TaqI allele (odds ratio=7.02 with 95% confidence interval 1.8-27.6). This gene-environment interaction was also found among those who reported no family history of any type of birth defect (odds ratio=5.60 with 95% confidence interval 1.4-22.9). Similar associations were seen for CL/P, but these were not statistically significant.

  2. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  3. Polymorphic variations in the FANCA gene in high‐risk non‐BRCA1/2 breast cancer individuals from the French Canadian population

    OpenAIRE

    Litim, Nadhir; Labrie, Yvan; Desjardins, Sylvie; Ouellette, Geneviève; Plourde, Karine; Belleau, Pascal; Durocher, Francine

    2012-01-01

    The majority of genes associated with breast cancer susceptibility, including BRCA1 and BRCA2 genes, are involved in DNA repair mechanisms. Moreover, among the genes recently associated with an increased susceptibility to breast cancer, four are Fanconi Anemia (FA) genes: FANCD1/BRCA2, FANCJ/BACH1/BRIP1, FANCN/PALB2 and FANCO/RAD51C. FANCA is implicated in DNA repair and has been shown to interact directly with BRCA1. It has been proposed that the formation of FANCA/G (dependent upon the phos...

  4. Large-scale extraction of gene interactions from full-text literature using DeepDive.

    Science.gov (United States)

    Mallory, Emily K; Zhang, Ce; Ré, Christopher; Altman, Russ B

    2016-01-01

    A complete repository of gene-gene interactions is key for understanding cellular processes, human disease and drug response. These gene-gene interactions include both protein-protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene-gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein-protein and transcription factor interactions from over 100,000 full-text PLOS articles. We built an extractor for gene-gene interactions that identified candidate gene-gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100,000 full-text articles. Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app russ.altman@stanford.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  5. The Ethics of Translational Science: Imagining Public Benefit in Gene-Environment Interaction Research

    Directory of Open Access Journals (Sweden)

    Sara L. Ackerman

    2017-06-01

    Full Text Available Biomedical research is increasingly informed by expectations of “translation,” which call for the production of scientific knowledge that can be used to create services and products that improve health outcomes. In this paper, we ask how translation, in particular the idea of social responsibility, is understood and enacted in the post-genomic life sciences. Drawing on theories examining what constitutes “good science,” and interviews with 35 investigators who study the role of gene-environment interactions in the etiology of cancer, diabetes, and cardiovascular disease, we describe the dynamic and unsettled ethics of translational science through which the expected social value of scientific knowledge about complex disease causation is negotiated. To describe how this ethics is formed, we first discuss the politics of knowledge production in interdisciplinary research collectives. Researchers described a commitment to working across disciplines to examine a wide range of possible causes of disease, but they also pointed to persistent disciplinary and ontological divisions that rest on the dominance of molecular conceptions of disease risk. The privileging of molecular-level causation shapes and constrains the kinds of knowledge that can be created about gene-environment interactions. We then turn to scientists’ ideas about how this knowledge should be used, including personalized prevention strategies, targeted therapeutics, and public policy interventions. Consensus about the relative value of these anticipated translations was elusive, and many scientists agreed that gene-environment interaction research is part of a shift in biomedical research away from considering important social, economic, political and historical causes of disease and disease disparities. We conclude by urging more explicit engagement with questions about the ethics of translational science in the post-genomic life sciences. This would include a consideration

  6. Mutational analysis of the BRCA1 gene in 30 Czech ovarian cancer ...

    Indian Academy of Sciences (India)

    Ovarian cancer is one of the most severe of oncological diseases. Inherited mutations in cancer susceptibility genes play a causal role in 5–10% of newly diagnosed tumours. BRCA1 and BRCA2 gene alterations are found in the majority of these cases. The aim of this study was to analyse the BRCA1 gene in the ovarian ...

  7. Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

    Directory of Open Access Journals (Sweden)

    J. Sunil Rao

    2007-01-01

    Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

  8. Comparative effects of DHEA and DHT on gene expression in human LNCaP prostate cancer cells.

    Science.gov (United States)

    Steele, Vernon E; Arnold, Julia T; Lei, Hanh; Izmirlian, Grant; Blackman, Marc R

    2006-01-01

    DHEA is widely used as a dietary supplement in older men. Because DHEA can be converted to androgens or estrogens, such use may promote prostate cancer. In this study, the effects of DHEA were compared with those of DHT using gene expression array profiles in human LNCaP prostate cancer cells. LNCaP cells were exposed to DHEA (300 nM), DHT (300 nM), or vehicle for 48 h, and mRNA expression was measured using Affymetrix HU-95 gene chips. Gene expression values were sorted in ascending order on the p-values corresponding to the extent of differential RNA expression between control and either hormone treatment. S100 calcium binding protein, neurotensin, 24-dehydrocholesterol reductase, and anterior-gradient 2 homologue were the four most differentially expressed genes (p-values all DHT treatment (p DHT were used for pathway analysis. DHT decreased expression of more genes involved in intercellular communication, signal transduction, nucleic acid binding and transport, and in structural components, such as myosin and golgin, than DHEA. These data revealed consistent, measurable changes in gene expression patterns following treatment of LNCaP prostate cancer cells with DHEA and DHT. Understanding the mechanisms of DHEA versus DHT actions in the prostate may help clarify the separate and interactive effects of androgenic and estrogenic actions in prostate cancer progression.

  9. Cancer-Predicting Gene Expression Changes in Colonic Mucosa of Western Diet Fed Mlh1 +/- Mice

    Science.gov (United States)

    Dermadi Bebek, Denis; Valo, Satu; Reyhani, Nima; Ollila, Saara; Päivärinta, Essi; Peltomäki, Päivi; Mutanen, Marja; Nyström, Minna

    2013-01-01

    Colorectal cancer (CRC) is the second most common cause of cancer-related deaths in the Western world and interactions between genetic and environmental factors, including diet, are suggested to play a critical role in its etiology. We conducted a long-term feeding experiment in the mouse to address gene expression and methylation changes arising in histologically normal colonic mucosa as putative cancer-predisposing events available for early detection. The expression of 94 growth-regulatory genes previously linked to human CRC was studied at two time points (5 weeks and 12 months of age) in the heterozygote Mlh1 +/- mice, an animal model for human Lynch syndrome (LS), and wild type Mlh1 +/+ littermates, fed by either Western-style (WD) or AIN-93G control diet. In mice fed with WD, proximal colon mucosa, the predominant site of cancer formation in LS, exhibited a significant expression decrease in tumor suppressor genes, Dkk1, Hoxd1, Slc5a8, and Socs1, the latter two only in the Mlh1 +/- mice. Reduced mRNA expression was accompanied by increased promoter methylation of the respective genes. The strongest expression decrease (7.3 fold) together with a significant increase in its promoter methylation was seen in Dkk1, an antagonist of the canonical Wnt signaling pathway. Furthermore, the inactivation of Dkk1 seems to predispose to neoplasias in the proximal colon. This and the fact that Mlh1 which showed only modest methylation was still expressed in both Mlh1 +/- and Mlh1 +/+ mice indicate that the expression decreases and the inactivation of Dkk1 in particular is a prominent early marker for colon oncogenesis. PMID:24204690

  10. Cancer-predicting gene expression changes in colonic mucosa of Western diet fed Mlh1+/- mice.

    Directory of Open Access Journals (Sweden)

    Marjaana Pussila

    Full Text Available Colorectal cancer (CRC is the second most common cause of cancer-related deaths in the Western world and interactions between genetic and environmental factors, including diet, are suggested to play a critical role in its etiology. We conducted a long-term feeding experiment in the mouse to address gene expression and methylation changes arising in histologically normal colonic mucosa as putative cancer-predisposing events available for early detection. The expression of 94 growth-regulatory genes previously linked to human CRC was studied at two time points (5 weeks and 12 months of age in the heterozygote Mlh1(+/- mice, an animal model for human Lynch syndrome (LS, and wild type Mlh1(+/+ littermates, fed by either Western-style (WD or AIN-93G control diet. In mice fed with WD, proximal colon mucosa, the predominant site of cancer formation in LS, exhibited a significant expression decrease in tumor suppressor genes, Dkk1, Hoxd1, Slc5a8, and Socs1, the latter two only in the Mlh1(+/- mice. Reduced mRNA expression was accompanied by increased promoter methylation of the respective genes. The strongest expression decrease (7.3 fold together with a significant increase in its promoter methylation was seen in Dkk1, an antagonist of the canonical Wnt signaling pathway. Furthermore, the inactivation of Dkk1 seems to predispose to neoplasias in the proximal colon. This and the fact that Mlh1 which showed only modest methylation was still expressed in both Mlh1(+/- and Mlh1(+/+ mice indicate that the expression decreases and the inactivation of Dkk1 in particular is a prominent early marker for colon oncogenesis.

  11. Gene-based testing of interactions in association studies of quantitative traits.

    Directory of Open Access Journals (Sweden)

    Li Ma

    Full Text Available Various methods have been developed for identifying gene-gene interactions in genome-wide association studies (GWAS. However, most methods focus on individual markers as the testing unit, and the large number of such tests drastically erodes statistical power. In this study, we propose novel interaction tests of quantitative traits that are gene-based and that confer advantage in both statistical power and biological interpretation. The framework of gene-based gene-gene interaction (GGG tests combine marker-based interaction tests between all pairs of markers in two genes to produce a gene-level test for interaction between the two. The tests are based on an analytical formula we derive for the correlation between marker-based interaction tests due to linkage disequilibrium. We propose four GGG tests that extend the following P value combining methods: minimum P value, extended Simes procedure, truncated tail strength, and truncated P value product. Extensive simulations point to correct type I error rates of all tests and show that the two truncated tests are more powerful than the other tests in cases of markers involved in the underlying interaction not being directly genotyped and in cases of multiple underlying interactions. We applied our tests to pairs of genes that exhibit a protein-protein interaction to test for gene-level interactions underlying lipid levels using genotype data from the Atherosclerosis Risk in Communities study. We identified five novel interactions that are not evident from marker-based interaction testing and successfully replicated one of these interactions, between SMAD3 and NEDD9, in an independent sample from the Multi-Ethnic Study of Atherosclerosis. We conclude that our GGG tests show improved power to identify gene-level interactions in existing, as well as emerging, association studies.

  12. ADAMTS14 Gene Polymorphism and Environmental Risk in the Development of Oral Cancer.

    Directory of Open Access Journals (Sweden)

    Shih-Chi Su

    Full Text Available Oral cancer is a common malignancy that is shown to be causally associated with hereditary and acquired factors. ADAMTS14 is a member of the ADAMTS (a disintegrin-like and metalloproteinase domain with thrombospondin motifs metalloproteinase family that plays an important role in extracellular matrix (ECM assembly and degradation. Elevation or deficiency of certain ADAMTS proteinases has been known to be implicated in a wide range of pathological processes including atherosclerosis, arthritis, and cancer. The present study aimed to explore the impact of ADAMTS14 gene polymorphisms, combined with environmental risks on the susceptibility to oral tumorigenesis.Four single-nucleotide polymorphisms (SNPs of the ADAMTS14 gene, including rs10823607, rs12774070, rs4747096, and rs61573157 were evaluated from 1200 normal controls and 850 patients with oral cancer. We failed to detect a significant association of four individual SNPs with oral cancer between case and control group. However, while considering behavioral exposure of environmental carcinogens, the presence of four ADAMTS14 SNPs, combined with betel nut chewing and/or smoking, profoundly leveraged the risk of oral cancer. Moreover, we observed a significant association of rs12774070, which is predicted to alter the expression and function of ADAMTS14 by in silico and bioinformatics analyses, with poor tumor cell differentiation (AOR: 0.59; 95% CI: 0.38-0.92; p = 0.02 in patients who chewed betel nuts.These results implicate the interaction between ADAMTS14 gene polymorphisms and environmental mutagens as a risk factor of oral tumorigenesis and suggest a correlation of rs12774070 with the degree of oral tumor cell differentiation.

  13. Protein-protein interactions and cancer: targeting the central dogma.

    Science.gov (United States)

    Garner, Amanda L; Janda, Kim D

    2011-01-01

    Between 40,000 and 200,000 protein-protein interactions have been predicted to exist within the human interactome. As these interactions are of a critical nature in many important cellular functions and their dysregulation is causal of disease, the modulation of these binding events has emerged as a leading, yet difficult therapeutic arena. In particular, the targeting of protein-protein interactions relevant to cancer is of fundamental importance as the tumor-promoting function of several aberrantly expressed proteins in the cancerous state is directly resultant of its ability to interact with a protein-binding partner. Of significance, these protein complexes play a crucial role in each of the steps of the central dogma of molecular biology, the fundamental processes of genetic transmission. With the many important discoveries being made regarding the mechanisms of these genetic process, the identification of new chemical probes are needed to better understand and validate the druggability of protein-protein interactions related to the central dogma. In this review, we provide an overview of current small molecule-based protein-protein interaction inhibitors for each stage of the central dogma: transcription, mRNA splicing and translation. Importantly, through our analysis we have uncovered a lack of necessary probes targeting mRNA splicing and translation, thus, opening up the possibility for expansion of these fields.

  14. Multi drug resistance to cancer chemotherapy: Genes involved and blockers

    International Nuclear Information System (INIS)

    Sayed-Ahmed, Mohamed M.

    2007-01-01

    During the last three decades, important and considerable research efforts had been performed to investigate the mechanism through which cancer cells overcome the cytotoxic effects of a variety of chemotherapeutic drugs. Most of the previously published work has been focused on the resistance of tumor cells to those anticancer drugs of natural source. Multidrug resistance (MDR) is a cellular cross-resistance to a broad spectrum of natural products used in cancer chemotherapy and is believed to be the major cause of the therapeutic failures of the drugs belonging to different naturally obtained or semisynthetic groups including vinca alkaloids, taxans, epipodophyllotoxins and certain antibiotics. This phenomenon results from overexpression of four MDR genes and their corresponding proteins that act as membrane-bound ATP consuming pumps. These proteins mediate the efflux of many structurally and functionally unrelated anticancer drugs of natural source. MDR may be intrinsic or acquired following exposure to chemotherapy. The existence of intrinsically resistant tumor cell clone before and following chemotherapeutic treatment has been associated with a worse final outcome because of increased incidence of distant metasis. In view of irreplaceability of natural product anticancer drugs as effective chemotherapeutic agents, and in view of MDR as a major obstacle to successful chemotherapy, this review is aimed to highlight the genes involved in MDR, classical MDR blockers and gene therapy approaches to overcome MDR. (author)

  15. Preliminary screening of the radiosensitivity-associated genes on colorectal cancer

    International Nuclear Information System (INIS)

    Xing Chungen; Yang Xiaodong; Zhou Liying; Wu Yongyou; Jiang Yinfen; Dai Hong; Lv Xiaodong; Gong Wei

    2007-01-01

    The screening of radiosensitive genes of human colorectal cancer was made by gene chip. Two human colorectal cancer cell lines LOVO and SW480 were cultivated and the total RNA was extracted from at least lxl0 7 cells. Then the gene expression profiling was performed by HG-U133 Plus 2.0 Array and the difference of gene expression has been analyzed. The results shows that there are 16882 genes expressed in LOVO cell and 17114 genes expressed in SW480 cell through gene expression profiling. It has been found that the genes with 2-fold expressed differentially include 908 genes up-regulated and 1312 genes down-regulated. The same genes, such as Fas and NFkB which is up-regulated, Caspas6, and RAD21 which is down-regulated, have been proved to be related to radiosensitivity. The genes with high expression level including CEACAM5, THBS1, SERPINE2, ARL7, HPGD in LOVO cell may also be related to the radiosensitivity. And the genes with high expression level including SCD, NQ01, LYZ, KRT20, ATP1B1 in SW480 cell may be related to the radioresistance of human colorectal cancer. It could be concluded that the radiosensitivity of colorectal cancer can be reflected from gene and protein expression level. And gene expression profiling is a fast and sensitive tool to predict the radiosensitivity and screen radiosensitive genes of colorectal cancer. (authors)

  16. Artificial neural network inference (ANNI: a study on gene-gene interaction for biomarkers in childhood sarcomas.

    Directory of Open Access Journals (Sweden)

    Dong Ling Tong

    Full Text Available OBJECTIVE: To model the potential interaction between previously identified biomarkers in children sarcomas using artificial neural network inference (ANNI. METHOD: To concisely demonstrate the biological interactions between correlated genes in an interaction network map, only 2 types of sarcomas in the children small round blue cell tumors (SRBCTs dataset are discussed in this paper. A backpropagation neural network was used to model the potential interaction between genes. The prediction weights and signal directions were used to model the strengths of the interaction signals and the direction of the interaction link between genes. The ANN model was validated using Monte Carlo cross-validation to minimize the risk of over-fitting and to optimize generalization ability of the model. RESULTS: Strong connection links on certain genes (TNNT1 and FNDC5 in rhabdomyosarcoma (RMS; FCGRT and OLFM1 in Ewing's sarcoma (EWS suggested their potency as central hubs in the interconnection of genes with different functionalities. The results showed that the RMS patients in this dataset are likely to be congenital and at low risk of cardiomyopathy development. The EWS patients are likely to be complicated by EWS-FLI fusion and deficiency in various signaling pathways, including Wnt, Fas/Rho and intracellular oxygen. CONCLUSIONS: The ANN network inference approach and the examination of identified genes in the published literature within the context of the disease highlights the substantial influence of certain genes in sarcomas.

  17. ANLN functions as a key candidate gene in cervical cancer as determined by integrated bioinformatic analysis

    Directory of Open Access Journals (Sweden)

    Xia L

    2018-04-01

    Full Text Available Leilei Xia,1,* Xiaoling Su,1,2,* Jizi Shen,1,* Qi Meng,1 Jiuqiong Yan,1 Caihong Zhang,1 Yu Chen,1 Han Wang,3 Mingjuan Xu,1 1Department of Obstetrics and Gynecology, Changhai Hospital, Second Military Medical University, Shanghai, People’s Republic of China; 2Department of Obstetrics and Gynecology, No. 455 Hospital, Shanghai, People’s Republic of China; 3Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, People’s Republic of China *These authors contributed equally to this work Background: Cervical cancer, one of the leading causes of female deaths, remains a top cause of mortality in gynecologic oncology and tends to affect younger individuals. However, the pathogenesis of cervical cancer is still far from clear. Given the high incidence and mortality of cervical cancer, uncovering the causes and pathogenesis as well as identifying novel biomarkers are of great significance and are desperately needed.Materials and methods: First, raw data were downloaded from the Gene Expression Omnibus database. The Robuse Multi-Array Average algorithm and combat function of the sva package were subsequently applied to preprocess and remove batch effects. Differentially expressed genes (DEGs analyzed with the limma package were followed by gene ontology and pathway analysis, and a protein–protein interaction (PPI network based on the STRING website and the Cytoscape software was constructed. Weighted Correlation Network Analysis (WGCNA was utilized to build the coexpression network. Subsequently, UALCAN websites were employed to conduct survival analysis. Finally, the oncomine database was used to validate the expression of ANLN in other datasets.Results: GSE29570 and GSE89657, including 49 cervical cancer tissues and 20 normal cervical tissues, were screened as the datasets. Three-hundred-twenty-four DEGs were identified and, among them, 123 were upregulated, while 201 were downregulated. The

  18. Methylation of cancer-stem-cell-associated Wnt target genes predicts poor prognosis in colorectal cancer patients

    NARCIS (Netherlands)

    de Sousa E Melo, Felipe; Colak, Selcuk; Buikhuisen, Joyce; Koster, Jan; Cameron, Kate; de Jong, Joan H.; Tuynman, Jurriaan B.; Prasetyanti, Pramudita R.; Fessler, Evelyn; van den Bergh, Saskia P.; Rodermond, Hans; Dekker, Evelien; van der Loos, Chris M.; Pals, Steven T.; van de Vijver, Marc J.; Versteeg, Rogier; Richel, Dick J.; Vermeulen, Louis; Medema, Jan Paul

    2011-01-01

    Gene signatures derived from cancer stem cells (CSCs) predict tumor recurrence for many forms of cancer. Here, we derived a gene signature for colorectal CSCs defined by high Wnt signaling activity, which in agreement with previous observations predicts poor prognosis. Surprisingly, however, we

  19. Derivation of a triple mosaic adenovirus for cancer gene therapy.

    Directory of Open Access Journals (Sweden)

    Yizhe Tang

    2009-12-01

    Full Text Available A safe and efficacious cancer medicine is necessary due to the increasing population of cancer patients whose particular diseases cannot be cured by the currently available treatment. Adenoviral (Ad vectors represent a promising therapeutic medicine for human cancer therapy. However, several improvements are needed in order for Ad vectors to be effective cancer therapeutics, which include, but are not limited to, improvement of cellular uptake, enhanced cancer cell killing activity, and the capability of vector visualization and tracking once injected into the patients. To this end, we attempted to develop an Ad as a multifunctional platform incorporating targeting, imaging, and therapeutic motifs. In this study, we explored the utility of this proposed platform by generating an Ad vector containing the poly-lysine (pK, the herpes simplex virus type 1 (HSV-1 thymidine kinase (TK, and the monomeric red fluorescent protein (mRFP1 as targeting, tumor cell killing, and imaging motifs, respectively. Our study herein demonstrates the generation of the triple mosaic Ad vector with pK, HSV-1 TK, and mRFP1 at the carboxyl termini of Ad minor capsid protein IX (pIX. In addition, the functionalities of pK, HSV-1 TK, and mRFP1 proteins on the Ad vector were retained as confirmed by corresponding functional assays, indicating the potential multifunctional application of this new Ad vector for cancer gene therapy. The validation of the triple mosaic Ad vectors also argues for the ability of pIX modification as a base for the development of multifunctional Ad vectors.

  20. Identification of differentially expressed genes and biological pathways in bladder cancer

    Science.gov (United States)

    Tang, Fucai; He, Zhaohui; Lei, Hanqi; Chen, Yuehan; Lu, Zechao; Zeng, Guohua; Wang, Hangtao

    2018-01-01

    The purpose of the present study was to identify key genes and investigate the related molecular mechanisms of bladder cancer (BC) progression. From the Gene Expression Omnibus database, the gene expression dataset GSE7476 was downloaded, which contained 43 BC samples and 12 normal bladder tissues. GSE7476 was analyzed to screen the differentially expressed genes (DEGs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for the DEGs using the DAVID database, and a protein-protein interaction (PPI) network was then constructed using Cytoscape software. The results of the GO analysis showed that the upregulated DEGs were significantly enriched in cell division, nucleoplasm and protein binding, while the downregulated DEGs were significantly enriched in ‘extracellular matrix organization’, ‘proteinaceous extracellular matrix’ and ‘heparin binding’. The results of the KEGG pathway analysis showed that the upregulated DEGs were significantly enriched in the ‘cell cycle’, whereas the downregulated DEGs were significantly enriched in ‘complement and coagulation cascades’. JUN, cyclin-dependent kinase 1, FOS, PCNA, TOP2A, CCND1 and CDH1 were found to be hub genes in the PPI network. Sub-networks revealed that these gene were enriched in significant pathways, including the ‘cell cycle’ signaling pathway and ‘PI3K-Akt signaling pathway’. In summary, the present study identified DEGs and key target genes in the progression of BC, providing potential molecular targets and diagnostic biomarkers for the treatment of BC. PMID:29532898

  1. Multiple loci with different cancer specificities within the 8q24 gene desert

    DEFF Research Database (Denmark)

    Ghoussaini, M.; Song, H.; Koessler, T.

    2008-01-01

    this gene desert were specifically associated with risks of different cancers. One block was solely associated with risk of breast cancer, three others were associated solely with the risk of prostate cancer, and a fifth was associated with the risk of prostate, colorectal, and ovarian cancer...

  2. Direct observation of nanoparticle-cancer cell nucleus interactions.

    Science.gov (United States)

    Dam, Duncan Hieu M; Lee, Jung Heon; Sisco, Patrick N; Co, Dick T; Zhang, Ming; Wasielewski, Michael R; Odom, Teri W

    2012-04-24

    We report the direct visualization of interactions between drug-loaded nanoparticles and the cancer cell nucleus. Nanoconstructs composed of nucleolin-specific aptamers and gold nanostars were actively transported to the nucleus and induced major changes to the nuclear phenotype via nuclear envelope invaginations near the site of the construct. The number of local deformations could be increased by ultrafast, light-triggered release of the aptamers from the surface of the gold nanostars. Cancer cells with more nuclear envelope folding showed increased caspase 3 and 7 activity (apoptosis) as well as decreased cell viability. This newly revealed correlation between drug-induced changes in nuclear phenotype and increased therapeutic efficacy could provide new insight for nuclear-targeted cancer therapy.

  3. Functional screen for genes responsible for tamoxifen resistance in human breast cancer cells

    NARCIS (Netherlands)

    Meijer, Danielle; van Agthoven, Ton; Bosma, Peter T.; Nooter, Kees; Dorssers, Lambert C. J.

    2006-01-01

    Antiestrogens, such as tamoxifen, are widely used for endocrine treatment of estrogen receptor-positive breast cancer. However, as breast cancer progresses, development of tamoxifen resistance is inevitable. The mechanisms underlying this resistance are not well understood. To identify genes

  4. Cyclophilin B as a co-regulator of prolactin-induced gene expression and function in breast cancer cells.

    Science.gov (United States)

    Fang, Feng; Zheng, Jiamao; Galbaugh, Traci L; Fiorillo, Alyson A; Hjort, Elizabeth E; Zeng, Xianke; Clevenger, Charles V

    2010-06-01

    The effects of prolactin (PRL) during the pathogenesis of breast cancer are mediated in part though Stat5 activity enhanced by its interaction with its transcriptional inducer, the prolyl isomerase cyclophilin B (CypB). We have demonstrated that knockdown of CypB decreases cell growth, proliferation, and migration, and CypB expression is associated with malignant progression of breast cancer. In this study, we examined the effect of CypB knockdown on PRL signaling in breast cancer cells. CypB knockdown with two independent siRNAs was shown to impair PRL-induced reporter expression in breast cancer cell line. cDNA microarray analysis was performed on these cells to assess the effect of CypB reduction, and revealed a significant decrease in PRL-induced endogenous gene expression in two breast cancer cell lines. Parallel functional assays revealed corresponding alterations of both anchorage-independent cell growth and cell motility of breast cancer cells. Our results demonstrate that CypB expression levels significantly modulate PRL-induced function in breast cancer cells ultimately resulting in enhanced levels of PRL-responsive gene expression, cell growth, and migration. Given the increasingly appreciated role of PRL in the pathogenesis of breast cancer, the actions of CypB detailed here are of biological significance.

  5. Long and noncoding RNAs (lnc-RNAs determine androgen receptor dependent gene expression in prostate cancer growth in vivo

    Directory of Open Access Journals (Sweden)

    Richard G Pestell

    2014-04-01

    Full Text Available Hyperactive androgen receptor (AR activity remains a key determinant of the onset and progression of prostate cancer and resistance to current therapies. The mechanisms governing castrate resistant prostate cancer are poorly understood, but defining these molecular events is essential in order to impact deaths from prostate cancer. Yang et al. demonstrate that two lnc-RNAs known to be overexpressed in therapy resistant prostate cancer, PRNCR1 (also known as PCAT8 and PCGEM1, bound to the AR to enhance ligand-dependent and ligand-independent AR gene expression and proliferation of prostate cancer cells.1 The sequence of these interactions involved the binding of PRNCR1 to the acetylated AR and a subsequent association of DOT1L, which was required for the sequential recruitment of the lncRNA PCGEM1 to the AR amino terminus, which in turn was methylated by DOT1L.

  6. Trends in gastrectomy and ADH1B and ALDH2 genotypes in Japanese alcoholic men and their gene-gastrectomy, gene-gene and gene-age interactions for risk of alcoholism.

    Science.gov (United States)

    Yokoyama, Akira; Yokoyama, Tetsuji; Matsui, Toshifumi; Mizukami, Takeshi; Kimura, Mitsuru; Matsushita, Sachio; Higuchi, Susumu; Maruyama, Katsuya

    2013-01-01

    The life-time drinking profiles of Japanese alcoholics have shown that gastrectomy increases susceptibility to alcoholism. We investigated the trends in gastrectomy and alcohol dehydrogenase-1B (ADH1B) and aldehyde dehydrogenase-2 (ALDH2) genotypes and their interactions in alcoholics. This survey was conducted on 4879 Japanese alcoholic men 40 years of age or older who underwent routine gastrointestinal endoscopic screening during the period 1996-2010. ADH1B/ALDH2 genotyping was performed in 3702 patients. A history of gastrectomy was found in 508 (10.4%) patients. The reason for the gastrectomy was peptic ulcer in 317 patients and gastric cancer in 187 patients. The frequency of gastrectomy had gradually decreased from 13.3% in 1996-2000 to 10.5% in 2001-2005 and to 7.8% in 2006-2010 (P alcoholism-susceptibility genotypes, ADH1B*1/*1 and ALDH2*1/*1, modestly but significantly tended not to occur in the same individual (P = 0.026). The frequency of ADH1B*1/*1 decreased with ascending age groups. The high frequency of history of gastrectomy suggested that gastrectomy is still a risk factor for alcoholism, although the percentage decreased during the period. The alcoholism-susceptibility genotype ADH1B*1/*1 was less frequent in the gastrectomy group, suggesting a competitive gene-gastrectomy interaction for alcoholism. A gene-gene interaction and gene-age interactions regarding the ADH1B genotype were observed.

  7. The ordering of expression among a few genes can provide simple cancer biomarkers and signal BRCA1 mutations

    Directory of Open Access Journals (Sweden)

    Parmigiani Giovanni

    2009-08-01

    Full Text Available Abstract Background A major challenge in computational biology is to extract knowledge about the genetic nature of disease from high-throughput data. However, an important obstacle to both biological understanding and clinical applications is the "black box" nature of the decision rules provided by most machine learning approaches, which usually involve many genes combined in a highly complex fashion. Achieving biologically relevant results argues for a different strategy. A promising alternative is to base prediction entirely upon the relative expression ordering of a small number of genes. Results We present a three-gene version of "relative expression analysis" (RXA, a rigorous and systematic comparison with earlier approaches in a variety of cancer studies, a clinically relevant application to predicting germline BRCA1 mutations in breast cancer and a cross-study validation for predicting ER status. In the BRCA1 study, RXA yields high accuracy with a simple decision rule: in tumors carrying mutations, the expression of a "reference gene" falls between the expression of two differentially expressed genes, PPP1CB and RNF14. An analysis of the protein-protein interactions among the triplet of genes and BRCA1 suggests that the classifier has a biological foundation. Conclusion RXA has the potential to identify genomic "marker interactions" with plausible biological interpretation and direct clinical applicability. It provides a general framework for understanding the roles of the genes involved in decision rules, as illustrated for the difficult and clinically relevant problem of identifying BRCA1 mutation carriers.

  8. HFE gene C282Y variant is associated with colorectal cancer in Caucasians: a meta-analysis.

    Science.gov (United States)

    Chen, Weidong; Zhao, Hua; Li, Tiegang; Yao, Hongliang

    2013-08-01

    The HFE gene has been suggested to play an important role in the pathogenesis of colorectal cancer. However, the results have been conflicting. In this study, we performed a meta-analysis to clarify the association of HFE gene C282Y variant with colorectal cancer. PubMed and Embase were retrieved to identify the potential literature. Pooled odds ratio (OR) with 95 % confidence interval (CI) was calculated using fixed- or random-effects model. A total of eight papers including nine studies (7,588 colorectal cancer cases and 81,571 controls) for HFE gene C282Y variant were included in the meta-analysis. The result indicated that HFE gene C282Y variant was significantly associated with colorectal cancer under recessive model (OR = 2.00, 95 % CI = 1.32-3.04), with no evidence of between-study heterogeneity (I (2) = 0.2 %, p = 0.432). Further subgroup analysis by number of cases suggested the effect was significant in studies with more than 500 cases (OR = 2.51, 95 % CI = 1.58-3.98, I (2) = 0.0 %, p = 0.921), but not in studies with less than 500 cases (OR = 0.75, 95 % CI = 0.28-1.97, I (2) = 0.0 %, p = 0.622). The current meta-analysis supported the positive association of HFE gene C282Y variant with colorectal cancer. Further large-scale studies with the consideration for gene-gene/gene-environment interactions should be conducted to investigate the association.

  9. A Catalog of Genes Homozygously Deleted in Human Lung Cancer and the Candidacy of PTPRD as a Tumor Suppressor Gene

    Science.gov (United States)

    Kohno, Takashi; Otsuka, Ayaka; Girard, Luc; Sato, Masanori; Iwakawa, Reika; Ogiwara, Hideaki; Sanchez-Cespedes, Montse; Minna, John D.; Yokota, Jun

    2010-01-01

    A total of 176 genes homozygously deleted in human lung cancer were identified by DNA array-based whole genome scanning of 52 lung cancer cell lines and subsequent genomic PCR in 74 cell lines, including the 52 cell lines scanned. One or more exons of these genes were homozygously deleted in one (1%) to 20 (27%) cell lines. These genes included known tumor suppressor genes, e.g., CDKN2A/p16, RB1, and SMAD4, and candidate tumor suppressor genes whose hemizygous or homozygous deletions were reported in several types of human cancers, such as FHIT, KEAP1, and LRP1B/LRP-DIP. CDKN2A/p16 and p14ARF located in 9p21 were most frequently deleted (20/74, 27%). The PTPRD gene was most frequently deleted (8/74, 11%) among genes mapping to regions other than 9p21. Somatic mutations, including a nonsense mutation, of the PTPRD gene were detected in 8/74 (11%) of cell lines and 4/95 (4%) of surgical specimens of lung cancer. Reduced PTPRD expression was observed in the majority (>80%) of cell lines and surgical specimens of lung cancer. Therefore, PTPRD is a candidate tumor suppressor gene in lung cancer. Microarray-based expression profiling of 19 lung cancer cell lines also indicated that some of the 176 genes, such as KANK and ADAMTS1, are preferentially inactivated by epigenetic alterations. Genetic/epigenetic as well as functional studies of these 176 genes will increase our understanding of molecular mechanisms behind lung carcinogenesis. PMID:20073072

  10. The potential for tumor suppressor gene therapy in head and neck cancer.

    Science.gov (United States)

    Birkeland, Andrew C; Ludwig, Megan L; Spector, Matthew E; Brenner, J Chad

    2016-01-01

    Head and neck squamous cell carcinoma remains a highly morbid and fatal disease. Importantly, genomic sequencing of head and neck cancers has identified frequent mutations in tumor suppressor genes. While targeted therapeutics increasingly are being investigated in head and neck cancer, the majority of these agents are against overactive/overexpressed oncogenes. Therapy to restore lost tumor suppressor gene function remains a key and under-addressed niche in trials for head and neck cancer. Recent advances in gene editing have captured the interest of both the scientific community and the public. As our technology for gene editing and gene expression modulation improves, addressing lost tumor suppressor gene function in head and neck cancers is becoming a reality. This review will summarize new techniques, challenges to implementation, future directions, and ethical ramifications of gene therapy in head and neck cancer.

  11. Prostate cancer metastasis-driving genes: hurdles and potential approaches in their identification

    Directory of Open Access Journals (Sweden)

    Yan Ting Chiang

    2014-08-01

    Full Text Available Metastatic prostate cancer is currently incurable. Metastasis is thought to result from changes in the expression of specific metastasis-driving genes in nonmetastatic prostate cancer tissue, leading to a cascade of activated downstream genes that set the metastatic process in motion. Such genes could potentially serve as effective therapeutic targets for improved management of the disease. They could be identified by comparative analysis of gene expression profiles of patient-derived metastatic and nonmetastatic prostate cancer tissues to pinpoint genes showing altered expression, followed by determining whether silencing of such genes can lead to inhibition of metastatic properties. Various hurdles encountered in this approach are discussed, including (i the need for clinically relevant, nonmetastatic and metastatic prostate cancer tissues such as xenografts of patients' prostate cancers developed via subrenal capsule grafting technology and (ii limitations in the currently available methodology for identification of master regulatory genes.

  12. Germline mutations in 40 cancer susceptibility genes among Chinese patients with high hereditary risk breast cancer.

    Science.gov (United States)

    Li, Junyan; Jing, Ruilin; Wei, Hongyi; Wang, Minghao; Qi, Xiaowei; Liu, Haoxi; Liu, Jian; Ou, Jianghua; Jiang, Weihua; Tian, Fuguo; Sheng, Yuan; Li, Hengyu; Xu, Hong; Zhang, Ruishan; Guan, Aihua; Liu, Ke; Jiang, Hongchuan; Ren, Yu; He, Jianjun; Huang, Weiwei; Liao, Ning; Cai, Xiangjun; Ming, Jia; Ling, Rui; Xu, Yan; Hu, Chunyan; Zhang, Jianguo; Guo, Baoliang; Ouyang, Lizhi; Shuai, Ping; Liu, Zhenzhen; Zhong, Ling; Zeng, Zhen; Zhang, Ting; Xuan, Zhaoling; Tan, Xuanni; Liang, Junbin; Pan, Qinwen; Chen, Li; Zhang, Fan; Fan, Linjun; Zhang, Yi; Yang, Xinhua; Li, Jingbo; Chen, Chongjian; Jiang, Jun

    2018-05-12

    Multigene panel testing of breast cancer predisposition genes have been extensively conducted in Europe and America, which is relatively rare in Asia however. In this study, we assessed the frequency of germline mutations in 40 cancer predisposition genes, including BRCA1 and BRCA2, among a large cohort of Chinese patients with high hereditary risk of BC. From 2015 to 2016, consecutive BC patients from 26 centers of China with high hereditary risk were recruited (n=937). Clinical information was collected and next-generation sequencing (NGS) was performed using blood samples of participants to identify germline mutations. In total, we acquired 223 patients with putative germline mutations, including 159 in BRCA1/2, 61 in 15 other BC susceptibility genes and 3 in both BRCA1/2 and non-BRCA1/2 gene. Major mutant non-BRCA1/2 genes were TP53 (n=18), PALB2 (n=11), CHEK2 (n=6), ATM (n=6), and BARD1 (n=5). No factors predicted pathologic mutations in non-BRCA1/2 genes when treated as a whole. TP53 mutations were associated with HER-2 positive BC and younger age at diagnosis; and CHEK2 and PALB2 mutations were enriched in patients with luminal BC. Among high hereditary risk Chinese BC patients, 23.8% contained germline mutations, including 6.8% in non-BRCA1/2 genes. TP53 and PALB2 had a relatively high mutation rates (1.9% and 1.2%). Although no factors predicted for detrimental mutations in non-BRCA1/2 genes, some clinical features were associated with mutations of several particular genes. This article is protected by copyright. All rights reserved. © 2018 UICC.

  13. Insertional mutagenesis in mice deficient for p15Ink4b, p16Ink4a, p21Cip1, and p27Kip1 reveals cancer gene interactions and correlations with tumor phenotypes

    DEFF Research Database (Denmark)

    Kool, Jaap; Uren, Anthony G; Martins, Carla P

    2010-01-01

    -throughput murine leukemia virus insertional mutagenesis screens in mice that are deficient for one or two CDK inhibitors. We retrieved 9,117 retroviral insertions from 476 lymphomas to define hundreds of loci that are mutated more frequently than expected by chance. Many of these loci are skewed toward a specific...... revealed a significant overlap between the datasets. Together, our findings highlight the importance of genetic context within large-scale mutation detection studies, and they show a novel use for insertional mutagenesis data in prioritizing disease-associated genes that emerge from genome-wide association...

  14. Prediction of novel target genes and pathways involved in irinotecan-resistant colorectal cancer.

    Directory of Open Access Journals (Sweden)

    Precious Takondwa Makondi

    Full Text Available Acquired drug resistance to the chemotherapeutic drug irinotecan (the active metabolite of which is SN-38 is one of the significant obstacles in the treatment of advanced colorectal cancer (CRC. The molecular mechanism or targets mediating irinotecan resistance are still unclear. It is urgent to find the irinotecan response biomarkers to improve CRC patients' therapy.Genetic Omnibus Database GSE42387 which contained the gene expression profiles of parental and irinotecan-resistant HCT-116 cell lines was used. Differentially expressed genes (DEGs between parental and irinotecan-resistant cells, protein-protein interactions (PPIs, gene ontologies (GOs and pathway analysis were performed to identify the overall biological changes. The most common DEGs in the PPIs, GOs and pathways were identified and were validated clinically by their ability to predict overall survival and disease free survival. The gene-gene expression correlation and gene-resistance correlation was also evaluated in CRC patients using The Cancer Genomic Atlas data (TCGA.The 135 DEGs were identified of which 36 were upregulated and 99 were down regulated. After mapping the PPI networks, the GOs and the pathways, nine genes (GNAS, PRKACB, MECOM, PLA2G4C, BMP6, BDNF, DLG4, FGF2 and FGF9 were found to be commonly enriched. Signal transduction was the most significant GO and MAPK pathway was the most significant pathway. The five genes (FGF2, FGF9, PRKACB, MECOM and PLA2G4C in the MAPK pathway were all contained in the signal transduction and the levels of those genes were upregulated. The FGF2, FGF9 and MECOM expression were highly associated with CRC patients' survival rate but not PRKACB and PLA2G4C. In addition, FGF9 was also associated with irinotecan resistance and poor disease free survival. FGF2, FGF9 and PRKACB were positively correlated with each other while MECOM correlated positively with FGF9 and PLA2G4C, and correlated negatively with FGF2 and PRKACB after doing gene-gene

  15. Gene expression analysis in human breast cancer associated blood vessels.

    Directory of Open Access Journals (Sweden)

    Dylan T Jones

    Full Text Available Angiogenesis is essential for solid tumour growth, whilst the molecular profiles of tumour blood vessels have been reported to be different between cancer types. Although presently available anti-angiogenic strategies are providing some promise for the treatment of some cancers it is perhaps not surprisingly that, none of the anti-angiogenic agents available work on all tumours. Thus, the discovery of novel anti-angiogenic targets, relevant to individual cancer types, is required. Using Affymetrix microarray analysis of laser-captured, CD31-positive blood vessels we have identified 63 genes that are upregulated significantly (5-72 fold in angiogenic blood vessels associated with human invasive ductal carcinoma (IDC of the breast as compared with blood vessels in normal human breast. We tested the angiogenic capacity of a subset of these genes. Genes were selected based on either their known cellular functions, their enriched expression in endothelial cells and/or their sensitivity to anti-VEGF treatment; all features implicating their involvement in angiogenesis. For example, RRM2, a ribonucleotide reductase involved in DNA synthesis, was upregulated 32-fold in IDC-associated blood vessels; ATF1, a nuclear activating transcription factor involved in cellular growth and survival was upregulated 23-fold in IDC-associated blood vessels and HEX-B, a hexosaminidase involved in the breakdown of GM2 gangliosides, was upregulated 8-fold in IDC-associated blood vessels. Furthermore, in silico analysis confirmed that AFT1 and HEX-B also were enriched in endothelial cells when compared with non-endothelial cells. None of these genes have been reported previously to be involved in neovascularisation. However, our data establish that siRNA depletion of Rrm2, Atf1 or Hex-B had significant anti-angiogenic effects in VEGF-stimulated ex vivo mouse aortic ring assays. Overall, our results provide proof-of-principle that our approach can identify a cohort of

  16. Spatial evolutionary games of interaction among generic cancer cells

    DEFF Research Database (Denmark)

    Bach, L.A.; Sumpter, D.J.T.; Alsner, J.

    2003-01-01

    Evolutionary game models of cellular interactions have shown that heterogeneity in the cellular genotypic composition is maintained through evolution to stable coexistence of growth-promoting and non-promoting cell types. We generalise these mean-field models and relax the assumption of perfect m...... at a cellular level. This study thus points a new direction towards more plausible spatial tumour modelling and the understanding of cancerous growth....

  17. Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

    NARCIS (Netherlands)

    Chiu, Hua Sheng; Somvanshi, Sonal; Patel, Ektaben; Chen, Ting Wen; Singh, Vivek P.; Zorman, Barry; Patil, Sagar L.; Pan, Yinghong; Chatterjee, Sujash S.; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. 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Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Pinero, Edna M.Mora; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz; Sood, Anil K.; Gunaratne, Preethi H.; Sumazin, Pavel

    2018-01-01

    Long noncoding RNAs (lncRNAs) are commonly dysregulated in tumors, but only a handful are known to play pathophysiological roles in cancer. We inferred lncRNAs that dysregulate cancer pathways, oncogenes, and tumor suppressors (cancer genes) by modeling their effects on the activity of transcription

  18. Music training and speech perception: a gene-environment interaction.

    Science.gov (United States)

    Schellenberg, E Glenn

    2015-03-01

    Claims of beneficial side effects of music training are made for many different abilities, including verbal and visuospatial abilities, executive functions, working memory, IQ, and speech perception in particular. Such claims assume that music training causes the associations even though children who take music lessons are likely to differ from other children in music aptitude, which is associated with many aspects of speech perception. Music training in childhood is also associated with cognitive, personality, and demographic variables, and it is well established that IQ and personality are determined largely by genetics. Recent evidence also indicates that the role of genetics in music aptitude and music achievement is much larger than previously thought. In short, music training is an ideal model for the study of gene-environment interactions but far less appropriate as a model for the study of plasticity. Children seek out environments, including those with music lessons, that are consistent with their predispositions; such environments exaggerate preexisting individual differences. © 2015 New York Academy of Sciences.

  19. Id-1 and Id-2 genes and products as markers of epithelial cancer

    Science.gov (United States)

    Desprez, Pierre-Yves [El Cerrito, CA; Campisi, Judith [Berkeley, CA

    2008-09-30

    A method for detection and prognosis of breast cancer and other types of cancer. The method comprises detecting expression, if any, for both an Id-1 and an Id-2 genes, or the ratio thereof, of gene products in samples of breast tissue obtained from a patient. When expressed, Id-1 gene is a prognostic indicator that breast cancer cells are invasive and metastatic, whereas Id-2 gene is a prognostic indicator that breast cancer cells are localized and noninvasive in the breast tissue.

  20. Study of miRNA Based Gene Regulation, Involved in Solid Cancer, by the Assistance of Argonaute Protein

    Directory of Open Access Journals (Sweden)

    Surya Narayan Rath

    2016-09-01

    Full Text Available Solid tumor is generally observed in tissues of epithelial or endothelial cells of lung, breast, prostate, pancreases, colorectal, stomach, and bladder, where several genes transcription is regulated by the microRNAs (miRNAs. Argonaute (AGO protein is a family of protein which assists in miRNAs to bind with mRNAs of the target genes. Hence, study of the binding mechanism between AGO protein and miRNAs, and also with miRNAs-mRNAs duplex is crucial for understanding the RNA silencing mechanism. In the current work, 64 genes and 23 miRNAs have been selected from literatures, whose deregulation is well established in seven types of solid cancer like lung, breast, prostate, pancreases, colorectal, stomach, and bladder cancer. In silico study reveals, miRNAs namely, miR-106a, miR-21, and miR-29b-2 have a strong binding affinity towards PTEN, TGFBR2, and VEGFA genes, respectively, suggested as important factors in RNA silencing mechanism. Furthermore, interaction between AGO protein (PDB ID-3F73, chain A with selected miRNAs and with miRNAs-mRNAs duplex were studied computationally to understand their binding at molecular level. The residual interaction and hydrogen bonding are inspected in Discovery Studio 3.5 suites. The current investigation throws light on understanding miRNAs based gene silencing mechanism in solid cancer.