TY - JOUR T1 - Exploring the link between germline and somatic genetic alterations in breast carcinogenesis. JF - PLoS One Y1 - 2010 A1 - Bonifaci, Núria A1 - Górski, Bohdan A1 - Masojć, Bartlomiej A1 - Wokołorczyk, Dominika A1 - Jakubowska, Anna A1 - Dębniak, Tadeusz A1 - Berenguer, Antoni A1 - Serra Musach, Jordi A1 - Brunet, Joan A1 - Dopazo, Joaquin A1 - Narod, Steven A A1 - Lubiński, Jan A1 - Lázaro, Conxi A1 - Cybulski, Cezary A1 - Pujana, Miguel Angel KW - Adult KW - Bone Morphogenetic Protein Receptors, Type I KW - Breast KW - Breast Neoplasms KW - Calcium-Calmodulin-Dependent Protein Kinases KW - Case-Control Studies KW - Cyclin-Dependent Kinases KW - Disease Progression KW - Estrogen Receptor alpha KW - Female KW - Gene Frequency KW - Genetic Predisposition to Disease KW - Genome-Wide Association Study KW - Genotype KW - Germ-Line Mutation KW - Humans KW - Odds Ratio KW - Poland KW - Polymorphism, Single Nucleotide KW - Protein Serine-Threonine Kinases KW - Protein-Tyrosine Kinases KW - Receptor Protein-Tyrosine Kinases KW - Receptor, EphA3 KW - Receptor, EphA7 KW - Receptor, EphB1 KW - Risk Factors AB -

Recent genome-wide association studies (GWASs) have identified candidate genes contributing to cancer risk through low-penetrance mutations. Many of these genes were unexpected and, intriguingly, included well-known players in carcinogenesis at the somatic level. To assess the hypothesis of a germline-somatic link in carcinogenesis, we evaluated the distribution of somatic gene labels within the ordered results of a breast cancer risk GWAS. This analysis suggested frequent influence on risk of genetic variation in loci encoding for "driver kinases" (i.e., kinases encoded by genes that showed higher somatic mutation rates than expected by chance and, therefore, whose deregulation may contribute to cancer development and/or progression). Assessment of these predictions using a population-based case-control study in Poland replicated the association for rs3732568 in EPHB1 (odds ratio (OR) = 0.79; 95% confidence interval (CI): 0.63-0.98; P(trend) = 0.031). Analyses by early age at diagnosis and by estrogen receptor α (ERα) tumor status indicated potential associations for rs6852678 in CDKL2 (OR = 0.32, 95% CI: 0.10-1.00; P(recessive) = 0.044) and rs10878640 in DYRK2 (OR = 2.39, 95% CI: 1.32-4.30; P(dominant) = 0.003), and for rs12765929, rs9836340, rs4707795 in BMPR1A, EPHA3 and EPHA7, respectively (ERα tumor status P(interaction)<0.05). The identification of three novel candidates as EPH receptor genes might indicate a link between perturbed compartmentalization of early neoplastic lesions and breast cancer risk and progression. Together, these data may lay the foundations for replication in additional populations and could potentially increase our knowledge of the underlying molecular mechanisms of breast carcinogenesis.

VL - 5 IS - 11 U1 - https://www.ncbi.nlm.nih.gov/pubmed/21124932?dopt=Abstract ER - TY - JOUR T1 - Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies JF - Nucl. Acids Res. Y1 - 2009 A1 - Medina, Ignacio A1 - Montaner, David A1 - Bonifaci, Núria A1 - Pujana, Miguel Angel A1 - Carbonell, José A1 - Tárraga, Joaquín A1 - Fatima Al-Shahrour A1 - Dopazo, Joaquin KW - babelomics KW - gene set KW - GESBAP KW - pathway-based analysis KW - SNP AB -

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/

VL - 37 UR - http://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W340 ER - TY - JOUR T1 - Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies. JF - Nucleic Acids Res Y1 - 2009 A1 - Medina, Ignacio A1 - Montaner, David A1 - Bonifaci, Núria A1 - Pujana, Miguel Angel A1 - Carbonell, José A1 - Tárraga, Joaquín A1 - Al-Shahrour, Fátima A1 - Dopazo, Joaquin KW - Biological Phenomena KW - Breast Neoplasms KW - Female KW - Genes KW - Genetic Variation KW - Genome-Wide Association Study KW - Humans KW - Polymorphism, Single Nucleotide KW - Software KW - User-Computer Interface AB -

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.

VL - 37 IS - Web Server issue U1 - https://www.ncbi.nlm.nih.gov/pubmed/19502494?dopt=Abstract ER - TY - JOUR T1 - Evidence for systems-level molecular mechanisms of tumorigenesis. JF - BMC Genomics Y1 - 2007 A1 - Hernández, Pilar A1 - Huerta-Cepas, Jaime A1 - Montaner, David A1 - Al-Shahrour, Fátima A1 - Valls, Joan A1 - Gómez, Laia A1 - Capellà, Gabriel A1 - Dopazo, Joaquin A1 - Pujana, Miguel Angel KW - Cell Transformation, Neoplastic KW - Gene Expression Profiling KW - Gene Expression Regulation, Neoplastic KW - Humans KW - Male KW - Models, Biological KW - Models, Genetic KW - Models, Statistical KW - Neoplasm Proteins KW - Neoplasms KW - Prostatic Neoplasms KW - Protein Interaction Mapping KW - RNA, Messenger KW - Signal Transduction KW - Systems biology AB -

BACKGROUND: Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth.

RESULTS: Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis.

CONCLUSION: Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.

VL - 8 U1 - https://www.ncbi.nlm.nih.gov/pubmed/17584915?dopt=Abstract ER -