<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hernandez, P.</style></author><author><style face="normal" font="default" size="100%">Huerta-Cepas, J.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Valls, J.</style></author><author><style face="normal" font="default" size="100%">Gomez, L.</style></author><author><style face="normal" font="default" size="100%">Capella, G.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Pujana, M. A.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Evidence for systems-level molecular mechanisms of tumorigenesis</style></title><secondary-title><style face="normal" font="default" size="100%">BMC Genomics</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">*Cell Transformation</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Messenger/metabolism Signal Transduction Systems Biology</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic *Gene Expression Profiling *Gene Expression Regulation</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic Humans Male Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Statistical Neoplasm Proteins/*physiology Neoplasms/etiology/*genetics Prostatic Neoplasms/genetics Protein Interaction Mapping RNA</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=17584915</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">8</style></volume><pages><style face="normal" font="default" size="100%">185</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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 &quot;CGPs&quot;) 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.</style></abstract><notes><style face="normal" font="default" size="100%">Hernandez, Pilar Huerta-Cepas, Jaime Montaner, David Al-Shahrour, Fatima Valls, Joan Gomez, Laia Capella, Gabriel Dopazo, Joaquin Pujana, Miguel Angel Research Support, Non-U.S. Gov’t England BMC genomics BMC Genomics. 2007 Jun 20;8:185.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Arbiza, L.</style></author><author><style face="normal" font="default" size="100%">Duchi, S.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Burguet, J.</style></author><author><style face="normal" font="default" size="100%">Pantoja-Uceda, D.</style></author><author><style face="normal" font="default" size="100%">Pineda-Lucena, A.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">H. Dopazo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Selective pressures at a codon-level predict deleterious mutations in human disease genes</style></title><secondary-title><style face="normal" font="default" size="100%">J Mol Biol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Sequence Amino Acid Substitution Codon/*genetics Databases</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Evolution</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Human Humans Models</style></keyword><keyword><style  face="normal" font="default" size="100%">Inborn/*genetics Genome</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Molecular Molecular Sequence Data *Mutation Neoplasms/genetics Proteins/genetics *Selection (Genetics) Tumor Suppressor Protein p53/chemistry/genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">p53 Genetic Diseases</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2006</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&amp;db=PubMed&amp;dopt=Citation&amp;list_uids=16584746</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">5</style></number><volume><style face="normal" font="default" size="100%">358</style></volume><pages><style face="normal" font="default" size="100%">1390-404</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Deleterious mutations affecting biological function of proteins are constantly being rejected by purifying selection from the gene pool. The non-synonymous/synonymous substitution rate ratio (omega) is a measure of selective pressure on amino acid replacement mutations for protein-coding genes. Different methods have been developed in order to predict non-synonymous changes affecting gene function. However, none has considered the estimation of selective constraints acting on protein residues. Here, we have used codon-based maximum likelihood models in order to estimate the selective pressures on the individual amino acid residues of a well-known model protein: p53. We demonstrate that the number of residues under strong purifying selection in p53 is much higher than those that are strictly conserved during the evolution of the species. In agreement with theoretical expectations, residues that have been noted to be of structural relevance, or in direct association with DNA, were among those showing the highest signals of purifying selection. Conversely, those changing according to a neutral, or nearly neutral mode of evolution, were observed to be irrelevant for protein function. Finally, using more than 40 human disease genes, we demonstrate that residues evolving under strong selective pressures (omega&lt;0.1) are significantly associated (p&lt;0.01) with human disease. We hypothesize that non-synonymous change on amino acids showing omega&lt;0.1 will most likely affect protein function. The application of this evolutionary prediction at a genomic scale will provide an a priori hypothesis of the phenotypic effect of non-synonymous coding single nucleotide polymorphisms (SNPs) in the human genome.</style></abstract><notes><style face="normal" font="default" size="100%">Arbiza, Leonardo Duchi, Serena Montaner, David Burguet, Jordi Pantoja-Uceda, David Pineda-Lucena, Antonio Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov’t England Journal of molecular biology J Mol Biol. 2006 May 19;358(5):1390-404. Epub 2006 Mar 15.</style></notes></record></records></xml>