<?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%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Martin-Campos, J. M.</style></author><author><style face="normal" font="default" size="100%">Lerma, E.</style></author><author><style face="normal" font="default" size="100%">Gimenez, G.</style></author><author><style face="normal" font="default" size="100%">Martinez-Guitarte, J. L.</style></author><author><style face="normal" font="default" size="100%">Combalia, N.</style></author><author><style face="normal" font="default" size="100%">Montaner, D.</style></author><author><style face="normal" font="default" size="100%">Matias-Guiu, X.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">de Leiva, A.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Mauricio, D.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Molecular profiling related to poor prognosis in thyroid carcinoma. Combining gene expression data and biological information</style></title><secondary-title><style face="normal" font="default" size="100%">Oncogene</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adenoma/genetics/metabolism/pathology Adolescent Adult Aged Carcinoma/genetics/metabolism/pathology Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/*genetics/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplasm/genetics/metabolism Reverse Transcriptase Polymerase Chain Reaction Signal Transduction Thyroid Neoplasms/classification/*genetics/metabolism Tumor Markers</style></keyword><keyword><style  face="normal" font="default" size="100%">Neoplastic Humans Male Middle Aged *Oligonucleotide Array Sequence Analysis Prognosis RNA</style></keyword><keyword><style  face="normal" font="default" size="100%">Papillary/genetics/metabolism/pathology Cell Differentiation Female *Gene Expression Profiling *Gene Expression Regulation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</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=17873908</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">11</style></number><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">1554-61</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Undifferentiated and poorly differentiated thyroid tumors are responsible for more than half of thyroid cancer patient deaths in spite of their low incidence. Conventional treatments do not obtain substantial benefits, and the lack of alternative approaches limits patient survival. Additionally, the absence of prognostic markers for well-differentiated tumors complicates patient-specific treatments and favors the progression of recurrent forms. In order to recognize the molecular basis involved in tumor dedifferentiation and identify potential markers for thyroid cancer prognosis prediction, we analysed the expression profile of 44 thyroid primary tumors with different degrees of dedifferentiation and aggressiveness using cDNA microarrays. Transcriptome comparison of dedifferentiated and well-differentiated thyroid tumors identified 1031 genes with &amp;gt;2-fold difference in absolute values and false discovery rate of &amp;lt;0.15. According to known molecular interaction and reaction networks, the products of these genes were mainly clustered in the MAPkinase signaling pathway, the TGF-beta signaling pathway, focal adhesion and cell motility, activation of actin polymerization and cell cycle. An exhaustive search in several databases allowed us to identify various members of the matrix metalloproteinase, melanoma antigen A and collagen gene families within the upregulated gene set. We also identified a prognosis classifier comprising just 30 transcripts with an overall accuracy of 95%. These findings may clarify the molecular mechanisms involved in thyroid tumor dedifferentiation and provide a potential prognosis predictor as well as targets for new therapies.&lt;/p&gt;</style></abstract><notes><style face="normal" font="default" size="100%">&lt;p&gt;Montero-Conde, C Martin-Campos, J M Lerma, E Gimenez, G Martinez-Guitarte, J L Combalia, N Montaner, D Matias-Guiu, X Dopazo, J de Leiva, A Robledo, M Mauricio, D Research Support, Non-U.S. Gov’t England Oncogene Oncogene. 2008 Mar 6;27(11):1554-61. Epub 2007 Sep 17.&lt;/p&gt;</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%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Milne, R. L.</style></author><author><style face="normal" font="default" size="100%">Moya, C. M.</style></author><author><style face="normal" font="default" size="100%">Cebrian, A.</style></author><author><style face="normal" font="default" size="100%">Leton, R.</style></author><author><style face="normal" font="default" size="100%">Cascon, A.</style></author><author><style face="normal" font="default" size="100%">Mercadillo, F.</style></author><author><style face="normal" font="default" size="100%">Landa, I.</style></author><author><style face="normal" font="default" size="100%">Borrego, S.</style></author><author><style face="normal" font="default" size="100%">Perez de Nanclares, G.</style></author><author><style face="normal" font="default" size="100%">Alvarez-Escola, C.</style></author><author><style face="normal" font="default" size="100%">Diaz-Perez, J. A.</style></author><author><style face="normal" font="default" size="100%">Carracedo, A.</style></author><author><style face="normal" font="default" size="100%">Urioste, M.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Neira, A.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author><author><style face="normal" font="default" size="100%">Santisteban, P.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Ponder, B. A.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Association study of 69 genes in the ret pathway identifies low-penetrance loci in sporadic medullary thyroid carcinoma</style></title><secondary-title><style face="normal" font="default" size="100%">Cancer Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic Proto-Oncogene Proteins c-ret/*genetics/metabolism Signal Transduction Thyroid Neoplasms/*genetics/metabolism Transcription</style></keyword><keyword><style  face="normal" font="default" size="100%">Medullary/*genetics/metabolism Case-Control Studies Cyclin-Dependent Kinase Inhibitor p15/biosynthesis/genetics Female Genetic Predisposition to Disease Germ-Line Mutation Haplotypes Humans Male Middle Aged Penetrance Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Promoter Regions</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=17909067</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">67</style></volume><pages><style face="normal" font="default" size="100%">9561-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">To date, few association studies have been done to better understand the genetic basis for the development of sporadic medullary thyroid carcinoma (sMTC). To identify additional low-penetrance genes, we have done a two-stage case-control study in two European populations using high-throughput genotyping. We selected 417 single nucleotide polymorphisms (SNP) belonging to 69 genes either related to RET signaling pathway/functions or involved in key processes for cancer development. TagSNPs and functional variants were included where possible. These SNPs were initially studied in the largest known series of sMTC cases (n = 266) and controls (n = 422), all of Spanish origin. In stage II, an independent British series of 155 sMTC patients and 531 controls was included to validate the previous results. Associations were assessed by an exhaustive analysis of individual SNPs but also considering gene- and linkage disequilibrium-based haplotypes. This strategy allowed us to identify seven low-penetrance genes, six of them (STAT1, AURKA, BCL2, CDKN2B, CDK6, and COMT) consistently associated with sMTC risk in the two case-control series and a seventh (HRAS) with individual SNPs and haplotypes associated with sMTC in the Spanish data set. The potential role of CDKN2B was confirmed by a functional assay showing a role of a SNP (rs7044859) in the promoter region in altering the binding of the transcription factor HNF1. These results highlight the utility of association studies using homogeneous series of cases for better understanding complex diseases.</style></abstract><notes><style face="normal" font="default" size="100%">Ruiz-Llorente, Sergio Montero-Conde, Cristina Milne, Roger L Moya, Christian M Cebrian, Arancha Leton, Rocio Cascon, Alberto Mercadillo, Fatima Landa, Inigo Borrego, Salud Perez de Nanclares, Guiomar Alvarez-Escola, Cristina Diaz-Perez, Jose Angel Carracedo, Angel Urioste, Miguel Gonzalez-Neira, Anna Benitez, Javier Santisteban, Pilar Dopazo, Joaquin Ponder, Bruce A Robledo, Mercedes Medullary Thyroid Carcinoma Clinical Group Research Support, Non-U.S. Gov’t United States Cancer research Cancer Res. 2007 Oct 1;67(19):9561-7.</style></notes></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">González-Neira, A</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">f single nucleotide polymorphism arrays: Design, tools and applications</style></title><secondary-title><style face="normal" font="default" size="100%">Microarray Technology Through Applications</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><publisher><style face="normal" font="default" size="100%">Taylor &amp; Francis, F. Falciani</style></publisher><pub-location><style face="normal" font="default" size="100%">New York, USA</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language></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%">Milne, R. L.</style></author><author><style face="normal" font="default" size="100%">Ribas, G.</style></author><author><style face="normal" font="default" size="100%">Gonzalez-Neira, A.</style></author><author><style face="normal" font="default" size="100%">Fagerholm, R.</style></author><author><style face="normal" font="default" size="100%">Salas, A.</style></author><author><style face="normal" font="default" size="100%">Gonzalez, E.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Nevanlinna, H.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">ERCC4 associated with breast cancer risk: a two-stage case-control study using high-throughput genotyping</style></title><secondary-title><style face="normal" font="default" size="100%">Cancer Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Breast Neoplasms/epidemiology/*genetics/pathology Case-Control Studies DNA-Binding Proteins/genetics/*physiology Female Finland/epidemiology Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Recessive Genetic Predisposition to Disease Genotype Humans Introns/genetics Linkage Disequilibrium Middle Aged Neoplasm Proteins/genetics/*physiology Neoplasm Staging *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide Risk Spain/epidemiology</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=17018596</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">19</style></number><volume><style face="normal" font="default" size="100%">66</style></volume><pages><style face="normal" font="default" size="100%">9420-7</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The failure of linkage studies to identify further high-penetrance susceptibility genes for breast cancer points to a polygenic model, with more common variants having modest effects on risk, as the most likely candidate. We have carried out a two-stage case-control study in two European populations to identify low-penetrance genes for breast cancer using high-throughput genotyping. Single-nucleotide polymorphisms (SNPs) were selected across preselected cancer-related genes, choosing tagSNPs and functional variants where possible. In stage 1, genotype frequencies for 640 SNPs in 111 genes were compared between 864 breast cancer cases and 845 controls from the Spanish population. In stage 2, candidate SNPs identified in stage 1 (nominal P &lt; 0.01) were tested in a Finnish series of 884 cases and 1,104 controls. Of the 10 candidate SNPs in seven genes identified in stage 1, one (rs744154) on intron 1 of ERCC4, a gene belonging to the nucleotide excision repair pathway, was associated with recessive protection from breast cancer after adjustment for multiple testing in stage 2 (odds ratio, 0.57; Bonferroni-adjusted P = 0.04). After considering potential functional SNPs in the region of high linkage disequilibrium that extends across the entire gene and upstream into the promoter region, we concluded that rs744154 itself could be causal. Although intronic, it is located on the first intron, in a region that is highly conserved across species, and could therefore be functionally important. This study suggests that common intronic variation in ERCC4 is associated with protection from breast cancer.</style></abstract><notes><style face="normal" font="default" size="100%">Milne, Roger Laughlin Ribas, Gloria Gonzalez-Neira, Anna Fagerholm, Rainer Salas, Antonio Gonzalez, Emilio Dopazo, Joaquin Nevanlinna, Heli Robledo, Mercedes Benitez, Javier Comparative Study Multicenter Study Research Support, Non-U.S. Gov’t United States Cancer research Cancer Res. 2006 Oct 1;66(19):9420-7.</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%">Cascon, A.</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">Rodriguez-Perales, S.</style></author><author><style face="normal" font="default" size="100%">Honrado, E.</style></author><author><style face="normal" font="default" size="100%">Martinez-Ramirez, A.</style></author><author><style face="normal" font="default" size="100%">Leton, R.</style></author><author><style face="normal" font="default" size="100%">Montero-Conde, C.</style></author><author><style face="normal" font="default" size="100%">Benitez, J.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A novel candidate region linked to development of both pheochromocytoma and head/neck paraganglioma</style></title><secondary-title><style face="normal" font="default" size="100%">Genes Chromosomes Cancer</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">80 and over Child Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent Adrenal Gland Neoplasms/*genetics Adult Aged Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/*genetics</style></keyword><keyword><style  face="normal" font="default" size="100%">Human</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 1/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 11/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 3/genetics Chromosomes</style></keyword><keyword><style  face="normal" font="default" size="100%">Pair 8/genetics Female Gene Deletion Head and Neck Neoplasms/*genetics Humans Male Middle Aged Nucleic Acid Hybridization Paraganglioma/*genetics Pheochromocytoma/*genetics Tumor Markers</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2005</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=15609347</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">42</style></volume><pages><style face="normal" font="default" size="100%">260-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Although the histologic distinction between pheochromocytomas and head and neck paragangliomas is clear, little is known about the genetic differences between them. To date, various sets of genes have been found to be involved in inherited susceptibility to developing both tumor types, but the genes involved in sporadic pathogenesis are still unknown. To define new candidate regions, we performed CGH analysis on 29 pheochromocytomas and on 24 paragangliomas mainly of head and neck origin (20 of 24), which allowed us to differentiate between the two tumor types. Loss of 3q was significantly more frequent in pheochromocytomas, and loss of 1q appeared only in paragangliomas. We also found gain of 11q13 to be a significantly frequent alteration in malignant cases of both types. In addition, recurrent loss of 8p22-23 was found in 62% of pheochromocytomas (including all malignant cases) versus in 33% of paragangliomas, suggesting that this region contains candidate genes involved in the pathogenesis of this abnormality. Using FISH analysis on tissue microarrays, we confirmed genomic deletion of this region in 55% of pheochromocytomas compared to 12% of paragangliomas. Loss of 8p22-23 appears to be an important event in the sporadic development of these tumors, and additional molecular studies are necessary to identify candidate genes in this chromosomal region.</style></abstract><notes><style face="normal" font="default" size="100%">Cascon, Alberto Ruiz-Llorente, Sergio Rodriguez-Perales, Sandra Honrado, Emiliano Martinez-Ramirez, Angel Leton, Rocio Montero-Conde, Cristina Benitez, Javier Dopazo, Joaquin Cigudosa, Juan C Robledo, Mercedes Research Support, Non-U.S. Gov’t United States Genes, chromosomes &amp; cancer Genes Chromosomes Cancer. 2005 Mar;42(3):260-8.</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%">L. Conde</style></author><author><style face="normal" font="default" size="100%">Vaquerizas, J. M.</style></author><author><style face="normal" font="default" size="100%">J. Santoyo</style></author><author><style face="normal" font="default" size="100%">Fatima Al-Shahrour</style></author><author><style face="normal" font="default" size="100%">Ruiz-Llorente, S.</style></author><author><style face="normal" font="default" size="100%">M. Robledo</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">PupaSNP Finder: a web tool for finding SNPs with putative effect at transcriptional level</style></title><secondary-title><style face="normal" font="default" size="100%">Nucleic Acids Res</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Amino Acid Substitution Binding Sites Humans Internet Phenotype *Polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">Genetic</style></keyword><keyword><style  face="normal" font="default" size="100%">Single Nucleotide RNA Splicing *Software Transcription Factors/metabolism *Transcription</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</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=15215388</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">Web Server issue</style></number><volume><style face="normal" font="default" size="100%">32</style></volume><pages><style face="normal" font="default" size="100%">W242-8</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">We have developed a web tool, PupaSNP Finder (PupaSNP for short), for high-throughput searching for single nucleotide polymorphisms (SNPs) with potential phenotypic effect. PupaSNP takes as its input lists of genes (or generates them from chromosomal coordinates) and retrieves SNPs that could affect the conserved regions that the cellular machinery uses for the correct processing of genes (intron/exon boundaries or exonic splicing enhancers), predicted transcription factor binding sites (TFBS) and changes in amino acids in the proteins. The program uses the mapping of SNPs in the genome provided by Ensembl. Additionally, user-defined SNPs (not yet mapped in the genome) can be easily provided to the program. Also, additional functional information from Gene Ontology, OMIM and homologies in other model organisms is provided. In contrast to other programs already available, which focus only on SNPs with possible effect in the protein, PupaSNP includes SNPs with possible transcriptional effect. PupaSNP will be of significant help in studies of multifactorial disorders, where the use of functional SNPs will increase the sensitivity of identification of the genes responsible for the disease. The PupaSNP web interface is accessible through http://pupasnp.bioinfo.cnio.es.</style></abstract><notes><style face="normal" font="default" size="100%">Conde, Lucia Vaquerizas, Juan M Santoyo, Javier Al-Shahrour, Fatima Ruiz-Llorente, Sergio Robledo, Mercedes Dopazo, Joaquin England Nucleic acids research Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W242-8.</style></notes></record></records></xml>