<?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%">Aguerri, M</style></author><author><style face="normal" font="default" size="100%">Calzada, D</style></author><author><style face="normal" font="default" size="100%">Montaner, D</style></author><author><style face="normal" font="default" size="100%">Mata, M</style></author><author><style face="normal" font="default" size="100%">Florido, F</style></author><author><style face="normal" font="default" size="100%">Quiralte, J</style></author><author><style face="normal" font="default" size="100%">Dopazo, J</style></author><author><style face="normal" font="default" size="100%">Lahoz, C</style></author><author><style face="normal" font="default" size="100%">Cardaba, B</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Differential gene-expression analysis defines a molecular pattern related to olive pollen allergy.</style></title><secondary-title><style face="normal" font="default" size="100%">J Biol Regul Homeost Agents</style></secondary-title><alt-title><style face="normal" font="default" size="100%">J Biol Regul Homeost Agents</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Olea</style></keyword><keyword><style  face="normal" font="default" size="100%">Principal Component Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Rhinitis, Allergic, Seasonal</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2013</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2013 Apr-Jun</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">27</style></volume><pages><style face="normal" font="default" size="100%">337-50</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Analysis of gene-expression profiles by microarrays is useful for characterization of candidate genes, key regulatory networks, and to define phenotypes or molecular signatures which improve the diagnosis and/or classification of the allergic processes. We have used this approach in the study of olive pollen response in order to find differential molecular markers among responders and non-responders to this allergenic source. Five clinical groups, non-allergic, asymptomatic, allergic but not to olive pollen, untreated-olive-pollen allergic patients and olive-pollen allergic patients (under specific-immunotherapy), were assessed during and outside pollen seasons. Whole-genome gene expression analysis was performed in RNAs extracted from PBMCs. After assessment of data quality and principal components analysis (PCA), differential gene-expression, by multiple testing and, functional analyses by KEGG, for pathways and Gene-Ontology for biological processes were performed. Relevance was defined by fold change and corrected P values (less than 0.05). The most differential genes were validated by qRT-PCR in a larger set of individuals. Interestingly, gene-expression profiling obtained by PCA clearly showed five clusters of samples that correlated with the five clinical groups. Furthermore, differential gene expression and functional analyses revealed differential genes and pathways in the five clinical groups. The 93 most significant genes found were validated, and one set of 35 genes was able to discriminate profiles of olive pollen response. Our results, in addition to providing new information on allergic response, define a possible molecular signature for olive pollen allergy which could be useful for the diagnosis and treatment of this and other sensitizations. &lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">2</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/23830385?dopt=Abstract</style></custom1></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%">Montero-Conde, C</style></author><author><style face="normal" font="default" size="100%">Martín-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%">Martínez-Guitarte, J L</style></author><author><style face="normal" font="default" size="100%">Combalía, N</style></author><author><style face="normal" font="default" size="100%">Montaner, D</style></author><author><style face="normal" font="default" size="100%">Matías-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%">Robledo, M</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><alt-title><style face="normal" font="default" size="100%">Oncogene</style></alt-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adenoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Adolescent</style></keyword><keyword><style  face="normal" font="default" size="100%">Adult</style></keyword><keyword><style  face="normal" font="default" size="100%">Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Biomarkers, Tumor</style></keyword><keyword><style  face="normal" font="default" size="100%">Carcinoma</style></keyword><keyword><style  face="normal" font="default" size="100%">Carcinoma, Papillary</style></keyword><keyword><style  face="normal" font="default" size="100%">Cell Differentiation</style></keyword><keyword><style  face="normal" font="default" size="100%">Female</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Profiling</style></keyword><keyword><style  face="normal" font="default" size="100%">Gene Expression Regulation, Neoplastic</style></keyword><keyword><style  face="normal" font="default" size="100%">Humans</style></keyword><keyword><style  face="normal" font="default" size="100%">Male</style></keyword><keyword><style  face="normal" font="default" size="100%">Middle Aged</style></keyword><keyword><style  face="normal" font="default" size="100%">Oligonucleotide Array Sequence Analysis</style></keyword><keyword><style  face="normal" font="default" size="100%">Prognosis</style></keyword><keyword><style  face="normal" font="default" size="100%">Reverse Transcriptase Polymerase Chain Reaction</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Neoplasm</style></keyword><keyword><style  face="normal" font="default" size="100%">Signal Transduction</style></keyword><keyword><style  face="normal" font="default" size="100%">Thyroid Neoplasms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2008</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2008 Mar 06</style></date></pub-dates></dates><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 &gt;2-fold difference in absolute values and false discovery rate of &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><issue><style face="normal" font="default" size="100%">11</style></issue><custom1><style face="normal" font="default" size="100%">https://www.ncbi.nlm.nih.gov/pubmed/17873908?dopt=Abstract</style></custom1></record></records></xml>