<?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%">Palacios, J.</style></author><author><style face="normal" font="default" size="100%">Honrado, E.</style></author><author><style face="normal" font="default" size="100%">Osorio, A.</style></author><author><style face="normal" font="default" size="100%">Cazorla, A.</style></author><author><style face="normal" font="default" size="100%">Sarrio, D.</style></author><author><style face="normal" font="default" size="100%">Barroso, A.</style></author><author><style face="normal" font="default" size="100%">Rodriguez, S.</style></author><author><style face="normal" font="default" size="100%">Cigudosa, J. C.</style></author><author><style face="normal" font="default" size="100%">Diez, O.</style></author><author><style face="normal" font="default" size="100%">Alonso, C.</style></author><author><style face="normal" font="default" size="100%">Lerma, E.</style></author><author><style face="normal" font="default" size="100%">Dopazo, J.</style></author><author><style face="normal" font="default" size="100%">Rivas, C.</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%">Phenotypic characterization of BRCA1 and BRCA2 tumors based in a tissue microarray study with 37 immunohistochemical markers</style></title><secondary-title><style face="normal" font="default" size="100%">Breast Cancer Res Treat</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Adult Apoptosis Breast Neoplasms/*genetics/*pathology Cell Cycle Proteins Cluster Analysis Female *Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">Biological/genetics/metabolism</style></keyword><keyword><style  face="normal" font="default" size="100%">BRCA1 *Genes</style></keyword><keyword><style  face="normal" font="default" size="100%">BRCA2 Humans Immunohistochemistry In Situ Hybridization</style></keyword><keyword><style  face="normal" font="default" size="100%">Fluorescence Phenotype Spain *Tissue Array Analysis *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=15770521</style></url></web-urls></urls><number><style face="normal" font="default" size="100%">1</style></number><volume><style face="normal" font="default" size="100%">90</style></volume><pages><style face="normal" font="default" size="100%">5-14</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Familial breast cancers that are associated with BRCA1 or BRCA2 germline mutations differ in both their morphological and immunohistochemical characteristics. To further characterize the molecular difference between genotypes, the authors evaluated the expression of 37 immunohistochemical markers in a tissue microarray (TMA) containing cores from 20 BRCA1, 14 BRCA2, and 59 sporadic age-matched breast carcinomas. Markers analyzed included, amog others, common markers in breast cancer, such as hormone receptors, p53 and HER2, along with 15 molecules involved in cell cycle regulation, such as cyclins, cyclin dependent kinases (CDK) and CDK inhibitors (CDKI), apoptosis markers, such as BCL2 and active caspase 3, and two basal/myoepithelial markers (CK 5/6 and P-cadherin). In addition, we analyzed the amplification of CCND1, CCNE, HER2 and MYC by FISH.Unsupervised cluster data analysis of both hereditary and sporadic cases using the complete set of immunohistochemical markers demonstrated that most BRCA1-associated carcinomas grouped in a branch of ER-, HER2-negative tumors that expressed basal cell markers and/or p53 and had higher expression of activated caspase 3. The cell cycle proteins associated with these tumors were E2F6, cyclins A, B1 and E, SKP2 and Topo IIalpha. In contrast, most BRCA2-associated carcinomas grouped in a branch composed by ER/PR/BCL2-positive tumors with a higher expression of the cell cycle proteins cyclin D1, cyclin D3, p27, p16, p21, CDK4, CDK2 and CDK1. In conclusion, our study in hereditary breast cancer tumors analyzing 37 immunohistochemical markers, define the molecular differences between BRCA1 and BRCA2 tumors with respect to hormonal receptors, cell cycle, apoptosis and basal cell markers.</style></abstract><notes><style face="normal" font="default" size="100%">Palacios, Jose Honrado, Emiliano Osorio, Ana Cazorla, Alicia Sarrio, David Barroso, Alicia Rodriguez, Sandra Cigudosa, Juan C Diez, Orland Alonso, Carmen Lerma, Enrique Dopazo, Joaquin Rivas, Carmen Benitez, Javier Research Support, Non-U.S. Gov’t Netherlands Breast cancer research and treatment Breast Cancer Res Treat. 2005 Mar;90(1):5-14.</style></notes></record></records></xml>