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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/75707
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dc.contributor.authorSilveira, Sara Martoreli-
dc.contributor.authorVillacis, Rolando Andre Rios-
dc.contributor.authorMarchi, Fabio Albuquerque-
dc.contributor.authorde Barros Filho, Mateus Camargo-
dc.contributor.authorLinde, Sandra Aparecida Drigo-
dc.contributor.authorNeto, Cristovam Scapulatempo-
dc.contributor.authorLopes, Ademar-
dc.contributor.authorda Cunha, Isabela Werneck-
dc.contributor.authorRogatto, Silvia Regina-
dc.date.accessioned2014-05-27T11:29:47Z-
dc.date.accessioned2016-10-25T18:50:10Z-
dc.date.available2014-05-27T11:29:47Z-
dc.date.available2016-10-25T18:50:10Z-
dc.date.issued2013-06-25-
dc.identifierhttp://dx.doi.org/10.1371/journal.pone.0067643-
dc.identifier.citationPLoS ONE, v. 8, n. 6, 2013.-
dc.identifier.issn1932-6203-
dc.identifier.urihttp://hdl.handle.net/11449/75707-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/75707-
dc.description.abstractUndifferentiated high-grade pleomorphic sarcomas (UPSs) display aggressive clinical behavior and frequently develop local recurrence and distant metastasis. Because these sarcomas often share similar morphological patterns with other tumors, particularly leiomyosarcomas (LMSs), classification by exclusion is frequently used. In this study, array-based comparative genomic hybridization (array CGH) was used to analyze 20 UPS and 17 LMS samples from untreated patients. The LMS samples presented a lower frequency of genomic alterations compared with the UPS samples. The most frequently altered UPS regions involved gains at 20q13.33 and 7q22.1 and losses at 3p26.3. Gains at 8q24.3 and 19q13.12 and losses at 9p21.3 were frequently detected in the LMS samples. Of these regions, gains at 1q21.3, 11q12.2-q12.3, 16p11.2, and 19q13.12 were significantly associated with reduced overall survival times in LMS patients. A multivariate analysis revealed that gains at 1q21.3 were an independent prognostic marker of shorter survival times in LMS patients (HR = 13.76; P = 0.019). Although the copy number profiles of the UPS and LMS samples could not be distinguished using unsupervised hierarchical clustering analysis, one of the three clusters presented cases associated with poor prognostic outcome (P = 0.022). A relative copy number analysis for the ARNT, SLC27A3, and PBXIP1 genes was performed using quantitative real-time PCR in 11 LMS and 16 UPS samples. Gains at 1q21-q22 were observed in both tumor types, particularly in the UPS samples. These findings provide strong evidence for the existence of a genomic signature to predict poor outcome in a subset of UPS and LMS patients. © 2013 Silveira et al.en
dc.language.isoeng-
dc.sourceScopus-
dc.subjectantineoplastic agent-
dc.subjectadjuvant therapy-
dc.subjectadolescent-
dc.subjectadult-
dc.subjectaged-
dc.subjectARNT gene-
dc.subjectcancer prognosis-
dc.subjectcancer radiotherapy-
dc.subjectchild-
dc.subjectchromosome 11q-
dc.subjectchromosome 16p-
dc.subjectchromosome 19q-
dc.subjectchromosome 1q-
dc.subjectchromosome 20q-
dc.subjectchromosome 3p-
dc.subjectchromosome 7q-
dc.subjectchromosome 8q-
dc.subjectchromosome 9p-
dc.subjectchromosome loss-
dc.subjectclinical article-
dc.subjectcomparative genomic hybridization-
dc.subjectfemale-
dc.subjectgene-
dc.subjectgene dosage-
dc.subjectgene mutation-
dc.subjecthuman-
dc.subjecthuman tissue-
dc.subjectleiomyosarcoma-
dc.subjectmale-
dc.subjectmuscle resection-
dc.subjectnucleotide sequence-
dc.subjectoverall survival-
dc.subjectPBXIP1 gene-
dc.subjectpleomorphic sarcoma-
dc.subjectprediction-
dc.subjectpreschool child-
dc.subjectquantitative analysis-
dc.subjectreal time polymerase chain reaction-
dc.subjectsarcoma-
dc.subjectschool child-
dc.subjectSLC27A3 gene-
dc.titleGenomic Signatures Predict Poor Outcome in Undifferentiated Pleomorphic Sarcomas and Leiomyosarcomasen
dc.typeoutro-
dc.contributor.institutionA. C. Camargo Cancer Center-
dc.contributor.institutionUniversidade de São Paulo (USP)-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.contributor.institutionHospital do Câncer de Barretos-
dc.description.affiliationNeogene Laboratory A. C. Camargo Cancer Center, São Paulo, São Paulo-
dc.description.affiliationInstitute of Mathematics and Statistics Inter-Institutional Program on Bioinformatics, USP, São Paulo, São Paulo-
dc.description.affiliationDepartment of Urology Faculty of Medicine, UNESP, Botucatu, São Paulo-
dc.description.affiliationDepartment of Pathology Barretos Cancer Hospital (Pio XII Foundation), Barretos, São Paulo-
dc.description.affiliationDepartment of Pelvic Surgery A. C. Camargo Cancer Center, São Paulo, São Paulo-
dc.description.affiliationDepartment of Pathology A. C. Camargo Cancer Center, São Paulo, São Paulo-
dc.description.affiliationUnespDepartment of Urology Faculty of Medicine, UNESP, Botucatu, São Paulo-
dc.identifier.doi10.1371/journal.pone.0067643-
dc.identifier.wosWOS:000321223000112-
dc.rights.accessRightsAcesso aberto-
dc.identifier.file2-s2.0-84879397016.pdf-
dc.relation.ispartofPLOS ONE-
dc.identifier.scopus2-s2.0-84879397016-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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