Web of Science: 5 citas, Scopus: 5 citas, Google Scholar: citas,
Development of robust discriminant equations for assessing subtypes of glioblastoma biopsies
Castells, Xavier (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia molecular)
Acebes, Juan José (Hospital Universitari de Bellvitge. Institut d'Investigació Biomèdica)
Majós, Carles (Hospital Universitari de Bellvitge. Institut de Diagnòstic per la Imatge)
Boluda, Susana (Hospital Universitari de Bellvitge. Institut de Neuropatologia, Institut d'Investigació Biomèdica)
Julià-Sapé, Margarida (Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Candiota Silveira, Ana Paula (Institut de Biotecnologia i de Biomedicina "Vicent Villar Palasí")
Ariño Carmona, Joaquín (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia molecular)
Barceló, Antonia (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia molecular)
Arús i Caraltó, Carles (Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular. Grup d'Aplicacions Biomèdiques de la RMN (GABRMN))

Fecha: 2012
Resumen: In the preceding decade, various studies on glioblastoma (Gb) demonstrated that signatures obtained from gene expression microarrays correlate better with survival than with histopathological classification. However, there is not a universal consensus formula to predict patient survival. We developed a gene signature using the expression profile of 47 Gbs through an unsupervised procedure and two groups were obtained. Subsequent to a training procedure through leave-one-out cross-validation, we fitted a discriminant (linear discriminant analysis (LDA)) equation using the four most discriminant probesets. This was repeated for two other published signatures and the performance of LDA equations was evaluated on an independent test set, which contained status of IDH1 mutation, EGFR amplification, MGMT methylation and gene VEGF expression, among other clinical and molecular information. The unsupervised local signature was composed of 69 probesets and clearly defined two Gb groups, which would agree with primary and secondary Gbs. This hypothesis was confirmed by predicting cases from the independent data set using the equations developed by us. The high survival group predicted by equations based on our local and one of the published signatures contained a significantly higher percentage of cases displaying IDH1 mutation and non-amplification of EGFR. In contrast, only the equation based on the published signature showed in the poor survival group a significant high percentage of cases displaying a hypothesised methylation of MGMT gene promoter and overexpression of gene VEGF. We have produced a robust equation to confidently discriminate Gb subtypes based in the normalised expression level of only four genes.
Nota: Número d'acord de subvenció EC/FP6/503094
Nota: Número d'acord de subvenció MICINN/SAF2005/03650
Nota: Número d'acord de subvenció MICINN/SAF2008/03323
Derechos: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. Creative Commons
Lengua: Anglès.
Documento: article ; publishedVersion
Materia: Glioblastoma ; Anterior descending branch of left coronary artery ; Subtype (attribute) ; Protein Overexpression ; Guillain-Barre Syndrome ; Validation ; Discriminant Analysis ; Scientific Publication ; Promoter
Publicado en: British journal of cancer, Vol. 106, número 11 (May 2012) , p. 1816-1825, ISSN 1532-1827

DOI: 10.1038/bjc.2012.174
PMID: 22568967


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