| Autor: |
González-García N; Department of Statistics, University of Salamanca, Salamanca, Spain.; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain., Nieto-Librero AB; Department of Statistics, University of Salamanca, Salamanca, Spain.; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain., Vital AL; Centre for Neuroscience and Cell Biology and Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal., Tao HJ; Neurosurgery Service, University Hospital of Coimbra, Coimbra, Portugal., González-Tablas M; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain.; Centre for Cancer Research (CIC-IBMCC; CSIC/USAL; IBSAL) and Department of Medicine, University of Salamanca, Salamanca, Spain.; Biomedical Research Networking Centre on Cancer-CIBERONC (CB16/12/00400),, Institute of Health Carlos III, Madrid, Spain., Otero Á; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain., Galindo-Villardón P; Department of Statistics, University of Salamanca, Salamanca, Spain.; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain., Orfao A; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain.; Centre for Cancer Research (CIC-IBMCC; CSIC/USAL; IBSAL) and Department of Medicine, University of Salamanca, Salamanca, Spain.; Biomedical Research Networking Centre on Cancer-CIBERONC (CB16/12/00400),, Institute of Health Carlos III, Madrid, Spain., Tabernero MD; Instituto de Investigación biomédica de Salamanca, IBSAL- University Hospital of Salamanca, Salamanca, Spain. taberner@usal.es.; Centre for Cancer Research (CIC-IBMCC; CSIC/USAL; IBSAL) and Department of Medicine, University of Salamanca, Salamanca, Spain. taberner@usal.es.; Biomedical Research Networking Centre on Cancer-CIBERONC (CB16/12/00400),, Institute of Health Carlos III, Madrid, Spain. taberner@usal.es.; Instituto de Estudios de Ciencias de La Salud de Castilla y León (IECSCYL-IBSAL), Salamanca, Spain. taberner@usal.es. |
| Abstrakt: |
Diagnosis and classification of gliomas mostly relies on histopathology and a few genetic markers. Here we interrogated microarray gene expression profiles (GEP) of 268 diffuse astrocytic gliomas-33 diffuse astrocytomas (DA), 52 anaplastic astrocytomas (AA) and 183 primary glioblastoma (GBM)-based on multivariate analysis, to identify discriminatory GEP that might support precise histopathological tumor stratification, particularly among inconclusive cases with II-III grade diagnosed, which have different prognosis and treatment strategies. Microarrays based GEP was analyzed on 155 diffuse astrocytic gliomas (discovery cohort) and validated in another 113 tumors (validation set) via sequential univariate analysis (pairwise comparison) for discriminatory gene selection, followed by nonnegative matrix factorization and canonical biplot for identification of discriminatory GEP among the distinct histological tumor subtypes. GEP data analysis identified a set of 27 genes capable of differentiating among distinct subtypes of gliomas that might support current histological classification. DA + AA showed similar molecular profiles with only a few discriminatory genes overexpressed (FSTL5 and SFRP2) and underexpressed (XIST, TOP2A and SHOX2) in DA vs AA and GBM. Compared to DA + AA, GBM displayed underexpression of ETNPPL, SH3GL2, GABRG2, SPX, DPP10, GABRB2 and CNTN3 and overexpression of CHI3L1, IGFBP3, COL1A1 and VEGFA, among other differentially expressed genes. |
