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Titolo:
Molecular classification of human diffuse gliomas by multidimensional scaling analysis of gene expression profiles parallels morphology-based classification, correlates with survival, and reveals clinically-relevant novel glioma subsets
Autore:
Fuller, GN; Hess, KR; Rhee, CH; Yung, WKA; Sawaya, RA; Bruner, JM; Zhang, W;
Indirizzi:
Univ Texas, MD Anderson Canc Ctr, Dept Pathol, Houston, TX 77030 USA Univ Texas Houston TX USA 77030 c Ctr, Dept Pathol, Houston, TX 77030 USA Univ Texas, MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA UnivTexas Houston TX USA 77030 Ctr, Dept Biostat, Houston, TX 77030 USA Univ Texas, MD Anderson Canc Ctr, Dept Neurooncol, Houston, TX 77030 USA Univ Texas Houston TX USA 77030 r, Dept Neurooncol, Houston, TX 77030 USA Univ Texas, MD Anderson Canc Ctr, Dept Neurosurg, Houston, TX 77030 USA Univ Texas Houston TX USA 77030 tr, Dept Neurosurg, Houston, TX 77030 USA
Titolo Testata:
BRAIN PATHOLOGY
fascicolo: 1, volume: 12, anno: 2002,
pagine: 108 - 116
SICI:
1015-6305(200201)12:1<108:MCOHDG>2.0.ZU;2-O
Fonte:
ISI
Lingua:
ENG
Soggetto:
GLIOBLASTOMA-MULTIFORME; OLIGODENDROGLIOMAS; ASTROCYTOMAS; PREDICTORS; MICROARRAY; PATTERNS;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Life Sciences
Citazioni:
27
Recensione:
Indirizzi per estratti:
Indirizzo: Fuller, GN Univ Texas, MD Anderson Canc Ctr, Dept Pathol 085, 1515 Holcombe Blvd, Houston, TX 77030 USA Univ Texas 1515 Holcombe Blvd Houston TX USA 77030 TX 77030 USA
Citazione:
G.N. Fuller et al., "Molecular classification of human diffuse gliomas by multidimensional scaling analysis of gene expression profiles parallels morphology-based classification, correlates with survival, and reveals clinically-relevant novel glioma subsets", BRAIN PATH, 12(1), 2002, pp. 108-116

Abstract

There are several currently employed classification systems for diffuse gliomas that sort tumors based on histological features. Contemporary molecular techniques, however, offer the promise of improved tumor classification and resultant patient stratification for treatment and prognosis. In particular, gene expression profiling has shown exceptional promise for providingan alternative and more objective molecular approach to glioma classification. In this study, we used cDNA array technology to profile the gene expression of 30 primary human glioma tissue samples comprising 4 different glioma subtypes as defined by current World Health Organization (WHO 2000) criteria: glioblastoma (GM, WHO grade IV), anaplastic astrocytoma (AA, WHO grade III), anaplastic oligodendroglioma (AO, WHO grade III), and oligodendroglioma (OL, WHO grade II). Gene expression data alone were used to group the tumors using multidimensional scaling, which is an unsupervised statisticalmethod. Results show that impressive separation of the 4 glioma subtypes can be achieved solely on the basis of molecular data. In addition, a subcluster of 3 glioblastomas was identified as distinct from other GMs and from the oligodendroglial tumors. These 3 patients have shown extended survival compared to other GMs in the study. Survival analysis of the full data set revealed a good correlation with the molecular classification. Results of this proof-of-principle study demonstrate that molecular profiling alone canrecapitulate conventional histologic classification and grading with high fidelity. In addition, results show that the molecular approach to tumor classification can generate clinically meaningful patient stratification, and, more importantly, is an efficient class-discovery tool for human gliomas,permitting the identification of previously unrecognized, clinically relevant tumor subsets.

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Documento generato il 01/04/20 alle ore 19:07:20