There are several currently employed classification systems for @entity11 that sort @entity5 based on histological features. Contemporary molecular techniques, however, offer the promise of improved @entity5 classification and resultant @entity1 stratification for treatment and prognosis. In particular, gene expression profiling has shown exceptional promise for providing an alternative and more objective molecular approach to @entity11 classification. In this study, we used cDNA array technology to profile the gene expression of 30 primary @entity1 @entity11 tissue samples comprising 4 different @entity11 subtypes as defined by current World Health Organization (WHO 2000) criteria: @entity463 ( @entity463 , WHO grade IV), @entity816 ( @entity816 , WHO grade III), @entity3271 ( @entity3271 , WHO grade III), and @entity3271 ( @entity3271 , WHO grade II). Gene expression data alone were used to group the @entity5 using multidimensional scaling, which is an unsupervised statistical method. Results show that impressive separation of the 4 @entity11 subtypes can be achieved solely on the basis of molecular data. In addition, a subcluster of 3 @entity463 was identified as distinct from other GMs and from the @entity5 . These 3 @entity1 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 can recapitulate conventional histologic classification and grading with high fidelity. In addition, results show that the molecular approach to @entity5 classification can generate clinically meaningful @entity1 stratification, and, more importantly, is an efficient class-discovery tool for @entity1 @entity11 , permitting the identification of previously unrecognized, clinically relevant @entity5 subsets.

Molecular classification of @entity1 XXXX by multidimensional scaling analysis of gene expression profiles parallels morphology-based classification, correlates with survival, and reveals clinically-relevant novel @entity11 subsets.

@entity1 :: ('9606', 'Species') :: ['human', 'patients', 'patient'] @entity5 :: ('MESH:D009369', 'Disease') :: ['tumor', 'oligodendroglial tumors', 'tumors'] @entity11 :: ('MESH:D005910', 'Disease') :: ['diffuse gliomas', 'glioma', 'gliomas'] @entity816 :: ('MESH:D001254', 'Disease') :: ['anaplastic astrocytoma', 'AA'] @entity463 :: ('MESH:D005909', 'Disease') :: ['glioblastomas', 'GM', 'glioblastoma'] @entity3271 :: ('MESH:D009837', 'Disease') :: ['AO', 'anaplastic oligodendroglioma', 'oligodendroglioma', 'OL']
@entity11 :: (MESH:D005910,Disease) :: ['diffuse gliomas']
