Development of robust discriminant equations for assessing subtypes of glioblastoma biopsies.

ABSTRACT:

Background

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.

Methods

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

SUBMITTER: Castells X 

PROVIDER: S-EPMC3364559 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature