Improved grading and survival prediction of human astrocytic brain tumors by artificial neural network analysis of gene expression microarray data
- 1 May 2008
- journal article
- Published by American Association for Cancer Research (AACR) in Molecular Cancer Therapeutics
- Vol. 7 (5), 1013-1024
- https://doi.org/10.1158/1535-7163.mct-07-0177
Abstract
Histopathologic grading of astrocytic tumors based on current WHO criteria offers a valuable but simplified representation of oncologic reality and is often insufficient to predict clinical outcome. In this study, we report a new astrocytic tumor microarray gene expression data set (n = 65). We have used a simple artificial neural network algorithm to address grading of human astrocytic tumors, derive specific transcriptional signatures from histopathologic subtypes of astrocytic tumors, and asses whether these molecular signatures define survival prognostic subclasses. Fifty-nine classifier genes were identified and found to fall within three distinct functional classes, that is, angiogenesis, cell differentiation, and lower-grade astrocytic tumor discrimination. These gene classes were found to characterize three molecular tumor subtypes denoted ANGIO, INTER, and LOWER. Grading of samples using these subtypes agreed with prior histopathologic grading for both our data set (96.15%) and an independent data set. Six tumors were particularly challenging to diagnose histopathologically. We present an artificial neural network grading for these samples and offer an evidence-based interpretation of grading results using clinical metadata to substantiate findings. The prognostic value of the three identified tumor subtypes was found to outperform histopathologic grading as well as tumor subtypes reported in other studies, indicating a high survival prognostic potential for the 59 gene classifiers. Finally, 11 gene classifiers that differentiate between primary and secondary glioblastomas were also identified. [Mol Cancer Ther 2008;7(5):1013–24]Other Versions
This publication has 41 references indexed in Scilit:
- DNA-microarray analysis of brain cancer: molecular classification for therapyNature Reviews Neuroscience, 2004
- The immunohistochemical expression of calcitonin receptor-like receptor (CRLR) in human gliomasJournal of Clinical Pathology, 2004
- Gene expression profiling identifies molecular subtypes of gliomasOncogene, 2003
- MIB-1 and DNA Topoisomerase IIα Could Be Helpful for Predicting Long-Term Survival of Patients With GlioblastomaAmerican Journal of Clinical Pathology, 2003
- Caloramator viterbensis sp. nov., a novel thermophilic, glycerol-fermenting bacterium isolated from a hot spring in ItalyInternational Journal of Systematic and Evolutionary Microbiology, 2002
- Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT MethodMethods, 2001
- R: A Language for Data Analysis and GraphicsJournal of Computational and Graphical Statistics, 1996
- R: A Language for Data Analysis and GraphicsJournal of Computational and Graphical Statistics, 1996
- Nonparametric Estimation from Incomplete ObservationsJournal of the American Statistical Association, 1958
- Nonparametric Estimation from Incomplete ObservationsJournal of the American Statistical Association, 1958