GliomaPredict: A Clinically Useful Tool for Assigning Glioma Patients to Specific Molecular Subtypes
Document Type
Article
Language
eng
Format of Original
4 p.
Publication Date
2010
Publisher
BioMed Central
Source Publication
BMC Medical Informatics and Decision Making
Source ISSN
1472-6947
Original Item ID
doi: 10.1186/1472-6947-10-38
Abstract
Background: Advances in generating genome-wide gene expression data have accelerated the development of molecular-based tumor classification systems. Tools that allow the translation of such molecular classification schemas from research into clinical applications are still missing in the emerging era of personalized medicine.
Results: We developed GliomaPredict as a computational tool that allows the fast and reliable classification of glioma patients into one of six previously published stratified subtypes based on sets of extensively validated classifiers derived from hundreds of glioma transcriptomic profiles. Our tool utilizes a principle component analysis (PCA)-based approach to generate a visual representation of the analyses, quantifies the confidence of the underlying subtype assessment and presents results as a printable PDF file. GliomaPredict tool is implemented as a plugin application for the widely-used GenePattern framework.
Conclusions: GliomaPredict provides a user-friendly, clinically applicable novel platform for instantly assigning gene expression-based subtype in patients with gliomas thereby aiding in clinical trial design and therapeutic decisionmaking. Implemented as a user-friendly diagnostic tool, we expect that in time GliomaPredict, and tools like it, will become routinely used in translational/clinical research and in the clinical care of patients with gliomas.
Recommended Citation
Li, Aiguo; Bozdag, Serdar; Kotliarov, Yuri; and Fine, Howard A., "GliomaPredict: A Clinically Useful Tool for Assigning Glioma Patients to Specific Molecular Subtypes" (2010). Mathematics, Statistics and Computer Science Faculty Research and Publications. 73.
https://epublications.marquette.edu/mscs_fac/73
Comments
Published version. BMC Medical Informatics and Decision Making, Vol. 10, No. 1 (2010): 38-41. DOI. © 2010 BioMed Central. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.