Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status. (June 2014)

• Record Type: Journal Article
• Authors: Baldock, Anne L.; Yagle, Kevin; Born, Donald E.; Ahn, Sunyoung; Trister, Andrew D.; Neal, Maxwell; Johnston, Sandra K.; Bridge, Carly A.; Basanta, David; Scott, Jacob; Malone, Hani; Sonabend, Adam M.; Canoll, Peter; Mrugala, Maciej M.; Rockhill, Jason K.; Rockne, Russell C.; Swanson, Kristin R.
• Is Part Of: Neuro-oncology. Volume 16(2014)Supplement 6
• Page Start: 779
• Page End: 786
• Publication Date: 2014-06
• Subjects: glioma -- growth kinetics -- IDH1 -- mathematical model -- patient-specific -- proliferation -- invasion; Brain Neoplasms -- Periodicals; Brain -- Tumors -- Periodicals; Brain -- Cancer -- Periodicals; Nervous system -- Cancer -- Periodicals; 616.99481
• DOI: 10.1093/neuonc/nou027
• Languages: English
• ISSNs: 1522-8517

Abstract

Abstract: Background: Glioblastomas with a specific mutation in the isocitrate dehydrogenase 1 (IDH1) gene have a better prognosis than gliomas with wild-type IDH1. Methods: Here we compare the IDH1 mutational status in 172 contrast-enhancing glioma patients with the invasion profile generated by a patient-specific mathematical model we developed based on MR imaging. Results: We show that IDH1-mutated contrast-enhancing gliomas were relatively more invasive than wild-type IDH1 for all 172 contrast-enhancing gliomas as well as the subset of 158 histologically confirmed glioblastomas. The appearance of this relatively increased, model-predicted invasive profile appears to be determined more by a lower model-predicted net proliferation rate rather than an increased model-predicted dispersal rate of the glioma cells. Receiver operator curve analysis of the model-predicted MRI-based invasion profile revealed an area under the curve of 0.91, indicative of a predictive relationship. The robustness of this relationship was tested by cross-validation analysis of the invasion profile as a predictive metric for IDH1 status. Conclusions: The strong correlation between IDH1 mutation status and the MRI-based invasion profile suggests that use of our tumor growth model may lead to noninvasive clinical detection of IDH1 mutation status and thus lead to better treatment planning, particularly prior to surgical resection, for contrast-enhancing gliomas.