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Updated: Apr 29, 2026
Primary Orthotopic Glioma Xenografts Recapitulate Infiltrative Growth and Isocitrate Dehydrogenase I Mutation
Published on: January 14, 2014
Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status
Anne L Baldock1, Kevin Yagle1, Donald E Born1
1Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, Chicago, Illinois (A.L.B., C.B., R.C.R., K.R.S.); Northwestern Brain Tumor Institute, Robert H. Lurie Comprehensive Cancer Center, Chicago, Ilinois (A.L.B., C.B., R.C.R., K.R.S.); Department of Pathology/Neuropathology, University of Washington School of Medicine, Seattle, Washington (K.Y., S.A., M.N., S.K.J.); Department of Pathology/Neuropathology, Stanford University, Stanford, California (D.E.B.); Department of Radiation Oncology, University of Washington School of Medicine, Seattle Washington (A.D.T., J.K.R.); Department of Integrated Mathematical Oncology, H Lee Moffitt Cancer Center and Research Institute, Tampa, Florida (D.B., J.S.); Department of Neurological Surgery, Columbia University, New York, New York (H.M., A.M.S.); Department of Pathology and Cell Biology, Columbia University, New York, New York (P.C.); Department of Neurology, University of Washington School of Medicine, Seattle, Washington (M.M.M.); Department of Applied Mathematics, University of Washington, Seattle, Washington (R.C.R., K.R.S.); Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, Illinois (K.R.S.).
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.
