Invasion and proliferation kinetics in enhancing gliomas predict IDH1 mutation status

See the editorial by Lathia, on pages 763–764. Since the 2008 discovery of a mutation in the isocitrate dehydrogenase 1 (IDH1) gene in a subset of glioma patients, more than 2 dozen manuscripts have been published about the role of this IDH1 mutation in the natural history of glioma.1–6 This unique mutation in IDH1, which changes arginine at position 132 to histidine, is disproportionately represented in lower-grade gliomas; it is present in >75% of grade II and III gliomas but only ∼10% of grade IV glioblastomas (GBMs).1,7 Furthermore, this mutation in IDH1 is more prevalent in younger patients. Glioma patients with the mutation show significantly longer survival times than those with the wild-type copy of the gene, having a median survival of 3.8 years versus 1.1 years.1,8 Additionally, secondary GBMs are predominantly mutant in IDH1 (83%), while very few primary GBMs (5%) harbor the mutation.7 Since IDH1mut GBMs (and perhaps more contrast-enhancing gliomas) have a significantly better prognosis than IDH1wt GBMs, it is clinically important to have pretreatment (presurgical) predictors of IDH1mut status. Our laboratory has developed a patient-specific mathematical model of glioma growth that is based on diagnostic and pretreatment MRI scans obtained in the course of normal clinical treatment.9–15 By combining our model formalism with tumor volume measures extracted from these routinely obtained pretreatment MRIs, we are able to estimate patient-specific parameters that quantify the net proliferation rate (ρ) of the glioma cells and their net dispersal or diffusion rate (D). These parameters can be used to characterize the differential role of proliferation versus diffusion in driving the overall tumor growth pattern seen in each patient. The variation in the parameters across patients is consistent with the wide heterogeneity in imaging results and invasive capacity typical of the disease.12 These 2 kinetic parameters can be combined to produce a biological aggressiveness ratio (ρ/D) that quantifies the relative proliferative to invasive nature of each tumor. This measure of biological aggressiveness is predictive of worse prognosis14 and increasing degrees of hypoxia,15 a known feature of tumor aggressiveness. Also, we have previously shown that a high ρ/D (characteristic of more nodular, less diffuse tumors) is more likely to represent a rapidly developing primary GBM that is relatively less invasive, whereas a low ρ/D (characteristic of a more diffuse, less nodular tumor) is associated with a slower developing but more invasive secondary GBM.16 This novel discovery suggests the possibility of predicting primary versus secondary GBM natural histories and, by extension, likely IDH1mutation status based on a single measure quantifiable from routinely obtained MR images alone. Further, a recent game theory-based consideration of the evolutionary role of IDH1 mutation in cellular populations suggested that such a mutation would select for a more invasive overall tumor phenotype.17 Combining these 2 insights suggests the following question: can we predict IDH1 mutation status from image-based analysis of tumor invasion using patient-specific mathematical models of glioma proliferation and invasion kinetics? One of our main hypotheses was that the most diffuse contrast-enhancing gliomas (low ρ/D) would be mutant in IDH1. To test this hypothesis, we examined the mutational status of IDH1 by mutation-specific immunohistochemistry in a cohort of 172 newly diagnosed, contrast-enhancing glioma patients, 91% of whom were ultimately found to have grade IV tumors. The concept was to distinguish IDH1 mutant tumors (with their associated favorable prognosis) within a cohort of contrast-enhancing gliomas by mapping a favorable molecular feature to patient-specific disease kinetics (ie, net proliferation and invasion rates).