Abstract
Abstract Oligodendroglioma are defined by a distinct molecular phenotype marked by 1p19q co-deletion and simultaneous presence of an IDH1/2 mutation. These tumors showed a favorable clinical course and long-term survival of around 15 years. Due to the long course of the disease, prospective studies to determine the effectiveness of different therapeutic strategies are difficult, since the percentage of patients with multiple therapies is high. Here we report a computational approach to map the longitudinal growth pattern, to quantify the effect of therapies on tumor growth and to identify similarities and spatial heterogeneity of oligodendroglioma growth. In our study, we included a cohort of 44 histopathologically and molecularly stratified oligodendrogliomas WHO°II (n=23) and WHO°III (n=21). We started our investigation with the longitudinal tumor segmentation. All volumetric data were pinpointed to the times of tumor therapy within all patients. Next, we extracted first-order features of tumor growth and response to chemo- or radiotherapy as well as resection, resulting in a total number of 98 features. An unsupervised cluster was used to identify similarities between patients, which revealed 3 subgroups. The first subgroup contained patients with predominantly frontal oligodendrogliomas marked by increased response to radiotherapy. The second subgroup included temporal oligodendrogliomas with high response rate to PC/PCV chemotherapy and flagged by epilepsy. The third group was heterogeneous with varying growth behaviors. A survival analysis showed a better separation between low- and high-risk patients based on the growth pattern model, in contrast to the WHO grading system. Taken together, our analysis revealed a novel classification of oligodendroglioma based on the longitudinal growth pattern and therapeutical response. We also detected a spatial difference between frontally or temporally localized oligodendrogliomas. We plan to further investigate molecular data that explain these spatial differences, which also may uncover novel therapeutic strategies.
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