A co-clinical radiogenomic validation study - Conserved magnetic resonance radiomic appearance of Periostin expressing Glioblastoma in patients and xenograft models

PURPOSE: Radiomics is the extraction of multidimensional imaging-features which when correlated with genomics is termed radiogenomics. However, radiogenomic biological validation is not sufficiently described in the literature. We seek to establish causality between differential gene expression status and MRI-extracted radiomic-features in glioblastoma. METHODS: Radiogenomic predictions and validation were done using the Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data glioblastoma patients (N=93) and orthotopic xenografts (OX)(N=40). Tumor phenotypes were segmented, and radiomic-features extracted using the developed radiome-sequencing pipeline. Patients and animals were dichotomized based on Periostin (POSTN) expression levels. RNA and protein levels confirmed RNAi-mediated POSTN knockdown in OX. Total RNA of tumor cells isolated from mouse brains (knockdown and control) was used for microarray-based expression profiling. Radiomic-features were utilized to predict POSTN expression status in patient, mouse, and inter-species. RESULTS: Our robust pipeline consists of segmentation, radiomic-feature extraction, feature normalization/selection, and predictive-modeling. The combination of skull stripping, brain-tissue focused normalization and patient-specific normalization are unique to this study, providing comparable cross-platform, cross-institution radiomic-features. POSTN expression status was not associated with qualitative or volumetric MRI parameters. Radiomic-features significantly predicted POSTN expression status in patients (AUC 76.56%, sensitivity/specificity: 73.91/78.26%) and OX (AUC 92.26%, sensitivity/specificity: 92.86%/91.67%). Furthermore, radiomic-features in OX were significantly associated with patients with similar POSTN expression levels (AUC 93.36%, sensitivity/specificity: 82.61%/95.74%; p-value 02.021E-15). CONCLUSION: We determined causality between radiomic texture features and POSTN expression levels in a pre-clinical model with clinical validation. Our biologically validated radiomic pipeline also showed the potential application for human-mouse matched co-clinical trials.

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