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A Coclinical Radiogenomic Validation Study: Conserved Magnetic Resonance Radiomic Appearance of Periostin-Expressing Glioblastoma in Patients and Xenograft Models
- Source :
- Clinical cancer research : an official journal of the American Association for Cancer Research. 24(24)
- Publication Year :
- 2017
-
Abstract
- 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. Experimental Design: 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 on the basis of 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 interspecies. 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 = 02.021E−15). Conclusions: We determined causality between radiomic texture features and POSTN expression levels in a preclinical model with clinical validation. Our biologically validated radiomic pipeline also showed the potential application for human–mouse matched coclinical trials.
- Subjects :
- 0301 basic medicine
Oncology
Adult
Data Analysis
Male
Cancer Research
medicine.medical_specialty
Microarray
Radiogenomics
Gene Expression
Periostin
Biology
Article
03 medical and health sciences
Mice
0302 clinical medicine
Text mining
Internal medicine
Gene expression
Image Interpretation, Computer-Assisted
medicine
Biomarkers, Tumor
Image Processing, Computer-Assisted
Animals
Humans
Aged
Aged, 80 and over
Gene knockdown
business.industry
Brain Neoplasms
Genomics
Middle Aged
Phenotype
Magnetic Resonance Imaging
Xenograft Model Antitumor Assays
Molecular Imaging
Gene expression profiling
Disease Models, Animal
030104 developmental biology
030220 oncology & carcinogenesis
Female
business
Glioblastoma
Cell Adhesion Molecules
Subjects
Details
- ISSN :
- 15573265
- Volume :
- 24
- Issue :
- 24
- Database :
- OpenAIRE
- Journal :
- Clinical cancer research : an official journal of the American Association for Cancer Research
- Accession number :
- edsair.doi.dedup.....98b207d7ffb97f79c061cacf61ba9dc6