Radiogenomics to characterize regional genetic heterogeneity in glioblastoma. 2017

Leland S Hu, and Shuluo Ning, and Jennifer M Eschbacher, and Leslie C Baxter, and Nathan Gaw, and Sara Ranjbar, and Jonathan Plasencia, and Amylou C Dueck, and Sen Peng, and Kris A Smith, and Peter Nakaji, and John P Karis, and C Chad Quarles, and Teresa Wu, and Joseph C Loftus, and Robert B Jenkins, and Hugues Sicotte, and Thomas M Kollmeyer, and Brian P O'Neill, and William Elmquist, and Joseph M Hoxworth, and David Frakes, and Jann Sarkaria, and Kristin R Swanson, and Nhan L Tran, and Jing Li, and J Ross Mitchell
Department of Radiology, Mayo Clinic, Phoenix, Arizona (L.S.H., T.W., J.M.H.); Department of Biostatistics, Mayo Clinic, Phoenix, Arizona (A.C.D.); Department of Research, Mayo Clinic, Arizona (J.R.M., K.S.); Department of Neurosurgery, Mayo Clinic, Phoenix, Arizona (K.R.S.); Department of Cancer and Cell Biology, Mayo Clinic, Scottsdale, Arizona (J.C.L.); Department of Pathology, Mayo Clinic, Rochester, Minnesota (R.B.J., T.M.K.); Department of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota (H.S.); Department of Neuro-oncology, Mayo Clinic, Rochester, Minnesota (B.P.O.); Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota (J.S.); Department of Pharmaceutics, University of Minnesota, Minneapolis, Minnesota (W.E.); Department of Cancer and Cell Biology, Translational Genomics Research Institute, Phoenix, Arizona (S.P., N.L.T.); School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona (J.L., T.W., S.N., N.G.); Department of Biomedical Informatics, Arizona State University, Tempe, Arizona (S.R.); School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona (J.P., D.F.); Department of Pathology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (J.M.E.); Department of Neurosurgery, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (K.A.S., P.N.); Department of Radiology, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (L.C.B., J.P. K., L.S.H.); Department of Imaging Research, Barrow Neurological Institute - St. Joseph's Hospital and Medical Center, Phoenix, Arizona (C.C.Q.).

Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology.

UI MeSH Term Description Entries
D007090 Image Interpretation, Computer-Assisted Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease. Image Interpretation, Computer Assisted,Computer-Assisted Image Interpretation,Computer-Assisted Image Interpretations,Image Interpretations, Computer-Assisted,Interpretation, Computer-Assisted Image,Interpretations, Computer-Assisted Image
D008279 Magnetic Resonance Imaging Non-invasive method of demonstrating internal anatomy based on the principle that atomic nuclei in a strong magnetic field absorb pulses of radiofrequency energy and emit them as radiowaves which can be reconstructed into computerized images. The concept includes proton spin tomographic techniques. Chemical Shift Imaging,MR Tomography,MRI Scans,MRI, Functional,Magnetic Resonance Image,Magnetic Resonance Imaging, Functional,Magnetization Transfer Contrast Imaging,NMR Imaging,NMR Tomography,Tomography, NMR,Tomography, Proton Spin,fMRI,Functional Magnetic Resonance Imaging,Imaging, Chemical Shift,Proton Spin Tomography,Spin Echo Imaging,Steady-State Free Precession MRI,Tomography, MR,Zeugmatography,Chemical Shift Imagings,Echo Imaging, Spin,Echo Imagings, Spin,Functional MRI,Functional MRIs,Image, Magnetic Resonance,Imaging, Magnetic Resonance,Imaging, NMR,Imaging, Spin Echo,Imagings, Chemical Shift,Imagings, Spin Echo,MRI Scan,MRIs, Functional,Magnetic Resonance Images,Resonance Image, Magnetic,Scan, MRI,Scans, MRI,Shift Imaging, Chemical,Shift Imagings, Chemical,Spin Echo Imagings,Steady State Free Precession MRI
D009367 Neoplasm Staging Methods which attempt to express in replicable terms the extent of the neoplasm in the patient. Cancer Staging,Staging, Neoplasm,Tumor Staging,TNM Classification,TNM Staging,TNM Staging System,Classification, TNM,Classifications, TNM,Staging System, TNM,Staging Systems, TNM,Staging, Cancer,Staging, TNM,Staging, Tumor,System, TNM Staging,Systems, TNM Staging,TNM Classifications,TNM Staging Systems
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D005240 Feasibility Studies Studies to determine the advantages or disadvantages, practicability, or capability of accomplishing a projected plan, study, or project. Feasibility Study,Studies, Feasibility,Study, Feasibility
D005909 Glioblastoma A malignant form of astrocytoma histologically characterized by pleomorphism of cells, nuclear atypia, microhemorrhage, and necrosis. They may arise in any region of the central nervous system, with a predilection for the cerebral hemispheres, basal ganglia, and commissural pathways. Clinical presentation most frequently occurs in the fifth or sixth decade of life with focal neurologic signs or seizures. Astrocytoma, Grade IV,Giant Cell Glioblastoma,Glioblastoma Multiforme,Astrocytomas, Grade IV,Giant Cell Glioblastomas,Glioblastoma, Giant Cell,Glioblastomas,Glioblastomas, Giant Cell,Grade IV Astrocytoma,Grade IV Astrocytomas
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D014408 Biomarkers, Tumor Molecular products metabolized and secreted by neoplastic tissue and characterized biochemically in cells or BODY FLUIDS. They are indicators of tumor stage and grade as well as useful for monitoring responses to treatment and predicting recurrence. Many chemical groups are represented including HORMONES; ANTIGENS; amino and NUCLEIC ACIDS; ENZYMES; POLYAMINES; and specific CELL MEMBRANE PROTEINS and LIPIDS. Biochemical Tumor Marker,Cancer Biomarker,Carcinogen Markers,Markers, Tumor,Metabolite Markers, Neoplasm,Tumor Biomarker,Tumor Marker,Tumor Markers, Biochemical,Tumor Markers, Biological,Biochemical Tumor Markers,Biological Tumor Marker,Biological Tumor Markers,Biomarkers, Cancer,Marker, Biochemical Tumor,Marker, Biologic Tumor,Marker, Biological Tumor,Marker, Neoplasm Metabolite,Marker, Tumor Metabolite,Markers, Biochemical Tumor,Markers, Biological Tumor,Markers, Neoplasm Metabolite,Markers, Tumor Metabolite,Metabolite Markers, Tumor,Neoplasm Metabolite Markers,Tumor Markers, Biologic,Tumor Metabolite Marker,Biologic Tumor Marker,Biologic Tumor Markers,Biomarker, Cancer,Biomarker, Tumor,Cancer Biomarkers,Marker, Tumor,Markers, Biologic Tumor,Markers, Carcinogen,Metabolite Marker, Neoplasm,Metabolite Marker, Tumor,Neoplasm Metabolite Marker,Tumor Biomarkers,Tumor Marker, Biochemical,Tumor Marker, Biologic,Tumor Marker, Biological,Tumor Markers,Tumor Metabolite Markers
D056915 DNA Copy Number Variations Stretches of genomic DNA that exist in different multiples between individuals. Many copy number variations have been associated with susceptibility or resistance to disease. Copy Number Polymorphism,DNA Copy Number Variant,Copy Number Changes, DNA,Copy Number Polymorphisms,Copy Number Variants, DNA,Copy Number Variation, DNA,DNA Copy Number Change,DNA Copy Number Changes,DNA Copy Number Polymorphism,DNA Copy Number Polymorphisms,DNA Copy Number Variants,DNA Copy Number Variation,Polymorphism, Copy Number,Polymorphisms, Copy Number
D023281 Genomics The systematic study of the complete DNA sequences (GENOME) of organisms. Included is construction of complete genetic, physical, and transcript maps, and the analysis of this structural genomic information on a global scale such as in GENOME WIDE ASSOCIATION STUDIES. Functional Genomics,Structural Genomics,Comparative Genomics,Genomics, Comparative,Genomics, Functional,Genomics, Structural

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