biostudies-literatureBeig NBLRD VANIBIB NIH HHSNational Institute of Diabetes and Digestive and Kidney DiseasesNCI NIH HHSphilanthropic funding including Sheila PrenowitzNCI NIHDOD Prostate Cancer Idea Development Award1866-1876https://www.ebi.ac.uk/biostudies/studies/S-EPMC7165059biostudies-literatureUnknown26(8)<h4>Purpose</h4>To (i) create a survival risk score using radiomic features from the tumor habitat on routine MRI to predict progression-free survival (PFS) in glioblastoma and (ii) obtain a biological basis for these prognostic radiomic features, by studying their radiogenomic associations with molecular signaling pathways.<h4>Experimental design</h4>Two hundred three patients with pretreatment Gd-T1w, T2w, T2w-FLAIR MRI were obtained from 3 cohorts: The Cancer Imaging Archive (TCIA; <i>n</i> = 130), Ivy GAP (<i>n</i> = 32), and Cleveland Clinic (<i>n</i> = 41). Gene-expression profiles of corresponding patients were obtained for TCIA cohort. For every study, following expert segmentation of tumor subcompartments (necrotic core, enhancing tumor, peritumoral edema), 936 3D radiomic features were extracted from each subcompartment across all MRI protocols. Using Cox regression model, radiomic risk score (RRS) was developed for every protocol to predict PFS on the training cohort (<i>n</i> = 130) and evaluated on the holdout cohort (<i>n</i> = 73). Further, Gene Ontology and single-sample gene set enrichment analysis were used to identify specific molecular signaling pathway networks associated with RRS features.<h4>Results</h4>Twenty-five radiomic features from the tumor habitat yielded the RRS. A combination of RRS with clinical (age and gender) and molecular features (MGMT and IDH status) resulted in a concordance index of 0.81 (<i>P</i> < 0.0001) on training and 0.84 (<i>P</i> = 0.03) on the test set. Radiogenomic analysis revealed associations of RRS features with signaling pathways for cell differentiation, cell adhesion, and angiogenesis, which contribute to chemoresistance in GBM.<h4>Conclusions</h4>Our findings suggest that prognostic radiomic features from routine Gd-T1w MRI may also be significantly associated with key biological processes that affect response to chemotherapy in GBM.Clinical cancer research : an official journal of the American Association for Cancer ResearchRadiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma.PMC7165059R01 CA1365351P20 CA233216-01R43 EB015199R01CA216579-01A1T32 CA0941861K25 DK115904-01A1R01 CA216579W81XWH-15-1-05581U01 CA239055-01I01 BX004121R01 CA220581-01A1U24 CA199374U01 CA239055R01 CA220581R01CA202752-01A1R01 CA2027521U24CA199374-01R01 CA208236R01CA208236-01A1Antunes JVerma RSaeed Bamashmos AIsmail MVaradan VTiwari PMadabhushi ABeig NBraman NAhluwalia MSPrasanna PBera KCorrea RHill VBStatsevych VSingh SfalseRadiogenomic-Based Survival Risk Stratification of Tumor Habitat on Gd-T1w MRI Is Associated with Biological Processes in Glioblastoma.<h4>Purpose</h4>To (i) create a survival risk score using radiomic features from the tumor habitat on routine MRI to predict progression-free survival (PFS) in glioblastoma and (ii) obtain a biological basis for these prognostic radiomic features, by studying their radiogenomic associations with molecular signaling pathways.<h4>Experimental design</h4>Two hundred three patients with pretreatment Gd-T1w, T2w, T2w-FLAIR MRI were obtained from 3 cohorts: The Cancer Imaging Archive (TCIA; <i>n</i> = 130), Ivy GAP (<i>n</i> = 32), and Cleveland Clinic (<i>n</i> = 41). Gene-expression profiles of corresponding patients were obtained for TCIA cohort. For every study, following expert segmentation of tumor subcompartments (necrotic core, enhancing tumor, peritumoral edema), 936 3D radiomic features were extracted from each subcompartment across all MRI protocols. Using Cox regression model, radiomic risk score (RRS) was developed for every protocol to predict PFS on the training cohort (<i>n</i> = 130) and evaluated on the holdout cohort (<i>n</i> = 73). Further, Gene Ontology and single-sample gene set enrichment analysis were used to identify specific molecular signaling pathway networks associated with RRS features.<h4>Results</h4>Twenty-five radiomic features from the tumor habitat yielded the RRS. A combination of RRS with clinical (age and gender) and molecular features (MGMT and IDH status) resulted in a concordance index of 0.81 (<i>P</i> < 0.0001) on training and 0.84 (<i>P</i> = 0.03) on the test set. Radiogenomic analysis revealed associations of RRS features with signaling pathways for cell differentiation, cell adhesion, and angiogenesis, which contribute to chemoresistance in GBM.<h4>Conclusions</h4>Our findings suggest that prognostic radiomic features from routine Gd-T1w MRI may also be significantly associated with key biological processes that affect response to chemotherapy in GBM.2020-01-01T00:00:00Z2020 Apr2024-10-15T23:28:02.298Z2020-10-29T09:32:21ZS-EPMC71650593207959010.1158/1078-0432.CCR-19-255610.1158/1078-0432.ccr-19-2556