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Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma.

ABSTRACT: BACKGROUND:To develop a radiomics signature for predicting overall survival (OS)/progression-free survival (PFS) in patients with medulloblastoma (MB), and to investigate the incremental prognostic value and biological pathways of the radiomics patterns. METHODS:A radiomics signature was constructed based on magnetic resonance imaging (MRI) from a training cohort (n = 83), and evaluated on a testing cohort (n = 83). Key pathways associated with the signature were identified by RNA-seq (GSE151519). Prognostic value of pathway genes was assessed in a public GSE85218 cohort. FINDINGS:The radiomics-clinicomolecular signature predicted OS (C-index 0.762) and PFS (C-index 0.697) better than either the radiomics signature (C-index: OS: 0.649; PFS: 0.593) or the clinicomolecular signature (C-index: OS: 0.725; PFS: 0.691) alone, with a better calibration and classification accuracy (net reclassification improvement: OS: 0.298, P = 0.022; PFS: 0.252, P = 0.026). Nine pathways were significantly correlated with the radiomics signature. Average expression value of pathway genes achieved significant risk stratification in GSE85218 cohort (log-rank P = 0.016). INTERPRETATION:This study demonstrated radiomics signature, which associated with dysregulated pathways, was an independent parameter conferring incremental value over clinicomolecular factors in survival predictions for MB patients. FUNDING:A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

SUBMITTER: Yan J

PROVIDER: S-EPMC7581926 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma.

Yan Jing J Zhang Shenghai S Li Kay Ka-Wai KK Wang Weiwei W Li Ke K Duan Wenchao W Yuan Binke B Wang Li L Liu Lei L Zhan Yunbo Y Pei Dongling D Zhao Haibiao H Sun Tao T Sun Chen C Wang Wenqing W Liu Zhen Z Hong Xuanke X Wang Xiangxiang X Guo Yu Y Li Wencai W Cheng Jingliang J Liu Xianzhi X Ng Ho-Keung HK Li Zhicheng Z Zhang Zhenyu Z

EBioMedicine 20201021

<h4>Background</h4>To develop a radiomics signature for predicting overall survival (OS)/progression-free survival (PFS) in patients with medulloblastoma (MB), and to investigate the incremental prognostic value and biological pathways of the radiomics patterns.<h4>Methods</h4>A radiomics signature was constructed based on magnetic resonance imaging (MRI) from a training cohort (n = 83), and evaluated on a testing cohort (n = 83). Key pathways associated with the signature were identified by RNA ...[more]

PMID: 33096488

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Project description:BackgroundUsing a pathway-focused approach, we aimed to provide a subgroup-specific basis for finding novel therapeutic strategies and further refinement of the risk stratification in pediatric medulloblastoma.MethodBased on genome-wide Cox regression and Gene Set Enrichment Analysis, we investigated prognosis-related signaling pathways and core genes in pediatric medulloblastoma subgroups using 530 patient data from Medulloblastoma Advanced Genomic International Consortium (MAGIC) project. We further examined the relationship between expression of the prognostic core genes and frequent chromosome aberrations using broad range copy number change data.ResultsIn SHH subgroup, relatively high expression of the core genes involved in p53, PLK1, FOXM1, and Aurora B signaling pathways are associated with poor prognosis, and their average expression synergistically increases with co-occurrence of losses of 17p, 14q, or 10q, or gain of 17q. In Group 3, in addition to high MYC expression, relatively elevated expression of PDGFRA, IGF1R, and FGF2 and their downstream genes in PI3K/AKT and MAPK/ERK pathways are related to poor survival outcome, and their average expression is increased with the presence of isochromosome 17q [i(17q)] and synergistically down-regulated with simultaneous losses of 16p, 8q, or 4q. In Group 4, up-regulation of the genes encoding various immune receptors and those involved in NOTCH, NF-κB, PI3K/AKT, or RHOA signaling pathways are associated with worse prognosis. Additionally, the expressions of Notch genes correlate with those of the prognostic immune receptors. Besides the Group 4 patients with previously known prognostic aberration, loss of chromosome 11, those with loss of 8q but without i(17q) show excellent survival outcomes and low average expression of the prognostic core genes whereas those harboring 10q loss, 1q gain, or 12q gain accompanied by i(17q) show bad outcomes. Finally, several metabolic pathways known to be reprogrammed in cancer cells are detected as prognostic pathways including glutamate metabolism in SHH subgroup, pentose phosphate pathway and TCA cycle in Group 3, and folate-mediated one carbon-metabolism in Group 4.ConclusionsThe results underscore several subgroup-specific pathways for potential therapeutic interventions: SHH-GLI-FOXM1 pathway in SHH subgroup, receptor tyrosine kinases and their downstream pathways in Group 3, and immune and inflammatory pathways in Group 4.

Project description:PurposePhase analysis can assess left ventricular dyssynchrony. The independent prognostic value of phase variables over positron emission tomography myocardial perfusion imaging (PET-MPI) variables including myocardial flow reserve (MFR) has not been studied. The aim of this study was to explore the prognostic value of phase variables for predicting mortality over standard PET-MPI variables.MethodsConsecutive patients who underwent pharmacological stress-rest 82Rb PET study were enrolled. All PET-MPI variables including phase variables (phase entropy, phase bandwidth, and phase standard deviation) were automatically obtained by QPET software (Cedars-Sinai, Los Angeles, CA). Cox proportional hazard analyses were used to assess associations with all-cause mortality (ACM).ResultsIn a total of 3963 patients (median age 71 years; 57% male), 923 patients (23%) died during a median follow-up of 5 years. Annualized mortality rates increased with stress phase entropy, with a 4.6-fold difference between the lowest and highest decile groups of entropy (2.6 vs. 12.0%/year). Abnormal stress phase entropy (optimal cutoff value, 43.8%) stratified ACM risk in patients with normal and impaired MFR (both p < 0.001). Among three phase variables, only stress phase entropy was significantly associated with ACM after the adjustment of standard clinical and PET-MPI variables including MFR and stress-rest change of phase variables, whether modeled as binary variables (adjusted hazard ratio, 1.44 for abnormal entropy [> 43.8%]; 95%CI, 1.18-1.75; p < 0.001) or continuous variables (adjusted hazard ratio, 1.05 per 5% increase; 95%CI, 1.01-1.10; p = 0.030). The addition of stress phase entropy to the standard PET-MPI variables significantly improved the discriminatory power for ACM prediction (p < 0.001), but the other phase variables did not (p > 0.1).ConclusionStress phase entropy is independently and incrementally associated with ACM beyond standard PET-MPI variables including MFR. Phase entropy can be obtained automatically and included in clinical reporting of PET-MPI studies to improve patient risk prediction.

Dataset Information

Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma.

Publications

Incremental prognostic value and underlying biological pathways of radiomics patterns in medulloblastoma.

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