Radiogenomic models predict glioblastoma immune signatures

Researchers have developed radiogenomic models capable of non-invasively predicting a specific immune cell signature in glioblastoma. These models utilize radiomic features extracted from MRI scans and transcriptomic data to identify macrophage subtype M0 immune signatures. The study, involving 176 patients across multiple datasets, demonstrated stable performance and potential for stratifying patients for immunotherapy in future clinical trials. AI

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IMPACT This research offers a non-invasive method to predict patient immune signatures, potentially improving immunotherapy stratification for glioblastoma.

RANK_REASON The cluster contains an academic paper detailing a new research methodology and findings. [lever_c_demoted from research: ic=1 ai=1.0]

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• glioblastoma
• TCGA-GBM
• CPTAC
• IvyGAP
• REMBRANDT
• CGGA
• LASSO
• Support vector machine
• macrophage

• paper
• safety