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述评:胶质母细胞瘤的放射组学:从肿瘤细胞转移到免疫微环境。

Editorial comment: Radiogenomics of glioblastoma: shifting the focus from tumor cells to immune microenvironment.

机构信息

Department of Biomedical Sciences, Humanitas University, Via R. Levi Montalcini 4, 20090, Pieve Emanuele, Milan, Italy.

Department of Neuroradiology, IRCCS Humanitas Research Hospital, Rozzano, Italy.

出版信息

Eur Radiol. 2023 Jan;33(1):207-208. doi: 10.1007/s00330-022-09195-3. Epub 2022 Oct 28.

Abstract

• The ICI score derived from gene expression profile of immune cells infiltrating GBM correlates with overall survival and is an effective prognostic biomarker.• In this study, the authors developed a radiomics-based machine learning model able to identify gene expression profiles of GBM intratumoral stromal and immune cells and predict the ICI score on the preoperative MRI scans with high accuracy.• Radiogenomics could potentially be applied in primary brain tumors to noninvasively assess the specific tumor immune characteristics, predict patients' prognosis and identify those patients with higher probability to respond to immunotherapy.

摘要

• 基于胶质母细胞瘤浸润免疫细胞的基因表达谱得出的 ICI 评分与总生存期相关,是一种有效的预后生物标志物。• 在这项研究中,作者开发了一种基于放射组学的机器学习模型,能够识别胶质母细胞瘤肿瘤内基质和免疫细胞的基因表达谱,并能够高精度地在术前 MRI 扫描上预测 ICI 评分。• 放射基因组学有可能应用于原发性脑肿瘤,以无创方式评估特定的肿瘤免疫特征,预测患者的预后,并识别那些更有可能对免疫治疗有反应的患者。

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