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质母细胞瘤的伪进展和真进展显示了空间变量的转录差异

Wesley Wang¹, Jonah Domingo Tugaoen¹, Paolo Fadda²

¹Department of Pathology, The Ohio State University Wexner Medical Center, The Ohio State University College of Medicine, 4166 Graves Hall, 333 W 10th Avenue, Columbus, OH, 43210, USA.

Acta neuropathologica communications

|December 4, 2023

概括

区分质母细胞瘤复发与伪进展至关重要. 这项研究揭示了不同的基因表达模式和空间免疫细胞差异,帮助病理学家准确诊断和管理癌症.

科学领域:

神经瘤学神经瘤学
癌症免疫学癌症免疫学
计算病理学计算病理学

背景情况:

对质母细胞瘤 (GBM) 复发的术后监测依赖于成像,但治疗诱导的伪进展模仿了这些迹象.
准确区分真实进展和伪进展对于适当的患者管理至关重要.
目前的诊断方法面临的挑战是由于相似的成像特征和混合组织学.

研究的目的:

验证当前的方法来区分GBM进展与伪进展.
描述真实进展和伪进展之间的分子和形态差异.
为了确定这些实体的客观分层,确定新的生物标志物.

主要方法:

从反复出现的GBM样本中分析RNA测序数据.
n对48个来自第二次神经外科切除的临床样本进行反对RNA表达分析.
组织学图像的自动图像处理和空间表达分析.
分段组织学图像的无监督聚类.

主要成果:

伪进展中的基因表达途径以免疫激活为特征,而进展显示细胞周期活性增加.
自动图像分析揭示了区分混合组织学病例的挑战.
组织学图像的无监督聚类发现了进展和伪进展之间的新型形态差异.
空间数据表明与瘤复发相关的髓状细胞两极分化.

结论:

独特的分子特征和空间免疫特征使GBM进展与伪进展区分开来.
使用无监督集群的形态分析为病理分层提供了新的见解.
了解瘤免疫微环境的演变是针对GBM复发的关键.

关键词:

临床决策的过程质母细胞瘤 (glioblastoma) 是一个新增增强功能新增增强功能病理学信息学病理学信息学虚假的进展情况.

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