Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and Technology, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon, 34141, Korea.
Department of Neurosurgery, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea.
Cancer Immunol Immunother. 2021 Jul;70(7):1995-2008. doi: 10.1007/s00262-020-02836-w. Epub 2021 Jan 8.
To understand the tumor immune microenvironment precisely, it is important to secure the quantified data of tumor-infiltrating immune cells, since the immune cells are true working unit. We analyzed unit immune cell number per unit volume of core tumor tissue of high-grade gliomas (HGG) to correlate their immune microenvironment characteristics with clinical prognosis and radiomic signatures.
The number of tumor-infiltrating immune cells from 64 HGG core tissue were analyzed using flow cytometry and standardized. After sorting out patient groups according to diverse immune characteristics, the groups were tested if they have any clinical prognostic relevance and specific radiomic signature relationships. Sparse partial least square with discriminant analysis using multimodal magnetic resonance images was employed for all radiomic classifications.
The median number of CD45 + cells per one gram of HGG core tissue counted 865,770 cells which was equivalent to 8.0% of total cells including tumor cells. There was heterogeneity in the distribution of immune cell subpopulations among patients. Overall survival was significantly better in T cell-deficient group than T cell-enriched group (p = 0.019), and T8 dominant group than T4 dominant group (p = 0.023). The number of tumor-associated macrophages (TAM) and M2-TAM was significantly decreased in isocitrate dehydrogenase mutated HGG. Radiomic signature classification showed good performance in predicting immune phenotypes especially with features extracted from apparent diffusion coefficient maps.
Absolute quantification of tumor-infiltrating immune cells confirmed the heterogeneity of immune microenvironment in HGG which harbors prognostic impact. This immune microenvironment could be predicted by radiomic signatures non-invasively.
为了准确了解肿瘤免疫微环境，获取肿瘤浸润免疫细胞的量化数据非常重要，因为免疫细胞是真正的工作单位。我们分析了高级别胶质瘤（HGG）核心肿瘤组织单位体积中的单位免疫细胞数量，以将其免疫微环境特征与临床预后和放射组学特征相关联。
使用流式细胞术对 64 例 HGG 核心组织中的肿瘤浸润免疫细胞数量进行分析并进行标准化。根据不同的免疫特征对患者进行分组后，检测其是否与临床预后相关及具有特定的放射组学特征关系。采用多模态磁共振图像稀疏偏最小二乘判别分析进行所有放射组学分类。
每克 HGG 核心组织中 CD45+细胞的中位数为 865770 个细胞，相当于包括肿瘤细胞在内的总细胞的 8.0%。患者之间免疫细胞亚群的分布存在异质性。T 细胞缺陷组的总生存期明显长于 T 细胞富集组（p=0.019），T8 优势组明显长于 T4 优势组（p=0.023）。在异柠檬酸脱氢酶突变的 HGG 中，肿瘤相关巨噬细胞（TAM）和 M2-TAM 的数量明显减少。放射组学特征分类在预测免疫表型方面表现出良好的性能，尤其是使用表观扩散系数图提取的特征。
肿瘤浸润免疫细胞的绝对定量证实了 HGG 中免疫微环境的异质性，这种异质性具有预后影响。这种免疫微环境可以通过放射组学特征进行无创预测。
