Department of Radiology, Seoul National University Hospital, Seoul, Korea.
Center for Nanoparticle Research, Institute for Basic Science (IBS), Seoul, Korea.
Sci Rep. 2018 Oct 30;8(1):16022. doi: 10.1038/s41598-018-34242-9.
Although there have been a plethora of radiogenomics studies related to glioblastoma (GBM), most of them only used genomic information from tumor cells. In this study, we used radiogenomics profiling to identify MRI-associated immune cell markers in GBM, which was also correlated with prognosis. Expression levels of immune cell markers were correlated with quantitative MRI parameters in a total of 60 GBM patients. Fourteen immune cell markers (i.e., CD11b, CD68, CSF1R, CD163, CD33, CD123, CD83, CD63, CD49d and CD117 for myeloid cells, and CD4, CD3e, CD25 and CD8 for lymphoid cells) were selected for RNA-level analysis using quantitative RT-PCR. For MRI analysis, quantitative MRI parameters from FLAIR, contrast-enhanced (CE) T1WI, dynamic susceptibility contrast perfusion MRI and diffusion-weighted images were used. In addition, PFS associated with interesting mRNA data was performed by Kaplan-Meier survival analysis. CD163, which marks tumor associated microglia/macrophages (TAMs), showed the highest expression level in GBM patients. CD68 (TAMs), CSF1R (TAMs), CD33 (myeloid-derived suppressor cell) and CD4 (helper T cell, regulatory T cell) levels were highly positively correlated with nCBV values, while CD3e (helper T cell, cytotoxic T cell) and CD49d showed a significantly negative correlation with apparent diffusion coefficient (ADC) values. Moreover, regardless of any other molecular characteristics, CD49d was revealed as one independent factor for PFS of GBM patients by Cox proportional-hazards regression analysis (P = 0.0002). CD49d expression level CD49d correlated with ADC can be considered as a candidate biomarker to predict progression of GBM patients.
尽管已经有大量与胶质母细胞瘤（GBM）相关的放射基因组学研究，但其中大多数仅使用肿瘤细胞的基因组信息。在这项研究中，我们使用放射基因组学分析来鉴定 GBM 中与 MRI 相关的免疫细胞标志物，这些标志物也与预后相关。在总共 60 名 GBM 患者中，免疫细胞标志物的表达水平与定量 MRI 参数相关。使用定量 RT-PCR 对 14 种免疫细胞标志物（即髓样细胞的 CD11b、CD68、CSF1R、CD163、CD33、CD123、CD83、CD63、CD49d 和 CD117，以及淋巴样细胞的 CD4、CD3e、CD25 和 CD8）进行 RNA 水平分析。对于 MRI 分析，使用 FLAIR、对比增强（CE）T1WI、动态对比灌注 MRI 和弥散加权图像的定量 MRI 参数。此外，通过 Kaplan-Meier 生存分析对与有趣 mRNA 数据相关的 PFS 进行分析。CD163 标记肿瘤相关的小胶质细胞/巨噬细胞（TAMs），在 GBM 患者中表达水平最高。CD68（TAMs）、CSF1R（TAMs）、CD33（髓样来源的抑制细胞）和 CD4（辅助性 T 细胞、调节性 T 细胞）水平与 nCBV 值高度正相关，而 CD3e（辅助性 T 细胞、细胞毒性 T 细胞）和 CD49d 与表观扩散系数（ADC）值呈显著负相关。此外，无论其他分子特征如何，Cox 比例风险回归分析显示 CD49d 是 GBM 患者 PFS 的一个独立因素（P=0.0002）。CD49d 表达水平与 ADC 相关，可以被认为是预测 GBM 患者进展的候选生物标志物。
