放射流式细胞术显示K-RAS肺癌中[18F]FDG摄取是由免疫细胞驱动的:单细胞水平的分析

Chrysoula Vraka, Monika Homolya, Öykü Özer, Andreas Spittler, Michael Machtinger, Herwig P. Moll, Emilio Casanova, Claudia Kuntner, Stefan Grünert, Marcus Hacker, Cécile Philippe
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摘要

肿瘤代谢是癌症的标志之一,但肿瘤微环境中的细胞异质性是一个重大挑战,因为批量分析掩盖了单个细胞群的不同代谢特征。这种复杂性使我们对肿瘤微环境中不同细胞类型摄取[18F]FDG的理解变得更加复杂。本研究旨在利用新技术放射流式细胞术(radioFlow)研究 Kirsten 大鼠肉瘤病毒驱动的癌症小鼠模型肺部单细胞水平的 [18F]FDG 摄取情况。研究方法给两种 Kirsten 大鼠肉瘤病毒驱动的肺癌小鼠模型注射[18F]FDG,进行小动物 PET/CT 和随后的肺部荧光激活细胞分选。然后用γ计数器测量分选细胞的放射性,并将其放射性与细胞数量进行归一化。结果对两种模型的肺组织进行的放射流动分析表明,在不同的实验中,细胞类型特异性摄取模式都很强。我们的主要发现表明,[18F]FDG PET 信号主要来自免疫细胞(CD45+、F4/80-,78.3% ± 6.6%;巨噬细胞,13.9% ± 4.3%),而肿瘤细胞只占 2.8% ± 1.0%,与结构细胞(CD45-;肿瘤细胞,5.0% ± 2.3%)的摄取相似。正常化结果显示,在两种肿瘤模型中,巨噬细胞的葡萄糖代谢率最高(57% ± 8%),其次是其余免疫细胞(27% ± 3%)。结论这些发现凸显了免疫细胞代谢对[18F]FDG 成像的重要影响,强调在解释癌症[18F]FDG 成像时需要考虑免疫的贡献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RadioFlow Cytometry Reveals That [18F]FDG Uptake in K-RAS Lung Cancer Is Driven by Immune Cells: An Analysis on a Single-Cell Level

Tumor metabolism is a hallmark of cancer, yet cellular heterogeneity within the tumor microenvironment presents a significant challenge, as bulk analysis masks the diverse metabolic profiles of individual cell populations. This complexity complicates our understanding of [18F]FDG uptake by distinct cell types in the tumor microenvironment. This study aims to investigate [18F]FDG uptake at the single-cell level in the lung of Kirsten rat sarcoma virus–driven cancer mouse models using the novel technique radio–flow cytometry (radioFlow). Methods: Two Kirsten rat sarcoma virus–driven lung cancer mouse models were injected with [18F]FDG for small-animal PET/CT and subsequent fluorescence-activated cell sorting of the lung. For radioFlow, the sorted cell fractions were then measured in a γ-counter and their radioactivity was normalized to the number of cells. Results: RadioFlow analysis of the lung tissue of both models showed a robust cell type–specific uptake pattern across experiments. Our key findings indicate that the [18F]FDG PET signal predominantly derives from immune cells (CD45+, F4/80, 78.3% ± 6.6%; macrophage, 13.9% ± 4.3%), whereas tumor cells contributed only with 2.8% ± 1.0%, similar to the uptake of structural cells (CD45; tumor cells, 5.0% ± 2.3%). Normalization showed that macrophages exhibited the highest glucose metabolism in both tumor models (57% ± 8%), followed by the remaining immune cells (27% ± 3%). Conclusion: These findings highlight the critical influence of immune cell metabolism on [18F]FDG imaging, emphasizing the need to account for immune contributions when interpreting [18F]FDG imaging in cancer.

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