Vraka Chrysoula, Homolya Monika, Özer Öykü, Spittler Andreas, Machtinger Michael, Moll Herwig P, Casanova Emilio, Kuntner Claudia, Grünert Stefan, Hacker Marcus, Philippe Cécile
Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria.
Institute of Pharmacology, Center of Physiology and Pharmacology and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria.
J Nucl Med. 2025 Feb 3;66(2):215-222. doi: 10.2967/jnumed.124.268799.
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 [F]FDG uptake by distinct cell types in the tumor microenvironment. This study aims to investigate [F]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). Two Kirsten rat sarcoma virus-driven lung cancer mouse models were injected with [F]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. 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 [F]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%). These findings highlight the critical influence of immune cell metabolism on [F]FDG imaging, emphasizing the need to account for immune contributions when interpreting [F]FDG imaging in cancer.
肿瘤代谢是癌症的一个标志，但肿瘤微环境中的细胞异质性带来了重大挑战，因为整体分析掩盖了各个细胞群体不同的代谢特征。这种复杂性使我们难以理解肿瘤微环境中不同细胞类型对[F]FDG的摄取情况。本研究旨在使用新技术放射流式细胞术（radioFlow），在 Kirsten 大鼠肉瘤病毒驱动的癌症小鼠模型的肺部单细胞水平上研究[F]FDG 的摄取情况。向两个 Kirsten 大鼠肉瘤病毒驱动的肺癌小鼠模型注射[F]FDG 进行小动物 PET/CT 检查以及随后对肺部进行荧光激活细胞分选。对于放射流式细胞术，然后在γ计数器中测量分选的细胞组分，并将其放射性归一化到细胞数量。两个模型的肺组织的放射流式细胞术分析在各实验中均显示出强大的细胞类型特异性摄取模式。我们的主要发现表明，[F]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%），而肿瘤细胞仅占 2.8%±1.0%，与结构细胞（CD45；肿瘤细胞，5.0%±2.3%）的摄取情况相似。归一化显示，在两个肿瘤模型中巨噬细胞均表现出最高的葡萄糖代谢（57%±8%），其次是其余免疫细胞（27%±3%）。这些发现突出了免疫细胞代谢对[F]FDG 成像的关键影响，强调在解释癌症中的[F]FDG 成像时需要考虑免疫细胞的作用。
