Department of Oncology, University of Oxford, Oxford, OX3 7DQ, UK.
Doctoral Training Centre, University of Oxford, Keble Road, Oxford, OX1 3NP, UK.
Breast Cancer Res. 2022 May 17;24(1):34. doi: 10.1186/s13058-022-01529-9.
PET imaging of 18F-fluorodeoxygucose (FDG) is used widely for tumour staging and assessment of treatment response, but the biology associated with FDG uptake is still not fully elucidated. We therefore carried out gene set enrichment analyses (GSEA) of RNA sequencing data to find KEGG pathways associated with FDG uptake in primary breast cancers.
Pre-treatment data were analysed from a window-of-opportunity study in which 30 patients underwent static and dynamic FDG-PET and tumour biopsy. Kinetic models were fitted to dynamic images, and GSEA was performed for enrichment scores reflecting Pearson and Spearman coefficients of correlations between gene expression and imaging.
A total of 38 pathways were associated with kinetic model flux-constants or static measures of FDG uptake, all positively. The associated pathways included glycolysis/gluconeogenesis ('GLYC-GLUC') which mediates FDG uptake and was associated with model flux-constants but not with static uptake measures, and 28 pathways related to immune-response or inflammation. More pathways, 32, were associated with the flux-constant K of the simple Patlak model than with any other imaging index. Numbers of pathways categorised as being associated with individual micro-parameters of the kinetic models were substantially fewer than numbers associated with flux-constants, and lay around levels expected by chance.
In pre-treatment images GLYC-GLUC was associated with FDG kinetic flux-constants including Patlak K, but not with static uptake measures. Immune-related pathways were associated with flux-constants and static uptake. Patlak K was associated with more pathways than were the flux-constants of more complex kinetic models. On the basis of these results Patlak analysis of dynamic FDG-PET scans is advantageous, compared to other kinetic analyses or static imaging, in studies seeking to infer tumour-to-tumour differences in biology from differences in imaging. Trial registration NCT01266486, December 24th 2010.
正电子发射断层扫描（PET）成像 18F-氟脱氧葡萄糖（FDG）被广泛用于肿瘤分期和治疗反应评估，但与 FDG 摄取相关的生物学仍未完全阐明。因此，我们对原发性乳腺癌的 RNA 测序数据进行了基因集富集分析（GSEA），以寻找与 FDG 摄取相关的 KEGG 途径。
从一项机会性窗口研究中分析了预处理数据，该研究中 30 名患者接受了静态和动态 FDG-PET 以及肿瘤活检。对动态图像进行了动力学模型拟合，并对反映基因表达与成像之间皮尔逊和斯皮尔曼相关系数的富集分数进行了 GSEA。
共有 38 条途径与动力学模型通量常数或 FDG 摄取的静态测量值相关，均呈正相关。相关途径包括糖酵解/糖异生（“GLYC-GLUC”），介导 FDG 摄取，与模型通量常数相关，但与静态摄取测量值无关，以及 28 条与免疫反应或炎症相关的途径。更多的途径（32 条）与简单 Patlak 模型的通量常数 K 相关，而与其他任何成像指标相关的途径较少。与动力学模型的单个微参数相关的途径数量明显少于与通量常数相关的途径数量，并且处于预期的随机水平。
在预处理图像中，GLYC-GLUC 与 FDG 动力学通量常数相关，包括 Patlak K，但与静态摄取测量值无关。与通量常数相关的免疫相关途径与静态摄取相关。Patlak K 与更多途径相关，而与更复杂的动力学模型的通量常数相关的途径较少。基于这些结果，与其他动力学分析或静态成像相比，动态 FDG-PET 扫描的 Patlak 分析在从成像差异推断肿瘤间生物学差异的研究中具有优势。试验注册号 NCT01266486，2010 年 12 月 24 日。
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