The importance of ¹⁸F-FDG PET in imaging head and neck squamous cell carcinoma (HNSCC) has grown in recent decades. Because PET has prognostic values, and provides functional and molecular information in HNSCC, the genetic and biologic backgrounds associated with PET parameters are of great interest. Here, as a systems biology approach, we aimed to investigate gene networks associated with tumor metabolism and their biologic function using RNA sequence and ¹⁸F-FDG PET data. Methods: Using RNA sequence data of HNSCC downloaded from The Cancer Genome Atlas data portal, we constructed a gene coexpression network. PET parameters including lesion–to–blood-pool ratio, metabolic tumor volume, and tumor lesion glycolysis were calculated. The Pearson correlation test was performed between module eigengene—the first principal component of modules’ expression profile—and the PET parameters. The significantly correlated module was functionally annotated with gene ontology terms, and its hub genes were identified. Survival analysis of the significantly correlated module was performed. Results: We identified 9 coexpression network modules from the preprocessed RNA sequence data. A network module was significantly correlated with total lesion glycolysis as well as maximum and mean ¹⁸F-FDG uptake. The expression profiles of hub genes of the network were inversely correlated with ¹⁸F-FDG uptake. The significantly annotated gene ontology terms of the module were associated with immune cell activation and aggregation. The module demonstrated significant association with overall survival, and the group with higher module eigengene showed better survival than the other groups with statistical significance (P = 0.022). Conclusion: We showed that a gene network that accounts for immune cell microenvironment was associated with ¹⁸F-FDG uptake as well as prognosis in HNSCC. Our result supports the idea that competition for glucose between cancer cell and immune cell plays an important role in cancer progression associated with hypermetabolic features. In the future, PET parameters could be used as a surrogate marker of HNSCC for estimating molecular status of immune cell microenvironment.

近几十年来，¹⁸ F-FDG PET在头颈鳞状细胞癌（HNSCC）成像中的重要性日益提高。因为PET具有预后价值，并且在HNSCC中提供功能和分子信息，所以与PET参数相关的遗传和生物学背景引起了人们极大的兴趣。在这里，作为一种系统生物学方法，我们旨在使用RNA序列和¹⁸ F-FDG PET数据研究与肿瘤代谢相关的基因网络及其生物学功能。方法：使用从The Cancer Genome Atlas数据门户网站下载的HNSCC的RNA序列数据，我们构建了一个基因共表达网络。计算PET参数，包括病灶与血池的比率，代谢肿瘤的体积和肿瘤病灶的糖酵解。在模块本征基因（模块表达谱的第一个主要组成部分）与PET参数之间进行了Pearson相关性测试。显着相关的模块在功能上用基因本体术语进行了注释，并确定了其中心基因。进行了显着相关模块的生存分析。结果：我们从预处理的RNA序列数据中识别出9个共表达网络模块。网络模块与总病变糖酵解以及最大和均值¹⁸显着相关F-FDG吸收。网络中枢基因的表达谱与¹⁸ F-FDG摄取呈负相关。该模块的显着注释的基因本体术语与免疫细胞的激活和聚集有关。该模块显示出与总体存活率显着相关，模块特征基因较高的组显示出比其他具有统计学意义的组更好的存活率（P = 0.022）。结论：我们发现一个解释免疫细胞微环境的基因网络与¹⁸HNSCC中F-FDG的摄取和预后。我们的结果支持这样的想法，即癌细胞与免疫细胞之间的葡萄糖竞争在与代谢异常有关的癌症进展中起着重要作用。将来，PET参数可以用作HNSCC的替代标记，以估计免疫细胞微环境的分子状态。