Department of General Surgery, Shengli Clinical Medical College, Fujian Provincial Hospital, Fuzhou, China.
Shengli Clinical Medical College, Fujian Medical University, Fuzhou, China.
Front Immunol. 2022 Sep 8;13:991656. doi: 10.3389/fimmu.2022.991656. eCollection 2022.
Glucose metabolism-related genes play an important role in the development and immunotherapy of many tumours, but their role in thyroid cancer is ambiguous. To investigate the role of glucose metabolism-related genes in the development of papillary thyroid cancer (PTC) and their correlation with the clinical outcome of PTC, we collected transcriptomic data from 501 PTC patients in the Cancer Genome Atlas (TCGA). We performed nonnegative matrix decomposition clustering of 2752 glucose metabolism-related genes from transcriptome data and classified PTC patients into three subgroups (C1 for high activation of glucose metabolism, C2 for low activation of glucose metabolism and C3 for moderate activation of glucose metabolism) based on the activation of different glucose metabolism-related genes in 10 glucose metabolism-related pathways. We found a positive correlation between the activation level of glucose metabolism and the tumour mutation burden (TMB), neoantigen number, mRNA stemness index (mRNAsi), age, and tumour stage in PTC patients. Next, we constructed a prognostic prediction model for PTC using six glucose metabolism-related genes (PGBD5, TPO, IGFBPL1, TMEM171, SOD3, TDRD9) and constructed a nomogram based on the risk score and clinical parameters of PTC patients. Both the prognostic risk prediction model and nomogram had high stability and accuracy for predicting the progression-free interval (PFI) in PTC patients. Patients were then divided into high-risk and low-risk groups by risk score. The high-risk group was sensitive to paclitaxel and anti-PD-1 treatment, and the low-risk group was sensitive to sorafenib treatment. We found that the high-risk group was enriched in inflammatory response pathways and associated with high level of immune cell infiltration. To verify the accuracy of the prognostic prediction model, we knocked down PGBD5 in PTC cells and found that the proliferation ability of PTC cells was significantly reduced. This suggests that PGBD5 may be a relatively important oncogene in PTC. Our study constructed a prognostic prediction model and classification of PTC by glucose metabolism-related genes, which provides a new perspective on the role of glucose metabolism in the development and immune microenvironment of PTC and in guiding chemotherapy, targeted therapy and immune checkpoint blockade therapy of PTC.
葡萄糖代谢相关基因在许多肿瘤的发生和免疫治疗中发挥着重要作用,但它们在甲状腺癌中的作用尚不清楚。为了研究葡萄糖代谢相关基因在甲状腺癌(PTC)发生发展中的作用及其与 PTC 临床结局的相关性,我们从癌症基因组图谱(TCGA)中收集了 501 例 PTC 患者的转录组数据。我们对转录组数据中的 2752 个葡萄糖代谢相关基因进行非负矩阵分解聚类,并根据 10 个葡萄糖代谢相关途径中不同葡萄糖代谢相关基因的激活情况,将 PTC 患者分为三个亚组(C1 为葡萄糖代谢高激活,C2 为葡萄糖代谢低激活,C3 为葡萄糖代谢中激活)。我们发现 PTC 患者葡萄糖代谢激活水平与肿瘤突变负担(TMB)、新抗原数量、mRNA 干性指数(mRNAsi)、年龄和肿瘤分期呈正相关。接下来,我们使用 6 个葡萄糖代谢相关基因(PGBD5、TPO、IGFBPL1、TMEM171、SOD3、TDRD9)构建了 PTC 预后预测模型,并基于 PTC 患者的风险评分和临床参数构建了列线图。该预后风险预测模型和列线图对预测 PTC 患者无进展生存期(PFI)均具有较高的稳定性和准确性。然后,根据风险评分将患者分为高危和低危组。高危组对紫杉醇和抗 PD-1 治疗敏感,低危组对索拉非尼治疗敏感。我们发现高危组富集在炎症反应途径中,与高水平的免疫细胞浸润相关。为了验证预后预测模型的准确性,我们在 PTC 细胞中敲低 PGBD5,发现 PTC 细胞的增殖能力显著降低。这表明 PGBD5 可能是 PTC 中相对重要的癌基因。我们的研究通过葡萄糖代谢相关基因构建了 PTC 的预后预测模型和分类,为葡萄糖代谢在 PTC 发生发展和免疫微环境中的作用以及指导 PTC 的化疗、靶向治疗和免疫检查点阻断治疗提供了新的视角。