Department of Urology, The Affiliated Suqian First People's Hospital of Nanjing Medical University, Suqian, China.
Department of Urology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
J Healthc Eng. 2022 Dec 21;2022:1147545. doi: 10.1155/2022/1147545. eCollection 2022.
Tumor cells with a hybrid metabolic state, in which glycolysis and oxidative phosphorylation (OXPHOS) can be used, usually have a strong ability to adapt to different stress environments due to their metabolic plasticity. However, few studies on tumor cells with this phenotype have been conducted in the field of renal cell carcinoma (RCC).
The metabolic pathway (glycolysis, OXPHOS) related gene sets were obtained from the Molecular Signatures Database (V7.5.1). The gene expression matrix, clinical information, and mutation data were obtained by Perl programming language (5.32.0) mining, the Cancer Genome Atlas and International Cancer Genome Consortium database. Gene Set Enrichment Analysis (GSEA) software (4.0.3) was utilised to analyse glycolysis-related gene sets. Analysis of survival, immune infiltration, mutation, etc. was performed using the R programming language (4.1.0).
Eight genes that are highly associated with glycolysis and OXHPOS were used to construct the cox proportional hazards model, and risk scores were calculated based on this to predict the prognosis of clear cell RCC patients and to classify patients into risk groups. Gene Ontology, the Kyoto Encyclopaedia of Genes and Genomes, and GSEA were analysed according to the differential genes to investigate the signal pathways related to the hybrid metabolic state. Immunoinfiltration analysis revealed that CD8+T cells, M2 macrophages, etc., had significant differences in infiltration. In addition, the analysis of mutation data showed significant differences in the number of mutations of PBRM1, SETD2, and BAP1 between groups. Cell experiments demonstrated that the DLD gene expression was abnormally high in various tumor cells and is associated with the strong migration ability of RCC.
We successfully constructed a risk score system based on glycolysis and OXPHOS-related genes to predict the prognosis of RCC patients. Bioinformatics analysis and cell experiments also revealed the effect of the hybrid metabolic activity on the migration ability and immune activity of RCC and the possible therapeutic targets for patients.
具有混合代谢状态的肿瘤细胞，即可以利用糖酵解和氧化磷酸化（OXPHOS），由于其代谢可塑性，通常具有很强的适应不同应激环境的能力。然而，在肾细胞癌（RCC）领域，对具有这种表型的肿瘤细胞的研究很少。
从分子特征数据库（V7.5.1）获得代谢途径（糖酵解、OXPHOS）相关基因集。通过 Perl 编程语言（5.32.0）挖掘、癌症基因组图谱和国际癌症基因组联合会数据库，获得基因表达矩阵、临床信息和突变数据。使用基因集富集分析（GSEA）软件（4.0.3）分析糖酵解相关基因集。使用 R 编程语言（4.1.0）进行生存、免疫浸润、突变等分析。
使用与糖酵解和 OXHPOS 高度相关的 8 个基因构建 cox 比例风险模型，并根据该模型计算风险评分，以预测透明细胞 RCC 患者的预后，并将患者分为风险组。根据差异基因进行基因本体论、京都基因与基因组百科全书和 GSEA 分析，以研究与混合代谢状态相关的信号通路。免疫浸润分析显示，CD8+T 细胞、M2 巨噬细胞等浸润存在显著差异。此外，突变数据分析表明，PBRM1、SETD2 和 BAP1 基因的突变数量在组间存在显著差异。细胞实验表明，在各种肿瘤细胞中，DLD 基因表达异常升高，与 RCC 的强迁移能力有关。
我们成功构建了一个基于糖酵解和 OXPHOS 相关基因的风险评分系统，以预测 RCC 患者的预后。生物信息学分析和细胞实验还揭示了混合代谢活性对 RCC 迁移能力和免疫活性的影响，以及可能的患者治疗靶点。
