Department of Urology, Weifang Pepole's Hospital, Weifang, Shandong, China.
Department of Urology, Shouguang Hospital of Traditional Chinese Medicine, Shouguang, China.
Medicine (Baltimore). 2024 Feb 23;103(8):e37207. doi: 10.1097/MD.0000000000037207.
Metabolic reprogramming of energy is a newly recognized characteristic of cancer. In our current investigation, we examined the possible predictive importance of long noncoding RNAs (lncRNAs) associated to fatty acid metabolism in clear cell renal cell carcinoma (ccRCC). We conducted an analysis of the gene expression data obtained from patients diagnosed with ccRCC using the Cancer Genome Atlas (TCGA) database and the ArrayExpress database. We performed a screening to identify lncRNAs that are differentially expressed in fatty acid metabolism. Based on these findings, we developed a prognostic risk score model using these fatty acid metabolism-related lncRNAs. We then validated this model using Cox regression analysis, Kaplan-Meier survival analysis, and principal-component analysis (PCA). Furthermore, the prognostic risk score model was successfully validated using both the TCGA cohort and the E-MTAB-1980 cohort. We utilized gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) to determine the correlation between fatty acid metabolism and the PPAR signaling pathway in patients with ccRCC at various clinical stages and prognoses. We have discovered compelling evidence of the interaction between immune cells in the tumor microenvironment and tumor cells, which leads to immune evasion and resistance to drugs. This was achieved by the utilization of advanced techniques such as the CIBERSORT method, ESTIMATE R package, ssGSEA algorithm, and TIMER database exploration. Ultimately, we have established a network of competing endogenous RNA (ceRNA) that is related to fatty acid metabolism. The findings of our study suggest that medicines focused on fatty acid metabolism could be clinically significant for individuals with ccRCC. The utilization of this risk model, which is centered around the lncRNAs associated with fatty acid metabolism, could potentially provide valuable prognostic information and hold immunotherapeutic implications for patients with ccRCC.
能量代谢重编程是癌症的一个新的特征。在我们目前的研究中,我们研究了与脂肪酸代谢相关的长非编码 RNA(lncRNA)在透明细胞肾细胞癌(ccRCC)中的潜在预测重要性。我们使用癌症基因组图谱(TCGA)数据库和 ArrayExpress 数据库分析了从诊断为 ccRCC 的患者获得的基因表达数据。我们进行了筛选,以确定在脂肪酸代谢中差异表达的 lncRNA。基于这些发现,我们使用这些与脂肪酸代谢相关的 lncRNA 开发了一个预后风险评分模型。然后,我们使用 Cox 回归分析、Kaplan-Meier 生存分析和主成分分析(PCA)对该模型进行了验证。此外,该预后风险评分模型还成功地在 TCGA 队列和 E-MTAB-1980 队列中得到了验证。我们利用基因集变异分析(GSVA)和基因集富集分析(GSEA)来确定不同临床阶段和预后的 ccRCC 患者中脂肪酸代谢与 PPAR 信号通路之间的相关性。我们发现了确凿的证据,证明肿瘤微环境中的免疫细胞与肿瘤细胞之间存在相互作用,导致免疫逃逸和药物耐药。这是通过使用 CIBERSORT 方法、ESTIMATE R 包、ssGSEA 算法和 TIMER 数据库探索等先进技术实现的。最终,我们建立了一个与脂肪酸代谢相关的竞争性内源 RNA(ceRNA)网络。我们的研究结果表明,针对脂肪酸代谢的药物可能对 ccRCC 患者具有重要的临床意义。该风险模型的使用,以与脂肪酸代谢相关的 lncRNA 为中心,可能为 ccRCC 患者提供有价值的预后信息,并具有免疫治疗意义。