Wei Zhihao, Cheng Gong, Ye Yuzhong, Le Changjie, Miao Qi, Chen Jiawei, Yang Hongmei, Zhang Xiaoping
Department of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Institute of Urology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Front Genet. 2022 Jul 8;13:894736. doi: 10.3389/fgene.2022.894736. eCollection 2022.
Renal cell carcinoma is one of the most common tumors in the urinary system, among which clear cell renal cell carcinoma is the most common subtype with poor prognosis. As one of the tumors closely related to lipid metabolism, the role of fatty acid metabolism in ccRCC was investigated to predict the prognosis and guide treatment strategies. RNA-seq and clinical information of patients with ccRCC and expression microarray of human renal cell carcinoma cell lines were obtained from TCGA and GEO databases. Fatty acid metabolism-related risk signature was established by the univariate Cox regression and LASSO analysis to predict patient prognosis and response to different treatment modalities. Using the fatty acid metabolism risk signature, the risk score for each sample in the TCGA cohort was calculated and divided into high-risk and low-risk groups, with the cutoff point being the median. Patients with higher risk scores had a poorer prognosis than those with lower risk scores. The response of each sample to immunotherapy was predicted from the "TIDE" algorithm, while the sensitivity of each sample to sunitinib was obtained using the "pRRophetic" R package. Patients with lower risk scores had higher expression of PD-L1 and better efficacy for sunitinib than those in the high-risk group and were less likely to develop drug resistance, while patients with high-risk scores had a strong response to the anti-CTLA4 antibody therapy. A nomogram was constructed by independent prognostic factors to predict the 1-, 3-, and 5-year survival. According to the calibration curves, the nomogram had an excellent ability to predict survival for patients with ccRCC. Therefore, the fatty acid metabolism risk signature we established can not only predict the survival of patients with ccRCC but also predict patient response to targeted therapy and immunotherapy to provide optimal treatment strategies for patients.
肾细胞癌是泌尿系统最常见的肿瘤之一，其中透明细胞肾细胞癌是最常见的亚型，预后较差。作为与脂质代谢密切相关的肿瘤之一，研究了脂肪酸代谢在透明细胞肾细胞癌中的作用，以预测预后并指导治疗策略。从TCGA和GEO数据库中获取了透明细胞肾细胞癌患者的RNA测序和临床信息以及人肾癌细胞系的表达微阵列。通过单因素Cox回归和LASSO分析建立脂肪酸代谢相关风险特征，以预测患者预后和对不同治疗方式的反应。使用脂肪酸代谢风险特征，计算了TCGA队列中每个样本的风险评分，并分为高风险和低风险组，分界点为中位数。风险评分较高的患者预后比风险评分较低的患者差。根据“TIDE”算法预测每个样本对免疫治疗的反应，同时使用“pRRophetic”R包获得每个样本对舒尼替尼的敏感性。风险评分较低的患者比高风险组患者的PD-L1表达更高，对舒尼替尼的疗效更好，且发生耐药的可能性更小，而高风险评分的患者对抗CTLA4抗体治疗反应强烈。通过独立预后因素构建列线图以预测1年、3年和5年生存率。根据校准曲线，列线图对透明细胞肾细胞癌患者的生存具有出色的预测能力。因此，我们建立的脂肪酸代谢风险特征不仅可以预测透明细胞肾细胞癌患者的生存，还可以预测患者对靶向治疗和免疫治疗的反应，为患者提供最佳治疗策略。
