Han Zhijun, Wang Hao, Long Jing, Qiu Yanning, Xing Xiao-Liang
Department of Urology, Department of Ultrasonography, Zhuzhou Hospital Affiliated to Xiangya School of Medicine, Central South University, Zhuzhou, China.
Hunan Provincial Key Laboratory for Synthetic Biology of Traditional Chinese Medicine, Hunan University of Medicine, Huaihua, China.
Front Oncol. 2022 Aug 26;12:931383. doi: 10.3389/fonc.2022.931383. eCollection 2022.
Kidney cancer (KC) is one of the most challenging cancers due to its delayed diagnosis and high metastasis rate. The 5-year survival rate of KC patients is less than 11.2%. Therefore, identifying suitable biomarkers to accurately predict KC outcomes is important and urgent.
Corresponding data for KC patients were obtained from the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) databases. Systems biology/bioinformatics/computational approaches were used to identify suitable biomarkers for predicting the outcome and immune landscapes of KC patients.
We found two ferroptosis- and immune-related differentially expressed genes (FI-DEGs) ( () and ()) independently correlated with the overall survival of KC patients. The area under the curve (AUC) values of the prognosis model using these two FI-DEGs exceeded 0.60 in the training, validation, and entire groups. The AUC value of the 1-year receiver operating characteristic (ROC) curve reached 0.70 in all the groups.
Our present study indicated that and could be prognostic biomarkers for KC patients. Whether this model can be used in clinical settings requires further validation.
肾癌（KC）因其诊断延迟和高转移率而成为最具挑战性的癌症之一。KC患者的5年生存率低于11.2%。因此，识别合适的生物标志物以准确预测KC的预后至关重要且迫在眉睫。
从国际癌症基因组联盟（ICGC）和癌症基因组图谱（TCGA）数据库中获取KC患者的相应数据。采用系统生物学/生物信息学/计算方法来识别用于预测KC患者预后和免疫格局的合适生物标志物。
我们发现两个铁死亡和免疫相关的差异表达基因（FI-DEGs）（（）和（））与KC患者的总生存期独立相关。使用这两个FI-DEGs的预后模型在训练组、验证组和整个组中的曲线下面积（AUC）值均超过0.60。1年受试者工作特征（ROC）曲线的AUC值在所有组中均达到0.70。
我们目前的研究表明，和可能是KC患者的预后生物标志物。该模型是否可用于临床环境需要进一步验证。
