医学
肾癌
免疫系统
肿瘤科
串扰
肾细胞癌
肾
基因
比例危险模型
急性肾损伤
内科学
计算生物学
生物信息学
癌症研究
生物
免疫学
遗传学
物理
光学
作者
Chen-Xia Juan,Ye Zhu,Yan Zhou,Wei Zhu,Xufang Wang,Wei-Ming He,Yan Chen
摘要
Kidney renal clear cell carcinoma (KIRC) has a poor prognosis and a high death rate globally. Cancer prognosis is strongly linked to immune-related genes (IRGs), according to numerous research. We utilized KIRC RNA-seq data from the TCGA database to build a prognostic model incorporating seven immune-related (IR) lncRNAs, and we constructed the model using LASSO regression. Additionally, we calculated a risk score for each patient using a prognostic model that divided patients into high-risk and low-risk groups. The ESTIMATE and CIBERSORT methodologies were then used to analyze the differences in the tumor microenvironment of the two groups of patients. Finally, we predicted three small molecule drugs that may have potential therapeutic effects for high-risk patients. We combined the acute kidney injury dataset to obtain differential genes that may serve standard biological functions with two risk groups. Our study shows that the model we constructed for IR-lncRNAs has reliable predictive efficacy for patients with KIRC.
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