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.
Journal of oncology. 2022 Feb 08*** epublish ***
Chenxia Juan, Ye Zhu, Yan Zhou, Weiwei Zhu, Xufang Wang, Weiming He, Yan Chen
Department of Nephrology, Jiangsu Province Hospital of Chinese Medicine, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, China., Department of Nephrology, Second Affiliated Hospital of Soochow University, Suzhou, Jiangsu, China., Department of Nephrology, Jiangsu Province Geriatric Hospital, Jiangsu Province Official Hospital, Nanjing, Jiangsu, China.