AUTHOR=Zhu Zhenpeng , Lei Zhenchuan , Qian Jinqin , Zhang Cuijian , Gong Yanqing , Yin Guicao , Li Yifan , Li Xuesong , Lin Jian , Zhou Liqun 

TITLE=The Ion Channel-Related Gene Signatures Correlated With Diagnosis, Prognosis, and Individualized Treatment in Patients With Clear Cell Renal Cell Carcinoma

JOURNAL=Frontiers in Pharmacology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/pharmacology/articles/10.3389/fphar.2022.889142

DOI=10.3389/fphar.2022.889142

ISSN=1663-9812

ABSTRACT=Background
Early detection and precise prognostic evaluation of clear cell renal cell carcinoma (ccRCC) are crucial for patient life expectancy. Ion channel-related genes (ICRGs) are of great diagnostic and prognostic value as components that maintain the normal structure of the kidney. Therefore, we systematically explored the diagnostic, prognostic and therapeutic value of ICRGs in ccRCC using the multi-database.
Methods
RNA transcriptome profile and clinical data of ccRCC patients which extracted and integrated from public databases including TCGA, ICGC, GEO and E-MTAB databases. Ion channel-related genes were obtained from the literature collection. The diagnostic signature was performed using the LASSO and SVM-REF analyses. Meanwhile, the prognostic signature was conducted using the LASSO analyses. Molecular subtyping was performed using the ConsensusClusterPlus and corresponding therapeutic target were evaluated using the pRRophetic package. In addition, prognostic nomogram was constructed based on the results of cox regression analyses.
Results
We successfully constructed diagnostic signature for 5 ICRGs and prognostic signature for 10 ICRGs with AUC values greater than 0.7, showing good predictive performance. Based on the risk score, we found that high-risk patients had a significantly worse prognosis. We also divided ccRCC patients into two clusters according to prognostic ICRGs, and there was significant survival outcome between the two clusters and different sensitivity to diverse clinical therapeutic strategy. Meanwhile, we constructed a nomogram based on clinical molecules and signature, and its predictive efficacy was better than signature or current TNM staging system.
Conclusion
In this study, we established useful signatures for early detection, prognosis evaluation, and individualized treatment for ccRCC. Moreover, the KCNJ16 deserves to be explored comprehensively in the furture