Affiliation:
1. Department of Anesthesiology Second Affiliated Hospital of Shantou University Medical College Shantou People's Republic of China
2. Department of Urology Second Affiliated Hospital of Shantou University Medical College Shantou People's Republic of China
3. State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer Sun Yat‐sen University Cancer Center Guangzhou People's Republic of China
4. Department of Urology Sun Yat‐sen University Cancer Center Guangzhou People's Republic of China
5. Department of Clinical Laboratory Medicine Second Affiliated Hospital of Shantou University Medical College Shantou People's Republic of China
Abstract
AbstractBackgroundThe effect of pain genes (NAV1, EHMT2, SP1, SLC6A4, COMT, OPRM1, OPRD1, CYP2D6, and CYP3A4) have not been reported previously in kidney renal clear cell carcinoma (KIRC) patients and thus we made a comprehensive analysis of pain genes in the prognosis of KIRC and tumor immunotherapy.MethodsIn this study, TCGA, Kaplan–Meier plotter, Metascape, STRING, Human Protein Atlas, Single Cell Expression Atlas database, LinkedOmics, cBioPortal, MethSurv, CancerSEA, COSMIC database and R package (ggplot2, version 3.3.3) were used for comprehensive analysis of pain genes in KIRC. Pearson and Spearman correlation coefficients were for co‐expression analysis. Immunotherapy and TISIDB database were used for tumor Immunotherapy.ResultsRepresentative pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4) were statistically significant (p < 0.0001) in the prognosis of KIRC. Immunotherapy (anti‐PD‐1 therapy, anti‐PD‐L1 therapy, and anti‐CTLA4 therapy) and immunomodulator (immunoinhibitor, immunostimulator, and MHC molecule) in KIRC were significant associated with pain genes (SP1, SLC6A4, COMT, OPRD1, CYP2D6, and CYP3A4), which were the important addition to clinical decision making for patients.ConclusionsOur study uncovered a mechanism for the effect of pain genes on KIRC outcome via the modulation of associated co‐expression gene networks, gene variation, and tumor Immunotherapy.