Metastatic Immune-Related Genes for Affecting Prognosis and Immune Response in Renal Clear Cell Carcinoma

被引:5
作者
Sun, Si [1 ,2 ]
Mao, Weipu [1 ,3 ,4 ]
Wan, Lilin [1 ,2 ]
Pan, Kehao [1 ,2 ]
Deng, Liting [2 ]
Zhang, Lei [1 ,3 ]
Zhang, Guangyuan [1 ,3 ]
Chen, Ming [1 ,3 ,4 ]
机构
[1] Southeast Univ, Zhongda Hosp, Dept Urol, Nanjing, Peoples R China
[2] Southeast Univ, Sch Med, Nanjing, Peoples R China
[3] Southeast Univ, Inst Urol, Surg Res Ctr, Med Sch, Nanjing, Peoples R China
[4] Southeast Univ, Zhongda Hosp, Nanjing Lishui Dist Peoples Hosp, Dept Urol,Lishui Branch, Nanjing, Peoples R China
关键词
renal clear cell carcinoma; metastatic immune-related genes; prognosis; immunotherapy; biomarkers; PROTEIN-KINASE-C; CANCER-CELLS; IN-VITRO; GROWTH; MICROENVIRONMENT; TRANSDUCTION; BIOLOGY; MEDIATE; MODEL; GAMMA;
D O I
10.3389/fmolb.2021.794326
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Background: In renal clear cell carcinoma, a common cancer of the urinary system, 25-30% patients are metastatic at initial diagnosis and 20-30% patients have a tendency of recurrence and metastasis after local surgery. With the rapid development of tumor immunology, immune agents have brought new directions to tumor therapy. However, no relevant studies have explored the role of immune-related genes in kidney cancer metastasis.Methods: Co-expressed metastatic immune-related differentially expressed genes (mIR-DEGs) were screened by GSE12606, GSE47352, and immunorelated genes. Then, differential expression analysis, prognostic analysis, and univariate and multivariate Cox regression analysis in KIRC were performed to determine independent prognostic factors associated, and the risk prognostic model was established. The correlation of hub mIR-DEGs with clinicopathological factors, immune invasion, and immune checkpoints was analyzed, and the expression of hub mIR-DEGs and their effect on tumor were re-evaluated by OCLR scores in KIRC.Results: By comprehensive bioassay, we found that FGF17, PRKCG, SSTR1, and SCTR were mIR-DEGs with independent prognostic values, which were significantly associated with clinicopathological factors and immune checkpoint-related genes. The risk prognostics model built on this basis had good predictive potential. In addition, targeted small molecule drugs, including calmidazolium and sulfasalazine, were predicted for mIR-DEGs. Further experimental results were consistent with the bioinformatics analysis.Conclusion: This study preliminarily confirmed that FGF17, PRKCG, SSTR1, and SCTR were targeted genes affecting renal cancer metastasis and related immune responses and can be used as potential therapeutic targets and prognostic biomarkers for renal cancer. Preliminary validation found that PRKCG and SSTR1 were consistent with predictions.
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页数:16
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