摘要
Abstract
Objective To analyze the expression level of troponin-associated protein(TROAP)in clear cell renal cell carcinoma(ccRCC)based on data mining,and evaluate the relationship between TROAP ex-pression and clinicopathological characteristics and prognosis.Methods UALCAN,GEPIA,LinkedOmics and other online tumor bioinformatics analysis websites were used to explore the expression information of TROAP in ccRCC tissues in TCGA database.The relationship between TROAP expression level and clinico-pathological features was analyzed on LinkedOmics and UALLCAN websites.GEPIA platform was used to analyze the relationship between TROAP expression level and patient prognosis.UALCAN and LinkedOmics were used to obtain TROAP expression-related genes,and DAVID online analysis tool was used for enrich-ment analysis.Results Compared with normal kidney tissues,the expression of TROAP gene was significant-ly increased in ccRCC tissues.The higher the tumor grade was in ccRCC patients.The TROAP expression was higher in patients with lymph node metastasis(N1)and distant metastasis(M1)than that in patients without metastasis(N0 and M0).The expression of TROAP increased with the increase of pathological stage and T stage,and the differences were statistically significant(P＜0.05).Compared with the low TROAP expression group,the overall survival rate and disease-free survival rate of patients in the high TROAP expression group were significantly decreased.A total of 891 genes related to TROAP expression were obtained,including 852 positive genes and 39 negative genes.TROAP expression related genes were enriched in cell cycle regulation,cell division,cell proliferation,Wnt signaling pathway,P53 signaling pathway,etc.Conclusion TROAP is highly expressed in ccRCC tissues,which is correlated with tumor progression and poor prognosis of patients,and has potential as a therapeutic target and prognostic marker for ccRCC.关键词
肾透明细胞癌/肌钙蛋白相关蛋白/预后/表达/数据挖掘Key words
Clear cell renal cell carcinoma/Trophinin-associated protein/Prognosis/Express/Data mining分类
临床医学
