Diagnostic and prognostic value of CEP55 in clear cell renal cell carcinoma as determined by bioinformatics analysis

Abstract

Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant adult kidney tumor. Tumor recurrence and metastasis is the primary cause of cancer-associated mortality in patients with ccRCC. Therefore, identification of efficient diagnostic and prognostic molecular markers may improve survival times. The GSE46699, GSE36895, GSE53000 and GSE53757 gene datasets were downloaded from the Gene Expression Omnibus database and contained 196 ccRCC samples and 164 adjacent normal kidney samples. Bioinformatics analysis was used to integrate the four microarray datasets to identify and analyze differentially expressed genes. Functional analysis revealed that there were 12 genes associated with cancer, based on the tumor-associated gene database. Erb-B2 receptor tyrosine kinase 4, centrosomal protein 55 (CEP55) and vascular endothelial growth factor A are oncogenes, all of which were associated with tumor stage, whereas only CEP55 was significantly associated with survival time as determined by Gene Expression Profiling Interactive Analysis. The mRNA expression levels of CEP55 in ccRCC samples were significantly higher than those observed in adjacent normal kidney tissues based on The Cancer Genome Atlas data and reverse transcription-polymerase chain reaction results. The receiver operating characteristic curve analysis revealed that CEP55 may be considered a diagnostic biomarker for ccRCC with an area under the curve of >0.85 in the training and validation sets. High CEP55 expression was strongly associated with sex, histological grade, stage, T classification, N classification and M classification. Univariate and multivariate Cox proportional hazards analyses demonstrated that CEP55 expression was an independent risk factor for poor prognosis. In addition, gene set enrichment analysis indicated that high CEP55 expression was associated with immunization, cell adhesion, inflammation, the Janus kinase/signal transducer and activator of transcription signaling pathway and cell proliferation. In conclusion, CEP55 was increased in ccRCC samples, and may be considered a potential diagnostic and prognostic biomarker for ccRCC.

TYROBP is a potential prognostic biomarker of clear cell renal cell carcinoma

“…Because ccRCC lacks obvious early symptoms, nearly 30% of patients with ccRCC have already developed to the metastatic phase by the time of diagnosis [3]. Although early and localized ccRCC can be cured by partial or radical nephrectomy, nearly 30% of patients had postoperative recurrence and metastasis, called metastatic renal cell carcinoma [4]. In recent decades, molecular targeted therapy, represented by sorafenib, has been used in metastatic renal cell carcinoma with significant objective response rates, although the clinical outcomes are still unsatisfactory because of drug resistance and adverse effects [5].…”

Novel prognostic prediction model constructed through machine learning on the basis of methylation-driven genes in kidney renal clear cell carcinoma

“…Another level of methylation is the influence of noncoding genes on protein expression regulation. microRNAs and ncRNAs may have important roles [ 13 ]. The methylation-mediated loss of miR-34b/c can up-regulate its oncogenic target genes [ 18 , 19 ].…”

“…With the rapid development of computer technology, an increasing number of biomarkers of various tumors are identified using bioinformatics analysis, and many tumor-associated databases are established [ 13 ]. The Cancer Genome Atlas (TCGA) is a public database that includes 33 cancer types and matched clinical data [ 14 ].…”

“…The Cancer Genome Atlas (TCGA) is a public database that includes 33 cancer types and matched clinical data [ 14 ]. Studies reveal many genes, such as CEP55, ACAA1, ACADSB, ALDH6A1 , and AUH , that may serve as potential diagnostic and prognostic biomarkers for KIRC [ 13 , 15 ]. The methylation-driven gene is differentially expressed in the control and the disease groups, and the methylation status is negatively correlated with corresponding gene expression value.…”

Identification of key genes related to macrophage infiltration in gastric cancer based on WGCNA

“…Based on the section of the pathological stages, the violin diagram was generated according to the pathological stages of the cases [17].…”