Abstract
BackgroundClear cell renal cell carcinoma (ccRCC) has been the commonest renal cell carcinoma (RCC). Although the disease classification, diagnosis and targeted therapy of RCC has been increasingly evolving attributing to the rapid development of current molecular pathology, the current clinical treatment situation is still challenging considering the comprehensive and progressively developing nature of malignant cancer. The study is to identify more potential responsible genes during the development of ccRCC using bioinformatic analysis, thus aiding more precise interpretation of the diseaseMethodsFirstly, different cDNA expression profiles from Gene Expression Omnibus (GEO) online database were used to screen the abnormal differently expressed genes (DEGs) between ccRCC and normal renal tissues. Then, based on the protein–protein interaction network (PPI) of all DEGs, the module analysis was performed to scale down the potential genes, and further survival analysis assisted our proceeding to the next step for selecting a credible key gene. Thirdly, immunohistochemistry (IHC) and quantitative real-time PCR (QPCR) were conducted to validate the expression change of the key gene in ccRCC comparing to normal tissues, meanwhile the prognostic value was verified using TCGA clinical data. Lastly, the potential biological function of the gene and signaling mechanism of gene regulating ccRCC development was preliminary explored.ResultsFour cDNA expression profiles were picked from GEO database based on the number of containing sample cases, and a total of 192 DEGs, including 39 up-regulated and 153 down-regulated genes were shared in four profiles. Based on the DEGs PPI network, four function modules were identified highlighting a FGF1 gene involving PI3K-AKT signaling pathway which was shared in 3/4 modules. Further, both the IHC performed with ccRCC tissue microarray which contained 104 local samples and QPCR conducted using 30 different samples confirmed that FGF1 was aberrant lost in ccRCC. And Kaplan–Meier overall survival analysis revealed that FGF1 gene loss was related to worse ccRCC patients survival. Lastly, the pathological clinical features of FGF1 gene and the probable biological functions and signaling pathways it involved were analyzed using TCGA clinical data.ConclusionsUsing bioinformatic analysis, we revealed that FGF1 expression was aberrant lost in ccRCC which statistical significantly correlated with patients overall survival, and the gene’s clinical features and potential biological functions were also explored. However, more detailed experiments and clinical trials are needed to support its potential drug-target role in clinical medical use.
Highlights
Clear cell renal cell carcinoma has been the commonest renal cell carcinoma (RCC)
Venn diagram [22] was used to identify the differently expressed genes (DEGs) that were shared in all four cDNA profiles followed by the shared DEGs’ basic interpretation including their main biological processes, molecular functions and the signaling pathways they mainly enriched in using Gene ontology analysis (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) software [23]
Identification of 192 DEGs in Clear cell renal cell carcinoma (ccRCC) comparing to normal renal tissues Four cDNA expression profiles from Gene Expression Omnibus (GEO) database were used to screen the DEGs in ccRCC vs. normal a
Summary
Clear cell renal cell carcinoma (ccRCC) has been the commonest renal cell carcinoma (RCC). Diagnosis and targeted therapy of RCC has been increasingly evolving attributing to the rapid development of current molecular pathology, the current clinical treatment situation is still challenging considering the comprehensive and progressively developing nature of malignant cancer. Attributing to the rapid development of molecular pathology, the classification and diagnosis of renal cell carcinoma have been increasingly evolving [2, 3]. In ccRCC, the most classic molecular genetic characteristics are the changes of related genes on the short arm of chromosome 3 (3p), especially the VHL gene. The “first hit” of cancer usually comes from the change of VHL gene (gene mutation or promoter methylation), followed by "second hit"—3p chromosome deletion, which leads to tumor occurrence, and the 3p variation occurs in nearly 90% of ccRCC cases [5]. Besides the VHL gene, some other 3p gene variations have been reported in ccRCC, for instance SETD2 [6] and BAP1 [7], whose mutation have been reported to be related with worse patients prognosis, as well as PBRM1 [8], which was associated with better patients survival
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