E2F3/5/8 serve as potential prognostic biomarkers and new therapeutic direction for human bladder cancer.

OBJECTS: Human bladder cancer (BC) is the most common urogenital system malignancy. E2F transcription factors (E2Fs) have been reported to be involved in the growth of various cancers. However, the expression patterns, prognostic value and immune infiltration in the tumor microenvironment of the 8 E2Fs in BC have yet fully to be explored. METHODS AND STRATEGY: We investigated the differential expression of E2Fs in BC patients, the prognostic value and correlation with immune infiltration by analyzing a range of databases. RESULTS: We found that the mRNA expression levels of E2F1/2/3/4/5/7/8 were significantly higher in BC patients than that of control tissues. And the increased mRNA expression levels of all E2Fs were associated with tumor stage of BC. The survival analysis revealed that the elevated mRNA expression levels of E2F3/5/8 were significantly correlated with the overall survival (OS) of BC patients. And the genetic changes of E2Fs in BC patients were associated with shorter overall survival (OS) and progression-free survival (PFS). In addition, we revealed that the E2F3/5/8 expressions were closely correlated with tumor-infiltrating lymphocytes (TILs). CONCLUSIONS: E2F3/5/8 might serve as promising prognostic biomarkers and new therapeutic direction for BC patients.

Identification of biomarkers of clear cell renal cell carcinoma by bioinformatics analysis.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype among renal cancer, and more and more researches find that the occurrence of ccRCC is associated with genetic changes, but the molecular mechanism still remains unclear. The present study aimed to identify aggregation trend of differentially expressed genes (DEGs) in ccRCC, which would be beneficial to the treatment of ccRCC and provide research ideas using a series of bioinformatics approach. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomes (KEGG) analysis were used to get the enrichment trend of DEGs of GSE53757 and GSE16449. Draw Venn Diagram was applied for co-expression of DEGs. Cytoscape with the Retrieval of Interacting Gene (STRING) datasets and Molecular Complex Detection (MCODE) were performed protein-protein interaction (PPI) of DEGs. The Kaplan-Meier Plotter analysis of top 15 upregulated and top 15 downregulated were selected in Gene Expression Profiling Interactive Analysis (GEPIA). Then, the expression level of hub genes between normal renal tissue and different pathological stages of ccRCC tissue, which significantly correlated with overall survival in ccRCC patients, were also analyzed by Ualcan based on The Cancer Genome Atlas (TCGA) database. In this study, we got 167 co-expression DEGs, including 72 upregulated DEGs and 95 downregulated DEGs. We identified 11 hub genes had significantly correlated with overall survival in ccRCC patients. Among them, KIF23, APLN, ADCY1, GREB1, TLR4, IRF8, CXCL1, CXCL2, deserved our attention.