No abstract

Early detection and accurate evaluation were both critical to improving the prognosis of clear cell Renal Cell Carcinoma (ccRCC) patients. More importantly, RNA Binding Proteins (RBPs) play a vital role in the tumorigenesis and progression of numerous cancers. However, the relationship between RBPs and ccRCC is still unclear. Exploring the potential biological functions of RBPs in ccRCC and establishing a prognostic signature to predict the survival probability remains meaningful. In this study, transcriptome profiling and the corresponding clinical information were obtained from the TCGA database, GEO database, and ICGC database. By using the "edgeR" R package, 200 DERBPs were found, including 128 up-regulated and 72 down-regulated RBPs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that DERBPs were mainly involved in regulating transcriptional processes and metabolism. Furthermore, there were 4 hub genes (RPS2, RPS14, RPS20, and RPLP0) were found in the PPI network, which may play vital biological roles among those DERBPs. Then we used LASSO regression to construct a prognostic signature and validated the signature in the GEO and ICGC cohort. The time-dependent receiver operating characteristic (ROC) curve showed that the signature could accurately predict the prognosis of ccRCC patients. Then we established a nomogram, and the calibration curve and ROC curve showed that the nomogram could accurately predict 1-year, 3-year, and 5-year overall survival (OS) of ccRCC patients (The AUC value: 0.871, 0.829, and 0.816). In conclusion, we constructed a 10-RBPs-based prognostic signature integrating clinical parameters to predict the prognosis of ccRCC patients. The prognostic signature based on the differentially expressed RBPs (DERBPs) might serve as promising diagnostic and prognostic biomarkers in ccRCC.

Purpose: Clear cell renal cell carcinoma (ccRCC) is among the most common malignant tumors worldwide, with a high incidence rate and poor prognosis. Currently, there are no biomarkers that can accurately guide prognostic evaluation and therapeutic strategy for ccRCC. The prognostic value and potential biological function of claudin-8 (CLDN8), a critical component of tight junctions in ccRCC, remain unclear. Methods: Sequencing data were obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, and Gene Expression Omnibus databases. R packages were used to explore CLDN8 mRNA expression levels and analyze differentially expressed genes. Results were validated in clinical specimens and cell lines, and bioinformatics analyses were conducted to explore the potential biological functions of CLDN8. Finally, functional analyses were carried out using 786-O ccRCC cell line. Results: Both CLDN8 mRNA and protein expression levels were significantly lower in ccRCC compared with the normal control tissues. Kaplan-Meier analyses showed that low CLDN8 expression levels were associated with the poor overall survival, while univariate and multivariate Cox regression indicated that CLDN8 could serve as an independent prognostic factor in patient with ccRCC. Bioinformatic and Western blot analyses showed that CLDN8 suppressed proliferation, migration, and invasion of 786-O ccRCC cells through the epithelial-mesenchymal transition and AKT pathways. Conclusion: CLDN8 could serve as an independent prognostic factor in ccRCC, in which it suppresses 786-O proliferation, migration, and invasion through EMT and AKT pathways.

Clear cell renal cell carcinoma (ccRCC) is one of the most common types of malignant tumors and early detection contributes to a better prognosis. Finding new biomarkers for the diagnosis or treatment remains meaningful. DEF6 guanine nucleotide exchange factor (DEF6) is upregulated in ccRCC compared to normal controls, but the relationship between DEF6 expression and prognosis in ccRCC is unclear. Moreover, the potential biological functions of DEF6 in ccRCC remains unclear. In the present study, the Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), TISIDB and the clinical database of the Peking University First Hospital were used to analyze DEF6 expression in ccRCC. Immunohistochemistry (IHC), western blotting and reverse transcription-quantitative PCR were used to examine the DEF6 protein and mRNA expression levels in cell lines and clinical samples. Subsequently, the Kaplan-Meier method and Cox regression analyses were used to determine the impact of DEF6 expression on the overall survival of patients alongside other clinical variables in both the TCGA database and the present clinical database. The results showed that both DEF6 mRNA and protein expression levels were upregulated in ccRCC compared to normal controls. The Kaplan-Meier survival analysis showed that patients with high DEF6 expression had poor prognoses from both the TCGA database and the present clinical database. Univariate survival analysis and multivariate survival analysis revealed that DEF6 could be an independent prognostic factor for ccRCC. Additionally, bioinformatics analysis indicated that differentially expressed genes related to DEF6 expression influenced ccRCC by regulating the tumor immune microenvironment. In conclusion, overexpression of DEF6 is significantly correlated with a poor prognosis for patients with ccRCC and DEF6 may influence the biological processes involved with ccRCC by regulating the immune microenvironment.