Background: Increasing evidence indicated that the aberrant expression of the cytoplasmic FMR1-interacting protein (CYFIP) family might possess critical role and potential functions in cancer. But the role of CYFIP2 in clear cell renal cell carcinoma (ccRCC) is still uncharacteristic. Methods: We investigated the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) database for the expression profile, clinicopathological variables, clinical prognosis information, and promoter methylation levels of CYFIPs in ccRCC. The aberrant CYFIP2 protein expression was validated by the Human Protein Atlas (HPA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to uncover CYFIP2 mRNA levels in 28 pairs of ccRCC cancer tissues. Kaplan-Meier analysis, univariate and multivariate Cox proportional hazard regression were performed to assess CYFIPs' prognosis value. Gene set enrichment analysis (GSEA) was used to determined hallmark functions, gene ontology of CYFIP2. TIMER database was utilized to assess the correlation with immune infiltration in ccRCC. Results: Results showed CYFIP2 was downregulated in ccRCC, relative to paired normal tissues in TCGA-KIRC database and 28 pairs of clinical samples (P < 0.0001). Similarly, a decreased CYFIP2 protein expression was confirmed by ccRCC tissues. The results showed CYFIP2 was negatively regulated by promoter DNA methylation. Survival analysis results showed CYFIP2 could be an independent biomarker for ccRCC and its reduction predicted a poor overall survival (OS) and disease-free survival (DFS). GSEA showed CYFIP2 was involved in metabolic pathways and epithelial-mesenchymal transition (EMT). Immune infiltration analysis revealed that a list of immune markers was significantly correlated with CYFIP2 expression especially with CD4+ cells and CD8+ cells in ccRCC. Conclusion:These results show that CYFIP2 was downregulated in ccRCC patients and predicted an unfavorable prognosis. CYFIP2 might be a potential novel prognostic molecule, and related to immune infiltration, the metabolism, as well as EMT process in ccRCC. CYFIP2 could act as tumor suppressor gene in ccRCC and positive modulation of CYFIP2 might lead to development of a novel strategy for ccRCC treatment.

Background: Studies report that conventional treatment of clear cell renal cell carcinoma (ccRCC) is effective, but several advanced patients present with poor prognosis. The current study explored potential new tumor markers and therapeutic targets in advanced ccRCC. Methods: Biomarker gene expression of ccRCC was retrieved from GEO database and the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) database. Gene ontology (GO) analysis and protein-protein interaction (PPI) networks of biomarker genes were constructed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tool. Kaplan-Meier analysis and receiver operating characteristic curve (ROC) analysis were performed to explore the prognostic and diagnostic roles of these genes. Gene set enrichment analysis (GSEA) analysis was used to determine hallmark functions of the biomarker genes. qRT-PCR was used to verify the reliability of the analysis results in tumor tissues. Results: A total of 21 upregulated genes were identified between advanced ccRCC and early ccRCC (grade III+IV vs grade I+II). Gene ontology analysis showed that the 21 upregulated genes were mainly implicated in biological processes including metabolic and lipid transport. The findings showed that 7 out of the 21 genes were significantly upregulated in 72-paired samples retrieved from the TCGA-KIRC. High expression of 5 genes indicated a poor prognosis of overall survival and disease-free survival in KIRC. Three genes effectively distinguished renal cancer tissue and adjacent renal tissues in a total of 533 ccRCC samples. GSEA showed that the 3 biomarkers were significantly enriched in epithelial-mesenchymal transition, G2M checkpoint, and angiogenesis. The results of qRT-PCR showed that STEAP3, IBSP, and AQP9 had a significant identification effect in ccRCC. Conclusion:The findings showed that 3 biomarkers were significantly upregulated in advanced ccRCC and could be used for diagnosis, prediction, and potential novel therapeutic targets for progression of ccRCC.

Prostate cancer (PCa), characterized by high invasion, metastasis, and recurrence, is the most prevalent malignant tumor in men worldwide. A clear understanding of the underlying molecular mechanisms and their role during PCa tumorigenesis can help develop prognostic and targeted therapies. We analyzed datasets from public databases, including the Cancer Genome Atlas (TCGA) and Oncomine and Gene Expression Profiling Interactive Analysis for differential expression of solute carrier family 16 member 5 (SLC16A5). We further investigated its relationship with clinical stage, pathological grade, and prognosis of PCa. The promoter methylation level of SLC16A5 in PCa was also investigated by UALCAN. We also utilized datasets from UCSC Xena to explore the prognostic role of SLC16A5 methylation levels and CpG site. Correlations between SLC16A5 and immune infiltration were discovered through TIMER. We observed significantly lower levels of SLC16A5 mRNA in PCa relative to normal tissues across six datasets from Oncomine database (p < .001) and 498 cases from TCGA database (p < .0001). SLC16A5 is strongly negatively regulated by its DNA methylation, with a Spearman of À0.81 and Pearson of À0.80 (p < .001). The aberrant SLC16A5 expression resulted in a significant relationship with clinical stage, pathological grade, and lower SLC16A5 mRNA expression, and its hypermethylation was related to a poorer PCa prognosis. SLC16A5 acted as an important factor for PCa diagnosis, with an AUC of 0.9038 (95% CI: 0.8597-0.9479; p < .0001). Besides, the aberrant SLC16A5 expression revealed close correlations with multiple immune cells. Overall, these results indicate that decreased SLC16A5 expression might be a potential biomarker for determining prognosis and immune infiltration in PCa. The positive SLC16A5 modulation might be a promising therapeutic target for PCa.

Background Invasion and metastasis led to poor prognosis and death of clear cell renal cell carcinoma (ccRCC) patients. The deoxynucleotidyl transferase terminal interacting protein 1 (DNTTIP1) was reported to promote multiple tumor progression. However, there is no research about DNTTIP1 in ccRCC. Methods Kaplan–Meier survival analysis, multivariate analysis demonstrated the prognostic indicator in overall survival (OS) and disease-free survival (DFS) of ccRCC with DNTTIP1 expression in the Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC). Receiver operator characteristic (ROC) curve analyzed diagnostic ability of DNTTIP1 in TCGA-KIRC and validation dataset. The quantitative real-time polymerase chain reaction (qRT-PCR) detected the DNTTIP1 expression in renal cancer tissues, and the Office of Cancer Clinical Proteomics Research (CPTAC) verified the protein expression of DNTTIP1. Moreover, nomogram predicted the role of DNTTIP1 in ccRCC patient. Single-sample Gene Set Enrichment Analysis (SsGSEA) and GSEA evaluated the pathogenesis role of DNTTIP1 in TCGA-KIRC. Results DNTTIP1 expression was higher in ccRCC tumor tissues. High expression of DNTTIP1 was associated with poor OS (HR = 1.618, P < 0.0001), and poor DFS (HR = 1.789, P < 0.0001). SsGSEA and GSEA showed DNTTIP1 was associated with hypoxia, epithelial-mesenchymal transition (EMT), angiogenesis, G2M checkpoint. DNTTIP1 had a positive correlation with EMT biomarkers in ccRCC, and might be an effective target for ccRCC. Conclusion This study provided that higher expression of DNTTIP1 predicted poor prognosis in ccRCC, and DNTTIP1 might be a novel detection biomarker and therapeutic target of tumor malignant in the future.