Comparison of the Fatty Acid Metabolism Pathway in Pan-Renal Cell Carcinoma: Evidence from Bioinformatics.

This study analyzed and compared the potential role of fatty acid metabolism pathways in three subtypes of renal cell carcinoma. Biological pathways that were abnormally up- and downregulated were identified through gene set variation analysis in the subtypes. Abnormal downregulation of the fatty acid metabolism pathway occurred in all three renal cell carcinoma subtypes. Alteration of the fatty acid metabolism pathway was vital in the development of pan-renal cell carcinoma. Bioinformatics methods were used to obtain a panoramic view of copy number variation, single-nucleotide variation, mRNA expression, and the survival landscape of fatty acid metabolism pathway-related genes in pan-renal cell carcinoma. Most importantly, we used genes related to the fatty acid metabolism pathway to establish a prognostic-related risk model in the three subtypes of renal cell carcinoma. The data will be valuable for future clinical treatment and scientific research.

Identification of CPT1A as a Prognostic Biomarker and Potential Therapeutic Target for Kidney Renal Clear Cell Carcinoma and Establishment of a Risk Signature of CPT1A-Related Genes.

This study is aimed at investigating the expression, clinical significance, and biological role of CPT1A in kidney renal clear cell carcinoma (KIRC). We used the TCGA database and clinical pathology of tissue specimens to study the expression of CPT1A in KIRC. The expression of CPT1A in the kidney cancer tissue was significantly lower than that in the normal tissue. Survival curves demonstrated that the expression was correlated with prognosis in patients. We used the plasmid transfection method to explore the biological role of CPT1A in renal cancer cells and performed CCK-8, wound healing, and Transwell invasion experiments. The results demonstrated that CPT1A can inhibit the proliferation, migration, and invasion of renal cancer cells. Subsequently, we employed a bioinformatics analysis to further elucidate the role of CPT1A. The PPI network diagram was plotted, along with the coexpression diagram, between CPT1A and ten associated genes. The heat map was plotted, and the hazard ratio analysis of these eleven genes in KIRC was performed. Furthermore, the CPT1A, LPL, CPT2, and EHHADH genes were used to establish a reliable prognostic risk signature in KIRC. GSEA analysis demonstrated that CPT1A modulates tumor development via a variety of biological pathways in KIRC. We believe that CPT1A most likely suppresses tumor progression by employing tumor "slimming" in KIRC. Collectively, the results indicate the potential of CPT1A as a novel prognostic indicator and potential therapeutic target in KIRC.

Tripartite-motif family genes associated with cancer stem cells affect tumor progression and can assist in the clinical prognosis of kidney renal clear cell carcinoma.

Ubiquitination is presently a hot topic in the field of oncology. The tripartite-motif (TRIM) family of proteins represents one of the largest classes of putative single protein RING-finger E3 ubiquitin ligases, which play an essential role in the ubiquitination of proteins in the body. At the same time, research related to cancer stem cells (CSCs) is increasing in popularity in the field of oncology. CSCs are potentially chemically resistant and can be selectively enriched in patients receiving chemotherapy, ultimately leading to adverse outcomes, such as treatment failure and cancer recurrence. There is a close relationship between multiple TRIM family genes and CSCs. Accumulating evidence suggests that TRIM family proteins are expressed in diverse human cancers and act as regulators of oncoproteins or tumor suppressor proteins. In this study, we used biological information to explore the potential function of TRIM family genes related to CSCs in the development of pan-cancer. Kidney renal clear cell carcinoma (KIRC) is one of the deadliest malignant tumors in the world. Owing to its complex molecular and cellular heterogeneity, the effectiveness of existing KIRC-related risk prediction models is not satisfactory at present. Therefore, we focused on the potential role of these TRIM family genes in KIRC and used seven TRIM family genes to establish a prognostic risk model. This model includes TRIM16, TRIM32, TRIM24, TRIM8, TRIM27, PML, and TRIM11. In conclusion, this study provides further insight into the prognosis of KIRC, which may guide treatment.

A New Prognostic Risk Model Based on PPAR Pathway-Related Genes in Kidney Renal Clear Cell Carcinoma.

OBJECTIVE: This study is aimed at using genes related to the peroxisome proliferator-activated receptor (PPAR) pathway to establish a prognostic risk model in kidney renal clear cell carcinoma (KIRC). METHODS: For this study, we first found the PPAR pathway-related genes on the gene set enrichment analysis (GSEA) website and found the KIRC mRNA expression data and clinical data through TCGA database. Subsequently, we used R language and multiple R language expansion packages to analyze the expression, hazard ratio analysis, and coexpression analysis of PPAR pathway-related genes in KIRC. Afterward, using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) website, we established the protein-protein interaction (PPI) network of genes related to the PPAR pathway. After that, we used LASSO regression curve analysis to establish a prognostic survival model in KIRC. Finally, based on the model, we conducted correlation analysis of the clinicopathological characteristics, univariate analysis, and multivariate analysis. RESULTS: We found that most of the genes related to the PPAR pathway had different degrees of expression differences in KIRC. Among them, the high expression of 27 genes is related to low survival rate of KIRC patients, and the high expression of 13 other genes is related to their high survival rate. Most importantly, we used 13 of these genes successfully to establish a risk model that could accurately predict patients' prognosis. There is a clear correlation between this model and metastasis, tumor, stage, grade, and fustat. CONCLUSIONS: To the best of our knowledge, this is the first study to analyze the entire PPAR pathway in KIRC in detail and successfully establish a risk model for patient prognosis. We believe that our research can provide valuable data for future researchers and clinicians.

Genetic alteration and clinical significance of SUMOylation regulators in multiple cancer types.

The purpose of this study was to investigate the genetic variation, gene expression differences, and clinical significance of SUMOylation regulators in pan-cancers. Based on previous studies, we gained a better understanding of the biological process of SUMOylation and the status of current research. In the present study, we employed a wide range of bioinformatics methods. We used genetic variation and mRNA expression data in the Cancer Genome Atlas (TCGA) to construct a panoramic view of the single nucleotide variants, copy number variants, and gene expression changes in SUMOylation regulators in various tumors. Subsequently, we used the String website and the Cytoscape tool to construct the PPI network between these regulators. We used the GSCALite website to determine the relationship between these regulators and cancer pathways and drug sensitivity. We constructed images of co-expression between these regulators using the R programming language. Using clinical data from TCGA, we performed hazard ratio analysis for these regulators in pan-cancer. Most importantly, we used these regulators to successfully establish risk signatures related to patient prognosis in multiple tumors. Finally, in KIRC, we conducted gene-set enrichment analysis (GSEA) of the five molecules in its risk signatures. We found that these five molecules are involved in multiple cancer pathways. In short, we have comprehensively interpreted the detailed biological process of SUMOylation at the genetic level for the first time, successfully constructed multiple risk signatures, and conducted GSEA in KIRC. We believe that these findings provide credible and valuable information that is relevant for future clinical diagnoses and scientific research.

TRIM33 Overexpression Inhibits the Progression of Clear Cell Renal Cell Carcinoma In Vivo and In Vitro.

PURPOSE: To evaluate the expression of tripartite motif-containing 33 (TRIM33) in ccRCC tissues and explore the biological effect of TRIM33 on the progress of ccRCC. METHOD: The Cancer Genome Atlas (TCGA) database was used to examine the mRNA expression levels of TRIM33 in ccRCC tissues and its clinical relevance. Immunohistochemistry (IHC) was performed to evaluate its expression in ccRCC tissues obtained from our hospital. The correlation between TRIM33 expression and clinicopathological features of the patients was also investigated. The effects of TRIM33 on the proliferation of ccRCC cells were examined using the CCK-8 and colony formation assays. The effects of TRIM33 on the migration and invasion of ccRCC cells were explored through wound healing and transwell assays, along with the use of Wnt signaling pathway agonists in rescue experiments. Western blotting was used to explore the potential mechanism of TRIM33 in renal cancer cells. A xenograft model was used to explore the effect of TRIM33 on tumor growth. RESULT: Bioinformatics analysis showed that TRIM33 mRNA expression in ccRCC tissues was downregulated, and low TRIM33 expression was related to poor prognosis in ccRCC patients. In agreement with this, low TRIM33 expression was detected in human ccRCC tissues. TRIM33 expression levels were correlated with clinical characteristics, including tumor size and Furman's grade. Furthermore, TRIM33 overexpression inhibited proliferation, migration, and invasion of 786-O and ACHN cell lines. The rescue experiment showed that the originally inhibited migration and invasion capabilities were restored. TRIM33 overexpression reduced the expression levels of ß-catenin, cyclin D1, and c-myc, and inhibited tumor growth in ccRCC cells in vivo. CONCLUSION: TRIM33 exhibits an abnormally low expression in human ccRCC tissues. TRIM33 may serve as a potential therapeutic target and prognostic marker for ccRCC.

Porcupine Inhibitor LGK974 Downregulates the Wnt Signaling Pathway and Inhibits Clear Cell Renal Cell Carcinoma.

Targeted therapy for kidney cancer has achieved significant clinical results. However, because most patients who use targeted therapy will develop drug resistance, we still need to constantly explore new therapeutic targets. Although porcupine (PORCN) as a palmitoyltransferase plays a crucial role in the activation and secretion of Wnt proteins and affects the activity of the Wnt signaling pathway, little is known about the role of PORCN in clear cell renal cell carcinoma (ccRCC). We found that PORCN is highly expressed in renal cancer cell lines and patients with renal cell carcinoma with high expression of PORCN have a poor prognosis. Pathway analysis of PORCN and its related proteins showed that PORCN played a role through the Wnt signaling pathway, and there was a strong coexpression relationship between PORCN and Wnt proteins. Therefore, PORCN may be a potential and effective target for ccRCC. In the present study, we found that LGK974 could inhibit proliferation and colony formation and induce apoptosis in ccRCC cells. We also found that LGK974 could inhibit the migration and invasion of renal cell carcinoma and reduce the expression of mesenchymal markers. After treatment with LGK974, the expression level of ß-catenin, a key protein in the classical Wnt pathway, was significantly decreased, and the expression levels of the target genes cyclin D1, c-Myc, MMP9, and MMP2 in the Wnt signaling pathway were also significantly decreased, which represented a significant decrease in the activity of the Wnt signaling pathway. At the same time, the cycle of renal cancer cells was significantly blocked. In conclusion, our results indicate that LGK974 could significantly inhibit the progression of renal cancer cells in a safe concentration range, so PORCN may be a safe and effective target for patients with renal cancer.

Screening and Identification of Key Biomarkers for Bladder Cancer: A Study Based on TCGA and GEO Data.

Bladder cancer (BLCA) is a common malignant cancer, and it is the most common genitourinary cancer in the world. The recurrence rate is the highest of all cancers, and the treatment of BLCA has only slightly improved over the past 30 years. Genetic and environmental factors play an important role in the development and progression of BLCA. However, the mechanism of cancer development remains to be proven. Therefore, the identification of potential oncogenes is urgent for developing new therapeutic directions and designing novel biomarkers for the diagnosis and prognosis of BLCA. Based on this need, we screened overlapping differentially expressed genes (DEG) from the GSE7476, GSE13507, and TCGA BLCA datasets. To identify the central genes from these DEGs, we performed a protein-protein interaction network analysis. To investigate the role of DEGs and the underlying mechanisms in BLCA, we performed Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) analysis; we identified the hub genes via different evaluation methods in cytoHubba and then selected the target genes by performing survival analysis. Finally, the relationship between these target genes and tumour immunity was analysed to explore the roles of these genes. In summary, our current studies indicate that both cell division cycle 20 (CDC20) and abnormal spindle microtubule assembly (ASPM) genes are potential prognostic biomarkers for BLCA. It may also be a potential immunotherapeutic target with future clinical significance.