Exploring the oncogenic potential of circSOD2 in clear cell renal cell carcinoma: a novel positive feedback loop.

BACKGROUND: Existing studies have found that circular RNAs (circRNAs) act as sponges for micro RNAs (miRNAs) to control downstream genes. However, the specific functionalities and mechanisms of circRNAs in human clear cell renal cell carcinoma (ccRCC) have yet to be thoroughly investigated. METHODS: Patient cohorts from online databases were used to screen candidate circRNAs, while another cohort from our hospital was obtained for validation. CircSOD2 was identified as a potential oncogenic target, and its relevant characteristics were investigated during ccRCC progression through various assays. A positive feedback loop containing downstream miRNA and its target gene were identified using bioinformatics and validated by luciferase reporter assays, RNA pull-down, and high-throughput sequencing. RESULTS: CircSOD2 expression was elevated in tumor samples and significantly correlated with overall survival (OS) and the tumor stage of ccRCC patients, which appeared in the enhanced proliferation, invasion, and migration of tumor cells. Through competitive binding to circSOD2, miR-532-3p can promote the expression of PAX5 and the progression of ccRCC, and such regulation can be salvaged by miR-532-3p inhibitor. CONCLUSION: A novel positive feedback loop, PAX5/circSOD2/miR-532-3p/PAX5 was identified in the study, indicating that the loop may play an important role in the diagnosis and prognostic prediction in ccRCC patients.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood. METHOD: RNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan-Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry. RESULTS: Twenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells' malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization. CONCLUSION: The study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

A novel 7-chemokine-genes predictive signature for prognosis and therapeutic response in renal clear cell carcinoma.

Background: Renal clear cell carcinoma (ccRCC) is one of the most prevailing type of malignancies, which is affected by chemokines. Chemokines can form a local network to regulate the movement of immune cells and are essential for tumor proliferation and metastasis as well as for the interaction between tumor cells and mesenchymal cells. Establishing a chemokine genes signature to assess prognosis and therapy responsiveness in ccRCC is the goal of this effort. Methods: mRNA sequencing data and clinicopathological data on 526 individuals with ccRCC were gathered from the The Cancer Genome Atlas database for this investigation (263 training group samples and 263 validation group samples). Utilizing the LASSO algorithm in conjunction with univariate Cox analysis, the gene signature was constructed. The Gene Expression Omnibus (GEO) database provided the single cell RNA sequencing (scRNA-seq) data, and the R package "Seurat" was applied to analyze the scRNA-seq data. In addition, the enrichment scores of 28 immune cells in the tumor microenvironment (TME) were calculated using the "ssGSEA" algorithm. In order to develop possible medications for patients with high-risk ccRCC, the "pRRophetic" package is employed. Results: High-risk patients had lower overall survival in this model for predicting prognosis, which was supported by the validation cohort. In both cohorts, it served as an independent prognostic factor. Annotation of the predicted signature's biological function revealed that it was correlated with immune-related pathways, and the riskscore was positively correlated with immune cell infiltration and several immune checkpoints (ICs), including CD47, PDCD1, TIGIT, and LAG-3, while it was negatively correlated with TNFRSF14. The CXCL2, CXCL12, and CX3CL1 genes of this signature were shown to be significantly expressed in monocytes and cancer cells, according to scRNA-seq analysis. Furthermore, the high expression of CD47 in cancer cells suggested us that this could be a promising immune checkpoint. For patients who had high riskscore, we predicted 12 potential medications. Conclusion: Overall, our findings show that a putative 7-chemokine-gene signature might predict a patient's prognosis for ccRCC and reflect the disease's complicated immunological environment. Additionally, it offers suggestions on how to treat ccRCC using precision treatment and focused risk assessment.

TP53/BRAF mutation as an aid in predicting response to immune-checkpoint inhibitor across multiple cancer types.

Immunotherapy with checkpoint inhibitors, such as PD-1/PD-L1 blockage, is becoming standard of practice for an increasing number of cancer types. However, the response rate is only 10%-40%. Thus, identifying biomarkers that could accurately predict the ICI-therapy response is critically important. We downloaded somatic mutation data for 46,697 patients and tumor-infiltrating immune cells levels data for 11070 patients, then combined TP53 and BRAF mutation status into a biomarker model and found that the predict ability of TP53/BRAF mutation model is more powerful than some past models. Commonly, patients with high-TMB status have better response to ICI therapy than patients with low-TMB status. However, the genotype of TP53MUTBRAFWT in high-TMB status cohort have poorer response to ICI therapy than the genotype of BRAFMUTTP53WT in low-TMB status (Median, 18 months vs 47 month). Thus, TP53/BRAF mutation model can add predictive value to TMB in identifying patients who benefited from ICI treatment, which can enable more informed treatment decisions.

circCHST15 is a novel prognostic biomarker that promotes clear cell renal cell carcinoma cell proliferation and metastasis through the miR-125a-5p/EIF4EBP1 axis.

BACKGROUND: Circular RNAs (circRNAs) have been indicated as potentially critical mediators in various types of tumor progression, generally acting as microRNA (miRNA) sponges to regulate downstream gene expression. However, the aberrant expression profile and dysfunction of circRNAs in human clear cell renal cell carcinoma (ccRCC) need to be further investigated. This study mined key prognostic circRNAs and elucidates the potential role and molecular mechanism of circRNAs in regulating the proliferation and metastasis of ccRCC. METHODS: circCHST15 (hsa_circ_0020303) was identified by mining two circRNA microarrays from the Gene Expression Omnibus database and comparing matched tumor versus adjacent normal epithelial tissue pairs or matched primary versus metastatic tumor tissue pairs. These results were validated by quantitative real-time polymerase chain reaction and agarose gel electrophoresis. We demonstrated the biological effect of circCHST15 in ccRCC both in vitro and in vivo. To test the interaction between circCHST15 and miRNAs, we conducted a number of experiments, including RNA pull down assay, dual-luciferase reporter assay and fluorescence in situ hybridization. RESULTS: The expression of circCHST15 was higher in ccRCC tissues compared to healthy adjacent kidney tissue and higher in RCC cell lines compared to normal kidney cell lines. The level of circCHST15 was positively correlated with aggressive clinicopathological characteristics, and circCHST15 served as an independent prognostic indicator for overall survival and progression-free survival in patients with ccRCC after surgical resection. Our in vivo and in vitro data indicate that circCHST15 promotes the proliferation, migration, and invasion of ccRCC cells. Mechanistically, we found that circCHST15 directly interacts with miR-125a-5p and acts as a microRNA sponge to regulate EIF4EBP1 expression. CONCLUSIONS: We found that sponging of miR-125a-5p to promote EIF4EBP1 expression is the underlying mechanism of hsa_circ_0020303-induced ccRCC progression. This prompts further investigation of circCHST15 as a potential prognostic biomarker and therapeutic target for ccRCC.

DDX39B Predicts Poor Survival and Associated with Clinical Benefit of Anti-PD-L1 Therapy in ccRCC.

BACKGROUND: Immune checkpoint inhibitors (ICI) have been shown to improve overall survival (OS) in clear cell renal cell carcinoma (ccRCC) patients. However, less than half of the ccRCC patients have objective response to ICI. OBJECTIVE: We aim to assess the role of DDX39B in predicting ccRCC patients'OS and ICI therapy response. METHODS: DDX39B was detected by immunohistochemistry in a tissue microarray of 305 ccRCC patients. DDX39B and its relationship with the prognosis of ccRCC were also evaluated in TCGA set and a RECA-EU set. The expression of DDX39B and patients survival was also analysed in two datasets of ccRCC patients treated with ICI. RESULTS: Overexpression of DDX39B predicted poor OS of ccRCC patients in SYSU set, TCGA set, and a RECA-EU set. DDX39B expression was significantly positive with the expression of PD-L1 and other immunomodulators., DDX39B negatively correlated with cytotoxic T-lymphocyte and HDAC10 exon 3 inclusion in ccRCC. DDX39B knockdown decreased the expression of PD-L1 and increased the expression of HDAC10 exon 3 in renal cancer ACHN cells. Patients of ccRCC with lower levels of HDAC10 exon 3 inclusion have higher TNM stage, higher Fuhrman grade and poor OS. There was a tendency that patients with DDX39B high expression had longer OS and PFS than patients with DDX39B low expression in ccRCC patients treated with ICI. CONCLUSION: DDX39B gene is highly expressed in ccRCC and is closely related to patients' OS. DDX39B might increase PD-L1 expression via the enhancement of HDAC10 exon 3 skipping, thereby promoting the ICI therapy response.