Background Clear cell renal cell carcinoma (ccRCC) is still highly aggressive and lethal even with various therapeutic approaches. As the kidney is an iron metabolism-related organ, exploring and assessing the clinical value of ferroptosis, an iron-dependent regulated cell death, is practical and important. Methods Prognostic ferroptosis-related differentially expressed genes (DEGs) were identified from the KIRC cohort in the cancer genome atlas (TCGA) database, from which a prognostic signature was established using Lasso-penalized Cox regression analysis. Each patient in the KIRC cohort and the E-MTAB-1980 cohort (from the ArrayExpress database) was assigned a calculated signature-correlated risk score and categorized to be either in the high- or low-risk group divided by the median risk score in the KIRC cohort. Then, the independent prognostic value of the signature was further assessed by Kaplan-Meier (K-M) survival, time-dependent receiver operating characteristic (ROC) and Cox regression analyses based on overall survival (OS) in both cohorts. Finally, risk-related DEGs were identified in both cohorts and subjected to enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and immune infiltration. Results Among 60 ferroptosis-related genes, 32 prognostic DEGs were identified, from which we constructed a prognostic 12-gene signature with CARS1, HMGCR, CHAC1, GOT1, CD44, STEAP3, AKR1C1, CBS, DPP4, FANCD2, SLC1A5 and NCOA4. Patients in both cohorts were divided into high- and low-risk groups, which were visually distributed in two sets and had positive-risk-related mortality. The K-M survival and the ROC curves validated that the signature has prognostic value with P < 0.05 and area under the curve > 0.7 in both cohorts, respectively. Multivariate Cox regression further confirmed the risk score as an independent prognostic predictor for OS. Commonly enriched terms in GO and KEGG not only showed a high iron correlation but also, interestingly, immune relevance of 3 immune cells (macrophages, mast cells and regulatory T cells) and 1 immune-related function (antigen processing cell co-stimulation). Conclusion We established a novel 12 ferroptosis-related-gene signature that was proven to be an independent prognostic predictor for OS and inferred to be related to tumour immunity in ccRCC; however, the underlying mechanism is still poorly characterized and needs further exploration.

We aimed to identify novel circular RNAs (circRNAs) as prognostic competing endogenous RNAs (ceRNAs) to serve as genetic biomarkers and therapeutic targets for renal cell carcinoma (RCC). High-throughput sequencing data of circRNAs from Gene Expression Omnibus (GEO) and of microRNAs (miRNAs) and messenger RNAs (mRNAs) from The Cancer Genome Atlas (TCGA) were retrieved to identify differentially expressed RNAs (DERNAs). DEmRNAs were subjected to weighted gene coexpression network analysis (WGCNA) to identify prognostic DEmRNA (proDEmRNA) modules. Overlapping DEcircRNA-DEmiRNA and DEmiRNA-proDEmRNA interactions among the TargetScan, miRanda and RNAhybrid databases were constructed and identified. The circRNA-miRNA-mRNA ceRNA network was constructed using mutual DEmiRNAs in two interaction networks as nodes. mRNAs validated as significantly overexpressed in RCC by Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA) and quantitative polymerase chain reaction (q-PCR), along with the correlative miRNAs, were used for survival analysis. Finally, a ceRNA network with 13 upregulated circRNAs, 8 downregulated miRNAs and 21 upregulated mRNAs was constructed, in which Anti-Silencing Function 1B Histone Chaperone (ASF1B) and Forkhead Box M1 (FOXM1) were considered significant by Oncomine, GEPIA and q-PCR. Survival analysis showed that ASF1B, FOXM1 and hsa_miR_1254 were significantly negatively correlated but hsa_miR_129-5p was positively correlated with overall survival time. Exploration of the ceRNA network revealed the prognostic hsa_circ_0002024/hsa_miR_129-5p/ASF1B axis. Therefore, hsa_-circ_0002024 was identified as a prognostic ceRNA that might sponge hsa_miR_129-5p to regulate ASF1B and affect RCC prognosis. However, further validation is needed.

Background Clear cell renal cell carcinoma (ccRCC) is still highly aggressive and lethal even with various therapeutic approaches. As kidney is an iron-metabolism-related organ, exploring and assessing the clinical value of ferroptosis, an iron-dependent regulated cell death, is practical and significant. Methods Prognostic ferroptosis-related differentially expressed genes (DEGs) were identified from KIRC cohort in TCGA database, from which a prognostic signature was established using the Lasso-penalized Cox regression analysis. Each patient in the KIRC cohort and the E-MTAB-1980 cohort (from the ArrayExpress database) was assigned with a calculated signature-correlated risk score and categorized to be either in high- or low-risk group divided by the median risk score in the KIRC cohort. Then, the independent prognostic value of the signature was further assessed by Kaplan-Meier (K-M) survival, time-dependent receiver operating characteristic (ROC) and Cox regression analyses base on overall survival (OS) in both cohorts. Lastly, risk-related DEGs were identified in both cohorts and applied with the enrichment analyses for Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and immune infiltration. Results Within 60 ferroptosis-related genes, 32 prognostic DEGs were identified, from which we constructed a prognostic 12-gene signature including CARS1, HMGCR, CHAC1, GOT1, CD44, STEAP3, AKR1C1, CBS, DPP4, FANCD2, SLC1A5 and NCOA4. Patients in both cohorts were divided into high- and low-risk group which were visually distributed in two sets and with positive-risk-related mortality. The K-M survival and the ROC curves validated the signature as prognostic valuable with P <0.05 and area under the curve >0.7 in both cohorts, respectively. Multivariate Cox regression further confirmed the risk score as an independent prognostic predictor for OS. Commonly enriched term in GO and KEGG not only shown a highly iron correlation, but also, interesting, an immunity relevancy of 3 immune cells (macrophages, mast cells and regulatory T cell) and 1 immune-related function (antigen processing cell co-stimulation). Conclusion We established a novel 12 ferroptosis-related-gene signature which was proved as an independent prognostic predictor for OS and inferred as relating to tumor immunity in ccRCC, however, the underlying mechanism is still poorly characterized and needed further exploration.