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 withP < 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.

DNA storage, characterized by its durability, data density, and cost-effectiveness, is a promising solution for managing the increasing data volumes in healthcare.

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.

Purpose: This study aimed to explore the function and clinical significance of AVL9 in colorectal cancer (CRC). Materials and Methods: The GEO, TCGA, and GEPIA databases were searched to evaluate the expression level of AVL9, while the SurvExpress online tool was used to explore its related clinical survival prognosis. The cBioPortal and LinkedOmics databases were used to identify AVL9 expression-related genes. Protein–protein interaction (PPI) networks were analyzed using Cytoscape 3.7.1 and DAVID6.8, which was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) signal pathway enrichment. The immunohistochemistry of AVL9 in CRC was detected using an online tool protein atlas. RNA isolation and reverse transcription–quantitative polymerase chain reaction (RT-qPCR) assays were used to detect AVL9 expression in tissue and plasma samples. Results: Our study confirmed that AVL9 was highly expressed in CRC lesions versus the adjacent normal tissues (P < 0.001). High AVL9 expression was negatively associated with survival outcomes (P < 0.05). GO analysis showed that AVL9 expression-related genes were enriched in single organismal cell–cell adhesion, post-transcriptional regulation of gene expression, and negative regulation of the vascular endothelial growth factor receptor signaling pathway (P < 0.05). On a KEGG pathway analysis, these genes were mainly involved in progesterone-mediated oocyte maturation, axon guidance, the insulin signaling pathway, and the ubiquitin-mediated proteolysis signaling pathways (P < 0.05). In the PPI analysis, the KBTBD2, KIAA1147, EPDR1, and RNF216 genes interacted with AVL9, and GEPIA predicted that their expression levels were all positively correlated with AVL9. Furthermore, a clinicopathological parameter analysis found that high AVL9 expression was positively correlated with differentiation and TNM stage. RT-qPCR analysis further showed that plasma AVL9 expression was upregulated in CRC patients versus healthy controls. Conclusion: AVL9 could serve as a potential biomarker and therapeutic target for CRC.

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 0.7 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.

Background: Ferroptosis is a new form of regulated cell death (RCD) that plays a crucial role in the genesis and prognosis of tumor. Nevertheless, the relationship between ferroptosis and the prognosis of thyroid carcinoma (THCA) remains unclear and needs to be explored. Methods: By analyzing data from the THCA cohort in the TCGA database, ferroptosis-related differentially expressed genes (DEGs) with prognostic value were identified, which were used to establish a prognostic signature based on Lasso-penalized Cox regression analysis. Then, the model was testified with Kaplan-Meier survival, Cox regression and receiver operating characteristic (ROC) analyses based on overall survival (OS). Finally, DEGs between the low-risk and high-risk groups were identified and used to conduct GO enrichment analysis, KEGG pathways analysis and immune infiltration analysis.Results: A 6-gene signature was constructed which including DPP4, GPX4, GSS, HMGCR, TFRC and PGD. The area under the curve (AUC) were 0.890 (1 year), 0.863 (2 years) and 0.883 (3 years) which validated the prominent predictive capacity of the model. Multivariate Cox regression certified the model as a prognostic-related independent predictor for OS.Conclusion: In this study, we established an innovative prognostic signature of 6 ferroptosis-related genes which can be as a prognostic-related independent predictor for OS in THCA, while the potential mechanisms was still unclear and needed further exploration.