Background: This study was designed to establish a sensitive prognostic model based on apoptosis-related genes to predict overall survival (OS) in patients with clear cell renal cell carcinoma (ccRCC).Methods: Obtaining the expression of apoptosis-related genes and associated clinical parameters from online datasets (The Cancer Genome Atlas, TCGA), their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by internal and external databases (both TCGA and ArrayExpress).Results: A total of nine apoptosis-related genes (SLC27A2, TNFAIP2, IFI44, CSF2, IL4, MDK, DOCK8, WNT5A, APP) were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in both the internal and external datasets of OS (all p < 0.05) and verified their expressions by qRT-PCR. Moreover, we conducted the Receiver Operating Characteristic (ROC), finding the area under the ROC curves (AUCs) were all above 0.70 which indicated that riskScore was a stable independent prognostic factor (p < 0.05). Furthermore, prognostic nomograms were established to figure out the relationship between 1-, 3- and 5-year OS and individual parameters for ccRCC patients. Additionally, survival analyses indicated that our riskScore worked well in predicting OS in subgroups of age, gender, grade, stage, T, M, N0, White (all p < 0.05), except for African, Asian and N1 (p > 0.05). We also explored its association with immune infiltration and applied cMap database to seek out highly correlated small molecule drugs.Conclusion: Our study successfully constructed a prognostic model containing nine hub apoptosis-related genes for ccRCC, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

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Background: Currently, patients with diabetic erectile dysfunction (DMED) were not satisfied with the effects of first-line phosphodiesterase type 5 inhibitors (PDE5Is).Hence, this paper was designed to mine hub biomarkers in DMED and explore its potential mechanisms.Methods: Gene expression matrix of DMED was downloaded from the gene expression omnibus (GEO; GSE2457) dataset. The top 20 genes were selected based on the connectivity degrees in protein-protein interaction (PPI) network. Functional enrichment analysis was utilized to reveal DMED-related signaling pathways. We also explored the roles of immunity, m6A, ferroptosis, or cuproptosis in DMED and constructed Sprague Dawley (SD) rats DMED model to verify gene expressions by quantitative real-time polymerase chain reaction (qRT-PCR).Results: Based on the threshold, a total of 122 differently expressed genes (DEGs) were identified in DMED, including 39 up-regulated and 83 down-regulated genes.Functional enrichment analysis implied that these DEGs were significantly enriched in peroxisome proliferator-activated receptors, ferroptosis, hypoxia-inducible factor 1 signaling pathways, and so on. SD rats DMED model was also successfully established by us and validated by intracavernous pressure/mean arterial pressure, Masson's trichrome staining, and immunohistochemical analysis. We further verified the expression of these top 20 genes from the PPI network by qRT-PCR in the SD rats DMED model and finally identified Sparc, Lox, Srebf1, and Mmp3 as hub biomarkers (all p < 0.05). As for immunity and cuproptosis, our analysis indicated that DMED had nothing to do with them (all p > 0.05). Actually, DMED was markedly associated with m6A regulators and ferroptosis. Conclusions:We identified Sparc, Lox, Srebf1, and Mmp3 as potential hub biomarkers in the SD rats DMED model for future drug development and found its significant associations with m6A regulators and ferroptosis, but not with immunity or cuproptosis.

BackgroundADAMTS14 played a crucial role in the formation and development of various cancers. Currently, no associations had been revealed between ADAMTS14 and clear cell renal cell carcinoma (ccRCC). Hence, this study was designed to assess the prognostic values and immunological roles of ADAMTS14 in ccRCC and to reveal its potential mechanisms.MethodsADAMTS14-related expression profiles and related clinical data were downloaded from The Cancer Genome Atlas (TCGA) dataset, validated by the ICGC dataset, qRT-PCR, and immunohistochemistry. We utilized gene set enrichment analysis (GSEA) to find potentially ADAMTS14-related pathways and applied univariate/multivariate Cox regression analyses to identify independent factors significantly related to overall survival (OS) for ccRCC. A nomogram consisted of independent prognostic factors was also conducted. We further explored the associations between ADAMTS14 with immunity and revealed its potential mechanisms.ResultsADAMTS14 displayed a higher expression in ccRCC tumor than in adjacent normal tissues, and further validated results of the ICGC dataset; qRT-PCR and immunohistochemistry remained consistent (all p &lt; 0.05). Moreover, elevated ADAMTS14 expression was significantly associated with poor OS (p &lt; 0.001). Through univariate/multivariate Cox regression analyses, ADAMTS14 was found to be an independent prognostic factor for ccRCC (both p &lt; 0.05) and GSEA identified several signaling pathways including INSULIN, MTOR, and PPAR pathways. The nomogram based on independent prognostic factors was successfully established and well evaluated. Moreover, the expression of ADAMTS14 was remarkably associated with immune checkpoint molecules, tumor mutational burden (TMB), immune cells, and tumor immune microenvironment (all p &lt; 0.05). Results from TIDE and TCIA showed that highly expressed ADAMTS14 could predict worse efficacy of immunotherapy (all p &lt; 0.05). As for its potential mechanisms, we also revealed several LncRNA/RNA binding protein (RBP)/ADAMTS14 mRNA networks.ConclusionsADAMTS14 was found to play oncogenic roles in ccRCC and to be significantly associated with immunity. Several LncRNA/RBP/ADAMTS14 mRNA networks were also identified for its potential mechanisms.

Background:The aim of this study was to investigate the immunological and prognostic roles of protein phosphatase 1 regulatory subunit 18 (PPP1R18) for overall survival (OS) in kidney renal clear cell carcinoma (KIRC) patients, as well as the prediction of its potential mechanisms. Methods:Based on PPP1R18 single gene expression matrices and clinical information from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and GSE6344 datasets, the relationships between PPP1R18 and prognosis/immunity were fully explored. Univariate and multivariate Cox regression analyses were applied to assess its independent prognostic ability and gene set enrichment analysis (GSEA) was implemented to find its related pathways. Besides, we also explored possible mechanisms of PP-P1R18 involved in KIRC.Results: PPP1R18 was highly expressed in KIRC samples than in non-tumor tissues in TCGA, ICGC and GSE6344 datasets, with validations from quantitative real-time polymerase chain reaction (qRT-PCR) in both cell lines and KIRC tissues (all P < 0.05). Univariate and multivariate Cox regression analyses indicated that PPP1R18 was also considered to be with independent prognostic ability in KIRC (both P < 0.01). GSEA results showed that PPP1R18 gene expression was significantly related to Chemokine, JAK STAT, MAPK, and NOTCH pathways. Furthermore, PPP1R18 was also firmly associated with microsatellite instability (MSI), tumor mutational burden (TMB), immune microenvironment, immune cells, immune checkpoints and immune infiltration (all P < 0.05). Analysis of tumor immune dysfunction and exclusion (TIDE) and Imvigor210 datasets suggested that patients with low PPP1R18 expression are more likely to benefit from immunotherapy. Finally, we identified two potential mechanisms of a classical competing endogenous RNA (ceRNA) mechanism and an RNA-binding protein (RBP) involved mechanism of PPP1R18 in KIRC.Conclusions: PPP1R18 played oncogenic and immunological roles of OS in KIRC, offering potential antigens for developing KIRC mRNA vaccines.