A novel signature constructed by ferroptosis-associated genes (FAGs) for the prediction of prognosis in bladder urothelial carcinoma (BLCA) and associated with immune infiltration.

BACKGROUND: Ferroptosis, a novel form of regulated cell death, has been implicated in the pathogenesis of cancers. Nevertheless, the potential function and prognostic values of ferroptosis in bladder urothelial carcinoma (BLCA) are complex and remain to be clarified. Therefore, we proposed to systematically examine the roles of ferroptosis-associated genes (FAGs) in BLCA. METHODS: According to The Cancer Genome Atlas (TCGA) database, differently expressed FAGs (DEFAGs) and differently expressed transcription factors (DETFs) were identified in BLCA. Next, the network between DEFAGs and DETFs, GO annotations and KEGG pathway analyses were performed. Then, through univariate, LASSO and multivariate regression analyses, a novel signature based on FAGs was constructed. Moreover, survival analysis, PCA analysis, t-SNE analysis, ROC analysis, independent prognostic analysis, clinicopathological and immune correlation analysis, and experimental validation were utilized to evaluate the signature. RESULTS: Twenty-eight DEFAGs were identified, and four FAGs (CRYAB, TFRC, SQLE and G6PD) were finally utilized to establish the FAGs based signature in the TCGA cohort, which was subsequently validated in the GEO database. Moreover, we found that immune cell infiltration, immunotherapy-related biomarkers and immune-related pathways were significantly different between two risk groups. Besides, nine molecule drugs with the potential to treat bladder cancer were identified by the connectivity map database analysis. Finally, the expression levels of crucial FAGs were verified by the experiment, which were consistent with our bioinformatics analysis, and knockdown of TFRC could inhibit cell proliferation and colony formation in BLCA cell lines in vitro. CONCLUSIONS: Our study identified prognostic ferroptosis-associated genes and established a novel FAGs signature, which could accurately predict prognosis in BLCA patients.

A Novel Set of Immune-associated Gene Signature predicts Biochemical Recurrence in Localized Prostate Cancer Patients after Radical Prostatectomy.

Background: Decision-making regarding biochemical recurrence (BCR) in localized prostate cancer (PCa) patients after radical prostatectomy (RP) mainly relies on clinicopathological parameters with a low predictive accuracy. Currently, accumulating evidence suggests that immune-associated genes (IAGs) play irreplaceable roles in tumorigenesis, progression and metastasis. Considering the critical role of immune in PCa, we therefore attempted to identify the novel IAGs signature and validate its prognostic value that can better forecast the risk for BCR and guide clinical treatment. Methods: RNA-sequencing and corresponding clinicopathological data were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA) was utilized to screen out the candidate module closely related to BCR, and univariate and LASSO Cox regression analyses were performed to build the gene signature. Kaplan-Meier (KM) survival analysis, time-dependent receiver operating curve (ROC), independent prognostic analysis and nomogram were also applied to evaluate the prognostic value of the signature. Besides, Gene ontology analysis (GO), Kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to explore potential biological pathways. Results: A total of six IAGs (SSTR1, NFATC3, NRP1, TUBB3, IL1R1, GDF15) were eventually identified and used to establish a novel IAGs signature. The Kaplan-Meier analysis revealed that patients with low-risk scores had longer recurrence-free survival (RFS) than those with high-risk scores in both GSE70769 and TCGA cohorts. Further, our signature was also proven to be a valuable independent prognostic factor for BCR. We also constructed a nomogram based on the gene signature and related clinicopathologic features, which excellently predict 1-year, 3-year and 5-year prognosis of localized PCa patients after RP. Moreover, functional enrichment analysis demonstrated the vital biological processes, and stratified GSEA revealed that a crucial immune-related pathway (T cell receptor signaling pathway) was notably enriched in the high-risk group. Conclusions: We successfully developed a novel robust IAGs signature that is powerful in BCR prediction in localized PCa patients after RP, and created a prognostic nomogram. In addition, the signature might help clinicians in selecting high-risk subpopulation, predicting survival status of patients and promoting more individualized therapies than traditional clinical factors.

Apolipoprotein C1 promotes prostate cancer cell proliferation in vitro.

Here, we aimed to investigate the carcinogenic effects of apolipoprotein C1 (APOC1) in prostate cancer (PCa). APOC1 expression was evaluated in PCa and normal prostate specimens, and lentivirus-mediated RNA interference was used to knockdown APOC1 in DU145 cells. The effects of APOC1 silencing on cell proliferation, cell cycle arrest, and apoptosis were assessed. APOC1 expression was much higher in PCa tissues than in normal tissues. Moreover, APOC1 silencing inhibited cell proliferation and colony formation, arrested cell cycle progression, and enhanced apoptosis in DU145 cells. Additionally, APOC1 silencing decreased survivin, phospho-Rb, and p21 levels and increased cleaved caspase-3 expression. These data supported the procarcinogenic effects of APOC1 in the pathogenesis of PCa and suggested that targeting APOC1 may have applications in the treatment of PCa.