RESUMEN
Iridocyclitis and the use of glucocorticoid medication have been widely studied as susceptibility factors for cataracts. However, the causal relationship between them remains unclear. This study aimed to investigate the causal relationship between the development of iridocyclitis and the genetic liability of glucocorticoid medication use on the risk of senile cataracts occurrence by performing Two-sample Mendelian randomization (MR) analyses. Instrumental variables (IVs) significantly associated with exposure factors (P < 5 × 10-8) were identified using published genome-wide association data from the FinnGen database and UK Biobank. Reliability analyses were conducted using five approaches, including inverse-variance weighted (IVW), MR-Egger regression, simple median, weighted median, and weighted mode. A sensitivity analysis using the leave-one-out method was also performed. Genetic susceptibility to glucocorticoid use was associated with an increased risk of developing senile cataracts (OR, 1.10; 95% CI, 1.02-1.17; P < 0.05). Moreover, iridocyclitis was significantly associated with a higher risk of developing senile cataracts (OR, 1.03; 95% CI, 1.01-1.05; P < 0.05). Nonetheless, some heterogeneity in the IVs was observed, but the MR results remained consistent after penalizing for outliers. The estimates were consistent in multivariate analyses by adjusting for body mass index (BMI) and diabetes mellitus type 2 (T2DM). This study provides new insights into the prevention and management of senile cataracts by highlighting the increased risk associated with iridocyclitis and the use of glucocorticoids.
RESUMEN
BACKGROUND: Ferroptosis has recently been associated with multiple degenerative diseases. Ferroptosis induction in cancer cells is a feasible method for treating neoplastic diseases. However, the association of iron proliferation-related genes with prognosis in HER2+ breast cancer (BC) patients is unclear. AIM: To identify and evaluate fresh ferroptosis-related biomarkers for HER2+ BC. METHODS: First, we obtained the mRNA expression profiles and clinical information of HER2+ BC patients from the TCGA and METABRIC public databases. A four-gene prediction model comprising PROM2, SLC7A11, FANCD2, and FH was subsequently developed in the TCGA cohort and confirmed in the METABRIC cohort. Patients were stratified into high-risk and low-risk groups based on their median risk score, an independent predictor of overall survival (OS). Based on these findings, immune infiltration, mutations, and medication sensitivity were analyzed in various risk groupings. Additionally, we assessed patient prognosis by combining the tumor mutation burden (TMB) with risk score. Finally, we evaluated the expression of critical genes by analyzing single-cell RNA sequencing (scRNA-seq) data from malignant vs normal epithelial cells. RESULTS: We found that the higher the risk score was, the worse the prognosis was (P < 0.05). We also found that the immune cell infiltration, mutation, and drug sensitivity were different between the different risk groups. The high-risk subgroup was associated with lower immune scores and high TMB. Moreover, we found that the combination of the TMB and risk score could stratify patients into three groups with distinct prognoses. HRisk-HTMB patients had the worst prognosis, whereas LRisk-LTMB patients had the best prognosis (P < 0.0001). Analysis of the scRNA-seq data showed that PROM2, SLC7A11, and FANCD2 were significantly differentially expressed, whereas FH was not, suggesting that these genes are expressed mainly in cancer epithelial cells (P < 0.01). CONCLUSION: Our model helps guide the prognosis of HER2+ breast cancer patients, and its combination with the TMB can aid in more accurate assessment of patient prognosis and provide new ideas for further diagnosis and treatment.
RESUMEN
Intense ultraviolet (UV) exposure can cause phototoxic reactions, such as skin inflammation, resulting in injury. UV is a direct cause of DNA damage, but the mechanisms underlying transcriptional regulation within cells after DNA damage are unclear. The bioinformatics analysis of transcriptome sequencing data from UV-irradiated and non-UV-irradiated skin showed that transcription-related proteins, such as HSF4 and COIL, mediate cellular response to UV irradiation. HSF4 and COIL can form a complex under UV irradiation, and the preference for binding target genes changed because of the presence of a large number of R-loops in cells under UV irradiation and the ability of COIL to recognize R-loops. The regulation of target genes was altered by the HSF4-COIL complex, and the expression of inflammation and ageing-related genes, such as Atg7, Tfpi, and Lims1, was enhanced. A drug screen was performed for the recognition sites of COIL and R-loop. N6-(2-hydroxyethyl)-adenosine can competitively bind COIL and inhibit the binding of COIL to the R-loop. Thus, the activation of downstream inflammation-related genes and inflammatory skin injury was inhibited.
