Background. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancers. As cuproptosis, a new cell death mechanism proposed recently, differs from all other known mechanisms regulating cell death, we aimed to create prognostic markers using cuproptosis-related long non-coding ribonucleic acids (RNAs; lncRNAs) and elucidate the molecular mechanism. Methods. Data from transcriptome RNA sequencing of ccRCC samples and the relevant clinical data were downloaded from The Cancer Genome Atlas, and Pearson’s correlation analysis was implemented to obtain the cuproptosis-related lncRNAs. Then, univariate Cox, multivariate Cox, and Least Absolute Shrinkage and Selection Operator Cox analyses were performed to construct the risk signatures. The cuproptosis-related lncRNAs predictive signature was evaluated with receiver operating characteristic curves and subgroup analysis. Finally, Gene Set Enrichment Analysis (GSEA), single-sample GSEA (ssGSEA), tumor immune microenvironment (TIME), and immune checkpoints were performed to explore the relationship between immunity and patient prognosis. Results. Five cuproptosis-related lncRNAs, including FOXD2-AS1, LINC00460, AC091212.1, AC007365.1, and AC026401.3, were used to construct the signature. In the training and test sets, low-risk groups (as identified by a risk score lower than the median) demonstrated a better prognosis with an area under the curve for 1-, 3-, and 5-year survival being 0.793, 0.716, and 0.719, respectively. GSEA analysis suggested significant enrichment of the tricarboxylic acid cycle and metabolism-related pathways in the low-risk group. Besides, both ssGSEA and TIME suggested that the high-risk group exhibited more active immune infiltration. Conclusion. We proposed a cuproptosis-related lncRNAs signature, which had the potential for prognoses and prediction. Our findings might contribute to elucidating potential genomic biomarkers and targets for future therapies in the cuproptosis-related signaling pathways.

Background: The purpose of our research was to discover the adverse events (AEs) not mentioned in the previous y drug instructions after using gemcitabine, so as to guide clinical medication. Methods: The Food and Drug Administration Adverse Event Reporting System (FAERS) database was utilized to retrieve AEs associated with the use of gemcitabine up to 2023. Four methods were used to detect new signals of adverse drug reactions（Reporting Odds Ratio, Proportional Reporting Ratio, Bayesian Confidence Propagation Neural Network, and Empirical Bayesian Geometric Mean）. AEs were considered positive signals only if they were detected by all four algorithms. Results: Between 2014 and 2023, 14,905 individuals experienced 42,360 AEs following the use of gemcitabine. totaling 437 preferred terms (PTs) distributed across 20 system organ classes (SOCs). We focused on AEs that were either not mentioned or mentioned less frequently in SOCs related to eye diseases, the nervous system, and the ear and labyrinth. After the administration of gemcitabine, patients exhibited retinopathy (Case number: 28), Purtscher retinopathy (Case number: 10), choroidal effusion (Case number: 9), amaurosis (Case number: 9), cystoid macular edema (Case number: 8), and other ocular organ system-related AEs. In terms of the nervous system, peripheral neuropathy (Case number: 363), neurotoxicity (Case number: 117), polyneuropathy (Case number: 92), and other neurologic AEs were observed. Furthermore, in the ear and labyrinth, ototoxicity (Case number: 9) was reported. Conclusion: Our study identified previously undetected AEs following treatment with gemcitabine, which may provide new insights for future medication guidance.

Bladder cancer is the second most common malignant tumor in the male genitourinary system. This study explored the prognostic role of necroptosis-related long noncoding RNAs (LncRNAs) in bladder cancer.We used univariate Cox, least absolute shrinkage and selection operator and multivariate Cox regression models to establish a necroptosis-related lncRNA prognostic signature. Then, 13 necroptosis-related lncRNAs were included in risk signature. Patients were divided into the high- and low-risk group based on the median risk score. The risk signature predicted that the areas under the receiver operating characteristic curve of patients at 1 year, 3 years and 5 years were 0.74, 0.78 and 0.79, respectively. Next, nomograms and correction curves were established using risk signature and clinicopathological factors. The nomogram-corrected curve shows a good fit. Gene Set Enrichment Analysis was used to explore the possible molecular mechanisms underlying the different prognosis of the low-risk and high-risk of patients, and showed that tumor-related signaling pathways and intercellular connectivity-related signaling pathways were significantly enriched in the high-risk group, while metabolism-related pathways were enriched in the low-risk group. In addition, Immune cell infiltration analysis and was performed on the two groups of patients and the response to immunotherapy was judged. Finally, tumor mutation data were analyzed, and potentially sensitive chemotherapy drugs were screened. The low-risk group was more sensitive to methotrexate while the patients in the high-risk group were more sensitive to cisplatin, docetaxel, paclitaxel and thapsigargin.