Bioinformatics analysis and identification of cuproptosis-related long non-coding RNAs in colorectal cancer.

Objective: Identifying precise biomarkers for colorectal cancer (CRC) detection and management remains challenging. Here, we developed an innovative prognostic model for CRC using cuproptosis-related long non-coding RNAs (lncRNAs).

Methods: In this retrospective study, CRC patient transcriptomic and clinical data were sourced from The Cancer Genome Atlas database.

Identification of prognostic RNA editing profiles for clear cell renal carcinoma.

Objective: Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer and currently lacks effective biomarkers. This research aims to analyze and identify RNA editing profile associated with ccRCC prognosis through bioinformatics and experiments.

Methods: Transcriptome data and clinical information for ccRCC were retrieved from the TCGA database, and RNA editing files were obtained from the Synapse database.

Drugs associated with a risk of supraventricular tachycardia: analysis using the OpenVigil database.

Objective: The OpenVigil database can be used to assess medications that may cause supraventricular tachycardia (SVT) and to produce a reference for their safe use in clinical settings.

Methods: We analyzed first-quarter data from 2004 to 2023, obtained by searching the OpenVigil database using the keyword "supraventricular tachycardia." Trade names and generic names were obtained by querying the RxNav database, and the proportions were summarized.