Analysis of immune-related genes and potential therapeutic drugs in refractory lupus nephritis: Comparison with drug-sensitive lupus nephritis based on RNA transcription data

Based on the gene expression omnibus database, the immune-related genes associated with refractory lupus nephritis (RLN) are analyzed by comparing the RNA expression data of drug-sensitive lupus nephritis (DLN) with that of RLN. Subsequently, potential therapeutic drugs were screened based on the identified genes. The RNA expression datasets related to DLN and RLN were sourced from the gene expression omnibus database. Differential analysis was performed to ascertain differentially expressed genes. These differentially expressed genes were then cross-referenced with immune-related genes obtained from the ImmPort database to identify potential candidate genes. To investigate the underlying biological mechanisms, gene ontology and kyoto encyclopedia of genes and genomes analyses were performed. Core genes were subsequently identified using the STRING database, along with least absolute shrinkage and selection operator regression analysis and support vector machine-recursive feature elimination (SVM-RFE) techniques. The receiver operating characteristic curve was utilized to confirm and assess the significance of the core genes. A nomogram prediction model was developed, with the concordance index (C-index) applied to evaluate its precision. The immune cell infiltration in both RLN and DLN was examined, investigating the relationships between core genes and immune cells, as well as interactions among the immune cells. Coremine Medical was engaged to discover traditional Chinese medicines that exhibited significant associations with the core genes. Additionally, the Traditional Chinese Medicine Systems Pharmacology database was employed to identify small molecule compounds with therapeutic potential found within these traditional medicines. Finally, the protein structures of the key genes and their corresponding small molecule compounds were processed using Vina software and PyMol software for molecular docking, ensuring the reliability of the results. In this investigation, a total of 5 essential genes were pinpointed: MMP-9, IRF7, CCR6, OAS1, and IFIH1. Furthermore, small molecule compounds that may have therapeutic potential were identified based on these central genes, including tanshinone IIA (Tan IIA), luteolin, ellagic acid, baicalein, and quercetin. The immune mechanism of RLN is complex, arising from a synergy of multiple factors, targets, and pathways. This approach is valuable for elucidating the mechanisms underlying RLN resistance and offers a novel perspective for enhancing immunotherapy effectively.