Brigatinib activates inflammasomes: Implication for immune-related adverse eventsNoda, Tanaka, Maruta
et alToxicol Appl Pharmacol (2025) 498, 117310
Abstract: Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKI), including brigatinib, are widely used to treat ALK-positive non-small cell lung cancer. However, severe adverse effects associated with brigatinib, such as interstitial pneumonia and liver dysfunction, may involve immune system activation. The precise mechanisms underlying these immune-related adverse effects remain unclear. In this study, we evaluated the direct activation of inflammasomes by brigatinib and other ALK TKI (crizotinib, alectinib, ceritinib) in differentiated THP-1 cells. Additionally, we analyzed the inflammasome-activating potential of supernatants from functional liver cell (FLC)-4 cells treated with these drugs. Our results demonstrate that brigatinib directly activates inflammasomes in THP-1 cells, inducing the production of interleukin-1β and the activation of caspase-1. In contrast, no inflammasome activation was observed with the other ALK TKIs. Furthermore, supernatants from FLC-4 cells, characterized by high drug-metabolizing activity, were shown to activate inflammasomes in differentiated THP-1 cells following treatment with brigatinib. Brigatinib treatment significantly increased the levels of damage-associated molecular patterns (DAMPs), including heat shock protein 90 and S100A6, in the supernatants of FLC-4 cells. These findings suggest that brigatinib induces the release of DAMPs from hepatocytes, which subsequently activate inflammasomes. This mechanism may be essential for brigatinib-induced immune system activation and the development of immune-related adverse events.Copyright © 2025 Elsevier Inc. All rights reserved.
Identification of Five NK Cell-Related Hub Genes in COPD Using Single-Cell RNA Sequencing AnalysisDeng, Yang, Gan
et alJ Inflamm Res (2025) 18, 2169-2183
Abstract: COPD is a healthcare problem. However, the underlying mechanism remains unclear. Our study aimed to explore the key genes involved in immune infiltration in COPD using bioinformatic tools.In this study, scRNA-seq analysis was utilized to explore specific marker genes of each immune cell subtype in COPD. TSNE analysis was used to evaluate the relationship between each immune cell cluster. Lasso regression identified 21 genes as characteristics of COPD modulated by the single-cell NK cell subpopulation. The "limma" package was used for differentially expressed analysis. The pseudotime analysis reveals the continuous changes of NK cells along their developmental trajectory. Further, we constructed a hub gene network to examine the correlation between hub genes and immune factors, transcriptional regulation factors, and potential therapeutic drugs. GO and KEGG enrichment analysis revealed the biological functions of the hub genes. RT-qPCR was used for validation of the five hub in COPD patients.NK cell subtypes are closely related to other immune cell subtypes and considered as the most important immune cells in the immune microenvironment of COPD patients. LASSO regression identified 21 genes as NK cells-characteristic genes for COPD. The GSE57148 as the training set has a AUC of 0.9489 and GSE8581 as the validation set has a AUC of 0.7303. The GO semantic similarity further confirmed five NK cell-related hub genes, C1orf56, S100A6, IGFBP7, ANXA1, and PTPN7. RT-qPCR experiment revealed that the mRNA expression of five hub genes in the normal group was lower than that in the disease group. We also found that five hub genes correlated with immune cell infiltration. The potential therapeutic agents for COPD may be zalcitabine, PP-2, PD-98059, and TGX-221 based on the CMap database prediction.We proposed that peripheral NK cells may play a role in the pathogenesis of COPD through bioinformatic analysis. These hub genes may provide insights into mechanistic research and new targets for new therapies in patients with COPD.© 2025 Deng et al.
Integrative proteomic analysis reveals the potential diagnostic marker and drug target for the Type-2 diabetes mellitusJia, Jiang, Lin
et alJ Diabetes Metab Disord (2025) 24 (1), 55
Abstract: The escalating prevalence of Type-2 diabetes mellitus (T2DM) poses a significant global health challenge. Utilizing integrative proteomic analysis, this study aimed to identify a panel of potential protein markers for T2DM, enhancing diagnostic accuracy and paving the way for personalized treatment strategies.Proteome profiles from two independent cohorts were integrated: cohort 1 composed of 10 T2DM patients and 10 healthy controls (HC), and cohort 2 comprising 87 T2DM patients and 60 healthy controls. Differential expression analysis, functional enrichment analysis, receiver operating characteristic (ROC) analysis, and classification error matrix analysis were employed.Comparative proteomic analysis identified the differential expressed proteins (DEPs) and changes in biological pathways associated with T2DM. Further combined analysis refined a group of protein panel (including CA1, S100A6, and DDT), which were significantly increased in T2DM in both two cohorts. ROC analysis revealed the area under curve (AUC) values of 0.94 for CA1, 0.87 for S100A6, and 0.97 for DDT; the combined model achieved an AUC reaching 1. Classification error matrix analysis demonstrated the combined model could reach an accuracy of 1 and 0.875 in the 60% training set and 40% testing set.This study incorporates different cohorts of T2DM, and refines the potential markers for T2DM with high accuracy, offering more reliable markers for clinical translation.The online version contains supplementary material available at 10.1007/s40200-025-01562-3.© The Author(s) 2025.
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