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Integrative analysis of FAERS, network toxicology, and Mendelian randomization identifies potential targets in paclitaxel-associated systemic sclerosis

计算生物学 医学 生物信息学 疾病 孟德尔随机化 不利影响 临床试验 紫杉醇 生物 多发性硬化 纤维化 生物标志物 自身免疫性疾病 免疫学 多效性 基因 基因调控网络
作者
Xinfeng Wang,Chengyan Zhang
出处
期刊:Frontiers in Immunology [Frontiers Media]
卷期号:17: 1696820-1696820
标识
DOI:10.3389/fimmu.2026.1696820
摘要

Systemic sclerosis (SSc) is a rare and complex autoimmune disease characterized by fibrosis of the skin and internal organs as well as vascular abnormalities. Studies have suggested that paclitaxel may induce adverse reactions resembling systemic sclerosis; however, the underlying mechanisms remain not fully understood. We retrieved reports of paclitaxel-associated SSc from the FDA Adverse Event Reporting System (FAERS). Potential shared targets between paclitaxel and SSc were identified through network toxicology analysis. Mendelian randomization (MR) was then used to explore associations between these targets and SSc susceptibility. Disproportionality analyses demonstrated significant safety signals linking paclitaxel with SSc, scleroderma, and scleroderma-like reactions. A total of 76 overlapping targets were identified between paclitaxel and SSc. Based on expression quantitative trait loci (eQTL) from the IEU OpenGWAS database, MR analysis suggested 11 targets potentially associated with SSc susceptibility. Functional enrichment analyses revealed that these genes were involved in oxidative stress response, regulation of cell death, lipid metabolism, and apoptosis. Among them, AKT1 and BCL2 were highlighted as central nodes in the protein-protein interaction network, representing candidate targets for further investigation. Molecular docking simulations provided exploratory computational evidence of potential interactions, which do not confirm functional or mechanistic roles. Overall, this study systematically explored potential molecular targets related to paclitaxel-associated SSc and provides hypothesis-generating insights that may guide future mechanistic studies and risk assessment strategies.
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