ArticleFrontiers in immunology2026
Integrative analysis of FAERS, network toxicology, and Mendelian randomization identifies potential targets in paclitaxel-associated systemic sclerosis.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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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