Unveiling the therapeutic potential and leukemia risk of PD-166866 in sepsis via an integrated computational-experimental strategy.

[OBJECTIVE] This study evaluates the anti-sepsis efficacy and potential risks of the FGFR1 inhibitor PD-166866 by integrating network pharmacology, transcriptome sequencing, and network toxicology.

[METHODS] In terms of druggability, network pharmacology was used to screen drug-disease common targets and conduct enrichment analysis. Meanwhile, transcriptome sequencing was performed on the LPS-induced Raw264.7 cell model for target validation. In terms of toxicology, network toxicology was applied to predict the potential toxicity of small molecules, which was further verified by gene expression and survival analysis using the TCGA and Kaplan-Meier Plotter databases.

[RESULTS] A total of 39 common targets between PD-166866 and sepsis were identified. The core pathways include the Rap1 signaling pathway, and the core targets are SRC, EGFR, and CCND1; molecular docking showed stable binding between PD-166866 and these targets. Transcriptomic analysis confirmed that PD-166866 can significantly regulate the expression of inflammation-related genes and inhibit the Rap1 pathway. Network toxicology indicated a significant risk of hematological toxicity associated with this drug. Transcriptome sequencing revealed that PD-166866 treatment led to the downregulation of IRAK3 and IKBKE, and the low expression of these two genes was significantly associated with poor prognosis in leukemia patients, confirming the potential hematological toxicity of PD-166866.

[CONCLUSION] This study confirms that PD-166866 exerts anti-sepsis effects by regulating pathways such as Rap1, but it also has the potential risk of inducing leukemia. More importantly, this study successfully established a comprehensive evaluation framework integrating in silico and in vitro experiments. It provides a feasible methodological reference for systematically evaluating the dual attributes of "efficacy-risk" in the early stage of drug development and reducing the initial reliance on traditional animal models.