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DOI 10.1016/j.isci.2026.115183

Медицинская библиотека · iScience · 2026

Identification and validation of key PANoptosis-related genes via integrative machine learning and single-cell sequencing in AILI.

Li Shuo, He Chenhui, Wang Meng, Ran Binli, Li Guanghui, Dong Guangzhong, Zhang Heng, Mei Chaopeng, Song Yaodong, Yu Qiwen, Chen Sanyang, Zhu Changju, Li Jiye

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Аннотация

Acetaminophen (APAP) overdose is a leading cause of drug-induced liver injury and acute liver failure. PANoptosis, a recently defined form of programmed cell death, is closely linked to immune regulation; however, its role in APAP-induced liver injury (AILI) remains unclear. Here, we aimed to identify PANoptosis-related biomarkers and elucidate their functions in AILI. By integrating bulk RNA-seq, weighted gene co-expression network analysis, machine learning, and single-cell RNA-seq, we identified Cdkn1a and Pdk1 as key PANoptosis-related genes with high diagnostic potential. Immune infiltration analyses revealed significant associations between these genes and multiple immune cell populations. Single-cell analysis demonstrated cell-type-specific expression patterns and enhanced signaling between hepatocytes and macrophages, as well as between T cells and neutrophils. Experimental validation confirmed that Cdkn1a and Pdk1 correlated with liver injury severity, and in vivo knockdown of Pdk1 exacerbated AILI by promoting PANoptosis. Collectively, our findings identify Cdkn1a and Pdk1 as promising biomarkers in AILI.

Для цитирования: Li Shuo, He Chenhui, Wang Meng, Ran Binli, Li Guanghui, Dong Guangzhong, Zhang Heng, Mei Chaopeng, Song Yaodong, Yu Qiwen, Chen Sanyang, Zhu Changju, Li Jiye. Identification and validation of key PANoptosis-related genes via integrative machine learning and single-cell sequencing in AILI.. iScience. 2026. DOI: 10.1016/j.isci.2026.115183.
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