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Volume 26
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10.3390/ijms26178533
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Machine Learning Integration of Bulk and Single-Cell RNA-Seq Data Reveals Cathepsin B as a Central PANoptosis Regulator in Influenza

by
Bin Liu
1,
Lin Zhu
1,
Caijuan Zhang
1,
Dunfang Wang
1,
Haifan Liu
1,
Jianyao Liu
1,
Jingwei Sun
2,
Xue Feng
1,* and
Weipeng Yang
1,*
1
State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100010, China
2
School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing 100029, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2025, 26(17), 8533; https://doi.org/10.3390/ijms26178533
Submission received: 1 July 2025 / Revised: 25 July 2025 / Accepted: 26 August 2025 / Published: 2 September 2025
(This article belongs to the Section Molecular Informatics)
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Abstract

Influenza A virus (IAV) infection triggers excessive activation of PANoptosis—a coordinated form of programmed cell death integrating pyroptosis, apoptosis, and necroptosis—which contributes to severe immunopathology and acute lung injury. However, the molecular regulators that drive PANoptosis during IAV infection remain poorly understood. In this study, we integrated bulk and single-cell RNA sequencing (scRNA-seq) datasets to dissect the cellular heterogeneity and transcriptional dynamics of PANoptosis in the influenza-infected lung. PANoptosis-related gene activity was quantified using the AUCell, ssGSEA, and AddModuleScore algorithms. Machine learning approaches, including Support Vector Machine (SVM), Random Forest (RF), and Least Absolute Shrinkage and Selection Operator (LASSO) regression, were employed to identify key regulatory genes. scRNA-seq analysis revealed that PANoptosis activity was primarily enriched in macrophages and neutrophils. Integration of transcriptomic and computational data identified cathepsin B (CTSB as a central regulator of PANoptosis. In vivo validation in an IAV-infected mouse model confirmed elevated expression of PANoptosis markers and upregulation of CTSB. Mechanistically, CTSB may facilitate NLRP3 inflammasome activation and promote lysosomal dysfunction-associated inflammatory cell death. These findings identify CTSB as a critical mediatoCTSBr linking lysosomal integrity to innate immune-driven lung injury and suggest that targeting CTSB could represent a promising therapeutic strategy to alleviate influenza-associated immunopathology.
Keywords: PANoptosis; influenza A virus; cathepsin B (CTSB); single-cell RNA sequencing; machine learning PANoptosis; influenza A virus; cathepsin B (CTSB); single-cell RNA sequencing; machine learning
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MDPI and ACS Style

Liu, B.; Zhu, L.; Zhang, C.; Wang, D.; Liu, H.; Liu, J.; Sun, J.; Feng, X.; Yang, W. Machine Learning Integration of Bulk and Single-Cell RNA-Seq Data Reveals Cathepsin B as a Central PANoptosis Regulator in Influenza. Int. J. Mol. Sci. 2025, 26, 8533. https://doi.org/10.3390/ijms26178533

AMA Style

Liu B, Zhu L, Zhang C, Wang D, Liu H, Liu J, Sun J, Feng X, Yang W. Machine Learning Integration of Bulk and Single-Cell RNA-Seq Data Reveals Cathepsin B as a Central PANoptosis Regulator in Influenza. International Journal of Molecular Sciences. 2025; 26(17):8533. https://doi.org/10.3390/ijms26178533

Chicago/Turabian Style

Liu, Bin, Lin Zhu, Caijuan Zhang, Dunfang Wang, Haifan Liu, Jianyao Liu, Jingwei Sun, Xue Feng, and Weipeng Yang. 2025. "Machine Learning Integration of Bulk and Single-Cell RNA-Seq Data Reveals Cathepsin B as a Central PANoptosis Regulator in Influenza" International Journal of Molecular Sciences 26, no. 17: 8533. https://doi.org/10.3390/ijms26178533

APA Style

Liu, B., Zhu, L., Zhang, C., Wang, D., Liu, H., Liu, J., Sun, J., Feng, X., & Yang, W. (2025). Machine Learning Integration of Bulk and Single-Cell RNA-Seq Data Reveals Cathepsin B as a Central PANoptosis Regulator in Influenza. International Journal of Molecular Sciences, 26(17), 8533. https://doi.org/10.3390/ijms26178533

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