Evidence map›Paper›PMID 41165836›Full record

ArticleNaunyn-Schmiedeberg's archives of pharmacology2026

Mitochondrial autophagy mechanism and berberine therapeutic target discovery in hepatocellular carcinoma based on single-cell and transcriptome analysis.

Shumin Wen, Xiaofeng Cheng, Zhangrong Zhu, Tao Liu, Min Chen

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Article in Naunyn-Schmiedeberg's archives of pharmacology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shumin WenDepartment of Oncology, Yibin Integrated Traditional Chinese and Western Medicine Hospital, Yinbin, Sichuan Province, China.
Xiaofeng ChengDepartment of Oncology, Yibin Integrated Traditional Chinese and Western Medicine Hospital, Yinbin, Sichuan Province, China.
Zhangrong ZhuDepartment of Oncology, Yibin Integrated Traditional Chinese and Western Medicine Hospital, Yinbin, Sichuan Province, China.
Tao LiuDepartment of Oncology, Yibin Integrated Traditional Chinese and Western Medicine Hospital, Yinbin, Sichuan Province, China.
Min ChenDepartment of Preventive Medicine, Yibin Integrated Traditional Chinese and Western Medicine Hospital, Yinbin, Sichuan Province, China. zyahzcm@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor worldwide, and its progression is closely related to mitochondrial damage, but its mechanism is not yet clear. The natural compound berberine has multi-target anti-tumor potential, but further exploration is needed to determine whether it regulates mitochondrial autophagy. This study aims to explore the molecular mechanisms of HCC and evaluate the possibility of berberine intervention, providing new research directions and a theoretical basis for its treatment. This study integrated GEO data, single-cell sequencing, and in vitro cell experiments to systematically analyze the differential gene expression characteristics and pathway regulatory networks of HCC by screening core targets through the intersection with autophagy genes and combining single-cell data to reveal the interaction between malignant cells and immune cells. In addition, potential therapeutic targets of berberine were validated through in vitro experiments, and its mechanism of action was analyzed through bioinformatics. This study screened 5700 differentially expressed genes and 4515 modular genes through GEO database analysis. After intersecting with the autophagy dataset, 132 HCC autophagy-related genes were obtained. Further identification of 20 hub genes, which are mainly involved in the regulation of autophagy and the formation of autophagosomes, was performed. Enrichment analysis showed that pathways such as Autophagy other, Mitophagy animal, and HIF-1 signaling pathway were significantly activated in HCC. The single-cell immune microenvironment reveals a significant increase in macrophage and neutrophil infiltration in tumor tissues, while NK cell function may be inhibited. In addition, berberine reverses the malignant phenotype of HCC cells by targeting genes such as BECN1, HSP90AA1, ATG5, PINK1, HIF1A, and GSK3B, regulating the Autophagy other, Mitophagy animal, and HIF-1 signaling pathways. This study reveals the core mechanism of mitochondrial autophagy in HCC and proposes a new strategy for berberine targeted therapy, laying a theoretical foundation for molecular typing and combination therapy development of hepatocellular carcinoma.

Indexed as

Antineoplastic AgentsAutophagyBerberineCarcinoma, HepatocellularLiver NeoplasmsMitochondriaCell Line, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansSingle-Cell AnalysisTranscriptomeAntineoplastic AgentsBerberineAutophagyBerberineHepatocellular carcinomaSingle-cell technologyTranscriptomics

Identifiers

PMID41165836

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.