The intervention effect of Aitongxiao prescription on primary liver cancer rats was evaluated based on high-throughput miRNA sequencing and bioinformatics analysis

被引:1
|
作者
Xu, Lijing [1 ]
Cheng, Jinlai [2 ]
Li, Zhuoxian [1 ]
Wen, Xiaoyu [3 ]
Sun, Yuhao [4 ]
Xia, Meng [1 ]
Leng, Jing [1 ,5 ]
机构
[1] Guangxi Univ Chinese Med, Basic Med Coll, Nanning, Peoples R China
[2] China Acad Chinese Med Sci, Inst Chinese Mat Med, Beijing, Peoples R China
[3] Guilin Life & Hlth Career Tech Coll, Rehabil Coll, Guilin, Peoples R China
[4] Univ Gottingen, Inst Microbiol & Genet, Dept Mol Genet, Gottingen, Germany
[5] Guangxi Univ Chinese Med, Guangxi Key Lab Translat Med Treating High Inciden, Nanning, Peoples R China
来源
FRONTIERS IN ONCOLOGY | 2023年 / 13卷
基金
中国国家自然科学基金;
关键词
Aitongxiao prescription; primary liver cancer; exosomal microRNAs; high-throughput sequencing; bioinformatics analysis; HEPATOCELLULAR-CARCINOMA PROLIFERATION; EXOSOMES; EXPRESSION; INVASION; MIGRATION; CELLS; RECURRENCE; MICRORNAS; PROGNOSIS; BIOMARKER;
D O I
10.3389/fonc.2023.1050069
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Liver cancer is a common malignant tumor known for its difficult treatment and poor prognosis. As a traditional Chinese medicine prescription, Aitongxiao prescription (ATXP) has been used in clinical treatment of primary liver cancer (PLC) for more than ten years, and its therapeutic effect is obvious and has been verified over time. However, the mechanism of ATXP in treating PLC has not been fully elucidated. This study aimed to detect the liver-protective effect of ATXP on a PLC rat model and explore its potential mechanism from the perspective of plasma extracellular vesicle miRNAs. Fifty SPF male SD rats were randomly selected, with six rats as the control group, and the remaining rats were injected with DEN to establish a primary liver cancer model. The model rats were randomly divided into the model group and the ATXP group. After 4 weeks of intervention, the liver-protective effect of ATXP was evaluated using plasma biochemical indicators and histopathological methods. Plasma extracellular vesicles were isolated and extracted, and identified by transmission electron microscopy, nanoparticle tracking analysis, and western blot. Significant differentially expressed miRNAs in extracellular vesicles were screened by Illumina sequencing to explore the therapeutic targets of ATXP and conduct functional analysis. The results showed that ATXP significantly reduced plasma liver function in PLC rats and alleviated liver pathological damage. In addition, plasma extracellular vesicles were isolated and identified. According to the results of GO and KEGG analysis, they were related to multiple biological processes and covered multiple signaling pathways (PI3K-Akt and MAPK signaling pathways, etc.). The interaction between miR-199a-3p and MAP3K4 was determined by bioinformatics methods and dual-luciferase reporter gene detection, confirming that MAP3K4 is the target gene of miR-199a-3p. In conclusion, ATXP protects the liver from DEN-induced PLC, which may be related to the regulation of plasma extracellular vesicle miR-199a-3p. This study further reveals the mechanism of ATXP in treating liver cancer and provides a theoretical basis for subsequent research.
引用
收藏
页数:15
相关论文
共 50 条
  • [31] PipeCraft: Flexible open-source toolkit for bioinformatics analysis of custom high-throughput amplicon sequencing data
    Anslan, Sten
    Bahram, Mohammad
    Hiiesalu, Indrek
    Tedersoo, Leho
    MOLECULAR ECOLOGY RESOURCES, 2017, 17 (06) : e234 - e240
  • [32] Integrative bioinformatics analysis of high-throughput sequencing and in vitro functional analysis leads to uncovering key hub genes in esophageal squamous cell carcinoma
    Shen, Feng
    Liu, Xing
    Ding, Fengjiao
    Yu, Zhonglin
    Shi, Xinyi
    Cheng, Lushan
    Zhang, Xuewei
    Jing, Chengbao
    Zhao, Zilong
    Cao, Hongyou
    Zhao, Bing
    Liu, Jing
    HEREDITAS, 2025, 162 (01):
  • [33] Identification of colorectal cancer-restricted microRNAs and their target genes based on high-throughput sequencing data
    Chang, Jing
    Huang, Liya
    Cao, Qing
    Liu, Fang
    ONCOTARGETS AND THERAPY, 2016, 9 : 1787 - 1794
  • [34] Identification of miRNA profiling in prediction of tumor recurrence and progress and bioinformatics analysis for patients with primary esophageal cancer: Study based on TCGA database
    Chen, Fangyao
    Zhou, Hui
    Wu, Chenqiuzi
    Yan, Hong
    PATHOLOGY RESEARCH AND PRACTICE, 2018, 214 (12) : 2081 - 2086
  • [35] Analysis of Fungal Diversity of Moldy Walnut Kernel Based on High-throughput Sequencing Technology
    Fang Y.
    Su G.
    Wang W.
    Bai Y.
    Wang F.
    Pei D.
    Journal of Chinese Institute of Food Science and Technology, 2023, 23 (08) : 369 - 378
  • [36] Microbial Diversity Analysis of Sufu from Different Origins Based on High-throughput Sequencing
    Fu R.
    Liu C.
    Xu L.
    Zhang H.
    Xia T.
    Chen W.
    Science and Technology of Food Industry, 2023, 44 (02) : 134 - 142
  • [37] Analysis of the Relationship between Bladder Cancer Gene Mutation and Clinical Prognosis by High-Throughput Sequencing
    Li, Xiaohang
    Liu, Jie
    Li, An'an
    Liu, Xin
    Miao, Yuesong
    Wang, Zhiyong
    LABORATORY MEDICINE, 2023, 54 (02) : 142 - 152
  • [38] seqCNA: an R package for DNA copy number analysis in cancer using high-throughput sequencing
    Mosen-Ansorena, David
    Telleria, Naiara
    Veganzones, Silvia
    De la Orden, Virginia
    Maestro, Maria Luisa
    Aransay, Ana M.
    BMC GENOMICS, 2014, 15
  • [39] seqCNA: an R package for DNA copy number analysis in cancer using high-throughput sequencing
    David Mosen-Ansorena
    Naiara Telleria
    Silvia Veganzones
    Virginia De la Orden
    Maria Luisa Maestro
    Ana M Aransay
    BMC Genomics, 15
  • [40] Unveiling the LncRNA-miRNA-mRNA Regulatory Network in Arsenic-Induced Nerve Injury in Rats through High-Throughput Sequencing
    Chu, Fang
    Lu, Chunqing
    Jiao, Zhe
    Yang, Wenjing
    Yang, Xiyue
    Ma, Hao
    Yu, Hao
    Wang, Sheng
    Li, Yang
    Sun, Dianjun
    Sun, Hongna
    TOXICS, 2023, 11 (12)