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硫利达嗪抗宫颈癌的潜在作用机制

谢芹 赵春阳 张葆溯 赵洪波

谢芹, 赵春阳, 张葆溯, 赵洪波. 硫利达嗪抗宫颈癌的潜在作用机制[J]. 昆明医科大学学报, 2022, 43(3): 13-20. doi: 10.12259/j.issn.2095-610X.S20220317
引用本文: 谢芹, 赵春阳, 张葆溯, 赵洪波. 硫利达嗪抗宫颈癌的潜在作用机制[J]. 昆明医科大学学报, 2022, 43(3): 13-20. doi: 10.12259/j.issn.2095-610X.S20220317
Qin XIE, Chunyang ZHAO, Baosu ZHANG, Hongbo ZHAO. Potential Mechanism of Thioridazine in Anti-cervical Cancer[J]. Journal of Kunming Medical University, 2022, 43(3): 13-20. doi: 10.12259/j.issn.2095-610X.S20220317
Citation: Qin XIE, Chunyang ZHAO, Baosu ZHANG, Hongbo ZHAO. Potential Mechanism of Thioridazine in Anti-cervical Cancer[J]. Journal of Kunming Medical University, 2022, 43(3): 13-20. doi: 10.12259/j.issn.2095-610X.S20220317

硫利达嗪抗宫颈癌的潜在作用机制

doi: 10.12259/j.issn.2095-610X.S20220317
基金项目: 云南省科技厅-昆明医科大学应用基础研究联合专项基金资助项目(202101AY070001-075);云南省教育厅科学研究基金资助项目(2021J0226)
详细信息
    作者简介:

    谢芹(1997~),女,四川安岳人,在读硕士研究生,主要从事生物信息,网络药理学研究工作

    通讯作者:

    赵洪波,E-mail:zhaohongbo@kmmu.edu.cn

  • 中图分类号: R737.3

Potential Mechanism of Thioridazine in Anti-cervical Cancer

  • 摘要:   目的  运用生物信息学分析, 探讨硫利达嗪抗宫颈癌的潜在作用机制。  方法  通过PharmMapper工具预测能够与硫利达嗪相互作用的靶基因,然后使用STRING在线工具对靶基因进行通路和组织表达富集分析。使用GeneCards和DisGeNET数据库筛选宫颈癌相关基因,与硫利达嗪的靶基因取交集,得到硫利达嗪可能作用于宫颈癌的交互基因。通过STRING构建蛋白互作(PPI)网络,推测核心靶点,评估其重要性。使用clusterProfiler软件进行GO和KEGG通路分析。  结果  通过PharmMapper预测得到47个靶基因,富集到肿瘤相关通路和宫颈癌细胞。与669个宫颈癌基因取交集,获得硫利达嗪和宫颈癌交互基因21个,其中10个关键节点基因为EGFR、PPARG、AR、NOS3、ALB、ESR1、MAPK1、MAPK14、ANXA5和MAPK8,且在宫颈癌PPI网络中处于重要位置。交互基因涉及到的生物进程主要有负离子转运的正调控、丝氨酸肽基磷酸化、类固醇代谢过程、血液凝固、细胞对化学应激的反应等。富集的KEGG通路包括调控癌症通路、松弛素信号通路、内分泌耐药、蛋白聚糖与肿瘤、细胞衰老、GnRH信号通路和VEGF信号通路等。  结论  硫利达嗪具有潜在的抗肿瘤作用,可能通过多靶点和多信号通路的方式在宫颈癌的治疗上发挥作用。
  • 图  1  宫颈癌基因和硫利达嗪靶基因的Upset图

    Figure  1.  Upset map of cervical cancer genes and thioridazine target genes

    图  2  交互基因的蛋白互作网络图

    Figure  2.  PPI network of interacting genes

    图  3  关键靶基因的蛋白互作网络图

    Figure  3.  PPI network of key target genes

    图  4  GO富集分析结果

    Figure  4.  Results of GO enrichment analysis

    图  5  KEGG通路富集分析结果

    Figure  5.  Results of KEGG pathway enrichment analysis

    表  1  排名前10的靶基因通路分析结果

    Table  1.   Top10 pathways results of target genes

    ID号名称基因数FDR
    hsa04926松弛素信号通路91.50E-08
    hsa05200肿瘤通路134.88E-08
    hsa01522内分泌耐药76.70E-07
    hsa05205蛋白聚糖与肿瘤83.01E-06
    hsa05166人类T细胞白血病
    病毒1感染
    84.18E-06
    hsa04218细胞衰老76.70E-06
    hsa04912促性腺激素释放
    激素信号通路
    66.70E-06
    hsa04914孕酮介导的卵
    母细胞成熟
    67.36E-06
    hsa05161乙型肝炎77.36E-06
    hsa04933糖尿病并发症中
    的AGE-RAGE信号通路
    67.85E-06
    下载: 导出CSV

    表  2  排名前10的靶基因疾病富集分析结果

    Table  2.   Top10 disease enrichment results of target genes

    ID号名称基因数FDR
    DOID:162肿瘤120.0022
    DOID:14566细胞增殖疾病130.0022
    DOID:4疾病310.0022
    DOID:65结缔组织疾病100.0064
    DOID:7解剖实体疾病250.0064
    DOID:0050636家族性内脏
    淀粉样变性
    30.0183
    DOID:28内分泌系统疾病70.0183
    DOID:0080001骨疾病80.0184
    DOID:11801蛋白质-能量营
    养不良
    20.0184
    DOID:0060075雌激素受体
    阳性乳腺癌
    20.0244
    下载: 导出CSV

    表  3  排名前10的靶基因组织表达富集分析

    Table  3.   Top10 tissue expression enrichment results of target genes

    ID号名称基因数FDR
    BTO:0000180宫颈癌细胞102.03E-06
    BTO:0000174胚胎结构222.03E-06
    BTO:0000759202.71E-06
    BTO:0000132血小板104.54E-06
    BTO:0001078胎盘164.54E-06
    BTO:0001546慢性淋巴细胞
    白血病细胞
    88.77E-06
    BTO:0001489全身469.93E-06
    BTO:0000345消化腺221.02E-05
    BTO:0001491脏器301.07E-05
    BTO:0000522腺体341.77E-05
    下载: 导出CSV

    表  4  关键靶基因在宫颈癌PPI网络中的排名

    Table  4.   Ranking of key target genes in the cervical cancer PPI network

    靶基因Degree值排名
    EGFR3296
    ALB27113
    ESR125520
    ANXA520032
    PPARG18237
    AR15953
    MAPK114372
    MAPK1414177
    MAPK813879
    NOS3105127
    合计525
    下载: 导出CSV
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