Manoochehri Hamed, Farrokhnia Maryam, Sheykhhasan Mohsen, Mahaki Hanie, Tanzadehpanah Hamid
The Persian Gulf Marine Biotechnology Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran.
Cellular and Molecular Research Center, Qom University of Medical Sciences, Qom, Iran.
Heliyon. 2024 Jul 9;10(14):e34300. doi: 10.1016/j.heliyon.2024.e34300. eCollection 2024 Jul 30.
All-trans retinoic acid (ATRA) has promising activity against breast cancer. However, the exact mechanisms of ATRA's anticancer effects remain complex and not fully understood. In this study, a network pharmacology and molecular docking approach was applied to identify key target genes related to ATRA's anti-breast cancer activity. Gene/disease enrichment analysis for predicted ATRA targets was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID), the Comparative Toxicogenomics Database (CTD), and the Gene Set Cancer Analysis (GSCA) database. Protein-Protein Interaction Network (PPIN) generation and analysis was conducted via Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and cytoscape, respectively. Cancer-associated genes were evaluated using MyGeneVenn from the CTD. Differential expression analysis was conducted using the Tumor, Normal, and Metastatic (TNM) Plot tool and the Human Protein Atlas (HPA). The Glide docking program was used to predict ligand-protein binding. Treatment response predication and clinical profile assessment were performed using Receiver Operating Characteristic (ROC) Plotter and OncoDB databases, respectively. Cytotoxicity and gene expression were measured using MTT/fluorescent assays and Real-Time PCR, respectively. Molecular functions of ATRA targets (n = 209) included eicosanoid receptor activity and transcription factor activity. Some enriched pathways included inclusion body myositis and nuclear receptors pathways. Network analysis revealed 35 hub genes contributing to 3 modules, with 16 of them were associated with breast cancer. These genes were involved in apoptosis, cell cycle, androgen receptor pathway, and ESR-mediated signaling, among others. CCND1, ESR1, MMP9, MDM2, NCOA3, and RARA were significantly overexpressed in tumor samples. ATRA showed a high affinity towards CCND1/CDK4 and MMP9. CCND1, ESR1, and MDM2 were associated with poor treatment response and were downregulated after treatment of the breast cancer cell line with ATRA. CCND1 and ESR1 exhibited differential expression across breast cancer stages. Therefore, some part of ATRA's anti-breast cancer activity may be exerted through the CCND1/CDK4 complex.
全反式维甲酸（ATRA）对乳腺癌具有显著的抗癌活性。然而，ATRA抗癌作用的确切机制仍然复杂，尚未完全明确。在本研究中，采用网络药理学和分子对接方法来鉴定与ATRA抗乳腺癌活性相关的关键靶基因。使用注释、可视化与整合发现数据库（DAVID）、比较毒理基因组学数据库（CTD）和基因集癌症分析（GSCA）数据库对预测的ATRA靶点进行基因/疾病富集分析。分别通过检索相互作用基因/蛋白质的搜索工具（STRING）和Cytoscape生成并分析蛋白质-蛋白质相互作用网络（PPIN）。使用来自CTD的MyGeneVenn评估癌症相关基因。使用肿瘤、正常和转移（TNM）绘图工具以及人类蛋白质图谱（HPA）进行差异表达分析。使用Glide对接程序预测配体-蛋白质结合。分别使用受试者工作特征（ROC）绘图仪和OncoDB数据库进行治疗反应预测和临床特征评估。分别使用MTT/荧光测定法和实时定量PCR测量细胞毒性和基因表达。ATRA靶点（n = 209）的分子功能包括类花生酸受体活性和转录因子活性。一些富集的途径包括包涵体肌炎和核受体途径。网络分析揭示了35个枢纽基因，它们构成3个模块，其中16个与乳腺癌相关。这些基因参与细胞凋亡、细胞周期、雄激素受体途径和雌激素受体（ESR）介导的信号传导等过程。细胞周期蛋白D1（CCND1）、雌激素受体1（ESR1）、基质金属蛋白酶9（MMP9）、小鼠双微体2（MDM2）、核受体共激活因子3（NCOA3）和维甲酸受体α（RARA）在肿瘤样本中显著过表达。ATRA对CCND1/细胞周期蛋白依赖性激酶4（CDK4）和MMP9具有高亲和力。CCND1、ESR1和MDM2与治疗反应不佳相关，在用ATRA处理乳腺癌细胞系后它们的表达下调。CCND1和ESR1在乳腺癌各阶段表现出差异表达。因此，ATRA抗乳腺癌活性的部分作用可能是通过CCND1/CDK4复合物发挥的。
