[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-333621-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-333621-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","key-target-genes-related-to-anti-breast-cancer-activity-of-atra-a-network-pharmacology-molecular-docking-and-experimental-investigation","Key target genes related to anti-breast cancer activity of ATRA - A network pharmacology, molecular docking and experimental investigation","","All-trans retinoic acid (ATRA) shows promising activity against breast cancer, yet the precise mechanisms behind its anticancer effects remain complex. This study applied a network pharmacology and molecular docking workflow to identify key target genes involved in ATRA’s anti-breast cancer activity. Predicted targets underwent gene/disease enrichment using DAVID, CTD and GSCA, followed by protein-protein interaction analysis via STRING and Cytoscape. Molecular functions and enriched pathways supported major roles in eicosanoid and transcription factor activity, while hub genes and modules linked to apoptosis and cell-cycle regulation were highlighted, with validation by expression and cytotoxicity assays.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & Report",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/key-target-genes-related-to-anti-breast-cancer-activity-of-atra-a-network-pharmacology-molecular-docking-and-experimental-investigation/333621/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/key-target-genes-related-to-anti-breast-cancer-activity-of-atra-a-network-pharmacology-molecular-docking-and-experimental-investigation/333621.png","ImageObject",300,407,{"name":42,"@type":43},"Noah","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-10-28","2026-09-21",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",5,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What was the main goal of the study on ATRA and breast cancer?","Question",{"text":63,"@type":64},"To identify key target genes related to ATRA’s anti-breast cancer activity using a network pharmacology strategy combined with molecular docking and experimental validation.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"Which databases and tools were used to analyze predicted ATRA targets?",{"text":68,"@type":64},"Gene/disease enrichment used DAVID, CTD and GSCA; protein-protein interaction networks were generated using STRING and analyzed with Cytoscape; differential expression used TNM Plot and Human Protein Atlas.",{"name":70,"@type":61,"acceptedAnswer":71},"What types of genes and pathways were highlighted by the network analysis?",{"text":72,"@type":64},"The analysis revealed hub genes within multiple modules, with many linked to processes such as apoptosis and cell-cycle regulation, and signaling pathways including ESR-mediated signaling; CCND1 and ESR1 were reported as associated with differential expression and treatment response.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},333621,1791081752,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,100,105,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":97,"show_sort_weight":98,"slug":99},"Comic",60,"comic",{"id":101,"doc_module":4,"doc_module_name":25,"category_name":102,"show_sort_weight":103,"slug":104},6,"Technology",50,"technology",{"id":106,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},7,"Healthcare",40,"healthcare",{"id":111,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":112,"slug":113},8,30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":55,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":111,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":127,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144,"preview_page_count":4},8796095462418,"https://ap-avatar.wpscdn.com/avatar/80000253c1241d02b47?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778826106357471780","Heliyon 10 (2024) e34300  \nContents lists available at ScienceDirect  \nHeliyon  \njournal [homepage:](homepage: www.cell.com/heliyon)[ www.cell.com/heliyon](homepage: www.cell.com/heliyon)  \nResearch article  \nKey target genes related to anti-breast cancer activity of ATRA: A network pharmacology, molecular docking and  \nexperimental investigation  \nHamed Manoochehri a , Maryam Farrokhnia a, * , Mohsen Sheykhhasan b , Hanie Mahaki c , Hamid Tanzadehpanah d, e  \na The Persian Gulf Marine Biotechnology Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran  \nb Cellular and Molecular Research Center, Qom University of Medical Sciences, Qom, Iran  \nc Vascular and Endovascular Surgery Research Center, Mashhad University of Medical Sciences, Mashhad, Iran d Antimicrobial Resistance Research Center, Mashhad University of Medical Sciences, Mashhad, Iran e Metabolic Syndrome Research Center, Mashhad University of Medical Sciences, Mashhad, Iran  \nA R T I C L E I N F O  \nKeywords:  \nAll-trans-retinoic acid Breast neoplasia Drug-target prediction Network pharmacology  \nProtein-protein interaction network  \nA B S T R A C T  \nAll-trans retinoic acid (ATRA) has promising activity against breast cancer. However, the exact mechanisms ofATRA’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  \n* Corresponding author. The Persian Gulf Biomedical Sciences Research Institute, Parastar Street, Molalem Square, Bushehr, Iran. E-mail address: [farrokhnia.m@gmail.com](farrokhnia.m@gmail.com) (M. Farrokhnia).  \n[https://doi.org/10.1016/j.heliyon.2024.e34300](https://doi.org/10.1016/j.heliyon.2024.e34300)  \nReceived 17 April 2024; Received in revised form 5 July 2024; Accepted 8 July 2024 Available online 9 July 2024  \n2405-8440/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)).  \nH. Manoochehri et al.  \nHeli","cbCaibYgdDU9sZGQ","https://ap.wps.com/l/cbCaibYgdDU9sZGQ","pdf",14308450,"English","# Introduction\n## Breast cancer burden and heterogeneity\n## Current therapeutic classes and limitations\n## TNBC characteristics and emerging options","[{\"question\":\"What was the main goal of the study on ATRA and breast cancer?\",\"answer\":\"To identify key target genes related to ATRA’s anti-breast cancer activity using a network pharmacology strategy combined with molecular docking and experimental validation.\"},{\"question\":\"Which databases and tools were used to analyze predicted ATRA targets?\",\"answer\":\"Gene/disease enrichment used DAVID, CTD and GSCA; protein-protein interaction networks were generated using STRING and analyzed with Cytoscape; differential expression used TNM Plot and Human Protein Atlas.\"},{\"question\":\"What types of genes and pathways were highlighted by the network analysis?\",\"answer\":\"The analysis revealed hub genes within multiple modules, with many linked to processes such as apoptosis and cell-cycle regulation, and signaling pathways including ESR-mediated signaling; CCND1 and ESR1 were reported as associated with differential expression and treatment response.\"}]","Key target genes related to anti-breast cancer activity of ATRA - A network pharmacology, molecular docking and experimental investigation | PDF",1790003291,48]