[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-339848-105":59,"doc-detail-339848-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","insights-into-immune-microenvironment-and-therapeutic-targeting-in-androgen-associated-prostate-cancer-subtypes-research-paper","Insights into immune microenvironment and therapeutic targeting in androgen-associated prostate cancer subtypes - research paper","","Androgen signaling is central to prostate cancer development, and distinct androgen-responsive gene programs may shape patient prognosis and therapeutic response. Using consensus clustering on androgen-responsive gene expression from TCGA, patients were separated into two subtypes (C1 and C2) with different survival outcomes. Comparative analyses characterized immune infiltration, mutation patterns, and functional pathways. Integrated bioinformatics and machine learning highlighted candidate therapeutic genes, while single-cell transcriptomics mapped heterogeneous expression across tumor microenvironment cell types. Virtual screening proposed candidate drugs targeting BIRC5-associated interactions, supporting subtype-specific precision therapy.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/insights-into-immune-microenvironment-and-therapeutic-targeting-in-androgen-associated-prostate-cancer-subtypes-research-paper/339848/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/insights-into-immune-microenvironment-and-therapeutic-targeting-in-androgen-associated-prostate-cancer-subtypes-research-paper/339848.png","ImageObject",300,407,{"name":92,"@type":93},"Ezra","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-28","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"How were prostate cancer patients classified into subtypes in the study?","Question",{"text":112,"@type":113},"Patients from the TCGA database were stratified using consensus clustering based on the expression profiles of androgen-responsive genes, resulting in two subtypes (C1 and C2).","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What differences between the two subtypes were reported?",{"text":117,"@type":113},"The study reports subtype-specific patterns in gene upregulation, immune infiltration, mutation landscapes, and functional pathways, and it notes a shorter progression-free survival in the C1 subtype.",{"name":119,"@type":110,"acceptedAnswer":120},"What therapeutic targets and drug candidates were identified?",{"text":121,"@type":113},"Integrated bioinformatics and machine learning highlighted genes such as BIRC5, CENPA, and MMP11 as potential therapeutic targets, and virtual screening identified candidate drugs targeting BIRC5-associated interactions.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},339848,1790447276,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145},1099514068035,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nInsights into immune microenvironment and therapeutic targeting in androgen‑associated prostate cancer subtypes  \nLiang Huang1, Yu Xie1, Shusuan Jiang1, Tao Dai1, Zhenzhou Xu1 & Hong Shan2*  \nProstate cancer, one of the most prevalent malignancies among men worldwide, is intricately linked with androgen signaling, a key driver of its pathogenesis and progression. Understanding the diverse expression patterns of androgen‑responsive genes holds paramount importance in unraveling the biological intricacies of this disease and prognosticating patient outcomes. In this study, utilizing consensus clustering analysis based on the expression profiles of androgen‑responsive genes, prostate cancer patients from theTCGA database were stratified into two distinct subtypes, denoted as C1 and C2 . Notably, the C1 subtype demonstrates a significant upregulation of certain genes, such as CGA and HSD17B12, along with a shorter progression‑free survival duration, indicating a potentially unfavorable prognosis. Further analyses elucidated the immune infiltration disparities, mutation landscapes, and gene functional pathways characteristic of each subtype. Through integrated bioinformatics approaches and machine learning techniques, key genes such as BIRC5, CENPA, and MMP11 were identified as potential therapeutic targets, providing novel insights into tailored treatment strategies. Additionally, single‑cell transcriptome analysis shed light on the heterogeneous expression patterns of these genes across different cell types within the tumor microenvironment. Furthermore, virtual screening identified candidate drugs targeting the BIRC5 receptor, offering promising avenues for drug development. Collectively, these findings deepen our understanding of prostate cancer biology, paving the way for personalized therapeutic interventions and advancing the quest for more effective treatments in prostate cancer management.  \nKeywords Prostate cancer, Androgen-responsive genes, Tumor microenvironment, Machine learning, Immune infiltration  \nProstate cancer is the second most common cancer in men and the fifth leading cause of death worldwide, and its incidence is closely related to age1. As a complex disease, its development and progression are influenced by a variety of genetic and environmental factors, making it a significant challenge in the field of oncology2,3. Despite advances in diagnostic methods, the variability in how the disease progresses—ranging from indolent to aggressively metastatic forms—poses unique challenges for treatment and management4. Early detection through prostate-specific antigen testing has improved outcomes, yet the heterogeneity of the disease often leads to variable responses to conventional therapies, underlining the need for more personalized approaches to treatment5,6.  \nAndrogens, such as testosterone, play a pivotal role in the normal development and functioning of the prostate gland but are also implicated in the pathogenesis of prostate cancer7,8. These hormones exert their effects by binding to the androgen receptor (AR), which then activates a cascade of genetic expressions that promote cellular growth and survival9. In the context of prostate cancer, the AR pathway is a critical driver of tumor growth and progression, making it a primary target for therapeutic intervention10, 11. androgen deprivation therapy (ADT), which inhibit the action of testosterone or the AR itself, have been standard treatments and provide significant benefits in many cases12–14. However, resistance to these therapies frequently develops, leading to disease progression and the need for alternative strategies15–17.  \n1Department of Urology, the Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Hunan Cancer Hospital, Changsha, Hunan, China. 2Department of Emergency Medicine, The Affiliated Changsha Central Hospital, Hengyang Medic","cbCairJS1QE1wv7Z","https://ap.wps.com/l/cbCairJS1QE1wv7Z","pdf",9508398,15,"English","# Methods\n## Data collection","[{\"question\":\"How were prostate cancer patients classified into subtypes in the study?\",\"answer\":\"Patients from the TCGA database were stratified using consensus clustering based on the expression profiles of androgen-responsive genes, resulting in two subtypes (C1 and C2).\"},{\"question\":\"What differences between the two subtypes were reported?\",\"answer\":\"The study reports subtype-specific patterns in gene upregulation, immune infiltration, mutation landscapes, and functional pathways, and it notes a shorter progression-free survival in the C1 subtype.\"},{\"question\":\"What therapeutic targets and drug candidates were identified?\",\"answer\":\"Integrated bioinformatics and machine learning highlighted genes such as BIRC5, CENPA, and MMP11 as potential therapeutic targets, and virtual screening identified candidate drugs targeting BIRC5-associated interactions.\"}]","Insights into immune microenvironment and therapeutic targeting in androgen-associated prostate cancer subtypes - research paper | PDF",1790032622,38]