[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-328266-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-328266-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","shared-genetics-between-breast-cancer-and-predisposing-diseases-identifies-novel-breast-cancer-treatments-abstract","Shared Genetics Between Breast Cancer and Predisposing Diseases Identifies Novel Breast Cancer Treatments - Abstract","","Current effective breast cancer treatments often produce severe side effects, motivating new therapies. Drug repurposing can speed progress because FDA-approved drugs already have known safety and pharmacological profiles. Here, shared genetics between breast cancer and linked predisposing diseases is used to propose novel repurposing candidates. GWAS summary statistics identify pleiotropic genes under genetic correlation, which are mapped to pathways and linked to drug targets. This prioritizes drugs by predisposing disease and highlights shared etiology explaining repurposing.",{"@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/shared-genetics-between-breast-cancer-and-predisposing-diseases-identifies-novel-breast-cancer-treatments-abstract/328266/",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/shared-genetics-between-breast-cancer-and-predisposing-diseases-identifies-novel-breast-cancer-treatments-abstract/328266.png","ImageObject",300,407,{"name":42,"@type":43},"Maeve","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",7,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What is the main motivation for the study?","Question",{"text":63,"@type":64},"Breast cancer treatments can cause severe side effects, and there is a need for new therapies. The study also aims to accelerate drug repurposing by using shared genetics with known risk factors.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How are shared genetic signals used to propose drug repurposing?",{"text":68,"@type":64},"Predisposing diseases are compiled from literature, and GWAS summary statistics identify genes in loci genetically correlated with breast cancer. Shared genes are then connected via a network approach to canonical pathways, and drugs treating the predisposing diseases are linked through their targets to those pathways.",{"name":70,"@type":61,"acceptedAnswer":71},"What key findings support the approach?",{"text":72,"@type":64},"The analysis identifies 84 positively correlated loci containing 194 shared genes and links 76 drugs to shared genes via pathways. Among candidate drugs, 15 are already in advanced clinical trials or approved for breast cancer, indicating the method can recover likely successful candidates.","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},328266,1790930770,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,114,119,122,126],{"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":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":107,"show_sort_weight":108,"slug":109},"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":97,"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},5909877438554,"https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272","University of Massachusetts Lowell  \nUniversity of Massachusetts Lowell  \nbreast cancer, shared genetics, predisposing disease, risk factors, drug repurposing, drug genetics  \n June 21st, 2024  \n [https://doi.org/10.21203/rs.3.rs-4536370/v1](https://doi.org/10.21203/rs.3.rs-4536370/v1)  \n 􀁱 􀅏 This work is licensed under a Creative Commons Attribution 4.0 International License.  \nRead Full License  \n No competing interests reported.  \nCurrent effective breast cancer treatment options have severe side effects, highlighting a need for new therapies. Drug repurposing can accelerate improvements to care, as FDA-approved drugs have known safety and pharmacological pro¦les. Some drugs for other conditions, such as metformin, an antidiabetic, have been tested in clinical trials for repurposing for breast cancer. Here, we exploit the genetics of breast cancer and linked predisposing diseases to propose novel drug repurposing. We hypothesize that if a predisposing disease contributes to breast cancer pathology, identifying the pleiotropic genes related to the risk of cancer could prioritize drug targets, among all drugs treating a predisposing disease. We aim to develop a method to not only prioritize drug repurposing, but also to highlight shared etiology explaining repurposing.  \nWe compile breast cancer's predisposing diseases from literature. For each predisposing disease, we use GWAS summary statistics to identify genes in loci showing genetic correlation with breast cancer. Then, we use a network approach to link these shared genes to canonical pathways, and similarly for all drugs treating the predisposing disease, we link their targets to pathways. In this manner, we are able to prioritize a list of drugs based on each predisposing disease, with each drug linked to a set of implicating pathways. Finally, we evaluate our recommendations against drugs currently under investigation for breast cancer.  \nWe identify 84 loci harboring mutations with positively correlated effects between breast cancer and its predisposing diseases; these contain 194 identi¦ed shared genes. Out of the 112 drugs indicated for the predisposing diseases, 76 drugs can be linked to shared genes via pathways (candidate drugs for repurposing) . Fifteen out of these candidate drugs are already in advanced clinical trial phases or approved for breast cancer (OR = 9 .28, p = 7 .99e-03, one-sided Fisher’s exact test), highlighting the ability of our approach to identify likely successful candidate drugs for repurposing.  \nOur novel approach accelerates drug repurposing for breast cancer by leveraging shared genetics with its known risk factors. The result provides 59 novel candidate drugs alongside biological insights supporting each recommendation.  \nBreast cancer is a major public health issue and the most common type of cancer in women worldwide ( 1) . Current treatment options, such as chemotherapy, hormone therapy, and immunotherapy (2), while effective, often have severe side-effects that impair patients’ quality of life and adherence to treatment (3, 4) . On the other hand, existing FDA-approved drugs have established safety and pharmacological pro¦les and testing them for repurposing for breast cancer treatment has been an attractive strategy (5) . For instance, metformin, the most commonly prescribed anti-diabetic drug, has shown anti-proliferative effects in pre-clinical studies and is currently undergoing clinical trials for breast cancer treatment. This surprising effect may be explained by its downstream effects activating AMPK protein kinase, a tumor suppressor critical in regulating cell proliferation (6, 7) . However, oncology clinical trials are slow, expensive and have up to 95% attrition rates, mainly due to lack of understanding of the mechanism of action of the tested drug prior to the clinical trial (8–10) . Therefore, new approaches are needed to both accelerate drug repurposing for breast cancer treatment and provide biological insights to ","cbCaicCzKNjahRkb","https://ap.wps.com/l/cbCaicCzKNjahRkb","pdf",1489233,"English","# Background\n# Methods\n# Results\n# Implications","[{\"question\":\"What is the main motivation for the study?\",\"answer\":\"Breast cancer treatments can cause severe side effects, and there is a need for new therapies. The study also aims to accelerate drug repurposing by using shared genetics with known risk factors.\"},{\"question\":\"How are shared genetic signals used to propose drug repurposing?\",\"answer\":\"Predisposing diseases are compiled from literature, and GWAS summary statistics identify genes in loci genetically correlated with breast cancer. Shared genes are then connected via a network approach to canonical pathways, and drugs treating the predisposing diseases are linked through their targets to those pathways.\"},{\"question\":\"What key findings support the approach?\",\"answer\":\"The analysis identifies 84 positively correlated loci containing 194 shared genes and links 76 drugs to shared genes via pathways. Among candidate drugs, 15 are already in advanced clinical trials or approved for breast cancer, indicating the method can recover likely successful candidates.\"}]","Shared Genetics Between Breast Cancer and Predisposing Diseases Identifies Novel Breast Cancer Treatments - Abstract | PDF",1789979108,48]