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A genetics-driven method prioritizes pleiotropic genes and links shared targets to canonical pathways, then evaluates recommendations against drugs already under investigation. 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\n[https://doi.org/10.1186/s40246-024-00688-4](https://doi.org/10.1186/s40246-024-00688-4)  \nRESEARCH Open Access  \nShared genetics between breast cancer and predisposing diseases identifies novel breast cancer treatment candidates  \nPanagiotis N. Lalagkas 1 and Rachel D. Melamed 1*  \nAbstract  \nBackground Current 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 profiles. 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 opportunities. We hypothesize that if a predisposing disease contributes to breast cancer pathology, identifying the pleiotropic genes related to the risk of cancer could prioritize drugs, among all drugs treating a predisposing disease. We aim to develop a method to not only prioritize drugs for repurposing, but also to highlight shared etiology explaining repurposing.  \nMethods We compile breast cancer’s predisposing diseases from literature. For each predisposing disease, we use GWAS summary statistics data 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. 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.  \nResults We identify 84 loci harboring mutations with positively correlated effects between breast cancer and its predisposing diseases; these contain 194 identified shared genes. Out of the 112 drugs indicated for the predisposing diseases, 74 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.  \nConclusions Our novel approach accelerates drug repurposing for breast cancer by leveraging shared genetics with its known predisposing diseases. The result provides 59 novel candidate drugs alongside biological insights supporting each recommendation.  \nKeywords Breast cancer, Shared genetics, Predisposing disease, Risk factors, Drug repurposing, Drug genetics  \n*Correspondence:  \nRachel D. Melamed  \n[Rachel_Melamed@uml.edu](Rachel_Melamed@uml.edu)  \n1Department of Biological Sciences, University of Massachusetts, Lowell, MA, USA  \n© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/l](http://creativecommons.org/l)icenses/by/4.0/.  \nLalagkas and Melamed Human Genomics (2024) 18:124  \nBac","cbCaia5CgJ1QQWlZ","https://ap.wps.com/l/cbCaia5CgJ1QQWlZ","pdf",1900812,11,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Background\n## Existing treatments and limitations\n## Rationale for genetics-informed repurposing","[{\"question\":\"What is the main goal of the study on shared genetics?\",\"answer\":\"To leverage shared genetics between breast cancer and predisposing diseases to prioritize drug repurposing candidates and provide biological explanations for shared etiology.\"},{\"question\":\"How are predisposing diseases and shared genetic signals used in the method?\",\"answer\":\"The approach compiles predisposing diseases from literature, then uses GWAS summary statistics to identify genes in loci with genetic correlation to breast cancer.\"},{\"question\":\"What outcomes does the study report from its prioritization pipeline?\",\"answer\":\"It identifies shared genes and links many drugs for predisposing diseases to implicated pathways, including drugs that are already in advanced clinical trials or approved for breast cancer.\"}]","Shared genetics between breast cancer and predisposing diseases identifies novel breast cancer treatment candidates - Research open access | PDF",1789984047,28]