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The number of possible drug combinations is enormous, and clinicians need knowledge of optimal protein co-targets rather than relying mainly on empirical clinical practice. A signaling-based stratified pipeline is proposed to identify co-target proteins for drug combinations using signaling pathways, network metrics, and tissue-specific co-existing mutations. The approach aims to block parallel or complementary routes, reducing resistance, and was tested on patient-derived breast and colorectal ESR1|PIK3CA and BRAF|PIK3CA subnetworks, yielding promising, xenograft-validated results.",{"@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":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/anticancer-target-combinations-network-informed-signaling-based-approach-to-discovery/329941/",{"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/anticancer-target-combinations-network-informed-signaling-based-approach-to-discovery/329941.png","ImageObject",300,407,{"name":92,"@type":93},"Ophelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-24","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why are combination strategies important in anticancer drug discovery?","Question",{"text":112,"@type":113},"Sequential single therapies are limited by resistance, and many drug combinations remain unexplored. Combinatorial strategies help target multiple proteins to reduce the chance that cancer bypasses blocked targets.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What is the proposed method based on?",{"text":117,"@type":113},"The method is a signaling-based, network-informed stratified pipeline. It selects co-target proteins using signaling pathways, network concepts and metrics, and tissue-specific co-existing mutations.",{"name":119,"@type":110,"acceptedAnswer":120},"How was the approach tested and what were the findings?",{"text":121,"@type":113},"It was applied to patient-derived breast and colorectal ESR1|PIK3CA and BRAF|PIK3CA subnetworks. Results suggested effective co-targeting protein pairs with specific drug combinations, and the pipeline’s results were validated using patient-based xenografts.","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},329941,1790394036,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"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,"preview_page_count":4},7971461741311,"https://ap-avatar.wpscdn.com/avatar/74000253aff267980c6?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779345379180704826","bioRxiv preprint doi: [https://doi.org/10.1101/2024.10.11.617918](https://doi.org/10.1101/2024.10.11.617918); this version posted October 15, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made  \navailable under aCC-BY-NC 4.0 International license.  \n1 Anticancer Target Combinations: Network- 2 Informed Signaling-Based Approach to  \n3 Discovery  \n4 Bengi Ruken Yavuz 1, Hyunbum Jang 1,2, and Ruth Nussinov1,2,3 * 5  \n6 1Cancer Innovation Laboratory, National Cancer Institute at Frederick, Frederick, MD 21702,  \n7 USA  \n8 2Computational Structural Biology Section, Frederick National Laboratory for Cancer Research, 9 Frederick, MD 21702, USA  \n10 3Department of Human Molecular Genetics and Biochemistry, Sackler School of Medicine, Tel  \n11 Aviv University, Tel Aviv 69978, Israel 12  \n13  \n14  \n15 *Corresponding Author: RN, [NussinoR@mail.nih.gov](NussinoR@mail.nih.gov)  \n16 Ruth Nussinov  \n17 Frederick National Laboratory for Cancer Research  \n18 Frederick, MD 21702, U. S.A.  \n19 Phone: 301-846-5579  \n20 [E-mails:](E-mails: NussinoR@mail.nih.gov)[ ](E-mails: NussinoR@mail.nih.gov)[NussinoR@mail.nih.gov](E-mails: NussinoR@mail.nih.gov)  \n21  \n22  \n23  \n24  \nbioRxiv preprint doi: [https://doi.org/10.1101/2024.10.11.617918](https://doi.org/10.1101/2024.10.11.617918); this version posted October 15, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made  \navailable under aCC-BY-NC 4.0 International license.  \n25 Abstract  \n26  \n27 While anticancer drug discovery has seen dramatic innovations and successes, sequential single  \n28 therapies are time-limited by resistance, and combinatorial strategies have been lagging. The  \n29 number of possible drug combinations is vast. To select drug combinations the oncologist requires  \n30 knowledge of the optimal combination of proteins to co-target. Currently, combinations that the  \n31 oncologist considers are primarily from empirical observations and clinical praxis. Our aim is to  \n32 develop a signaling-based method to discover optimal proteins for the oncologist to co-target with  \n33 drug combinations, and test it on available, patient-derived data. To temper the expected resistance  \n34 to single drug regimen, we offer a concept-based stratified pipeline aimed at selecting co-targets  \n35 for drug combinations. Our strategy is unique in its co-target selection being based on signaling  \n36 pathways. This is significant since in cancer, drug resistance commonly bypasses blocked proteins  \n37 by wielding alternative, or complementary, routes to execute cell proliferation. Our network- 38 informed signaling-based approach harnesses advanced network concepts and metrics, and our  \n39 compiled, tissue-specific co-existing mutations. Co-existing driver mutations are common in  \n40 resistance. Thus, to mimic cancer and counter drug resistance scenarios, our pipeline seeks co- 41 targets that when targeted by drug combinations, can shut off cancer’s modus operandi. That is, 42 its parallel or complementary signaling pathways would be blocked. Rotating through  \n43 combinations could further lessen emerging resistance. We applied it to patient-derived breast and  \n44 colorectal ESR1|PIK3CA and BRAF|PIK3CA subnetworks. Consistently, in breast cancer, our  \n45 results suggest co-targeting proteins from the ESR1|PIK3CA subnetwork with an alpelisib- 46 LJM716 combination. In colorectal cancer, they co-target BRAF|PIK3CA with alpelisib,  \nbioRxiv preprint doi: [https://doi.org/10.1101/2024.10.11.617918](https://doi.org/10.1101/2024.10.11.617918); this version posted October 15, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display th","cbCaiuhLod97OZ2O","https://ap.wps.com/l/cbCaiuhLod97OZ2O","pdf",7436512,74,"English","# Abstract\n# Keywords\n# Introduction","[{\"question\":\"Why are combination strategies important in anticancer drug discovery?\",\"answer\":\"Sequential single therapies are limited by resistance, and many drug combinations remain unexplored. Combinatorial strategies help target multiple proteins to reduce the chance that cancer bypasses blocked targets.\"},{\"question\":\"What is the proposed method based on?\",\"answer\":\"The method is a signaling-based, network-informed stratified pipeline. It selects co-target proteins using signaling pathways, network concepts and metrics, and tissue-specific co-existing mutations.\"},{\"question\":\"How was the approach tested and what were the findings?\",\"answer\":\"It was applied to patient-derived breast and colorectal ESR1|PIK3CA and BRAF|PIK3CA subnetworks. Results suggested effective co-targeting protein pairs with specific drug combinations, and the pipeline’s results were validated using patient-based xenografts.\"}]","Anticancer Target Combinations - Network-Informed Signaling-Based Approach to Discovery | PDF",1789986223,186]