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Systematic screening helps find combinations that are clinically relevant for specific patient subtypes. This study reports data for 109 anticancer combinations tested across 755 pan-cancer cell lines using a 7×7 concentration matrix with over four million sensitivity measurements. A workflow based on combination Emax and the highest single agent method prioritizes clinically translatable hits, supported by multi-omics predictors and emergent biomarker rationale, with experimentally confirmed in vitro and in vivo combinations focused on hematologic cancers and apoptotic targets.",{"@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/large-scale-pan-cancer-cell-line-screening-identifies-actionable-and-effective-drug-combinations/342762/",{"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/large-scale-pan-cancer-cell-line-screening-identifies-actionable-and-effective-drug-combinations/342762.png","ImageObject",300,407,{"name":92,"@type":93},"Aurora","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-24","2026-09-22",true,{"@type":102,"interactionType":103,"userInteractionCount":8},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why are systematic drug combination screens needed in oncology?","Question",{"text":112,"@type":113},"Single agents often show limited activity in patients, and effects of combinations are context-specific. Systematic screens help identify combinations that are clinically relevant and actionable for defined patient subtypes.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were drug combinations evaluated in this study?",{"text":117,"@type":113},"109 anticancer combinations were tested using a 7×7 concentration matrix across 755 pan-cancer cell lines, generating more than four million sensitivity measurements. Benefit was assessed with combination Emax and the highest single agent approach.",{"name":119,"@type":110,"acceptedAnswer":120},"What makes the study’s workflow clinically translatable?",{"text":121,"@type":113},"The workflow prioritizes hits by defining patient populations, linking tolerability rationale to tumor type and combination-specific emergent biomarkers, and using exposures aligned to clinical doses.","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},342762,1790241009,{"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":8,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":46,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":31},4810365810221,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","RESEARCH ARTICLE  \nLarge-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug  \nCombinations   \nAzadeh C. Bashi1, Elizabeth A. Coker2, Krishna C. Bulusu1, Patricia Jaaks2, Claire Crafter1,  \nHoward Lightfoot2, Marta Milo1, Katrina McCarten2, David F. Jenkins3, Dieudonne van der Meer2,  \nJames T. Lynch1, Syd Barthorpe2, Courtney L. Andersen3, Simon T. Barry1, Alexandra Beck2, Justin Cidado3, Jacob A. Gordon3, Caitlin Hall2, James Hall2, Iman Mali2, Tatiana Mironenko2, Kevin Mongeon3,  \nJames Morris2, Laura Richardson2, Paul D. Smith1, Omid Tavana3, Charlotte Tolley2, Frances Thomas2, Brandon S. Willis3, Wanjuan Yang2, Mark J. O’Connor1, Ultan McDermott1, Susan E. Critchlow1, Lisa Drew3, Stephen E. Fawell3, Jerome T. Mettetal3, and Mathew J. Garnett2  \nABSTRACT  Oncology drug combinations can improve therapeutic responsesand increase treatment options for patients. The number of possible combinations is vast and responses  \ncan be context-specific. Systematic screens can identify clinically relevant, actionable combinations in defined patient subtypes. We present data for 109 anticancer drug combinations from AstraZeneca’s oncology small molecule portfolio screened in 755 pan-cancer cell lines. Combinations were screened in a 7 × 7 concentration matrix, with more than 4 million measurements of sensitivity, producing an exceptionally data-rich resource. We implement a new approach using combination Emax (viability effect) and highest single agent (HSA) to assess combination benefit. We designed a clinical translatability workflow to identify combinations with clearly defined patient populations, rationale for tolerability based on tumor type and combination-specific “emergent” biomarkers, and exposures relevant to clinical doses. We describe three actionable combinations in defined cancer types, confirmed in vitro and in vivo, with a focus on hematologic cancers and apoptotic targets.  \nSIGNIFICANCE: We present the largest cancer drug combination screen published to date with 7 × 7 concentration response matrices for 109 combinations in more than 750 cell lines, complemented by multi-omics predictors of response and identification of“emergent” combination biomarkers. We prioritize hits to optimize clinical translatability, and experimentally validate novel combination hypotheses.  \nINTRODUCTION  \nMany anticancer agents have limited single agent activity in the clinic, making drug combinations an important treatment strategy. The first successful combination chemotherapy, introduced more than 50 years ago, consisted of a cocktail of four drugs (cyclophosphamide, vincristine, procarbazine, and prednisone) and resulted in durable clinical responses in patients with Hodgkin lymphoma (1, 2) . These chemotherapy combinations were often determined empirically in the clinic using existing monotherapy treatments. The recent advent of molecularly targeted agents has led to the development of more rationally designed combinations. Inhibiting multiple nodes in either the same or parallel signaling pathways can help tackle problems such as pathway redundancy, feedback reactivation, and tumor heterogeneity, all of which can contribute to reduced efficacy and disease progression (3) . There are, however, several challenges that need to be addressed when identifying efficacious drug combinations. First, obtaining deep pharmacologic profiles of available targeted and chemotherapeutic agents is a complex  \n1Oncology R&D, AstraZeneca, Cambridge, United Kingdom. 2Wellcome Sanger Institute, Cambridge, United Kingdom. 3Oncology R&D, AstraZeneca, Waltham, Massachusetts.  \nP. Jaaks and C. Crafter are joint second authors.  \nA.C. Bashi, E.A. Coker, and K.C. Bulusu contributed equally to this article. Current address for E.A. Coker: Oncology R&D, AstraZeneca, Cambridge, United Kingdom.  \nCorresponding Authors: Mathew J. Garnett, Wellcome Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, United [Kingdom. E-mail: mg12@sanger.ac.uk","cbCaiuC9hlad4WJR","https://ap.wps.com/l/cbCaiuC9hlad4WJR","pdf",19866811,"English","# Abstract\n# Significance\n# Introduction\n## Rationale for drug combination strategies\n## Challenges in identifying effective combinations","[{\"question\":\"Why are systematic drug combination screens needed in oncology?\",\"answer\":\"Single agents often show limited activity in patients, and effects of combinations are context-specific. Systematic screens help identify combinations that are clinically relevant and actionable for defined patient subtypes.\"},{\"question\":\"How were drug combinations evaluated in this study?\",\"answer\":\"109 anticancer combinations were tested using a 7×7 concentration matrix across 755 pan-cancer cell lines, generating more than four million sensitivity measurements. Benefit was assessed with combination Emax and the highest single agent approach.\"},{\"question\":\"What makes the study’s workflow clinically translatable?\",\"answer\":\"The workflow prioritizes hits by defining patient populations, linking tolerability rationale to tumor type and combination-specific emergent biomarkers, and using exposures aligned to clinical doses.\"}]","Large-scale Pan-cancer Cell Line Screening Identifies Actionable and Effective Drug Combinations | PDF",1790048078]