[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-331512-105":59,"doc-detail-331512-en":131},{"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":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","normal-tissue-transcriptional-signatures-for-tumor-type-agnostic-phenotype-prediction","Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction","","Cancer transcriptional patterns contain both type-specific traits and shared hallmarks, yet whether they sufficiently capture the full heterogeneity of tumor phenotypes remains unresolved. The study proposes that shared transcriptomic signatures reflect repurposed functional tasks of normal tissues. Starting from normal tissue transcriptomic profiles, non-negative matrix factorization derives six archetypal transcriptomic phenotypes that jointly describe normal patterns and malignant variations. Signature enrichment tracks tumor survival and drug sensitivity beyond actionable DNA alterations, and HR+/HER2- breast metastases show signatures resembling invaded tissue.",{"@graph":69,"@context":123},[70,84,106],{"@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/normal-tissue-transcriptional-signatures-for-tumor-type-agnostic-phenotype-prediction/331512/",{"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/normal-tissue-transcriptional-signatures-for-tumor-type-agnostic-phenotype-prediction/331512.png","ImageObject",300,407,{"name":92,"@type":93},"Eden","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-24","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",13,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main hypothesis of the study?","Question",{"text":113,"@type":114},"The study hypothesizes that shared transcriptomic signatures arise from repurposed functional tasks performed by normal tissues.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How are the six transcriptomic phenotypes (archetypes) derived?",{"text":118,"@type":114},"The authors use non-negative matrix factorization starting from normal tissue transcriptomic profiles to obtain six distinct archetypes.",{"name":120,"@type":111,"acceptedAnswer":121},"What tumor characteristics do the normal tissue signatures correlate with?",{"text":122,"@type":114},"Differential enrichment of these signatures correlates with patient survival and drug sensitivity, independent of clinically actionable DNA alterations.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},331512,1790008902,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":105,"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},1374391974468,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nNormal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction  \nCorey Weistuch1, Kevin A. Murgas2, Jiening Zhu3, Larry Norton4, Ken A. Dill5, Allen R. Tannenbaum3,6 & Joseph O. Deasy1􀀍  \nCancer transcriptional patterns reflect both unique features and shared hallmarks across diverse cancer types, but whether differences in these patterns are sufficient to characterize the full breadth of tumor phenotype heterogeneity remains an open question. We hypothesized that these shared transcriptomic signatures reflect repurposed versions of functional tasks performed by normal tissues. Starting with normal tissue transcriptomic profiles, we use non-negative matrix factorization to derive six distinct transcriptomic phenotypes, called archetypes, which combine to describe both normal tissue patterns and variations across a broad spectrum of malignancies. We show that differential enrichment of these signatures correlates with key tumor characteristics, including overall patient survival and drug sensitivity, independent of clinically actionable DNA alterations. Additionally, we show that in HR+/HER2-breast cancers, metastatic tumors adopt transcriptomic signatures consistent with the invaded tissue. Broadly, our findings suggest that cancer often arrogates normal tissue transcriptomic characteristics as a component of both malignant progression and drug response. This quantitative framework provides a strategy for connecting the diversity of cancer phenotypes and could potentially help manage individual patients.  \nKeywords Molecular profiling, Metastatic breast cancer, Drug sensitivity prediction, Cancer ecology and evolution, Prognosis  \nRecent studies have identified conserved phenotype states that predict drug sensitivities and other critical cancer traits across various tumor types1–6. These advances have been driven by the adoption of novel mathematical methods in biological research, particularly for characterizing the geometry and clustering of high-dimensional data4,5,7–10. Distances from these clusters or “states” can then linked to specific drug sensitivities, metastatic potentials, and other key cancer traits2, 10–13. Such approaches have shown promise in guiding therapy selection and personalized treatment planning across tumor types, particularly for rare and therapy-resistant malignancies10.  \nThe immense phenotype diversity of cancer phenotypes poses a significant challenge, with no universally accepted standard for defining and measuring shared tumor states. Developing a standardized atlas of systemlevel, multi-gene properties could be crucial for monitoring, predicting, and treating these conserved tumor states, thus enabling a more systematic approach to understanding cancer behaviors14–16. However, it remains unclear where these states come from and how broadly they can be applied. Therefore, two key needs must be addressed: 1) the identification of signatures with clear biological origins; and 2) a comprehensive study that evaluates how conserved tumor states correlate with drug sensitivities, metastatic patterns, and patient outcomes.  \nUnlike tumors, normal tissues typically have well-separated gene expression profiles and defined functional roles. Furthermore, many of the transcriptional differences observed across cancers mimic patterns of variability observed in normal tissues, making them an ideal system for contextualizing observed patterns of intertumor and intratumor heterogeneity16–18. Leveraging these links could therefore unveil new and general connections between the well-defined functional roles of normal tissues and recurring patterns of tumor heterogeneity.  \nHere, we use a statistical decomposition method to isolate and interpret transcriptomic motifs utilized both by normal tissues and tumors, referring to these signatures as normal tissue archetypes19. By restricting our analysis  \n1Department o","cbCaioZ6ziIYfBCt","https://ap.wps.com/l/cbCaioZ6ziIYfBCt","pdf",7479376,"English","# Abstract\n## Hypothesis and approach\n## Derived archetypes and tumor correlations\n## Prognostic and treatment relevance","[{\"question\":\"What is the main hypothesis of the study?\",\"answer\":\"The study hypothesizes that shared transcriptomic signatures arise from repurposed functional tasks performed by normal tissues.\"},{\"question\":\"How are the six transcriptomic phenotypes (archetypes) derived?\",\"answer\":\"The authors use non-negative matrix factorization starting from normal tissue transcriptomic profiles to obtain six distinct archetypes.\"},{\"question\":\"What tumor characteristics do the normal tissue signatures correlate with?\",\"answer\":\"Differential enrichment of these signatures correlates with patient survival and drug sensitivity, independent of clinically actionable DNA alterations.\"}]","Normal tissue transcriptional signatures for tumor-type-agnostic phenotype prediction | PDF",1789993664,33]