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The study investigates genetic variations among breast cancer subtypes at single-cell resolution to deepen insights into cancer progression. Methods: Single-cell RNA sequencing data were integrated from patient tumours and matched lymph metastasis, reduction mammoplasties, PDXs, PDX-derived organoids, and cell lines, forming a diverse dataset of 117 samples with 506,719 cells across HR+, HER2+, and TNBC subtypes including isogenic model pairs.",{"@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/single-cell-transcriptional-atlas-of-human-breast-cancers-and-model-systems-research-article/329178/",{"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/single-cell-transcriptional-atlas-of-human-breast-cancers-and-model-systems-research-article/329178.png","ImageObject",300,407,{"name":92,"@type":93},"River Wang","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What problem does the study address in breast cancer research?","Question",{"text":113,"@type":114},"It addresses the need for better understanding of breast cancer’s cellular diversity by analyzing the transcriptional landscape to support more effective treatments.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"Which data types and sample sources were integrated in the study?",{"text":118,"@type":114},"The study combines single-cell RNA sequencing from patient tumours, matched lymph metastasis, reduction mammoplasties, breast cancer PDXs, PDX-derived organoids, and cell lines.",{"name":120,"@type":111,"acceptedAnswer":121},"What dataset size and cancer subtypes are covered?",{"text":122,"@type":114},"The dataset includes 117 samples and 506,719 total cells, covering hormone receptor positive (HR+), HER2+ and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs.","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},329178,1790192901,{"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":140,"language":141,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":142,"faqs":143,"seo_title":144,"seo_description":67,"update_tm":145,"read_time":146,"preview_page_count":4},1099514067438,"https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542","DOI: 10.1002/ctm2.70044  \nRESEARCH ARTICLE  \nSingle-cell transcriptional atlas of human breast cancersand model systems  \nJulia E. Altman1, 2   Amy L. Olex3 David C. Boyd2  Rachel K. Myrick2 Madhavi Puchalapalli2, 5  Bin Hu2, 5  \n Emily K. Zboril2, 4  Carson J. Walker1, 2    Nicole S. Hairr2  Jennifer E. Koblinski2, 5  Mikhail G. Dozmorov6  X. Steven Chen7, 8  \nYunshun Chen9, 10 Jane E. Visvader9, 10  \nCharles M. Perou11   J. Chuck Harrell2, 5, 13  \nBrian D. Lehmann12  \n1 Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, USA  \n2 Department of Pathology, Virginia Commonwealth University, Richmond, Virginia, USA  \n3 C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, Richmond, Virginia, USA 4 Department of Biochemistry, Virginia Commonwealth University, Richmond, Virginia, USA  \n5Massey Comprehensive Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA  \n6 Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA  \n7 Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA  \n8 Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA  \n9Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia  \n10 Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia  \n11 Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina, USA  \n12 Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA  \n13 Center for Pharmaceutical Engineering, Virginia Commonwealth University, Richmond, Virginia, USA  \nCorrespondence  \nJ. Chuck Harrell, Department of Pathology, Virginia Commonwealth University, Richmond, Virginia. [Email:](Email: jcharrell@vcu.edu)[ jcharrell@vcu.edu](Email: jcharrell@vcu.edu)  \nGraphical Abstract  \n∙ Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines.  \nClin. Transl. Med. 2024;14:e70044 .  \n[https://doi.org/10.1002/ctm2.70044](https://doi.org/10.1002/ctm2.70044)  \n[wileyonlinelibrary.com/journal/ctm2](wileyonlinelibrary.com/journal/ctm2)  \nALTMAN et al.  \n∙ 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts.  \n∙ A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.  \nDOI: 10.1002/ctm2.70044  \nRESEARCH ARTICLE  \nSingle-cell transcriptional atlas of human breast cancersand model systems  \nJulia E. Altman1, 2   Amy L. Olex3 David C. Boyd2  Rachel K. Myrick2 Madhavi Puchalapalli2, 5  Bin Hu2, 5  \n Emily K. Zboril2, 4  Carson J. Walker1, 2    Nicole S. Hairr2  Jennifer E. Koblinski2, 5  Mikhail G. Dozmorov6  X. Steven Chen7, 8  \nYunshun Chen9, 10 Jane E. Visvader9, 10  \nCharles M. Perou11   J. Chuck Harrell2, 5, 13  \nBrian D. Lehmann12  \n1 Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia, USA  \n2 Department of Pathology, Virginia Commonwealth University, Richmond, Virginia, USA  \n3 C. Kenneth and Diane Wright Center for Clinical and Translational Research, Virginia Commonwealth University, Richmond, Virginia, USA 4 Department of Biochemistry, Virginia Commonwealth University, Richmond, Virginia, USA  \n5Massey Comprehensive Cancer Center, Virginia Commonwealth University, Richmond, Virginia, USA  \n6 Department of Biostatistics, Virginia Commonwealth University, Richmond, Virginia, USA  \n7 Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami, Florida, USA  \n8 Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA  \n9Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia  \n10 Departme","cbCaiburHRF66fJ3","https://ap.wps.com/l/cbCaiburHRF66fJ3","pdf",11241602,33,"English","# Abstract\n## Background\n## Methods","[{\"question\":\"What problem does the study address in breast cancer research?\",\"answer\":\"It addresses the need for better understanding of breast cancer’s cellular diversity by analyzing the transcriptional landscape to support more effective treatments.\"},{\"question\":\"Which data types and sample sources were integrated in the study?\",\"answer\":\"The study combines single-cell RNA sequencing from patient tumours, matched lymph metastasis, reduction mammoplasties, breast cancer PDXs, PDX-derived organoids, and cell lines.\"},{\"question\":\"What dataset size and cancer subtypes are covered?\",\"answer\":\"The dataset includes 117 samples and 506,719 total cells, covering hormone receptor positive (HR+), HER2+ and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs.\"}]","Single-cell transcriptional atlas of human breast cancers and model systems - Research Article | PDF",1789982918,83]