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This study assessed molecular classifier performance to stratify patients with clinically positive nodes into pN1 versus pN1 with additional positive nodes using clinical and DNA methylation data from The Cancer Genome Atlas in estrogen receptor-positive, HER2-negative invasive ductal carcinoma.",{"@graph":69,"@context":126},[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":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/epigenetic-signatures-predict-pathologic-nodal-stage-in-breast-cancer-patients-with-estrogen-receptor-positive-clinically-node-positive-disease/364977/",{"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/epigenetic-signatures-predict-pathologic-nodal-stage-in-breast-cancer-patients-with-estrogen-receptor-positive-clinically-node-positive-disease/364977.png","ImageObject",300,407,{"name":92,"@type":93},"kopisore","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118,122],{"name":109,"@type":110,"acceptedAnswer":111},"Why was this study conducted in breast cancer patients with clinically positive nodes?","Question",{"text":112,"@type":113},"Upfront surgery often leads to axillary lymph node dissection, but more than half of patients have limited nodal disease at surgery. The study aimed to improve stratification of these patients using molecular classifiers.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were patients grouped and what data types were used?",{"text":117,"@type":113},"Patients were divided into control (pN1, B 3 positive nodes) and case groups (greater than pN1, more positive nodes). Clinical variables and DNA methylation-based epigenetic signatures from the Cancer Genome Atlas were analyzed.",{"name":119,"@type":110,"acceptedAnswer":120},"Which epigenetic signatures predicted pathologic nodal stage and how accurate were they?",{"text":121,"@type":113},"Three DNA methylation signatures (EpiSig14, EpiSig13, EpiSig10) predicted pN1 disease with high accuracy, achieving an area under the curve of 0.98.",{"name":123,"@type":110,"acceptedAnswer":124},"What is the clinical implication of the epigenetic signatures?",{"text":125,"@type":113},"The signatures show excellent diagnostic accuracy for stratifying nodal disease and may support an accurate, cost-effective approach to identifying patients with predicted low nodal burden who could avoid the morbidity of ALND.","https://schema.org",{"og:url":83,"og:type":128,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":130,"canonical":83},"index,follow",{"doc_id":132,"site_id":62},364977,1790218391,{"code":4,"msg":5,"data":135},{"doc_id":132,"user_id":136,"nickname":92,"user_avatar":137,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":138,"file_id":139,"file_url":140,"file_type":141,"file_size":142,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":44,"language":143,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":144,"faqs":145,"seo_title":146,"seo_description":67,"update_tm":147,"read_time":148},962090880963,"https://ap-avatar.wpscdn.com/davatar_6f874abed73319feea01a86fa6f0fab8","Ann Surg Oncol  \n[https://doi.org/10.1245/s10434-022-11684-0](https://doi.org/10.1245/s10434-022-11684-0)  \nORIGINAL ARTICLE – BREAST ONCOLOGY  \nEpigenetic Signatures Predict Pathologic Nodal Stage in Breast Cancer Patients with Estrogen Receptor-Positive, Clinically NodePositive Disease  \nMiquel Ensenyat-Mendez, MSc1, Dennis R¨unger, PhD2, Javier I. J. Orozco, MD3, Julie Le, MD4,  \nJennifer L. Baker, MD4, Joanne Weidhaas, MD, PhD5, Diego M. Marzese, PhD1, and Maggie L. DiNome, MD6   \n1Cancer Epigenetics Laboratory at the Cancer Cell Biology Group, Institut d’Investigaci´o Sanit`aria Illes Balears (IdISBa), Palma, Spain; 2Statistics Core, Department of Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA; 3Saint John’s Cancer Institute, Providence Saint John’s Health Center, Santa Monica, CA; 4Department of Surgery, David Geffen School of Medicine at UCLA, Los Angeles, CA; 5Department of Radiation Oncology, David Geffen School of Medicine at UCLA, Los Angeles, CA; 6Department of Surgery, Duke University School of Medicine, Durham, NC  \nABSTRACT  \nBackground. Breast cancer patients with clinically positive nodes who undergo upfront surgery are often recommended for axillary lymph node dissection (ALND), yet more than half are found to have limited nodal disease (B 3 positive nodes, pN1) at surgery. In this study, we examined the efficiency of molecular classifiers in stratifying patients with clinically positive nodes to pN1 versus [ pN1 disease.  \nMethods. We evaluated the clinical and epigenetic data of patients in The Cancer Genome Atlas with estrogen receptor-positive, human epidermal growth factor receptor 2-negative invasive ductal carcinoma who underwent ALND for node-positive disease. Patients were divided into control (pN1, B 3 positive nodes) and case ([ pN1,[ 3 positive nodes) groups. Machine learning algorithms were trained on 50% of the cohort and validated on the remaining 50% to identify DNA methylation signatures  \nDiego M. Marzese and Maggie L. DiNome have contributed equally to this work.  \n􀀂 Society of Surgical Oncology 2022  \nFirst Received: 17 January 2022  \nAccepted: 16 March 2022  \nD. M. Marzese, PhD  \ne-mail: diego.marzese@ssib.es  \nM. L. DiNome, MD  \n[e-mail: Maggie.dinome@duke.edu](e-mail: Maggie.dinome@duke.edu)  \nthat predict [ pN1 disease. Clinical variables and epigenetic signatures were compared.  \nResults. Controls (n = 34) and case (n = 24) cohorts showed similar mean age (56.4 ± 12.2 vs. 57.6 ± 16.7 years; p = 0.77), number of nodes removed (16.1 ± 7.3 vs. 17.5 ± 6.2; p = 0.45), tumor grade (p = 0.76), presence of lymphovascular invasion (p = 0.18), extranodal extension (p = 0.17), tumor laterality (p = 0.89), and tumor location (p = 0.42) . The mean number of positive nodes was significantly different (1.76 ± 0.82, pN1; 8.83 ± 5.36, [ pN1; p \\ 0.001) . Three epigenetic signatures (EpiSig14, EpiSig13, EpiSig10) based on DNA methylation patterns of the primary tumors demonstrated high accuracy in predicting [ pN1 disease (area under the curve 0 .98) .  \nConclusions. Epigenetic signatures have an excellent diagnostic accuracy for stratifying nodal disease in patients with clinically positive nodes. Validation of this tool is warranted and may provide an accurate and cost-effective method of identifying patients with predicted low nodal burden who could be spared the morbidity of ALND.  \nHistoric randomized study data have failed to demonstrate a survival benefit for axillary lymph node dissection (ALND) for breast cancer patients; 1–3 however, ALND had long remained the standard of care for patients with lymph node-positive disease. The associated pain, functional morbidity, and lymphedema accompanying this surgical procedure have resulted in more contemporary clinical trials evaluating the safety of omission of ALND for select  \npatients with minimal nodal disease. These data have demonstrated that ALND does not impart oncologic benefit to patients with clinically negative, sentinel nod","cbCaimglTI3miTxL","https://ap.wps.com/l/cbCaimglTI3miTxL","pdf",545324,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions","[{\"question\":\"Why was this study conducted in breast cancer patients with clinically positive nodes?\",\"answer\":\"Upfront surgery often leads to axillary lymph node dissection, but more than half of patients have limited nodal disease at surgery. The study aimed to improve stratification of these patients using molecular classifiers.\"},{\"question\":\"How were patients grouped and what data types were used?\",\"answer\":\"Patients were divided into control (pN1, B 3 positive nodes) and case groups (greater than pN1, more positive nodes). Clinical variables and DNA methylation-based epigenetic signatures from the Cancer Genome Atlas were analyzed.\"},{\"question\":\"Which epigenetic signatures predicted pathologic nodal stage and how accurate were they?\",\"answer\":\"Three DNA methylation signatures (EpiSig14, EpiSig13, EpiSig10) predicted pN1 disease with high accuracy, achieving an area under the curve of 0.98.\"},{\"question\":\"What is the clinical implication of the epigenetic signatures?\",\"answer\":\"The signatures show excellent diagnostic accuracy for stratifying nodal disease and may support an accurate, cost-effective approach to identifying patients with predicted low nodal burden who could avoid the morbidity of ALND.\"}]","Epigenetic Signatures Predict Pathologic Nodal Stage in Breast Cancer Patients with Estrogen Receptor-Positive, Clinically Node-Positive Disease | PDF",1790159593,23]