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The study constructs a prognostic system for CF regimens, focusing on locally advanced disease, by analyzing biopsy specimens from 82 patients receiving the CF regimen plus radical surgery. Targeted enrichment sequencing identified variants in 56 autophagy- and esophageal cancer–related genes, with 13 single-nucleotide variants linked to recurrence, including ATG2A p.R478C and ULK2 splice-site variants associated with survival differences. A Naive Bayes machine-learning model using 21 features predicted recurrence with accuracy 0.88 and AUC 0.9, supporting guidance for neoadjuvant chemotherapy selection, including avoiding docetaxel.",{"@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":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/developing-a-machine-learning-model-to-enable-treatment-selection-for-neoadjuvant-chemotherapy-for-esophageal-cancer/366207/",{"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/developing-a-machine-learning-model-to-enable-treatment-selection-for-neoadjuvant-chemotherapy-for-esophageal-cancer/366207.png","ImageObject",300,407,{"name":92,"@type":93},"Terk","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":39},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does this study address in neoadjuvant chemotherapy for esophageal cancer?","Question",{"text":112,"@type":113},"It addresses the need to improve treatment selection for locally advanced esophageal cancer, since CF regimens are standard but docetaxel can lead to severe adverse events and reduce treatment completion. The study seeks prognostic markers to guide chemotherapy choices, including avoiding docetaxel.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were genetic variants identified in the patient samples?",{"text":117,"@type":113},"Biopsy specimens from 82 patients treated with the CF regimen plus radical surgery were analyzed using targeted enrichment sequencing. Variants in 56 autophagy- and esophageal cancer–related genes were assessed for association with recurrence.",{"name":119,"@type":110,"acceptedAnswer":120},"How well did the machine-learning model predict recurrence?",{"text":121,"@type":113},"A Naive Bayes machine-learning model using 21 features predicted esophageal cancer recurrence with an accuracy of 0.88 and an area under the curve of 0.9.","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},366207,1790198021,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":39,"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":41},1099525198933,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nDeveloping a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer  \nYutaka Miyawaki1,8, Masataka Hirasaki2,3,8􀀍, Yasuo Kamakura2, Tomonori Kawasaki4, Yasutaka Baba5, Tetsuya Sato6, Satoshi Yamasaki2, Hisayo Fukushima2, Kousuke Uranishi3, Yoshinori Makino2, Hiroshi Sato1 & Tetsuya Hamaguchi2,7  \nAlthough neoadjuvant chemotherapy with docetaxel + cisplatin + 5-fluorouracil (CF) has been the standard treatment for stage II and III esophageal cancers, it is associated with severe adverse events caused by docetaxel. Consequently, this study aimed to construct a prognostic system for CF regimens, especially for locally advanced esophageal cancers. Biopsy specimens from 82 patients treated with the CF regimen plus radical surgery were analyzed. Variants in 56 autophagy-and esophageal cancerrelated genes were identified using targeted enrichment sequencing. Overall, 13 single-nucleotide variants, including 8 non-synonymous single-nucleotide variants, were identified as significantly associated with esophageal cancer recurrence (p \u003C 0.05). Particularly, variants ofATG2A p.R478Cand ULK2 splice-site also showed significant differences in recurrence-free and overall survival. Subsequently, machine learning was used to construct a model for predicting esophageal cancer recurrence based on 21 features, including eight patient characteristics. A Naive Bayes machinelearning model was shown to be highly reliable for predicting esophageal cancer recurrence with an accuracy of 0.88 and an area under the curve of 0.9. We believe that our results provide useful guidance in the selection of neoadjuvant adjuvant chemotherapy, including avoidance of docetaxel.  \nKeywords Biomarker, Esophageal cancer, Neoadjuvant chemotherapy, Machine-learning, Targeted enrichment sequence, RNA sequence  \nEsophageal cancer ranks seventh in terms of incidence and sixth in terms of mortality globally1. The conventional standard treatment for stage II and III esophageal cancer in Japan was neoadjuvant chemotherapy with the cisplatin + 5-fluorouracil (5-FU) (CF) regimen followed by radical surgery2. According to previous reports, the 5-year survival rate for stage II cancers after neoadjuvant chemotherapy with the CF regimen is good at 69% . In contrast, the 5-year survival rate for stage III cancer is poor at 52%, indicating that neoadjuvant chemotherapy with the CF regimen has a limited effect in locally advanced cases3,4. Therefore, more potent neoadjuvant chemotherapy with the docetaxel +cisplatin + 5-FU (DCF) regimen has attracted attention in recent years. A phase III trial (JCOG1109) that compared the superiority of neoadjuvant chemotherapy with  \n1Department of Gastroenterological Surgery, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 2Department of Clinical Cancer Genomics, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 3Division of Biomedical Sciences, Research Center for Genomic Medicine, Saitama Medical University, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 4Department of Pathology, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 5Department of Diagnostic Radiology, Saitama Medical University International Medical Center, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 6Biomedical Research Center, Faculty of Medicine, Saitama Medical University, 1397-1 Yamane, Hidaka, Saitama 350-1298, Japan. 7Department of Medical Oncology, Gastroenterological Oncology, Saitama Medical University International Medical Center, 1397-1Yamane, Hidaka, Saitama 350-1298, Japan. 8Yutaka Miyawaki and Masataka Hirasaki equally contributed as co-first authors.  \n􀀍 email: [hirasaki@saitama-med.ac.jp](hirasaki@saitama-med.ac.jp)  \n[www. nature.com/scientificreports/](www. nature.com/","cbCaif5PmNLvwwVP","https://ap.wps.com/l/cbCaif5PmNLvwwVP","pdf",2146461,12,"English","# Overview\n## Current standard and limitations\n## Motivation for prognostic guidance\n# Study design and methods\n## Patient cohort and treatment context\n## Targeted enrichment sequencing of gene variants\n## Machine-learning model construction\n# Key findings\n## Variants associated with recurrence\n## Survival differences linked to specific variants\n## Predictive performance of the model\n# Clinical implications","[{\"question\":\"What problem does this study address in neoadjuvant chemotherapy for esophageal cancer?\",\"answer\":\"It addresses the need to improve treatment selection for locally advanced esophageal cancer, since CF regimens are standard but docetaxel can lead to severe adverse events and reduce treatment completion. The study seeks prognostic markers to guide chemotherapy choices, including avoiding docetaxel.\"},{\"question\":\"How were genetic variants identified in the patient samples?\",\"answer\":\"Biopsy specimens from 82 patients treated with the CF regimen plus radical surgery were analyzed using targeted enrichment sequencing. Variants in 56 autophagy- and esophageal cancer–related genes were assessed for association with recurrence.\"},{\"question\":\"How well did the machine-learning model predict recurrence?\",\"answer\":\"A Naive Bayes machine-learning model using 21 features predicted esophageal cancer recurrence with an accuracy of 0.88 and an area under the curve of 0.9.\"}]","Developing a machine-learning model to enable treatment selection for neoadjuvant chemotherapy for esophageal cancer | PDF",1790164244]