{"title":"基于肿瘤常驻微生物群的风险模型可预测局部晚期食管鳞状细胞癌患者的新辅助治疗反应","authors":"Hong Wu, Qianshi Liu, Jingpei Li, Xuefeng Leng, Yazhou He, Yiqiang Liu, Xia Zhang, Yujie Ouyang, Yang Liu, Wenhua Liang, Chuan Xu","doi":"10.1002/advs.202309742","DOIUrl":null,"url":null,"abstract":"<p>Few predictive biomarkers exist for identifying patients who may benefit from neoadjuvant therapy (NAT). The intratumoral microbial composition is comprehensively profiled to predict the efficacy and prognosis of patients with esophageal squamous cell carcinoma (ESCC) who underwent NAT and curative esophagectomy. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis is conducted to screen for the most closely related microbiota and develop a microbiota-based risk prediction (MRP) model on the genera of <i>TM7x</i>, <i>Sphingobacterium</i>, and <i>Prevotella</i>. The predictive accuracy and prognostic value of the MRP model across multiple centers are validated. The MRP model demonstrates good predictive accuracy for therapeutic responses in the training, validation, and independent validation sets. The MRP model also predicts disease-free survival (<i>p</i> = 0.00074 in the internal validation set and <i>p</i> = 0.0017 in the independent validation set) and overall survival (<i>p</i> = 0.00023 in the internal validation set and <i>p</i> = 0.11 in the independent validation set) of patients. The MRP-plus model basing on MRP, tumor stage, and tumor size can also predict the patients who can benefit from NAT. In conclusion, the developed MRP and MRP-plus models may function as promising biomarkers and prognostic indicators accessible at the time of diagnosis.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":"11 41","pages":""},"PeriodicalIF":14.3000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/advs.202309742","citationCount":"0","resultStr":"{\"title\":\"Tumor-Resident Microbiota-Based Risk Model Predicts Neoadjuvant Therapy Response of Locally Advanced Esophageal Squamous Cell Carcinoma Patients\",\"authors\":\"Hong Wu, Qianshi Liu, Jingpei Li, Xuefeng Leng, Yazhou He, Yiqiang Liu, Xia Zhang, Yujie Ouyang, Yang Liu, Wenhua Liang, Chuan Xu\",\"doi\":\"10.1002/advs.202309742\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Few predictive biomarkers exist for identifying patients who may benefit from neoadjuvant therapy (NAT). The intratumoral microbial composition is comprehensively profiled to predict the efficacy and prognosis of patients with esophageal squamous cell carcinoma (ESCC) who underwent NAT and curative esophagectomy. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis is conducted to screen for the most closely related microbiota and develop a microbiota-based risk prediction (MRP) model on the genera of <i>TM7x</i>, <i>Sphingobacterium</i>, and <i>Prevotella</i>. The predictive accuracy and prognostic value of the MRP model across multiple centers are validated. The MRP model demonstrates good predictive accuracy for therapeutic responses in the training, validation, and independent validation sets. The MRP model also predicts disease-free survival (<i>p</i> = 0.00074 in the internal validation set and <i>p</i> = 0.0017 in the independent validation set) and overall survival (<i>p</i> = 0.00023 in the internal validation set and <i>p</i> = 0.11 in the independent validation set) of patients. The MRP-plus model basing on MRP, tumor stage, and tumor size can also predict the patients who can benefit from NAT. In conclusion, the developed MRP and MRP-plus models may function as promising biomarkers and prognostic indicators accessible at the time of diagnosis.</p>\",\"PeriodicalId\":117,\"journal\":{\"name\":\"Advanced Science\",\"volume\":\"11 41\",\"pages\":\"\"},\"PeriodicalIF\":14.3000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/advs.202309742\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/advs.202309742\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/advs.202309742","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
目前很少有预测性生物标志物可用于识别可能从新辅助治疗(NAT)中获益的患者。该研究全面分析了瘤内微生物组成,以预测接受新辅助治疗和食管切除术的食管鳞状细胞癌(ESCC)患者的疗效和预后。通过最小绝对收缩和选择操作器(LASSO)回归分析,筛选出关系最密切的微生物群,并以TM7x属、鞘氨醇杆菌属和普雷沃特氏菌属为基础建立了基于微生物群的风险预测(MRP)模型。MRP 模型的预测准确性和预后价值在多个中心得到了验证。在训练集、验证集和独立验证集中,MRP 模型对治疗反应显示出良好的预测准确性。MRP 模型还能预测患者的无病生存期(内部验证集 p = 0.00074,独立验证集 p = 0.0017)和总生存期(内部验证集 p = 0.00023,独立验证集 p = 0.11)。基于 MRP、肿瘤分期和肿瘤大小的 MRP-plus 模型还能预测哪些患者能从 NAT 中获益。总之,所开发的 MRP 和 MRP-plus 模型可以作为有前途的生物标记物和预后指标,在诊断时就可以使用。
Tumor-Resident Microbiota-Based Risk Model Predicts Neoadjuvant Therapy Response of Locally Advanced Esophageal Squamous Cell Carcinoma Patients
Few predictive biomarkers exist for identifying patients who may benefit from neoadjuvant therapy (NAT). The intratumoral microbial composition is comprehensively profiled to predict the efficacy and prognosis of patients with esophageal squamous cell carcinoma (ESCC) who underwent NAT and curative esophagectomy. Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis is conducted to screen for the most closely related microbiota and develop a microbiota-based risk prediction (MRP) model on the genera of TM7x, Sphingobacterium, and Prevotella. The predictive accuracy and prognostic value of the MRP model across multiple centers are validated. The MRP model demonstrates good predictive accuracy for therapeutic responses in the training, validation, and independent validation sets. The MRP model also predicts disease-free survival (p = 0.00074 in the internal validation set and p = 0.0017 in the independent validation set) and overall survival (p = 0.00023 in the internal validation set and p = 0.11 in the independent validation set) of patients. The MRP-plus model basing on MRP, tumor stage, and tumor size can also predict the patients who can benefit from NAT. In conclusion, the developed MRP and MRP-plus models may function as promising biomarkers and prognostic indicators accessible at the time of diagnosis.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.