振动光谱法预测食管癌症新辅助放化疗的病理反应

T. N. Q. Nguyen, A. Maguire, C. Mooney, N. Jackson, N. Lynam‐Lennon, Vicki Weldon, C. Muldoon, A. Maguire, D. O’Toole, N. Ravi, J. Reynolds, J. O’Sullivan, A. Meade
{"title":"振动光谱法预测食管癌症新辅助放化疗的病理反应","authors":"T. N. Q. Nguyen, A. Maguire, C. Mooney, N. Jackson, N. Lynam‐Lennon, Vicki Weldon, C. Muldoon, A. Maguire, D. O’Toole, N. Ravi, J. Reynolds, J. O’Sullivan, A. Meade","doi":"10.1002/tbio.202000014","DOIUrl":null,"url":null,"abstract":"In oesophageal cancer (OC) neo-adju-vant chemoradiotherapy (neoCRT) is used to debulk tumour size prior to surgery, with a complete pathological response (pCR) observed in approximately (cid:1) 30% of patients. Presently no predictive quantitative methodology exists which can predict response, in particular a pCR or major response (MR), in patients prior to therapy. Raman and Fourier transform infrared imaging were performed on OC tissue specimens acquired from 50 patients prior to therapy, to develop a computa-tional model linking spectral data to treatment outcome. Modelling sensitivities and specificities above 85% were achieved using this approach. Parallel in-vitro studies using an isogenic model of radioresistant OC supplied further insight into OC cell spectral response to ionising radiation where a potential spectral biomarker of radioresistance was observed at 977 cm − 1 . This work demonstrates that chemical imaging may provide an option for triage of patients prior to neoCRT treatment allowing more precise prescription of treatment.","PeriodicalId":75242,"journal":{"name":"Translational biophotonics","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/tbio.202000014","citationCount":"2","resultStr":"{\"title\":\"Prediction of pathological response to neo‐adjuvant chemoradiotherapy for oesophageal cancer using vibrational spectroscopy\",\"authors\":\"T. N. Q. Nguyen, A. Maguire, C. Mooney, N. Jackson, N. Lynam‐Lennon, Vicki Weldon, C. Muldoon, A. Maguire, D. O’Toole, N. Ravi, J. Reynolds, J. O’Sullivan, A. Meade\",\"doi\":\"10.1002/tbio.202000014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In oesophageal cancer (OC) neo-adju-vant chemoradiotherapy (neoCRT) is used to debulk tumour size prior to surgery, with a complete pathological response (pCR) observed in approximately (cid:1) 30% of patients. Presently no predictive quantitative methodology exists which can predict response, in particular a pCR or major response (MR), in patients prior to therapy. Raman and Fourier transform infrared imaging were performed on OC tissue specimens acquired from 50 patients prior to therapy, to develop a computa-tional model linking spectral data to treatment outcome. Modelling sensitivities and specificities above 85% were achieved using this approach. Parallel in-vitro studies using an isogenic model of radioresistant OC supplied further insight into OC cell spectral response to ionising radiation where a potential spectral biomarker of radioresistance was observed at 977 cm − 1 . This work demonstrates that chemical imaging may provide an option for triage of patients prior to neoCRT treatment allowing more precise prescription of treatment.\",\"PeriodicalId\":75242,\"journal\":{\"name\":\"Translational biophotonics\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/tbio.202000014\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Translational biophotonics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1002/tbio.202000014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational biophotonics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/tbio.202000014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

在食管癌(OC)中,在手术前使用新辅助放化疗(neoCRT)来缩小肿瘤大小,在大约(cid:1) 30%的患者中观察到完全病理反应(pCR)。目前还没有预测定量方法可以预测治疗前患者的反应,特别是pCR或主要反应(MR)。在治疗前对50名患者的OC组织标本进行拉曼和傅里叶变换红外成像,以建立将光谱数据与治疗结果联系起来的计算模型。使用这种方法可以实现85%以上的建模灵敏度和特异性。使用耐辐射OC等基因模型的平行体外研究进一步深入了解OC细胞对电离辐射的光谱响应,其中在977 cm−1处观察到潜在的辐射抗性光谱生物标志物。这项工作表明,化学成像可以为新crt治疗前的患者分诊提供一种选择,允许更精确的治疗处方。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of pathological response to neo‐adjuvant chemoradiotherapy for oesophageal cancer using vibrational spectroscopy
In oesophageal cancer (OC) neo-adju-vant chemoradiotherapy (neoCRT) is used to debulk tumour size prior to surgery, with a complete pathological response (pCR) observed in approximately (cid:1) 30% of patients. Presently no predictive quantitative methodology exists which can predict response, in particular a pCR or major response (MR), in patients prior to therapy. Raman and Fourier transform infrared imaging were performed on OC tissue specimens acquired from 50 patients prior to therapy, to develop a computa-tional model linking spectral data to treatment outcome. Modelling sensitivities and specificities above 85% were achieved using this approach. Parallel in-vitro studies using an isogenic model of radioresistant OC supplied further insight into OC cell spectral response to ionising radiation where a potential spectral biomarker of radioresistance was observed at 977 cm − 1 . This work demonstrates that chemical imaging may provide an option for triage of patients prior to neoCRT treatment allowing more precise prescription of treatment.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
15 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信