E.C. Smyth , D. Watson , M.P. Castro , B. Nutzinger , S. Kapoor , S. Rajagopalan , C. Cheah , P.R. Nair , A. Alam , G. Devonshire , N. Grehan , R.P. Suseela , A. Tyagi , A.K. Agrawal , M. Sauban , A. Pampana , A. Ghosh , Y. Ullal , Y. Narvekar , M.D. Macpherson , R.C. Fitzgerald
{"title":"整合基因组畸变，预测接受新辅助化疗的胃食管腺癌患者的临床预后","authors":"E.C. Smyth , D. Watson , M.P. Castro , B. Nutzinger , S. Kapoor , S. Rajagopalan , C. Cheah , P.R. Nair , A. Alam , G. Devonshire , N. Grehan , R.P. Suseela , A. Tyagi , A.K. Agrawal , M. Sauban , A. Pampana , A. Ghosh , Y. Ullal , Y. Narvekar , M.D. Macpherson , R.C. Fitzgerald","doi":"10.1016/j.esmogo.2023.08.009","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study.</p></div><div><h3>Design</h3><p>TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors.</p></div><div><h3>Results</h3><p>A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (<em>P</em> = 0.0012). A significant association was also observed with disease-free survival (DFS; <em>P</em> = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (<em>P</em> = 0.0011).</p></div><div><h3>Conclusions</h3><p>TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.</p></div>","PeriodicalId":100490,"journal":{"name":"ESMO Gastrointestinal Oncology","volume":"3 ","pages":"Article 100010"},"PeriodicalIF":0.0000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949819823000109/pdfft?md5=c47bbdcdc5f341df1a7eb134067306ed&pid=1-s2.0-S2949819823000109-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Integration of genomic aberrations to predict clinical outcomes for patients with gastroesophageal adenocarcinoma receiving neoadjuvant chemotherapy\",\"authors\":\"E.C. Smyth , D. Watson , M.P. Castro , B. Nutzinger , S. Kapoor , S. Rajagopalan , C. Cheah , P.R. Nair , A. Alam , G. Devonshire , N. Grehan , R.P. Suseela , A. Tyagi , A.K. Agrawal , M. Sauban , A. Pampana , A. Ghosh , Y. Ullal , Y. Narvekar , M.D. Macpherson , R.C. Fitzgerald\",\"doi\":\"10.1016/j.esmogo.2023.08.009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background</h3><p>Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study.</p></div><div><h3>Design</h3><p>TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors.</p></div><div><h3>Results</h3><p>A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (<em>P</em> = 0.0012). A significant association was also observed with disease-free survival (DFS; <em>P</em> = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (<em>P</em> = 0.0011).</p></div><div><h3>Conclusions</h3><p>TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.</p></div>\",\"PeriodicalId\":100490,\"journal\":{\"name\":\"ESMO Gastrointestinal Oncology\",\"volume\":\"3 \",\"pages\":\"Article 100010\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2949819823000109/pdfft?md5=c47bbdcdc5f341df1a7eb134067306ed&pid=1-s2.0-S2949819823000109-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ESMO Gastrointestinal Oncology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949819823000109\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ESMO Gastrointestinal Oncology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949819823000109","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integration of genomic aberrations to predict clinical outcomes for patients with gastroesophageal adenocarcinoma receiving neoadjuvant chemotherapy
Background
Esophageal cancer [esophagogastric adenocarcinoma (OGA)] shows heterogeneity at the molecular level, leading to lower efficacy rates and highlighting the need for personalized treatment strategies. We have developed a computational model that uses both mechanistic and statistical approaches to integrate a patient’s genomic aberrations, revealing signaling pathway dysregulation and variable drug response. The model output, Therapy Response Index (TRI), has been used to predict therapeutic outcomes in this study.
Design
TRI’s ability to predict patient outcomes was retrospectively evaluated in a prospectively collected cohort of patients with operable OGA from the UK Oesophageal Cancer Clinical and Molecular Stratification (OCCAMS) consortium receiving neoadjuvant chemotherapy. Stratified random sampling was used to split the data into training and validation subsets. Multivariate Cox proportional hazard and proportional odds models were used to predict survival and pathological response as a function of TRI and clinical thresholds compared with clinical factors.
Results
A total of 270 patients with OGA were selected who had 50× whole genome sequencing carried out on tissue derived from either biopsy or resection. Patients were treated with chemotherapy drugs or regimens according to UK clinical guidelines. The association of TRI with overall survival (OS) was significant above and beyond standard clinical factors (P = 0.0012). A significant association was also observed with disease-free survival (DFS; P = 0.0288). A TRI optimized for tumor regression grade also displayed a significant association (P = 0.0011).
Conclusions
TRI was predictive of OS and DFS beyond clinical factors. These positive results suggest the potential utility of personalized biosimulation-informed therapy selection and that further assessment in prospective clinical studies is warranted.
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