Raghav Sundar1, Alvin Ng2, Hermioni Zouridis3, Nisha Padmanabhan4, Taotao Sheng4, Shenli Zhang4, Ming Hui Lee4, Wen Fong Ooi4, Aditi Qamra4, Imran Inam5, Lindsay C Hewitt6, Jimmy Bok-Yan So7, Vivien Koh8, Matthew G Nankivell9, Ruth E Langley9, William H Allum10, David Cunningham11, Steven G Rozen12, Wei Peng Yong8, Heike I Grabsch13, Patrick Tan14. 1. Department of Haematology-Oncology, National University Health System, Singapore; Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 2. Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore; Centre for Computational Biology, Duke-NUS Medical School, Singapore; NUS Graduate School for Integrative Sciences and Engineering, Singapore. 3. Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore; Technology Innovation and Delivery Excellence, AstraZeneca, USA. 4. Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore. 5. Division of Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK. 6. Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, the Netherlands. 7. Department of Surgery, National University Health System, Singapore; Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore. 8. Department of Haematology-Oncology, National University Health System, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore. 9. MRC Clinical Trials Unit at University College London, London, UK. 10. Department of Surgery, Royal Marsden Hospital, London, UK. 11. Department of Medicine, The Royal Marsden NHS Trust, London and Sutton, United Kingdom. 12. Centre for Computational Biology, Duke-NUS Medical School, Singapore. 13. Division of Pathology and Data Analytics, Leeds Institute of Medical Research at St James's, University of Leeds, Leeds, UK; Department of Pathology, GROW - School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, the Netherlands. Electronic address: h.grabsch@maastrichtuniversity.nl. 14. Cancer and Stem Cell Biology Program, Duke-NUS Medical School, Singapore; Cancer Science Institute of Singapore, National University of Singapore, Singapore; Biomedical Research Council, Agency for Science, Technology and Research, Singapore; SingHealth/Duke-NUS Institute of Precision Medicine, National Heart Centre Singapore, Singapore. Electronic address: gmstanp@duke-nus.edu.sg.
Abstract
BACKGROUND: DNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS). AIM: The aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort. METHODS: DNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy. RESULTS: A total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059) CONCLUSIONS: This is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC.
RCT Entities:
BACKGROUND: DNA methylation signatures describing distinct histological subtypes of oesophageal cancer have been reported. We studied DNA methylation in samples from the MRC OE02 phase III trial, which randomised patients with resectable oesophageal cancer to surgery alone (S) or neoadjuvant chemotherapy followed by surgery (CS). AIM: The aim of the study was to identify epigenetic signatures predictive of chemotherapy benefit in patients with oesophageal adenocarcinoma (OAC) from the OE02 trial and validate the findings in an independent cohort. METHODS: DNA methylation was analysed using the Illumina GoldenGate platform on surgically resected OAC specimens from patients in the OE02 trial. Cox proportional hazard analysis was performed to select probes predictive of survival in the CS arm. Non-negative matrix factorisation was used to perform clustering and delineate DNA methylation signatures. The findings were validated in an independent cohort of patients with gastroesophageal adenocarcinoma treated with neoadjuvant chemotherapy. RESULTS: A total of 229 patients with OAC were analysed from the OE02 trial (118 in the CS arm and 111 in the S arm). There was no difference in DNA methylation status between the CS and S arms. A metagene signature was created by dichotomising samples into two clusters. In cluster 1, patients in the CS arm had significant overall survival (OS) benefit (median OS CS: 931 days vs. S: 536 days [HR: 1.54, P = 0.031]). In cluster 2, patients in the CS arm had similar (or worse) OS compared with patients in the S arm (CS: 348 days vs. S: 472 days [HR: 0.70, P = 0.1], and test of interaction was significant (p = 0.005). In the validation cohort (n = 13), there was no difference in DNA methylation status in paired pre- and post-treatment samples. When the epigenetic signature was applied, cluster 1 samples had better OS (median OS, cluster 1: 1174 days vs. cluster 2: 392 days, HR: 3.47, p = 0.059) CONCLUSIONS: This is the first and largest study of DNA methylation in patients with OAC uniformly treated in a randomised phase III trial. We identified an epigenetic signature that may serve as a predictive biomarker for chemotherapy benefit in OAC.