Alberto Puccini1, Fotios Loupakis2, Sebastian Stintzing3, Shu Cao4, Francesca Battaglin5, Ryuma Togunaka1, Madiha Naseem1, Martin D Berger1, Shivani Soni1, Wu Zhang1, Christoph Mancao6, Bodour Salhia7, Shannon M Mumenthaler8, Daniel J Weisenberger9, Gangning Liang10, Chiara Cremolini11, Volker Heinemann3, Alfredo Falcone11, Joshua Millstein4, Heinz-Josef Lenz12. 1. Division of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. 2. Clinical and Experimental Oncology Department, Medical Oncology Unit 1, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy. 3. Comprehensive Cancer Center, Ludwig-Maximilian-University of Munich, Munich, Germany. 4. Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, USA. 5. Division of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Clinical and Experimental Oncology Department, Medical Oncology Unit 1, Veneto Institute of Oncology IOV-IRCCS, Padua, Italy. 6. Oncology Biomarker Development, Genentech Inc., Basel, Switzerland. 7. Department of Translational Genomics, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. 8. Lawrence J. Ellison Institute for Transformative Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, USA. 9. Department of Biochemistry and Molecular Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, USA. 10. Department of Urology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, USA. 11. Department of Medical Oncology, University of Pisa, Pisa, Italy. 12. Division of Medical Oncology, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, USA. Electronic address: lenz@med.usc.edu.
Abstract
BACKGROUND: CpG island DNA hypermethylation and global DNA hypomethylation are hallmark characteristics of colorectal cancer (CRC). Therefore, we aim to explore the effect of genetic variations within the genes that regulate the DNA methylation and demethylation pathways on outcomes in patients with metastatic CRC (mCRC) treated with first-line therapy and enrolled in three independent, randomised, open-label clinical trials. METHODS: A total of 884 patients with mCRC enrolled in TRIBE, MAVERICC and FIRE-3 trials were included. Single-nucleotide polymorphisms (SNPs) within genes involved in DNA methylation and demethylation pathways were analysed. The prognostic value of each SNP across all treatment arms was quantified using the inverse-variance-weighted effect size, a meta-analysis approach implemented in the METASOFT software. RESULTS: In the meta-analysis, DNMT3A rs11681717 was significantly associated with overall survival (hazard ratio = 1.26; 95% confidence interval [CI] 1.08-1.46; P = 0.002; false discovery rate [FDR] = 0.016), accounting for seven tests in the DNA methylation pathway. In addition, there was suggestive evidence of association for ten-eleven translocation (TET) genes variance with tumour response (TET1 rs3814177, odds ratio [OR] = 0.76, 95% CI 0.59-0.97, P = 0.025, FDR = 0.087; TET3 rs7560668, OR = 1.44; 95% CI 1.10-1.89; P = 0.009; FDR = 0.062). CONCLUSIONS: We showed that polymorphisms within the genes responsible for the DNA methylation and demethylation machineries are correlated with outcomes in patients with mCRC who were enrolled in three independent, randomised, open-label, phase II/III clinical trials. In addition, we demonstrated the feasibility of a meta-analysis approach to identify stronger and more convincing association between gene polymorphisms and outcome, potentially leading the way to a new method of analysis for similar data set.
BACKGROUND: CpG island DNA hypermethylation and global DNA hypomethylation are hallmark characteristics of colorectal cancer (CRC). Therefore, we aim to explore the effect of genetic variations within the genes that regulate the DNA methylation and demethylation pathways on outcomes in patients with metastatic CRC (mCRC) treated with first-line therapy and enrolled in three independent, randomised, open-label clinical trials. METHODS: A total of 884 patients with mCRC enrolled in TRIBE, MAVERICC and FIRE-3 trials were included. Single-nucleotide polymorphisms (SNPs) within genes involved in DNA methylation and demethylation pathways were analysed. The prognostic value of each SNP across all treatment arms was quantified using the inverse-variance-weighted effect size, a meta-analysis approach implemented in the METASOFT software. RESULTS: In the meta-analysis, DNMT3Ars11681717 was significantly associated with overall survival (hazard ratio = 1.26; 95% confidence interval [CI] 1.08-1.46; P = 0.002; false discovery rate [FDR] = 0.016), accounting for seven tests in the DNA methylation pathway. In addition, there was suggestive evidence of association for ten-eleven translocation (TET) genes variance with tumour response (TET1rs3814177, odds ratio [OR] = 0.76, 95% CI 0.59-0.97, P = 0.025, FDR = 0.087; TET3rs7560668, OR = 1.44; 95% CI 1.10-1.89; P = 0.009; FDR = 0.062). CONCLUSIONS: We showed that polymorphisms within the genes responsible for the DNA methylation and demethylation machineries are correlated with outcomes in patients with mCRC who were enrolled in three independent, randomised, open-label, phase II/III clinical trials. In addition, we demonstrated the feasibility of a meta-analysis approach to identify stronger and more convincing association between gene polymorphisms and outcome, potentially leading the way to a new method of analysis for similar data set.
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