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Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis

PURPOSE: We aimed to identify new predictive biomarkers for cetuximab in first-line treatment for patients with RAS wild-type metastatic colorectal cancer (mCRC). METHODS: The study included patients with KRAS wild-type unresectable liver-limited mCRC treated with chemotherapy with or without cetuxi...

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Autores principales: Zheng, Peng, Liang, Chunmin, Ren, Li, Zhu, Dexiang, Feng, Qingyang, Chang, Wenju, He, Guodong, Ye, Lechi, Chen, Jingwen, Lin, Qi, Yi, Tuo, Ji, Meiling, Niu, Zhengchuan, Jian, Mi, Wei, Ye, Xu, Jianmin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165607/
https://www.ncbi.nlm.nih.gov/pubmed/30305811
http://dx.doi.org/10.1155/2018/5072987
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author Zheng, Peng
Liang, Chunmin
Ren, Li
Zhu, Dexiang
Feng, Qingyang
Chang, Wenju
He, Guodong
Ye, Lechi
Chen, Jingwen
Lin, Qi
Yi, Tuo
Ji, Meiling
Niu, Zhengchuan
Jian, Mi
Wei, Ye
Xu, Jianmin
author_facet Zheng, Peng
Liang, Chunmin
Ren, Li
Zhu, Dexiang
Feng, Qingyang
Chang, Wenju
He, Guodong
Ye, Lechi
Chen, Jingwen
Lin, Qi
Yi, Tuo
Ji, Meiling
Niu, Zhengchuan
Jian, Mi
Wei, Ye
Xu, Jianmin
author_sort Zheng, Peng
collection PubMed
description PURPOSE: We aimed to identify new predictive biomarkers for cetuximab in first-line treatment for patients with RAS wild-type metastatic colorectal cancer (mCRC). METHODS: The study included patients with KRAS wild-type unresectable liver-limited mCRC treated with chemotherapy with or without cetuximab. Next-generation sequencing was done for single nucleotide polymorphism according to custom panel. Potential predictive biomarkers were identified and integrated into a predictive model within a training cohort. The model was validated in a validation cohort. RESULTS: Thirty-one of 247(12.6%) patients harbored RAS mutations. In training cohort (N=93), six potential predictive genes, namely, ATP6V1B1, CUL9, ERBB2, LY6G6D, PTCH1, and RBMXL3, were identified. According to predictive model, patients were divided into responsive group (n=66) or refractory group (n=27). In responsive group, efficacy outcomes were significantly improved by addition of cetuximab to chemotherapy. In refractory group, no benefit was observed. Interaction test was significant across all endpoints. In validation cohort (N=123), similar results were also observed. CONCLUSIONS: In the first-line treatment of mCRC, the predictive model integrating six new predictive mutations divided patients well, indicating a promising approach to further refine patient selection for cetuximab on the basis of RAS mutations.
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spelling pubmed-61656072018-10-10 Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis Zheng, Peng Liang, Chunmin Ren, Li Zhu, Dexiang Feng, Qingyang Chang, Wenju He, Guodong Ye, Lechi Chen, Jingwen Lin, Qi Yi, Tuo Ji, Meiling Niu, Zhengchuan Jian, Mi Wei, Ye Xu, Jianmin J Oncol Research Article PURPOSE: We aimed to identify new predictive biomarkers for cetuximab in first-line treatment for patients with RAS wild-type metastatic colorectal cancer (mCRC). METHODS: The study included patients with KRAS wild-type unresectable liver-limited mCRC treated with chemotherapy with or without cetuximab. Next-generation sequencing was done for single nucleotide polymorphism according to custom panel. Potential predictive biomarkers were identified and integrated into a predictive model within a training cohort. The model was validated in a validation cohort. RESULTS: Thirty-one of 247(12.6%) patients harbored RAS mutations. In training cohort (N=93), six potential predictive genes, namely, ATP6V1B1, CUL9, ERBB2, LY6G6D, PTCH1, and RBMXL3, were identified. According to predictive model, patients were divided into responsive group (n=66) or refractory group (n=27). In responsive group, efficacy outcomes were significantly improved by addition of cetuximab to chemotherapy. In refractory group, no benefit was observed. Interaction test was significant across all endpoints. In validation cohort (N=123), similar results were also observed. CONCLUSIONS: In the first-line treatment of mCRC, the predictive model integrating six new predictive mutations divided patients well, indicating a promising approach to further refine patient selection for cetuximab on the basis of RAS mutations. Hindawi 2018-09-16 /pmc/articles/PMC6165607/ /pubmed/30305811 http://dx.doi.org/10.1155/2018/5072987 Text en Copyright © 2018 Peng Zheng et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zheng, Peng
Liang, Chunmin
Ren, Li
Zhu, Dexiang
Feng, Qingyang
Chang, Wenju
He, Guodong
Ye, Lechi
Chen, Jingwen
Lin, Qi
Yi, Tuo
Ji, Meiling
Niu, Zhengchuan
Jian, Mi
Wei, Ye
Xu, Jianmin
Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title_full Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title_fullStr Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title_full_unstemmed Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title_short Additional Biomarkers beyond RAS That Impact the Efficacy of Cetuximab plus Chemotherapy in mCRC: A Retrospective Biomarker Analysis
title_sort additional biomarkers beyond ras that impact the efficacy of cetuximab plus chemotherapy in mcrc: a retrospective biomarker analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6165607/
https://www.ncbi.nlm.nih.gov/pubmed/30305811
http://dx.doi.org/10.1155/2018/5072987
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