Title |
Co-mutations in DNA damage response pathways serve as potential biomarkers for immune checkpoint blockade
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Published in |
Cancer Research, November 2018
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DOI | 10.1158/0008-5472.can-18-1814 |
Pubmed ID | |
Authors |
Zhijie Wang, Jing Zhao, Guoqiang Wang, Fan Zhang, Zemin Zhang, Fan Zhang, Yuzi Zhang, Hua Dong, Xiaochen Zhao, Jianchun Duan, Hua Bai, Yanhua Tian, Rui Wan, Miao Han, Yan Cao, Lei Xiong, Li Liu, Shuhang Wang, Shangli Cai, Tony S K Mok, Jie Wang |
Abstract |
Biomarkers such as programmed death receptor 1 ligand (PD-L1) expression, tumor mutational burden (TMB), and high microsatellite instability are potentially applicable to predict the efficacy of immune checkpoint blockade (ICB). However, several challenges such as defining the cut-off value, test platform uniformity, and low frequencies limit their broad clinical application. Here we identify co-mutations in the DNA damage response (DDR) pathways of homologous recombination repair and mismatch repair (HRR-MMR) or HRR and base excision repair (HRR-BER) (defined as co-mut+) that are associated with increased TMB and neoantigen load and increased levels of immune gene expression signatures. In four public clinical cohorts, co-mut+ patients presented a higher objective response rate and a longer progression-free survival or overall survival than co-mut- patients. Overall, identification of DDR co-mutations in HRR-MMR or HRR-BER as predictors of response to ICB provides a potentially convenient approach for future clinical practice. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 50% |
United Kingdom | 1 | 50% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 94 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 22 | 23% |
Student > Ph. D. Student | 10 | 11% |
Student > Bachelor | 10 | 11% |
Student > Postgraduate | 6 | 6% |
Student > Master | 6 | 6% |
Other | 11 | 12% |
Unknown | 29 | 31% |
Readers by discipline | Count | As % |
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Biochemistry, Genetics and Molecular Biology | 30 | 32% |
Medicine and Dentistry | 16 | 17% |
Agricultural and Biological Sciences | 5 | 5% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 2% |
Immunology and Microbiology | 2 | 2% |
Other | 3 | 3% |
Unknown | 36 | 38% |