Clinical Research Papers:
High-throughput RNAi screening of human kinases identifies predictors of clinical outcome in colorectal cancer patients treated with oxaliplatin
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Moubin Lin1,3,*, Yajie Zhang2,*, Ajian Li2, Erjiang Tang1, Jian Peng3, Wenxian Tang3, Yong Zhang3, Liang Lu3, Yihua Xiao3, Qing Wei4, Lu Yin3 and Huaguang Li1
1 Center for Translational Medicine, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
2 Department of General Surgery, RuiJin Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
3 Department of General Surgery, Yangpu Hospital, Tongji University School of Medicine, Shanghai, China
4 Department of Pathology, The Tenth People’s Hospital Affiliated to Shanghai Tongji University School of Medicine, Shanghai, China
* These authors have contributed equally to this work
Moubin Lin, email:
Huaguang Li, email:
Keywords: colorectal cancer, RNAi screening, chemotherapy, recurrence, survival
Received: February 05, 2015 Accepted: March 01, 2015 Published: March 30, 2015
The purpose of this study is to identify protein kinase genes that modulate oxaliplatin cytotoxicity in vitro and evaluate the roles of these genes in predicting clinical outcomes in CRC patients receiving oxaliplatin-based adjuvant chemotherapy. A high-throughput RNAi screening targeting 626 human kinase genes was performed to identify kinase genes whose inhibition potentiates oxaliplatin sensitivity in CRC cells. The associations between copy numbers of the candidate genes and recurrence-free survival and overall survival were analyzed in 142 stage III CRC patients receiving first-line oxaliplatin-based adjuvant chemotherapy who were enrolled from two independent hospitals. HT-RNAi screening identified 40 kinase genes whose inhibition potentiated oxaliplatin cytotoxicity in DLD1 cells. The relative copy number (RCN) of MAP4K1 and CDKL4 were associated with increased risks of both recurrence and death. Moreover, significant genes-based risk score and the ratios of RCN of different genes can further categorize patients into subgroups with distinctly differing outcomes. The estimated AUC for the prediction models including clinical variables plus kinase biomarkers was 0.77 for the recurrence and 0.82 for the survival models. The copy numbers of MAP4K1 and CDKL4 can predict clinical outcomes in CRC patients treated with oxaliplatin-based chemotherapy.
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