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
Department of General Surgery, Zhongshan Hospital, Fudan University, Shanghai, China.
Department of Anatomy, Histology & Embryology, Shanghai Medical College, Fudan University, Shanghai, China.
J Oncol. 2018 Sep 16;2018:5072987. doi: 10.1155/2018/5072987. eCollection 2018.
We aimed to identify new predictive biomarkers for cetuximab in first-line treatment for patients with RAS wild-type metastatic colorectal cancer (mCRC).
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.
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.
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.
我们旨在识别针对RAS野生型转移性结直肠癌(mCRC)患者一线治疗中使用西妥昔单抗的新预测生物标志物。
该研究纳入了接受或未接受西妥昔单抗化疗的KRAS野生型不可切除的肝局限性mCRC患者。根据定制面板对单核苷酸多态性进行下一代测序。在训练队列中识别潜在的预测生物标志物并将其整合到预测模型中。该模型在验证队列中进行验证。
247例患者中有31例(12.6%)存在RAS突变。在训练队列(N = 93)中,识别出六个潜在的预测基因,即ATP6V1B1、CUL9、ERBB2、LY6G6D、PTCH1和RBMXL3。根据预测模型,患者被分为反应组(n = 66)或难治组(n = 27)。在反应组中,化疗联合西妥昔单抗可显著改善疗效结果。在难治组中,未观察到益处。所有终点的交互检验均具有显著性。在验证队列(N = 123)中也观察到了类似结果。
在mCRC的一线治疗中,整合六个新预测突变的预测模型能很好地对患者进行分类,表明这是一种在RAS突变基础上进一步优化西妥昔单抗患者选择的有前景的方法。