AbstractTherapeutic responses of non-small cell lung cancer (NSCLC) to epidermal growth factor receptor (EGFR) - tyrosine kinase inhibitors (TKIs) are known to be associated with EGFR mutations. However, a proportion of NSCLCs carrying EGFR mutations still progress on EGFR-TKI underlining the imperfect correlation. Structure-function-based approaches have recently been reported to perform better in retrospectively predicting patient outcomes following EGFR-TKI treatment than exon-based method. Here, we develop a multicolor fluorescence-activated cell sorting (FACS) with an EGFR-TKI-based fluorogenic probe (HX103) to profile active-EGFR in tumors. HX103-based FACS shows an overall agreement with gene mutations of 82.6%, sensitivity of 81.8% and specificity of 83.3% for discriminating EGFR-activating mutations from wild-type in surgical specimens from NSCLC patients. We then translate HX103 to the clinical studies for prediction of EGFR-TKI sensitivity. When integrating computed tomography imaging with HX103-based FACS, we find a high correlation between EGFR-TKI therapy response and probe labeling. These studies demonstrate HX103-based FACS provides a high predictive performance for response to EGFR-TKI, suggesting the potential utility of an EGFR-TKI-based probe in precision medicine trials to stratify NSCLC patients for EGFR-TKI treatment.
摘要:非小细胞肺癌(NSCLC)对
表皮生长因子受体(
EGFR)
酪氨酸激酶
抑制剂(TKI)的治疗反应已知与
EGFR突变相关。然而, carrying
EGFR突变的NSCLC的一部分仍然在
EGFR-TKI下进展,强调了不完美的相关性。基于结构功能的方法最近被报道在回顾性预测
EGFR-TKI治疗后患者预后方面表现更好。在这里,我们开发了一种多彩荧光激活细胞分选(FACS),使用基于
EGFR-TKI的荧光探针(HX103)来对肿瘤中的活性
EGFR进行分析。基于HX103的FACS显示与NSCLC患者手术标本中
基因突变的总体一致性为82.6%,敏感性为81.8%,特异性为83.3%,可区分
EGFR活化突变和野生型。然后,我们将HX103转化为临床研究,以预测
EGFR-TKI的敏感性。当将计算机断层扫描成像与基于HX103的FACS相结合时,我们发现
EGFR-TKI治疗反应与探针标记之间存在高度相关性。这些研究表明,基于HX103的FACS提供了对
EGFR-TKI反应的高预测性能,表明
EGFR-TKI基于探针的精准医学试验在将NSCLC患者分层为
EGFR-TKI治疗方面具有潜在的实用性。