期刊
NATURE COMMUNICATIONS
卷 13, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-022-34627-5
关键词
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资金
- National Natural Science Foundation of China [92159302, 91859203, 22277084, 82104264, 82100119]
- Fundamental Research Funds for the Central Universities [SCU2022D025]
- National Major Scientific and Technological Special Project (Significant New Drugs Development) [2018ZX09201018-021]
- Science and Technology Project of Sichuan Province [2022ZDZX0018]
In this study, the authors present a fluorescence-activated cell sorting assay to identify activating EGFR mutations in lung cancer patients and demonstrate its utility in predicting response to EGFR-tyrosine kinase inhibitors.
The presence of activating epidermal growth factor receptor (EGFR) mutations in patients with lung cancer correlates to improved response to EGFR-tyrosine kinase inhibitors. Here, the authors present a fluorescence-activated cell sorting assay to identify EGFR mutations with functional activity in patients and demonstrate its utility in predicting response to EGFR-TKI. Therapeutic 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.
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