期刊
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
卷 9, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fcell.2021.724389
关键词
extracellular vesicle (EV); EGFR mutation; longitudinal monitoring; resistance mutation; non-small cell lung cancer; EV-protein; EV-RNA; tyrosine kinase inhibitor (TKI)
资金
- National Institutes of Health (NIH) [5-R33-CA-202867-02, U01CA210152, 1-R01-CA-208335-01-A1, NIH-MBSTP T32 EB005582]
- National Science Foundation (NSF) [DGE 1256260, DMR-0320740]
- University of Michigan College of Engineering
- Michigan Center for Materials Characterization
Identifying EGFR mutations in NSCLC patients through extracellular vesicles (EVs) offers a potential liquid biopsy target, with the ability to detect sensitizing and resistance mutations at RNA and protein levels. This study demonstrated the utility of EV-RNA in detecting both sensitizing and resistance mutations, and EV-Protein in detecting sensitizing mutations in NSCLC patients. The integration of EV analysis into liquid biopsy mutation screening shows promise in advancing patient monitoring and personalized treatment.
In non-small cell lung cancer (NSCLC), identifying the presence of sensitizing and resistance epidermal growth factor receptor (EGFR) mutations dictates treatment plans. Extracellular vesicles (EVs) are emerging as abundant, stable potential liquid biopsy targets that offer the potential to quantify EGFR mutations in NSCLC patients at the RNA and protein level at multiple points through treatment. In this study, we present a systematic approach for serial mutation profiling of 34 EV samples from 10 metastatic NSCLC patients with known EGFR mutations through treatment. Using western blot and droplet digital PCR (ddPCR), sensitizing (exon 19 deletion, L858R) mutations were detected in EV-Protein, and both sensitizing and resistance (T790M) mutations were quantified in EV-RNA. EGFR mutations were detected in EV-Protein from four patients at multiple time points through treatment. Using EV-RNA, tumor biopsy matched sensitizing mutations were detected in 90% of patients and resistance mutations in 100% of patients. Finally, mutation burden in EV-RNA at each time point was compared to disease status, described as either stable or progressing. For 6/7 patients who were longitudinally monitored through treatment, EV mutation burden mirrored clinical trajectory. When comparing mutation detection between EV-RNA and ctDNA using ddPCR, EVs had a better detection rate for exon 19 deletions and the L858R point mutation. In conclusion, this study demonstrates that integrating EV analysis into liquid biopsy mutation screening has the potential to advance beyond the current standard of care rule in test. The multi-analyte testing allows future integration of EGFR mutation monitoring with additional EV-markers for a comprehensive patient monitoring biomarker.
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