Theranostics 2022; 12(8):3676-3689. doi:10.7150/thno.72511 This issue
1. Department of New Biology, DGIST, Daegu 42988, Korea.
2. CTCELLS Inc., 206-C, R7, DGIST, Daegu 42988, Korea.
3. JE-UK Institute for Cancer Research, JEUK Co. Ltd., Gumi-si 39418, Korea.
4. College of Transdisciplinary Studies, DGIST, Daegu 42988, Korea.
5. Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan 50612, Korea.
6. Department of Rehabilitation Medicine, Pusan National University School of Medicine, Yangsan 50612, Korea.
7. Department of Laboratory Medicine, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan 50612, Korea.
8. Medical Oncology & Hematology, Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan 50612, Korea.
9. Division of Neurooncology and Department of Neurosurgery, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon 51353, Korea.
10. Department of Dental Pharmacology, School of Dentistry, Jeonbuk National University, Jeonju 54896, Korea.
11. Division of Medical Oncology, Department of Internal Medicine, Yonsei University College of Medicine, Gangnam Severance Hospital, Seoul 06273, Korea.
12. Division of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul 03722, Korea.
13. Center for Breast Cancer, National Cancer Center, Goyang 10408, Korea.
14. Institute of Tumour Biology, University Medical Centre Hamburg-Eppendorf, Hamburg 20246, Germany.
#These authors equally contributed to this work.
Understanding cancer heterogeneity is essential to finding diverse genetic mutations in metastatic cancers. Thus, it is critical to isolate all types of CTCs to identify accurate cancer information from patients. Moreover, full automation robustly capturing the full spectrum of CTCs is an urgent need for CTC diagnosis to be routine clinical practice.
Methods: Here we report the full capture of heterogeneous CTC populations using fully automated, negative depletion-based continuous centrifugal microfluidics (CCM).
Results: The CCM system demonstrated high performance (recovery rates exceeding 90% and WBC depletion rate of 99.9%) across a wide range of phenotypes (EpCAM(+), EpCAM(-), small-, large-sized, and cluster) and cancers (lung, breast, and bladder). Applied in 30 lung adenocarcinoma patients harboring epidermal growth factor receptor (EGFR) mutations, the system isolated diverse phenotypes of CTCs in marker expression and size, implying the importance of unbiased isolation. Genetic analyses of intra-patient samples comparing cell-free DNA with CCM-isolated CTCs yielded perfect concordance, and CTC enumeration using our technique was correlated with clinical progression as well as response to EGFR inhibitors.
Conclusion: Our system also introduces technical advances which assure rapid, reliable, and reproducible results, thus enabling a more comprehensive application of robust CTC analysis in clinical practice.
Keywords: cancer heterogeneity, circulating tumor cells, continuous centrifugal microfluidics, unbiased isolation, full automation