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BMC cancer · 2024

Detection of circulating tumor cells in patients with lung cancer using a rare cell sorter: a pilot study.

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Sugai Kazuto, Mori Tomoko, Bilal Turan, Furukawa Atsuko, Sekine Yasuharu, Kobayashi Naohiro, Kikuchi Shinji, Goto Yukinobu, Ichimura Hideo, Masuda Taisuke, Arai Fumihito, Sato Yukio, Matsusaka Satoshi

Аннотация

BACKGROUND: We developed a Rare Cell Sorter (RCS) for collecting single cell including circulating tumor cells (CTCs). This single-institution pilot study evaluated the ability of this device to detect tumor-like cells in patients with lung cancer and confirmed their genuineness based on the epidermal growth factor receptor (EGFR) mutation concordance with tissue samples.

METHODS: This study included patients treated for lung cancer from September 2021 to August 2022 in University of Tsukuba Hospital. Peripheral blood samples were obtained before surgery or during periodic medical checks for patients treated with drugs. We used the RCS to capture cells based on size. The cells were stained, and the Hoechst-positive, CD45-negative, and epithelial celladhesion molecule (EpCAM)- positive cells were defined as CTCs, were collected. The presumptive CTCs were counted and tested using digital droplet polymerase chain reaction for EGFR mutations and compared with the tissue EGFR status to check concordance.

RESULTS: Eighteen patients were included in this study and CTCs were detected in 6 patients (33%). The CTCs from three patients showed EGFR mutation, and the EGFR mutation status of CTCs concorded with that of tissue samples in 83% of the cases (5/6). Only one CTC showed a different status from the tissue, and the concordance rate of EGFR status between CTCs and the tissue was 96% (24/25).

CONCLUSION: The ability of the RCS to detect CTCs in patients with lung cancer was demonstrated based on the concordance of EGFR status in this pilot study. This novel hybrid method of CTC recovery using the RCS has the potential to recover a wide range of CTCs regardless of EpCAM. Further validation through a large-scale study is needed.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты