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Isolation of TTF-1 Positive Circulating Tumor Cells for Single-Cell Sequencing by Using an Automatic Platform Based on Microfluidic Devices.

Hei-Jen JouHsin-Cheng HoKuan-Yeh HuangChen-Yang ChenSheng-Wen ChenPei-Hsuan LoPin-Wen HuangChung-Er HuangMing Chen
Published in: International journal of molecular sciences (2022)
Single-cell sequencing provides promising information in tumor evolution and heterogeneity. Even with the recent advances in circulating tumor cell (CTC) technologies, it remains a big challenge to precisely and effectively isolate CTCs for downstream analysis. The Cell Reveal TM system integrates an automatic CTC enrichment and staining machine, an AI-assisted automatic CTC scanning and identification system, and an automatic cell picking machine for CTC isolation. H1975 cell line was used for the spiking test. The identification of CTCs and the isolation of target CTCs for genetic sequencing were performed from the peripheral blood of three cancer patients, including two with lung cancer and one with both lung cancer and thyroid cancer. The spiking test revealed a mean recovery rate of 81.81% even with extremely low spiking cell counts with a linear relationship between the spiked cell counts and the recovered cell counts (Y = 0.7241 × X + 19.76, R 2 = 0.9984). The three cancer patients had significantly higher TTF-1 + CTCs than healthy volunteers. All target CTCs were successfully isolated by the Cell Picker machine for a subsequent genetic analysis. Six tumor-associated mutations in four genes were detected. The present study reveals the Cell Reveal TM platform can precisely identify and isolate target CTCs and then successfully perform single-cell sequencing by using commercially available genetic devices.
Keyphrases
  • single cell
  • circulating tumor cells
  • rna seq
  • high throughput
  • circulating tumor
  • deep learning
  • cell therapy
  • machine learning
  • artificial intelligence
  • dna methylation
  • bone marrow
  • neural network
  • health information