4.8 Article

Microfluidic sorting and multimodal typing of cancer cells in self-assembled magnetic arrays

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.1001515107

关键词

lab-on-a-chip; magnetic beads; cell sorting; cancer diagnosis

资金

  1. ANR [08-BIOT-015-02]
  2. EU [NMP4-SL-2009-228980]
  3. Direction Generale de l'Armement and Institut National de Recherche contre le Cancer

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We propose a unique method for cell sorting, Ephesia, using columns of biofunctionalized superparamagnetic beads self-assembled in a microfluidic channel onto an array of magnetic traps prepared by microcontact printing. It combines the advantages of microfluidic cell sorting, notably the application of a well controlled, flow-activated interaction between cells and beads, and those of immunomagnetic sorting, notably the use of batch-prepared, well characterized antibody-bearing beads. On cell lines mixtures, we demonstrated a capture yield better than 94%, and the possibility to cultivate in situ the captured cells. A second series of experiments involved clinical samples-blood, pleural effusion, and fine needle aspirates-issued from healthy donors and patients with B-cell hematological malignant tumors (leukemia and lymphoma). The immunophenotype and morphology of B-lymphocytes were analyzed directly in the microfluidic chamber, and compared with conventional flow cytometry and visual cytology data, in a blind test. Immunophenotyping results using Ephesia were fully consistent with those obtained by flow cytometry. We obtained in situ high resolution confocal three-dimensional images of the cell nuclei, showing intranuclear details consistent with conventional cytological staining. Ephesia thus provides a powerful approach to cell capture and typing allowing fully automated high resolution and quantitative immunophenotyping and morphological analysis. It requires at least 10 times smaller sample volume and cell numbers than cytometry, potentially increasing the range of indications and the success rate of microbiopsy-based diagnosis, and reducing analysis time and cost.

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