Development of a Microfluidic Flow Cytometer with a Uniform Optical Field (Uni-μFCM) Enabling Quantitative Analysis of Single-Cell Proteins and Its Applications in Leukemia Gating, Tumor Classification, and
Hierarchy of Cancer Stem Cells.
ACS Sens 2023;
8:3498-3509. [PMID:
37602731 PMCID:
PMC10521140 DOI:
10.1021/acssensors.3c01060]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 08/02/2023] [Indexed: 08/22/2023]
Abstract
Fast and quantitative estimation of single-cell proteins with various distribution patterns remains a technical challenge. Here, a microfluidic flow cytometer with a uniform optical field (Uni-μFCM) was developed, which enabled the translation of multicolor fluorescence signals of bound antibodies into targeted protein numbers with arbitrary distributions of biological cells. As the core of Uni-μFCM, a uniform optical field for optical excitation and fluorescence detection was realized by adopting a microfabricated metal window to shape the optical beam for excitation, which was modeled and validated by both numerical simulation and experimental characterization. After the validation of Uni-μFCM in single-cell protein quantification by measuring single-cell expressions of three transcriptional factors from four cell lines of variable sizes and origins, Uni-μFCM was applied to (1) quantify membrane and cytoplasmic markers of myeloid and lymphocytic leukocytes to classify cell lines and normal and patient blood samples; (2) measure single-cell expressions of key cytokines affiliated with gene stabilities, differentiating paired oral and colon tumor cell lines with varied malignancies, and (3) quantify single-cell stemming markers of liver tumor cell lines, cell subtypes, and liver patient samples to determine a variety of lineage hierarchy. By quantitatively assessing complex cellular phenotypes, Uni-μFCM substantially expanded the phenotypic space accessible to single-cell applications in leukemia gating, tumor classification, and hierarchy determination of cancer stem cells.
Collapse