qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development

  • Si Chen
  • Jared Weddell
  • Pavan Gupta
  • Grace Conard
  • James Parkin
  • Princess I. Imoukhuede
Part of the Methods in Molecular Biology book series (MIMB, volume 1570)


Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

Key words

Quantitative flow cytometry qFlow cytometry Immuno-labeling Systems biology Vascular Endothelial Growth Factor (VEGF) Platelet-Derived Growth Factor (PDGF) Angiogenesis Background subtraction Mixture modeling Heterogeneity 



We would like to thank Dr. Barbara Pilas for her advice and help with flow cytometry. We would also like to thank Spencer B. Mamer and Ali Ansari for their help with editing. Finally, we would like to thank the American Heart Association Grant #16SDG26940002, American Cancer Society Illinois Division Basic Research Grant #282802, and National Science Foundation CBET Grant #1512598 for funding support.


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Copyright information

© Springer Science+Business Media LLC 2017

Authors and Affiliations

  • Si Chen
    • 1
  • Jared Weddell
    • 1
  • Pavan Gupta
    • 2
  • Grace Conard
    • 3
  • James Parkin
    • 4
  • Princess I. Imoukhuede
    • 1
  1. 1.Bioengineering DepartmentUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.Chicago College of Osteopathic MedicineDowners GroveUSA
  3. 3.Indiana University School of MedicineIndianapolisUSA
  4. 4.Bioengineering DepartmentCalifornia Institute of TechnologyPasadenaUSA

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