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Related Experiment Video

Updated: Feb 3, 2026

Single-cell Profiling of Developing and Mature Retinal Neurons

Single-cell Profiling of Developing and Mature Retinal Neurons

Published on: April 19, 2012

Ultrafast Single-Cell Level Enzymatic Tumor Profiling.

Ee Xien Ng¹, Guoyun Sun¹, Shih-Chung Wei^1,2

¹Department of Biomedical Engineering , National University of Singapore , 4 Engineering Drive 3, 04-08 , Singapore , Singapore.

Analytical Chemistry

|October 27, 2018

Summary

This summary is machine-generated.

A novel high-throughput screening platform analyzes single-cell protease activity in tumors. This enables rapid, precise tumor profiling for personalized cancer medicine and therapeutic decisions.

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Studying Proteolysis of Cyclin B at the Single Cell Level in Whole Cell Populations

Studying Proteolysis of Cyclin B at the Single Cell Level in Whole Cell Populations

Published on: September 17, 2012

Area of Science:

Biomedical Engineering
Oncology
Proteomics

Background:

Precision medicine demands timely clinical measurements for effective tumor analysis.
Rapid, large-scale single-cell screening is crucial for understanding tumor progression and guiding therapeutics.

Purpose of the Study:

To develop a high-throughput screening (HTS) platform for comprehensive single-cell analysis of tumor proteolytic activities.
To enable rapid, data-driven identification of cell types and states within tumors for clinical applications.

Main Methods:

A droplet-based microfluidic flow cytometer (Droplet-μFC) integrating optical fluorescence detectors and computational analysis was developed.
The platform analyzes multiple protease activities at single-cell resolution from patient-derived tumors (0.5-2 M cells) within 2 hours.
Computational clustering and cell mapping were employed for precise data analysis and tumor profiling.

Main Results:

The Droplet-μFC platform achieved a throughput of approximately 100 cells per second.
Distinct cell types and states were identified through high-precision protease profiling.
A library of protease activities across various cell types was generated.

Conclusions:

The developed platform provides rapid quantitative tumor profiling with detailed cell population distributions and functions.
This technology supports on-time clinical measurements essential for precision medicine and therapeutic strategies.
Advanced computational methods enhance the precision and utility of single-cell analysis in oncology.