Related Experiment Video
Updated: Jul 1, 2026
08:08
Quantitative Mass Spectrometric Profiling of Cancer-cell Proteomes Derived From Liquid and Solid Tumors
Published on: February 27, 2015
Democratized single-cell proteomics resolves cell state heterogeneity in skin tumors
Joseph Inns1, Andrew Michael Frey2, Weng Wi Ng3
1Translational and Clinical Research Institute, Newcastle University; and NIHR Newcastle Biomedical Research Centre (BRC), Newcastle upon Tyne, UK joe.inns@newcastle.ac.uk.
Life Science Alliance
|June 29, 2026
Summary
A new label-free single-cell proteomics method analyzes human tissue cost-effectively. This accessible technology reveals cellular heterogeneity and identifies novel tumor-associated macrophages in CYLD cutaneous syndrome.
Area of Science:
- Proteomics
- Cellular Biology
- Biotechnology
Background:
- Single-cell proteomics (SCP) offers insights into cellular heterogeneity beyond bulk analysis.
- Current SCP methods face challenges including high cost, sample loss, and specialized instrumentation requirements.
Purpose of the Study:
- To present a cost-effective, label-free single-cell proteomics methodology for human tissue.
- To address limitations of existing SCP techniques regarding cost, sample handling, and accessibility.
- To assess tumor heterogeneity in CYLD cutaneous syndrome (CCS) using the developed SCP method.
Main Methods:
- Developed a label-free SCP pipeline combining Fluorescence-Activated Cell Sorting (FACS), oil-immersion cell handling, mass spectrometry, and neural-network spectral libraries.
- Utilized a Bruker timsTOF HT platform for protein quantification.
- Adapted bioinformatic tools from single-cell RNA sequencing (scRNA-seq) for data analysis.
Main Results:
- Quantified over 4,000 proteins, averaging approximately 700 proteins per cell, in 419 CCS tumor cells.
- Successfully discriminated between macrophages, dendritic cells, and tumor keratinocytes using unbiased analysis.
- Validated cell annotations by cross-referencing with FACS markers.
- Identified a novel population of CCS tumor-associated macrophages with a tumor microenvironment remodeling signature.
Conclusions:
- The developed SCP technology is accessible and cost-effective for analyzing clinical human tissue.
- This methodology enables novel biological discoveries, including the identification of specific cell populations and their functional signatures.
- The study demonstrates the potential of SCP in understanding complex diseases like CCS and tumor microenvironments.
