Integrative spatial profiling pipeline for determining TME architectures in archival clinical specimens using CmTSA
Chaoxin Xiao1, Ruihan Zhou1, Qin Chen1
1State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Cell Discovery
|March 11, 2026
Summary
We developed a new imaging technology (HOC-FD) for analyzing the tumor microenvironment (TME) in archival samples. This method accurately maps cellular interactions and functional niches (FNs) for improved cancer research and immunotherapy.
Area of Science:
- Oncology
- Immunology
- Biotechnology
Background:
- The tumor microenvironment (TME) is crucial for tumor progression and therapeutic response.
- Current spatial transcriptomics and proteomics methods face limitations with archival samples (RNA instability, low resolution).
- Accurate profiling of TME spatial features is essential for understanding cancer biology.
Purpose of the Study:
- To develop a novel technology for high-resolution spatial profiling of archival FFPE tissues.
- To overcome limitations of existing spatial analysis methods in clinical specimens.
- To enable accurate identification and analysis of functional niches within the TME.
Main Methods:
- Developed hybrid optochemical fluorescence depletion (HOC-FD) technology.
- Integrated autofluorescence quenching with cyclic multiplex tyramide signal amplification (CmTSA).
- Implemented a computer vision pipeline with deep learning for cellular segmentation and RNN analysis for functional niche definition.
Main Results:
- HOC-FD enables concurrent labeling of 30-60 biomarkers with high signal-to-noise ratios in FFPE tissues.
- The computer vision pipeline accurately performs cellular segmentation and phenotype classification.
- Radius-constrained neighborhood network (RNN) analysis reliably defines spatially coherent functional niches with biological relevance.
Conclusions:
- The CmTSA platform combined with RNN analysis provides an integrated framework for TME spatial profiling.
- This approach enhances visualization and quantification of multicellular states within tumor architectures.
- The technology holds potential for advancing tumor immunology research and precision immunotherapies.
