Evidence map›Paper›PMID 41807362›Full record

ArticleCell discovery2026

Integrative spatial profiling pipeline for determining TME architectures in archival clinical specimens using CmTSA superplex technology.

Chaoxin Xiao, Ruihan Zhou, Qin Chen, Wanting Hou, Yulin Wang, Lu Liu, Huanhuan Wang, Xiaohong Yao, Rui Zhu, Zirui Wang and 11 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell discovery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors.

Chaoxin Xiao *State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Ruihan Zhou *State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Qin Chen *State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Wanting HouDivision of Abdominal Tumor, Department of Medical Oncology, Cancer Center and State Key Laboratory of Biological Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Yulin WangState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Lu LiuState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Huanhuan WangState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Xiaohong YaoDepartment of Pathology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, Sichuan, China.
Rui ZhuState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Zirui WangState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Leyi YaoDivision of Abdominal Tumor, Department of Medical Oncology, Cancer Center and State Key Laboratory of Biological Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Ouying YanDivision of Abdominal Tumor, Department of Medical Oncology, Cancer Center and State Key Laboratory of Biological Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Xiaoying LiDivision of Abdominal Tumor, Department of Medical Oncology, Cancer Center and State Key Laboratory of Biological Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Tongtong XuState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Fujun CaoState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Banglei YinState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Na XiaoState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China.
Lili JiangDepartment of Pathology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Wei WangDepartment of Pathology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Dan CaoDivision of Abdominal Tumor, Department of Medical Oncology, Cancer Center and State Key Laboratory of Biological Therapy, West China Hospital, Sichuan University, Chengdu, Sichuan, China. caodan@scu.edu.cn.
Chengjian ZhaoState Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy, Chengdu, Sichuan, China. chjianzhao@scu.edu.cn.

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82270542
6 · The paper itself

Abstract

The tumor microenvironment (TME) comprises diverse cellular components that spatially interact to form distinct functional niches (FNs). Profiling these TME spatial features has proven to be a critical approach for correlating tumor progression and therapeutic response. However, RNA stability limitations constrain the broad clinical implementation of spatial transcriptomics, while high background noise and low signal resolution compromise the accuracy of direct labeling-based spatial proteomic approaches in clinical specimens. To overcome these constraints in archival samples, we developed hybrid optochemical fluorescence depletion (HOC-FD) technology that integrates autofluorescence quenching with cyclic multiplex tyramide signal amplification (CmTSA) for formalin-fixed paraffin-embedded (FFPE) tissues. This unified platform enables the concurrent labeling of 30-60 biomarkers with ultrahigh signal-to-noise ratios while maintaining cost efficiency and compatibility with high-throughput processing of archival FFPE specimens. While superplex imaging captures multidimensional TME data, extracting spatial features from raw pixel-level outputs remains technically challenging. To resolve this problem, we implemented a computer vision pipeline beginning with deep learning-based cellular segmentation and phenotype classification under predefined biomarker annotation rules. Using single-cell spatial mapping of human colon and cervical cancer specimens, we systematically evaluated and selected radius-constrained neighborhood network (RNN) analysis to define functional niches, validating their accuracy and reliability in generating spatially coherent FNs with biological and prognostic relevance. In summary, the CmTSA platform combined with RNN-based spatial profiling provides an integrated framework for visualizing and quantifying multicellular functional states within architectures of the TME, potentially enhancing tumor immunology investigations and precision immunotherapies.

Identifiers

PMID41807362
PMCPMC12976111

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.