Evidence map›Paper›PMID 41862467›Full record

ArticleNature communications2026

Ultra-precision deconvolution of spatial transcriptomics decodes immune heterogeneity and fate-defining programs in tissues.

Yin Xu, Zurui Huang, Yawei Zhang, Minghui Gong, Zhenghang Wang, Peijin Guo, Feifan Zhang, Jing Yang, Guanghao Liang, Lihui Dong and 11 more

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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.

Yin Xu *RNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.ORCID http://orcid.org/0000-0003-4307-8425
Zurui Huang *RNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.ORCID http://orcid.org/0000-0002-2900-7930
Yawei Zhang *RNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Minghui Gong *RNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Zhenghang Wang *Department of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China.
Peijin GuoState Key Laboratory of Molecular Oncology, School of Basic Medical Sciences, Institute for Immunology, Tsinghua University, Beijing, China.
Feifan ZhangRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Jing YangRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.ORCID http://orcid.org/0000-0001-5199-7435
Guanghao LiangRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Lihui DongRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Renbao ChangRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Yu XiaState Key Laboratory of Molecular Oncology, School of Basic Medical Sciences, Institute for Immunology, Tsinghua University, Beijing, China.
Haochen NiRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Wenxuan GongRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Boyuan MeiState Key Laboratory of Molecular Oncology, School of Basic Medical Sciences, Institute for Immunology, Tsinghua University, Beijing, China.
Yuan GaoRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.
Zhaoqi LiuRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China.ORCID http://orcid.org/0000-0002-3798-9583
Lin ShenDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China.ORCID http://orcid.org/0000-0003-1134-2922
Jian LiDepartment of Gastrointestinal Oncology, Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Peking University Cancer Hospital & Institute, Beijing, China.ORCID http://orcid.org/0000-0002-9333-3255
Meng Michelle XuState Key Laboratory of Molecular Oncology, School of Basic Medical Sciences, Institute for Immunology, Tsinghua University, Beijing, China. michellexu@mail.tsinghua.edu.cn.ORCID http://orcid.org/0009-0007-1639-5640
Dali HanRNA Center for Cross-disciplinary Omics and Intelligent Decoding, China National Center for Bioinformation, Beijing, China. handl@big.ac.cn.ORCID http://orcid.org/0000-0001-7119-1578

Funding

National Natural Science Foundation of China (National Science Foundation of China) 22293052National Natural Science Foundation of China (National Science Foundation of China) T2495272Natural Science Foundation of Beijing Municipality (Beijing Natural Science Foundation) L244023
6 · The paper itself

Abstract

Elucidating the spatial organization and functional specialization of immune cells within complex tissues remains challenging. We present UCASpatial, an ultra-precision spatial transcriptomics deconvolution algorithm utilizing entropy-based weighting to accurately map cell subpopulations. Benchmarking confirms its superiority in identifying low-abundant cell subpopulations and distinguishing transcriptionally heterogeneous cell subpopulations. Applying UCASpatial to human colorectal cancer, we reveal that chromosome 20q gain in individual cancer clones orchestrates a T cell-excluded microenvironment, associated with HERV-H silencing and impaired type I interferon responses. In murine wound healing models, we reveal spatiotemporal dynamics distinguishing scarring from regenerative phenotypes. Specifically, we identify a pro-fibrotic community comprising Igfbp5

Indexed as

Colorectal NeoplasmsTranscriptomeAlgorithmsAnimalsFibroblastsHumansMacrophagesMiceMice, Inbred C57BLSpatial TranscriptomicsTumor MicroenvironmentWound Healing

Identifiers

PMID41862467
PMCPMC13168514

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.