Evidence map›Paper›PMID 39526396›Full record

ArticleNucleic acids research2025

scProAtlas: an atlas of multiplexed single-cell spatial proteomics imaging in human tissues.

Tiangang Wang, Xuanmin Chen, Yujuan Han, Jiahao Yi, Xi Liu, Pora Kim, Liyu Huang, Kexin Huang, Xiaobo Zhou

Abstract read
In one paragraph

Article in Nucleic acids research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Neutrophils in cancer.Nature reviews. Cancer · 2026
    Review
  2. Spatium: A Protein Language Foundation Model for Spatial Proteomics.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Review
  5. Decoding the breast cancer microenvironment by spatial multi-omics: from architecture to clinical translation.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Review
  6. Review
  7. Review
  8. Spatial omics for profiling the dynamic tumor microenvironment.Clinical & translational immunology · 2026
    Review
  9. Review
  10. Review
  11. Review
  12. 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

9 authors.

Tiangang WangSchool of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.
Xuanmin ChenSchool of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.
Yujuan HanWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, Sichuan 843000, P.R. China.
Jiahao YiDepartment of Medical Informatics, School of Biology and Engineering, Guizhou Medical University, Guiyang, Guizhou 561100, P.R. China.
Xi LiuSchool of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.
Pora KimCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0002-8321-6864
Liyu HuangSchool of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.ORCID 0000-0001-6534-2712
Kexin HuangSchool of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, P.R. China.ORCID 0009-0001-5697-6710
Xiaobo ZhouCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.ORCID 0000-0001-7191-6495

Funding

Multiscale Resolution and Deep Network Approaches for Deconvolving Different Cell Types in Bulk Tumor using Single-cell Sequencing Data (scDEC)R01CA241930 · NCI · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2019 to 2023
$2.7M
Functional annotation of new genes aided by deep learningR35GM138184 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KIM, PORA · 2020 to 2024
$1.7M
Optimizing mRNA sequences with deep neural networksR01LM014156 · NLM · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI Xiaobo Zhou · 2024 to 2026
$1.1M
Developing mRNAdesigner tool package for optimization of mRNA sequenceR01GM153822 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2024 to 2025
$624k
China Postdoctoral Science Foundation 2023M742498National Natural Science Foundation of China 62373292National Science Foundation NSF2217515NCI NIH HHS R01 CA241930NIGMS NIH HHS R01 GM153822NIGMS NIH HHS R35 GM138184NIH HHS R35GM138184NLM NIH HHS R01 LM014156
6 · The paper itself

Abstract

Spatial proteomics can visualize and quantify protein expression profiles within tissues at single-cell resolution. Although spatial proteomics can only detect a limited number of proteins compared to spatial transcriptomics, it provides comprehensive spatial information with single-cell resolution. By studying the spatial distribution of cells, we can clearly obtain the spatial context within tissues at multiple scales. Spatial context includes the spatial composition of cell types, the distribution of functional structures, and the spatial communication between functional regions, all of which are crucial for the patterns of cellular distribution. Here, we constructed a comprehensive spatial proteomics functional annotation knowledgebase, scProAtlas (https://relab.xidian.edu.cn/scProAtlas/#/), which is designed to help users comprehensively understand the spatial context within different tissue types at single-cell resolution and across multiple scales. scProAtlas contains multiple modules, including neighborhood analysis, proximity analysis and neighborhood network, to comprehensively construct spatial cell maps of tissues and multi-modal integration, spatial gene identification, cell-cell interaction and spatial pathway analysis to display spatial variable genes. scProAtlas includes data from eight spatial protein imaging techniques across 15 tissues and provides detailed functional annotation information for 17 468 394 cells from 945 region of interests. The aim of scProAtlas is to offer a new insight into the spatial structure of various tissues and provides detailed spatial functional annotation.

Indexed as

ProteomicsSingle-Cell AnalysisHumansSoftware

Identifiers

PMID39526396
PMCPMC11701751

What OpenQuestion 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 OpenQuestion graph.