Evidence map›Paper›PMID 41112263›Full record

ReviewFrontiers in immunology2025

Single-cell and spatial transcriptomics integration: new frontiers in tumor microenvironment and cellular communication.

Wenxin Shi, Zhiqiang Zhang, Xiaotong Xu, Yanpeng Tian, Li Feng, Xianghua Huang, Yanfang Du, Zhongkang Li

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

  1. Article
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  8. 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
  9. Novel Approaches for Investigating Host Responses to HIV Infection in Ex Vivo Human Genital Tissues.American journal of reproductive immunology (New York, N.Y. : 1989) · 2026
    Review
  10. Review
  11. February in focus in HCB: spatial transcriptomics.Histochemistry and cell biology · 2026
    Article
  12. Article
  13. Review
  14. Article
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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

8 authors.

Wenxin ShiDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Zhiqiang ZhangDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Xiaotong XuDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yanpeng TianDepartment of Obstetrics and Gynecology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Li FengDepartment of Obstetrics and Gynecology, The Fourth Hospital of Shijiazhuang, Shijiazhuang, China.
Xianghua HuangDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Yanfang DuDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Zhongkang LiDepartment of Obstetrics and Gynecology, The Second Hospital of Hebei Medical University, Shijiazhuang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-cell RNA sequencing (scRNA-seq) has emerged as an advanced biological technology capable of resolving the complexity of cancer landscapes at single-cell resolution. Spatial transcriptomics(ST), as an innovative complementary approach, effectively compensates for the lack of spatial information inherent in scRNA-seq data. This review explores the rapidly evolving integration of scRNA-seq and ST and their transformative role in deciphering the tumor microenvironment (TME). We highlight how these technologies jointly uncover cellular heterogeneity, stromal-immune interactions, and spatial niches driving tumor progression and therapy resistance. Moving beyond previous reviews, we emphasize emerging computational strategies for data integration-including deconvolution and mapping approaches-and evaluate their applications in characterizing immune evasion, fibroblast diversity, and cell-cell communication networks. Ultimately, this review provides a forward-looking perspective on how spatial multi-omics are poised to advance precision oncology through spatially-informed biomarkers and diagnostic tools. We conclude that the full clinical potential of these technologies relies on closing the gap between analytical innovation and robust clinical implementation.

Indexed as

Cell CommunicationNeoplasmsSingle-Cell AnalysisTranscriptomeTumor MicroenvironmentAnimalsBiomarkers, TumorGene Expression ProfilingHumansBiomarkers, Tumorcancer heterogeneityintercellular communicationsingle-cell RNA sequencingspatial transcriptomicstumor microenvironment

Identifiers

PMID41112263
PMCPMC12528096

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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.