Evidence mapPaperPMID 39806382Full record

ArticleCancer cell international2025

Characterizing tertiary lymphoid structures associated single-cell atlas in breast cancer patients.

Xiaokai Fan, Daqin Feng, Donggui Wei, Anqi Li, Fangyi Wei, Shufang Deng, Muling Shen, Congzhi Qin, Yongjia Yu, Lun Liang

Abstract read
In one paragraph

Article in Cancer cell international, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Review
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  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Spatial omics for profiling the dynamic tumor microenvironment.Clinical & translational immunology · 2026
    Review
  10. Article
  11. Review
  12. Article
  13. 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

10 authors.

Xiaokai Fan *Department of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Daqin Feng *Department of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Donggui Wei *Department of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Anqi LiDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Fangyi WeiDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Shufang DengDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Muling ShenDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Congzhi QinDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China.
Yongjia YuDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China. yyjfish@126.com.
Lun LiangDepartment of Neurosurgery, The First Affiliated Hospital, Guangxi Medical University, Nanning, China. lianglun@sr.gxmu.edu.cn.

Funding

Guangxi Key Research and Development Program No. 2023AB22116Guangxi medical and health appropriate technology development and application project No. S2018013National Natural Science Foundation of China No. 82260554Natural Science Foundation of Guangxi Province No. 2023GXNSFBA026092
6 · The paper itself

Abstract

The tertiary lymphoid structure (TLS) is recognized as a potential prognosis factor for breast cancer and is strongly associated with response to immunotherapy. Inducing TLS neogenesis can enhance the immunogenicity of tumors and improve the efficacy of immunotherapy. However, our understanding of TLS associated region at the single-cell level remains limited. Therefore, we employed high-resolution techniques, including single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST), and a TLS-specific signature to investigate TLS associated regions in breast cancer. We identified eighteen cell types within the TLS associated regions and calculated differential expression genes by comparing TLS associated regions with other areas. Notably, macrophages in the TLS associated regions exhibit lineage transformation, shifting from facilitators of immune activation to supporters of tumor cell growth. In terms of cell-cell communication within the TLS associated regions, KRT86

Indexed as

Cell–cell communicationCell componentsLineage trajectoryTertiary lymphoid structure

Identifiers

PMID39806382
PMCPMC11727541

What Socratic holds

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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.