Evidence map›Paper›PMID 40721545›Full record

ReviewDiscover oncology2025

Decoding tumor-infiltrating lymphocytes heterogeneity in ductal carcinoma in situ: immune microenvironment dynamics and prognostic insights.

Lingzi Wang, Yalong Yang, Yuhang Song, Jiahui Zeng, Hongmei Zheng, Xinhong Wu

Abstract readReview
In one paragraph

Review in Discover oncology, 2025. 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. 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

6 authors.

Lingzi Wang *Breast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China.
Yalong Yang *Breast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China.
Yuhang SongBreast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China.
Jiahui ZengBreast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China.
Hongmei ZhengBreast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China. zhenghongmeicj@163.com.
Xinhong WuBreast Cancer Center, Tongji Medical College, Hubei Provincial Clinical Research Center for Breast Cancer, Hubei Cancer Hospital, Huazhong University of Science and Technology, National Key Clinical Specialty Construction Discipline, Wuhan Clinical Research Center for Breast Cancer, No.116 Zhuo Daoquan South Road, Wuhan, 430079, Hubei, China. wuxinhong_9@sina.com.ORCID http://orcid.org/0000-0001-7185-6787

Funding

Hubei Cancer Hospital Biomedical Center Research Project 2022SWZX03Hubei Province Medical Youth Top Talent Project EWT [2023] 65, Oncology
6 · The paper itself

Abstract

With the widespread use of mammography, the incidence of ductal carcinoma in situ (DCIS) has significantly increased and currently accounts for approximately 20-25% of newly diagnosed breast cancer cases. While a significant proportion of DCIS lesions exhibit long-term indolence without progression to invasive carcinoma, the current paucity of validated biomarkers for invasive potential prediction creates a therapeutic dilemma in clinical practice, potentially leading to either overtreatment of biologically inert lesions or undertreatment of high-risk precursors. Reflecting the body's adaptive immune response, tumor-infiltrating lymphocytes (TILs) have been demonstrated to be associated with adverse clinicopathologic factors in DCIS. The relationship between total TILs and the risk of DCIS recurrence remains controversial, but subpopulations of TILs such as FOXP3 + T lymphocytes, B cells, CD68, and CD163 macrophages are found to be associated with DCIS recurrence. Increased levels of total TILs are associated with increased malignancy of breast lesions, and the number and composition of TILs subpopulations change during DCIS progression. Moreover, dense TILs are correlated with high PD-L1 expression and the "healing" phenomenon in DCIS. Further exploration of the immune microenvironment, TILs subpopulations, and adaptive immune responses in DCIS remains a critical unmet need, contributing to more refined risk stratification of DCIS patients and facilitating the implementation of new treatments.

Indexed as

Adaptive immunityDuctal carcinoma in situImmune checkpointImmune microenvironmentImmunotherapyPrognosisTumor-infiltrating lymphocytes

Identifiers

PMID40721545
PMCPMC12304345

What OpenQuestion 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 OpenQuestion graph.