Evidence map›Paper›PMID 41580422›Full record

ArticleNPJ breast cancer2026

CD52 signaling via macrophage Siglec-G represents a therapeutic target for cancer immunotherapy.

Xueting Qin, Yixin Chang, Yuanyuan Qiu, Weidong Han, Jing Nie

Abstract read
In one paragraph

Article in NPJ breast cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

5 authors.

Xueting QinSchool of Medicine, Nankai University, Tianjin, China.
Yixin ChangDepartment of Bio-therapeutic, the First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China.
Yuanyuan QiuSchool of Life Sciences, Biomedical Pioneering Innovation Center, Peking University, Beijing, China.
Weidong HanSchool of Medicine, Nankai University, Tianjin, China. hanwdrsw@163.com.
Jing NieDepartment of Bio-therapeutic, the First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China. nnjj2002@163.com.

Funding

Beijing Nova Program 20230484434National Natural Science Foundation of China 82370228National Science and Technology Major Project 2023ZD0501300National Science and Technology Major Project 2025ZD0543900
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) remains a lethal malignancy with limited targeted therapies and high metastatic rates. Cancer cells evade macrophage clearance by overexpressing anti-phagocytic cell surface proteins, termed "don't eat me" signals. Blocking antibodies (e.g., anti-CD47) against these signals show therapeutic promise in multiple cancers, yet variable responses and limited durability of efficacy to such agents imply additional unknown "don't eat me" signals exist. Here, we detected positive CD52 expression in tumors from TNBC patients and demonstrated that CD52 on TNBC cells facilitates immune evasion by engaging the inhibitory receptor sialic acid-binding Ig-like lectin G (Siglec-G) on tumor-associated macrophages. Genetic ablation of either CD52 or Siglec-G, as well as antibody-mediated blockade of their interaction restored macrophage phagocytic activity both in vitro and in vivo. This consequently suppressed tumor progression, improved survival, and promoted an immunologically active tumor microenvironment in TNBC mouse models. Additionally, cotreatment with anti-CD52 sensitized tumor cells to PD-1 blockade therapy in the spontaneous MMTV-PyMT TNBC model. Our findings identify CD52 as a prominently expressed anti-phagocytic checkpoint in TNBC and reveal the therapeutic potential of dual PD-1/CD52 blockade as a novel immunotherapeutic strategy.

Identifiers

PMID41580422
PMCPMC12936179

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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.