Evidence map›Paper›PMID 40000397›Full record

ArticleClinical and translational medicine2025

Predictive circulating biomarkers of the response to anti-PD-1 immunotherapy in advanced HER2 negative breast cancer.

Yuhan Wei, Hewei Ge, Yalong Qi, Cheng Zeng, Xiaoying Sun, Hongnan Mo, Fei Ma

Abstract read
In one paragraph

Article in Clinical and translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Article
  5. CD39Frontiers in oncology · 2025
    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

7 authors.

Yuhan Wei *Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Hewei Ge *Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Yalong QiDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Cheng ZengDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0002-9392-8259
Xiaoying SunDepartment of Medical Oncology, Cancer Hospital of HuanXing ChaoYang District, Beijing, China.
Hongnan MoDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Fei MaDepartment of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.ORCID 0000-0001-8554-7512

Funding

CAMS Innovation Fund for Medical Sciences CIFMS2022-I2M-C&T-B-067National Natural Science Foundation of China 82230058
6 · The paper itself

Abstract

backgroundImmunotherapy shows promise for treating advanced breast cancer, but only a few patients could respond. Predictive biomarkers from peripheral blood are urgently needed.

methodsWe designed a comprehensive 42-marker mass cytometry panel to profile the peripheral blood samples from 57 patients diagnosed with advanced HER2-negative breast cancer receiving anti-PD-1 combination therapy. Patients were categorized as responders and non-responders according to 6-month progression-free survival (PFS), followed by phenotypic and functional comparations to identify candidate predictive biomarkers. Longitudinal analysis of paired samples further revealed dynamic changes in these specific subpopulations.

resultsNon-responders exhibited significantly higher frequencies of CD39+ Tregs (adjusted p = .031) in the T-cell milieu at baseline, which exhibited a positive correlation with PD-1+ T cells in the NR group. Longitudinal assessment indicated a significant decrease of PD-1+ T cells and an increase of CD39+ Tregs following anti-PD-1 treatment, suggesting their potential role in immunotherapy resistance. In the myeloid compartment, responders showed significantly higher CCR2+ monocyte-derived dendritic cell frequencies than non-responders (adjusted p = .037). These cells were positively correlated with other dendritic cells in responders but negatively with naïve T cells in non-responders. Based on these two efficacy-related biomarkers, we developed an immunotherapy prognostic prediction model and confirmed its superiority in distinguishing patient PFS (p < .001).

conclusionPeripheral CD39+ Tregs and monocyte-derived dendritic cells are correlated with immunotherapy response, serving as potential biomarkers to guide therapeutic choices in immunotherapy. KEY POINTS: CD39+ Tregs in peripheral blood are associated with poor response to anti-PD-1 immunotherapy in advanced breast cancer. Higher frequencies of CCR2+ monocyte-derived dendritic cells correlate with better immunotherapy outcomes. A predictive model based on CD39+ Tregs and monocyte-derived dendritic cells effectively distinguishes patient progression-free survival. Peripheral blood biomarkers offer a non-invasive approach to guide immunotherapy choices.

Indexed as

Biomarkers, TumorBreast NeoplasmsImmunotherapyAdultAgedErb-b2 Receptor Tyrosine KinasesFemaleHumansMiddle AgedProgrammed Cell Death 1 ReceptorBiomarkers, TumorERBB2 protein, humanErb-b2 Receptor Tyrosine KinasesProgrammed Cell Death 1 Receptorbreast cancerCyTOFimmunotherapyPD‐1peripheral blood mononuclear cellpredictive biomarkerssystemic immunity

Identifiers

PMID40000397
PMCPMC11859116

What Socratic holds

Textmetadata
LicenceCC BY
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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.