Evidence map›Paper›PMID 41065842›Full record

ArticleCancer immunology, immunotherapy : CII2025

A pan-cancer single-cell analysis reveals the effect of PD-1 blockades on tumor angiogenesis by inhibiting the endothelial CXCL12-CXCR4 axis.

Mairedan Muhetarijiang, Pengwei Zhu, Han Zhang, Xiangjie Sun, Yakui Wu, Qianwen Xu, Ryan Justin, Chenxi Li, Dongchen Zhou, Biqi Zhang and 3 more

Abstract read
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2025. 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

13 authors.

Mairedan MuhetarijiangDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Pengwei Zhu *Department of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Han ZhangDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Xiangjie SunDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Yakui WuDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Qianwen XuDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Ryan JustinSchool of Medicine, Zhejiang University, Hangzhou, China.
Chenxi LiDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Dongchen ZhouDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Biqi ZhangDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.
Jun LiuJinhua People's Hospital, Jinhua, China.
Xiaosheng HuDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China. 1196017@zju.edu.cn.
Ting ChenDepartment of Cardiology, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China. ct010151452@zju.edu.cn.

Funding

National Key Research and Development Program of China 2023YFC3606500National Natural Science Foundation of China 32171098National Natural Science Foundation of China 82170489National Natural Science Foundation of China 82470428Natural Science Foundation of Zhejiang Province LMS25H010001Natural Science Foundation of Zhejiang Province LMS25H020003Project of Medical Science Research Foundation from the Health Department of Zhejiang Province, China WKJ-ZJ-2312Zhejiang Provincial Medical and Health Science and Technology Project, China 2025KY409
6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs), particularly programmed cell death protein 1 (PD-1) blockades, have redefined oncology in the last decade. Previous studies on PD-1 blockades mostly concentrate on their interactions with immune cells. This study aims to investigate how PD-1 blockades affect endothelial cell (EC) heterogeneity in the tumor microenvironment (TME) and to explore potential targets for enhancing the anti-tumor effects of PD-1 blockades. Here, we established a pan-cancer EC atlas from the public database and revealed that PD-1 blockades repress the angiogenic population in ECs and inhibit the CXCL12-CXCR4 signaling derived from ECs. Using a murine tumor model built with Lewis Lung Carcinoma cell line, we further validated our findings that a PD-1 blockade, as well as a CXCR4 antagonist AMD3100, inhibited EC population in tumors and their CXCL12 expression. In addition, the combo therapy of the PD-1 blockade and AMD3100 showed superior anti-tumor effects to monotherapy. Moreover, we predicted MYC to be the potential regulator through which PD-1 blockades affect ECs. Together, our results suggest that PD-1 blockades have an anti-angiogenic effect besides boosting T cell immunity, and the CXCL12/CXCR4 pathway is a potential target for enhancing the effectiveness of PD-1 blockades.

Indexed as

Chemokine CXCL12Endothelial CellsImmune Checkpoint InhibitorsNeoplasmsNeovascularization, PathologicProgrammed Cell Death 1 ReceptorReceptors, CXCR4AngiogenesisAnimalsBenzylaminesCarcinoma, Lewis LungCell Line, TumorCyclamsHumansMiceMice, Inbred C57BLBenzylaminesChemokine CXCL12CXCL12 protein, humanCXCR4 protein, humanCyclamsImmune Checkpoint InhibitorsPDCD1 protein, humanplerixaforProgrammed Cell Death 1 ReceptorReceptors, CXCR4CXCL12/CXCR4Endothelial cellIntegrated single-cell analysisPD-1 blockades

Identifiers

PMID41065842
PMCPMC12511515

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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.