Evidence map›Paper›PMID 39588148›Full record

ArticleFrontiers in pharmacology2024

Concurrent immune checkpoint blockade for enhanced cancer immunotherapy utilizing engineered hybrid nanovesicles.

Yuxuan Liu, Fuxu Yang, Zhimin Li, Ting Wang, Yeteng Mu, Yuxin Fan, Han Xue, Xiuli Hu, Xingang Guan, Hongxia Feng

Abstract read
In one paragraph

Article in Frontiers in pharmacology, 2024. 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. Targeted delivery platforms forFrontiers in pharmacology · 2026
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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.

Yuxuan Liu *Department of Dermatology, The Affiliated Wenling Hospital of Taizhou University, Taizhou, China.
Fuxu Yang *College of Medical Technology, Beihua University, Jilin, China.
Zhimin Li *College of Medical Technology, Beihua University, Jilin, China.
Ting WangMedical School, Taizhou University, Taizhou, China.
Yeteng MuCollege of Medical Technology, Beihua University, Jilin, China.
Yuxin FanCollege of Medical Technology, Beihua University, Jilin, China.
Han XueCollege of Medical Technology, Beihua University, Jilin, China.
Xiuli HuInstitute of Polymer Science and Engineering, School of Chemical Engineering, Hebei University of Technology, Tianjin, China.
Xingang GuanMedical School, Taizhou University, Taizhou, China.
Hongxia FengDepartment of Dermatology, The Affiliated Wenling Hospital of Taizhou University, Taizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, demonstrating unprecedented efficacy against advanced cancers. However, their clinical applications are significantly hampered by low overall response rates. Dual blockade of two immune checkpoints represents a promising strategy to enhance immunotherapeutic efficacy. In this study, we developed hybrid cell membrane nanovesicles adorned with PD-1 and SIRPα receptors for combination immunotherapy in melanoma. Our hybrid nanovesicles (PD-1/SIRPα NVs) demonstrated high specificity to PD-L1 and CD47 ligands, facilitating the phagocytosis of melanoma cells by macrophages. In a melanoma mouse model, PD-1/SIRPα NVs significantly suppressed 77% of tumor growth and elicited a robust antitumor immune response for immunotherapy. In conclusion, our findings highlight the promising potential of PD-1/SIRPα NVs as novel and effective ICIs for cancer immunotherapy.

Indexed as

cancer immunotherapycell membrane nanovesicleimmune checkpoint blockadePD-1SIRPα

Identifiers

PMID39588148
PMCPMC11586202

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.