Evidence map›Paper›PMID 40785846›Full record

ArticleBiomaterials research2025

Ultrasound-Targeted Nanobubbles Codelivering NKP-1339 and miR-142-5p for Synergistic Mitochondrial Immunogenic Cell Death and PD-L1 Inhibition in Cancer Therapy.

Yafei Zhang, Chaoqi Liu, Shuai Jin, Liangyun Xie, Qianwen Xiao, Jun Yao

Abstract read
In one paragraph

Article in Biomaterials research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yafei ZhangThe First Affiliated Hospital , and College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China.
Chaoqi LiuHubei Key Laboratory of Tumor Microenvironment and Immunotherapy, China Three Gorges University, Yichang, Hubei 443002, China.
Shuai JinThe First Clinical Medical College of Three Gorges University, Center People's Hospital of Yichang, Yichang, Hubei 443008, China.
Liangyun XieThe First Affiliated Hospital , and College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China.
Qianwen XiaoThe First Affiliated Hospital , and College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China.
Jun YaoThe First Affiliated Hospital , and College of Clinical Medicine of Henan University of Science and Technology, Luoyang 471003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The combination of chemical immunotherapy and gene therapy holds great promise for malignant tumor treatment. Here, we developed an ultrasound-targeted liposome nanobubbles system (NKP-1339/miR-142-NBs) for precise codelivery of drugs and genes to treat esophageal squamous cell carcinoma (ESCC) with ultrasound-targeted microbubble destruction (UTMD). This study systematically investigated the system's therapeutic mechanisms-including mitochondrial dysfunction induction, immunogenic cell death (ICD), and antitumor immune activation-alongside its pharmacokinetics and targeting efficiency. In an ESCC mouse model, NKP-1339/miR-142-NBs combined with ultrasound markedly suppressed tumor growth (79.72% ± 0.1% vs. NB control 18.79% ± 1.29%) through NKP-1339 triggering ICD and miR-142-5p down-regulating programmed death-ligand 1 (PD-L1) expression, synergistically potentiating immune responses. Furthermore, we found that triggering ICD, including the exposure of calreticulin on the cell membrane, was related to altering mitochondrial fission dynamics in the ESCC cells. The down-regulation of PD-L1 expression by miR-142-5p reactivated CD8

Identifiers

PMID40785846
PMCPMC12334082

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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.