Evidence map›Paper›PMID 41430089›Full record

ArticleScientific reports2025

Delivery of lipid nanoparticles containing small interfering RNA targeting transmembrane serine protease 4 in a human gastric cancer model using nude mice.

Hirofumi Tazawa, Yuko Ishida, Takahisa Suzuki, Yosuke Shimizu, Hirotaka Tashiro

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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.

Hirofumi TazawaDepartment of Surgery, NHO Kure Medical Center and Chugoku Cancer Center, Kure, Hiroshima, Japan. thiroes@gmail.com.
Yuko IshidaDepartment of Clinical research, NHO Kure Medical Center and Chugoku Cancer Center, Kure, Hiroshima, Japan.
Takahisa SuzukiDepartment of Surgery, NHO Kure Medical Center and Chugoku Cancer Center, Kure, Hiroshima, Japan.
Yosuke ShimizuDepartment of Surgery, NHO Kure Medical Center and Chugoku Cancer Center, Kure, Hiroshima, Japan.
Hirotaka TashiroDepartment of Surgery, NHO Kure Medical Center and Chugoku Cancer Center, Kure, Hiroshima, Japan. tashiro.hirotaka.zn@mail.hosp.go.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over-expression of transmembrane serine protease 4 (TMPRSS4), which promotes epithelial-to-mesenchymal transition and cancer cell invasion, is associated with poor prognosis in patients with gastric cancer. This study aimed to develop a new anti-TMPRSS4 small interfering RNA (siRNA) therapeutic strategy by engineering lipid nanoparticles (LNPs). The biodistribution and anti-tumor effect of anti-TMPRSS4-siRNA loaded LNPs were evaluated in vitro and in vivo in mice with gastric cancer tumors (subcutaneous xenograft NUGC-3 cell tumors). LNPs demonstrated enhanced accumulation in the tumor compared with naked siRNA. A significant reduction in gastric cancer tumor growth was observed in mice undergoing combination therapy with LNPs and fluorouracil (5-FU) compared to mice receiving 5-FU alone. Anti-TMPRSS4-siRNA loaded LNPs may be considered a promising therapeutic modality for gastric cancer.

Indexed as

LipidsMembrane ProteinsNanoparticlesRNA, Small InterferingSerine EndopeptidasesStomach NeoplasmsAnimalsCell Line, TumorDisease Models, AnimalFluorouracilHumansLiposomesMiceMice, NudeTissue DistributionXenograft Model Antitumor AssaysFluorouracilLipid NanoparticlesLipidsLiposomesMembrane ProteinsRNA, Small InterferingSerine EndopeptidasesTMPRSS4 protein, humanGastric cancerLipid nanoparticleSiRNATMPRSS4

Identifiers

PMID41430089
PMCPMC12749190

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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.