Evidence map›Paper›PMID 41085819›Full record

ArticleDiscover oncology2025

Interleukin-1 receptor-associated kinase-1 is a therapeutic target for gastric cancer.

Hui Shi, Jie Zhang, Xiaohua Bao

Abstract read
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Hui Shi *Department of Gastroenterology, The 964th Hospital of People's Liberation Army Joint Logistic Support Force, No. 4799 Xi'an Road, Changchun, P.R. China.
Jie Zhang *Department of Gastroenterology, The 964th Hospital of People's Liberation Army Joint Logistic Support Force, No. 4799 Xi'an Road, Changchun, P.R. China.
Xiaohua BaoDepartment of Gastroenterology, The 964th Hospital of People's Liberation Army Joint Logistic Support Force, No. 4799 Xi'an Road, Changchun, P.R. China. 13514296857@163.com.ORCID http://orcid.org/0009-0007-8785-3848

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Interleukin-1 receptor-associated kinase 1 (IRAK1), a pivotal mediator in innate immunity and inflammatory processes, exhibits constitutive activation across various cancers. Our study highlights the significant role of IRAK1 in gastric cancer progression. We observed elevated IRAK1 expression in both gastric cancer tissues and cells, which correlates with malignant phenotypes, including heightened proliferation, colony formation, and migratory capacity in normal gastric cells upon IRAK1 overexpression. Silencing IRAK1 genetically in gastric cancer cells effectively suppressed these oncogenic traits. Notably, we found that gastric cancer cells display marked sensitivity to IRAK1/4 inhibitor and pacritinib, the latter targeting JAK2 and IRAK1 specifically, over the pan-JAK inhibitor tofacitinib. In vivo experiments using a xenograft mouse model demonstrated the efficacy of pacritinib in arresting gastric cancer growth without eliciting significant systemic toxicity. Immunohistochemical analyses further confirmed pacritinib's ability to attenuate tumor progression by inhibiting IRAK1 activity. Collectively, our results underscore IRAK1 as a promising therapeutic target in gastric cancer. Furthermore, the pharmacological blockade of IRAK1 by pacritinib, an established drug for myelofibrosis and severe thrombocytopenia treatment, holds potential for repurposing in gastric cancer therapy.

Indexed as

Gastric cancerIRAK1PacritinibXenograft model

Identifiers

PMID41085819
PMCPMC12521082

What OpenQuestion holds

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LicenceCC BY
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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.