Evidence map›Paper›PMID 41049851›Full record

ReviewFrontiers in oncology2025

Decoding the microbial-local immune dialogue in liver cancer: from ecological drivers to precision therapeutics.

Yichi Xu, Bo Wen, Nan Gao, Shu Liu

Abstract readReview
In one paragraph

Review in Frontiers in oncology, 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. 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

4 authors.

Yichi XuGeriatric Department of the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Bo WenGeriatric Department of the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Nan GaoGeriatric Department of the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.
Shu LiuGeriatric Department of the First Affiliated Hospital of China Medical University, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The global incidence and mortality rates of liver cancer remain persistently high, attributable to its multifaceted etiology. Recent research has increasingly focused on the interaction between gut microbiota and the liver's immune system. The gut-liver axis, which connects the gut and liver via the portal vein system and biliary tract, is crucial in maintaining homeostasis; however, dysbiosis can compromise the gut's barrier function. The gut microbiota exerts influence over hepatic immune cells through various mechanisms, including alterations in microbial composition, production of metabolic products, and the presence of pathogen-associated molecular patterns. These interactions contribute to immune evasion, inflammation, and remodeling of the tumor microenvironment in liver cancer, thereby affecting the efficacy of immunotherapy. Despite these insights, the precise mechanisms underlying these interactions and their potential clinical applications remain inadequately understood. This article aims to review the mechanisms of interaction between the gut microbiota and the local immune response in liver cancer, integrating the latest research advancements. Additionally, it will explore the impact of these interactions on the tumor immune microenvironment, with the objective of providing a theoretical foundation and potential strategies for prevention and therapeutic intervention.

Indexed as

gut microbiotahepatocellular carcinomaimmune modulationlocal immune responsethe gut-liver axisthe immune microenvironment

Identifiers

PMID41049851
PMCPMC12491016

What OpenQuestion holds

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LicenceCC BY
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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.