Evidence map›Paper›PMID 41403696›Full record

ReviewFrontiers in cell and developmental biology2025

Mechanisms of rapid tumor progression after insufficient radiofrequency ablation of hepatocellular carcinoma.

Wenming Hou, Ge Ge, Xu Chen, Xinhua Xu

Abstract readReview
In one paragraph

Review in Frontiers in cell and developmental biology, 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
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1 · What the graph read from it

What it found

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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

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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

4 authors.

Wenming HouDepartment of Ultrasound, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Ge GeDepartment of Ultrasound, Taizhou Central Hospital (Taizhou University Hospital), Taizhou, Zhejiang, China.
Xu ChenDepartment of Pathology, Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Xinhua XuDepartment of Pathology, The People's Hospital of Yuhuan, Taizhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant tumors globally, characterized by high incidence and mortality rates. Radiofrequency ablation (RFA) is a widely adopted primary ablative therapy for HCC, playing a pivotal role in the management of small HCC and unresectable lesions. However, a subset of HCC patients experiences rapid tumor recurrence and progression following RFA. Objective: This review aims to summarize the mechanisms underlying rapid tumor progression after RFA for hepatocellular carcinoma, thereby providing a theoretical foundation and future research directions for preventing post-ablation recurrence and progression. Methods: A systematic review of the literature was performed to synthesize current evidence on the mechanisms of tumor recurrence and progression following RFA for HCC, and to discuss corresponding preventive and therapeutic strategies. Results: Insufficient radiofrequency ablation (IRFA) is a significant driver of tumor recurrence and progression. Post-ablation relapse is not a simple process of residual cell repopulation but a multifaceted vicious cycle initiated by ablation stress. The core mechanism involves residual tumor cells surviving within a synergistic, pro-tumorigenic microenvironment characterized by thermal injury, hypoxia, inflammation, non-coding RNA dysregulation, epigenetic alterations, and immunosuppression. This hostile niche exerts intense selective pressure, activating a complex molecular cascade that promotes cell survival, immune evasion, and malignant proliferation, ultimately driving rapid progression and invasive recurrence. Conclusion: IRFA for hepatocellular carcinoma leaves behind residual tumor cells that acquire aggressive malignant phenotypes through diverse biological mechanisms, driving disease recurrence and progression. Enhancing the precision of ablation techniques and developing integrated, multi-modal treatment strategies are promising avenues to suppress post-ablation recurrence and improve long-term patient outcomes.

Indexed as

hepatocellular carcinomainflammationradiofrequency ablationrecurrencetumor microenvironment

Identifiers

PMID41403696
PMCPMC12702870

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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.