Evidence map›Paper›PMID 40066330›Full record

ReviewFrontiers in pharmacology2025

Potential mechanism of traditional Chinese medicine intervention in gastric cancer: targeted regulation of autophagy.

Siyuan Sun, Wenqian Yu, Guangheng Zhang, Xiangyu Li, Linjing Song, Yehan Lv, Yi Chen

Abstract readReview
In one paragraph

Review in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. International journal of molecular sciences · 2026
    Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Programmed cell death in triple-negative breast cancer.Cellular & molecular biology letters · 2025
    Review
  7. Article
  8. 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

7 authors.

Siyuan Sun *Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Wenqian Yu *Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Guangheng ZhangFirst Clinical Medical College, Shandong University of Traditional Chinese Medicine, Jinan, China.
Xiangyu LiWangjing Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Linjing SongDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Yehan LvDongzhimen Hospital, Beijing University of Chinese Medicine, Beijing, China.
Yi ChenDepartment of Geriatrics, Third Affiliated Hospital, Beijing University of Chinese Medicine, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gastric cancer (GC) is a prevalent malignant tumor that originates from the epithelial cells of the gastric mucosa, predominantly in the form of adenocarcinoma. Extensive research has confirmed the significant role of autophagy in the initiation, progression, and chemoresistance of GC. The potential of traditional Chinese medicine (TCM) to exert anti-tumor effects by modulating autophagy has been demonstrated, particularly in the context of GC prevention and treatment. Natural products (NPs) have great therapeutic potential in the prevention and treatment of GC by targeting autophagy-related genes and signaling pathways to intervene in the biological behaviors of gastric cancer cells such as proliferation, metastasis, invasion and death. This article describes the molecular mechanisms and key markers of tumor autophagy, the signaling pathways involved in GC-associated autophagy (PI3K/AKT/mTOR, AMPK, MAPK, p53), and summarizes the mechanism of autophagy and

Indexed as

apoptosisautophagygastric cancernatural productstraditional Chinese medicine

Identifiers

PMID40066330
PMCPMC11891941

What OpenQuestion holds

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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.