Evidence map›Paper›PMID 42388302›Full record

ArticleFrontiers in microbiology2026

Characterization of the gastric mucosal microbiota in tumoral and peritumoral mucosa in patients with advanced gastric cancer from Northwest China.

Hongtai Cao, Qi Wang, Wen Ren, Anqi Wang, Wenji Tian, Dekui Zhang, Juanjuan Chen

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2026. 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

7 authors.

Hongtai Cao *Department of General Surgery, The Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, Gansu, China.
Qi Wang *Cuiying Biomedical Research Center, The Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, Gansu, China.
Wen RenCuiying Biomedical Research Center, The Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, Gansu, China.
Anqi WangNHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, Gansu, China.
Wenji TianDepartment of Oncology, Gansu Provincial Central Hospital, Lanzhou, Gansu, China.
Dekui ZhangDepartment of Gastroenterology, Lanzhou University Second Hospital, Lanzhou, Gansu, China.
Juanjuan ChenCuiying Biomedical Research Center, The Second Hospital and Clinical Medical School, Lanzhou University, Lanzhou, Gansu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The gastric microbiota affects tumor development and treatment response, yet the characteristics and interactions of mucosal bacteria and fungi in advanced gastric cancer (AGC) remain unclear. Methods: Here we analyzed 177 mucosal samples (88 peritumoral and 89 tumoral) from 91 AGC patients in Northwest China using shotgun metagenomic sequencing. Results: MetaPhlAn4 and Kaiju were used to annotate the gastric mucosal microbial composition. MetaPhlAn4 has identified 12 phyla (no phylum-level differences), 98 genera and 278 species. PERMANOVA revealed age and tumor location significantly influenced microbial composition in tumoral mucosa. Wilcoxon signed-rank test revealed that 10 species including Discussion: This study comprehensively characterizes the gastric mucosal bacteriome and mycobiome in AGC, illuminates potential microbiota-mediated carcinogenic mechanisms, identifies candidate biomarkers, and fills a regional research gap.

Indexed as

advanced gastric cancergastric mucosal microbiomemetabolic reprogrammingMetaPhlAn4 and kaijupredictive functional pathwaystumor and peritumor

Identifiers

PMID42388302
PMCPMC13319720

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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.