Evidence map›Paper›PMID 41286929›Full record

ArticleGenome biology2025

HGMT: a database of human gut microbiota for tumors and immunotherapy response.

Jinxin Liu, Mingyu Wang, Chentao Xu, Longhao Jia, Senying Lai, Zi-Chao Zhang, Jinglong Zhang, Wei-Hua Chen, Yucheng T Yang, Xing-Ming Zhao

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Genome biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Gut Microbiota and Extraintestinal Cancers: Mechanistic Insights and Microbiome-Targeted Interventions.JGH open : an open access journal of gastroenterology and hepatology · 2026
    Review
  4. 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

10 authors.

Jinxin Liu *Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China.
Mingyu Wang *Key Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China.
Chentao XuInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Longhao JiaInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Senying LaiInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Zi-Chao ZhangInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Jinglong ZhangInstitute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China.
Wei-Hua ChenKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Center for Artificial Intelligence Biology, Department of Bioinformatics and Systems Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China. weihuachen@hust.edu.cn.
Yucheng T YangHuzhou Central Hospital, Affiliated Central Hospital Huzhou University, Huzhou, 313000, China. yangyy@fudan.edu.cn.
Xing-Ming ZhaoDepartment of Neurology, Zhongshan Hospital, Fudan University, Shanghai, 200433, China. xmzhao@fudan.edu.cn.

Funding

Key Science and Technology Project of Hainan Province ZDYF2024SHFZ058Major Project of Guangzhou National Laboratory GZNL2024A01003National Key Research and Development Program of China 2023YFF1204800National Key Research and Development Program of China 2024YFA0918500National Natural Science Foundation of China T2225015Shanghai Municipal Education Commission 24KXZNA11Shanghai Science and Technology Commission Program 23JS1410100Shanghai Science and Technology Commission Program 24JS2810100
6 · The paper itself

Abstract

HGMT is a database designed to analyze, explore, and visualize gut microbiomes from diverse tumor types. We process metagenomic datasets from 18,630 stool samples across 37 tumor types, including 2,207 samples from immunotherapy-treated patients across 12 tumor types. HGMT provides an interactive portal for querying taxonomic and functional profiles, visualizing cross-dataset differential abundance taxa in tumors, and identifying their pan-tumor associations. Our analysis reveals the capability of gut microbiota in diagnosing gastrointestinal tumors and predicting immunotherapy response for non-small cell lung carcinoma. HGMT represents a valuable resource for investigating the roles of gut microbiota in tumors and immunotherapy response.

Indexed as

Gastrointestinal MicrobiomeImmunotherapyNeoplasmsHumansMetagenomicsGut microbiomeImmunotherapy responseTumor diagnosis

Identifiers

PMID41286929
PMCPMC12642048

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.