Evidence map›Paper›PMID 40969429›Full record

ArticleFrontiers in microbiology2025

Integrated microbiome-metabolome profiling unveils a predictive signature for early recurrence in hepatocellular carcinoma.

Qiqi Chen, Yi Wang, Daoyuan Wu, He Zhang, Qingxin Xia, Dingding Qu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Qiqi ChenHenan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.
Yi WangHenan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.
Daoyuan WuHenan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.
He ZhangHenan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.
Qingxin Xia *Henan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.
Dingding Qu *Henan Medical Key Laboratory of Tumor Pathology and Artificial Intelligence Diagnosis, Zhengzhou Key Laboratory of Accurate Pathological Diagnosis of Intractable Tumors, Henan Engineering Research Center of Pathological Diagnostic Antibody, Department of Pathology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hepatocellular carcinoma (HCC) exhibits high recurrence rates post-resection, yet predictive biomarkers remain elusive. Emerging evidence implicates intratumoral microbiota in cancer progression, but its role in HCC recurrence is unexplored. Here, we characterized microbial and metabolic profiles in 90 HCC patients [49 with early recurrence (RFS ≤ 2 years), 41 non-recurrent controls] using 16S rRNA sequencing and LC-MS metabolomics. Recurrent tumors showed reduced microbial diversity (Shannon index,

Indexed as

diagnostic micro-biomarkersearly recurrencehepatocellular carcinoma (HCC)intra-tumoral microbiomemicrobial metabolomics

Identifiers

PMID40969429
PMCPMC12442831

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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.