Evidence map›Paper›PMID 40013792›Full record

ArticlemSystems2025

Multi-omics analysis reveals associations between gut microbiota and host transcriptome in colon cancer patients.

Yuling Qin, Qiang Wang, Qiumei Lin, Fengfei Liu, Xiaolan Pan, Caibiao Wei, Junxian Chen, Taijun Huang, Min Fang, Weilong Yang and 1 more

Abstract read
In one paragraph

Article in mSystems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
  5. Review
  6. Review
  7. Review
  8. Review
  9. 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

11 authors.

Yuling Qin *Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Qiang Wang *Guangxi Clinical Research Center for Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, China.
Qiumei Lin *Department of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Fengfei LiuDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Xiaolan PanDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Caibiao WeiDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Junxian ChenDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Taijun HuangDepartment of Clinical Laboratory, Guangxi Medical University Cancer Hospital, Nanning, China.
Min FangGuangxi Clinical Research Center for Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, China.ORCID 0009-0008-7336-9606
Weilong YangGuangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.ORCID 0000-0002-0327-4272
Linghui PanGuangxi Clinical Research Center for Anesthesiology, Guangxi Medical University Cancer Hospital, Nanning, China.ORCID 0000-0003-1107-1261

Funding

Guangxi Clinical Research Center for Anesthesiology AD22035214National Science Foundation of China 81760530National Science Foundation of China 8236080196National Science Foundation of Guangxi 2022GXNSFAA035510Postdoctoral Science Foundation of China 2021M693803
6 · The paper itself

Abstract

Colon cancer (CC) is one of the most common cancers globally, which is associated with the gut microbiota intimately. In current research, exploring the complex interaction between microbiomes and CC is a hotspot. However, the information on microbiomes in most previous studies is based on fecal, which does not fully display the microbial environment of CC. Herein, we collected mucosal and tissue samples from both the tumor and normal regions of 19 CC patients and clarified the composition of mucosal microbiota by 16S rRNA and metagenomic sequencing. Additionally, RNA-Seq was also conducted to identify the different expression genes between tumor and normal tissue samples. We revealed significantly different microbial community structures and expression profiles to CC. Depending on correlation analysis, we demonstrated that 1,472 genes were significantly correlated with CC tumor microbiota. Our study reveals a significant enrichment of IMPORTANCE: This study contributes to our understanding of the interaction between microbiota and colon cancer (CC). By examining mucosal and tissue samples rather than solely relying on fecal samples, we have uncovered previously unknown aspects of CC-associated microbiota. Our findings reveal distinct microbial community structures and gene expression profiles correlated with CC progression. Notably, the enrichment of

Indexed as

Colonic NeoplasmsGastrointestinal MicrobiomeTranscriptomeAgedBacteriaFemaleHumansMaleMetagenomicsMiddle AgedMultiomicsRNA, Ribosomal, 16SRNA, Ribosomal, 16Sbile secretioncolon cancercorrelationimmunemucosal microbiotamulti-omicssurvival value

Identifiers

PMID40013792
PMCPMC11915798

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.