Evidence map›Paper›PMID 40325090›Full record

ArticleNPJ biofilms and microbiomes2025

Oral microbiota signature predicts the prognosis of colorectal carcinoma.

Shi-Hao Zhou, Yan Du, Wen-Qiong Xue, Min-Jun He, Ting Zhou, Zhi-Yang Zhao, Lu Pei, Yi-Wei Chen, Jin-Ru Xie, Chang-Ling Huang and 4 more

Abstract read
In one paragraph

Article in NPJ biofilms and microbiomes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Article
  9. Gut Microbial Metabolism in Colorectal Cancer.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  10. Article
  11. 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

14 authors.

Shi-Hao Zhou *School of Public Health, Sun Yat-sen University, Guangzhou, China.
Yan Du *State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Wen-Qiong XueState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Min-Jun HeSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Ting ZhouState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Zhi-Yang ZhaoSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Lu PeiState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Yi-Wei ChenState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Jin-Ru XieState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Chang-Ling HuangSchool of Public Health, Sun Yat-sen University, Guangzhou, China.
Yong-Qiao HeState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Tong-Min WangState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China.
Ying LiaoState Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou 510060, P.R, China. liaoying@sysucc.org.cn.
Wei-Hua JiaSchool of Public Health, Sun Yat-sen University, Guangzhou, China. jiawh@sysucc.org.cn.

Funding

Guang Dong Basic and Applied Basic Research Foundation 2023A1515110442the Fundamental 514 Research Funds for the Central Universities, Sun Yat-sen University 24ykgb002the National Key Research and Development Program of China 2021YFC2500400the National Natural Science Foundation of China 82404339the National Natural Science Foundation of China 82473703the Science and Technology Planning Project of Guangzhou, China 2024A04J4560the Young Talent Support Project of Guangzhou Association for Science and Technology QT2024-030
6 · The paper itself

Abstract

Emerging evidence links oral-derived gut microbes to colorectal cancer (CRC) development, but CRC prognosis-related microbial alterations in oral remain underexplored. In a retrospective study of 312 CRC patients, we examined the oral microbiota using 16S rRNA gene full-length amplicon sequencing to identify prognostic microbial biomarkers for CRC. Neisseria oralis and Campylobacter gracilis increased CRC progression risk (HR = 2.63 with P = 0.007, HR = 2.27 with P = 0.001, respectively), while Treponema medium showed protective effects (HR = 0.41, P = 0.0002). A microbial risk score (MRS) incorporating these species effectively predicted CRC progression risk (C-index = 0.68, 95% CI = 0.61-0.76). When compared to a model constructed solely from clinical factors, including tumor stage, lymphatic metastasis, and perineural invasion, the predictive accuracy significantly improved with the addition of the MRS, resulting in a C-index rising to 0.77 (P = 2.33 × 10

Indexed as

BacteriaColorectal NeoplasmsMicrobiotaMouthAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID40325090
PMCPMC12053567

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.