Evidence map›Paper›PMID 40591053›Full record

ArticleDiscover oncology2025

Predictive biomarkers in the gut microbiome and metabolome for severe acute radiation enteritis in cervical cancer radiotherapy.

Chen-Ying Ma, Jing Zhao, Xiao-Ting Xu, Xiao-Lan He, Song-Bing Qin, Ju-Ying Zhou

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Discover oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07259681 (Intestinal Microbiome Profiles in Women With Gynecological Tumors and Pelvic Toxicity Secondary to Radiotherapy and Chemotherapy), which is not on this map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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.

NCT07259681 not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Intestinal Microbiome Profiles in Women With Gynecological Tumors and Pelvic Toxicity Secondary to Radiotherapy and Chemotherapy: Comparison With Controls and Effect of Rectal Ozone Treatment.

Typeobservational_patient_registrySponsorBernardino Clavo, MD, PhDRan2026 to 2028Enrolled38ConditionsPelvic Toxicity, Radiation Toxicity, Chemotherapy Toxicity, Gynecological Tumors
3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Microbiome-Driven Risk Stratification and Biotherapeutics in Radiation Enteritis.Computational and structural biotechnology journal · 2026
    Review
  4. Review
  5. Review
  6. 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.

Chen-Ying MaDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Jing ZhaoDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Xiao-Ting XuDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Xiao-Lan HeDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Song-Bing QinDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China.
Ju-Ying ZhouDepartment of Radiation Oncology, The First Affiliated Hospital of Soochow University, No. 188 Shizi Street, Suzhou, 215006, China. zhoujuyingsy@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionRadiation enteritis (RE), a common side effect, is a growing health concern, particularly the severe acute form of RE (SARE), among cervical cancer patients undergoing radiation therapy. Currently, there is no noninvasive diagnostic method for SARE. This study aimed to identify gut microbiomics- and metabolomics-based signatures, and assess their predictive value for SARE.

methodsSamples from 50 cervical cancer patients receiving volumetric modulated arc therapy (VMAT) were collected for gut microbiota and metabolomic profiling. 16 S rDNA amplicon sequencing analyzed gut microbiota, and nontargeted liquid chromatography-mass spectrometry determined metabolomic profiles. Multivariate and pathway analyses identify independent metabolites associated with SARE. A predictive nomogram for SARE, combining multi-omics-based signatures and clinical characteristics, was constructed and evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curve.

resultsFecal microbiome analysis showed characteristic alterations in SARE, mainly including Faecalibacterium enterotype-3, Escherichia, and Shigella enterotype-2. Metabolomic analyses identified a panel of molecules significantly associated with SARE. Furthermore, an intuitive nomogram consisting of these multi-omics signatures (serum COX-2 and fecal phenylethylamine), combined with clinical characteristics with predictive value, was constructed to predict SARE. Notably, the evaluation of model performance suggested an excellent predictive discrimination for SARE [AUC, 0.975; 95% confidence interval (CI), 0.953-0.998]. Calibration curve analysis showed an adequate calibration for the model and good consistency between the predicted SARE cases with this newly developed model and the actual SARE cases.

conclusionThis study identified noninvasive signatures, including COX-2 and phenylethylamine, as promising predictive biomarkers for SARE and developed an intuitive nomogram with good predictive accuracy for SARE in cervical cancer patients.

Indexed as

BiomarkersCervical cancerGut microbiomeMetabolomicsRadiation enteritisRadiotherapy

Identifiers

PMID40591053
PMCPMC12214197

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Registered trials

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.