ArticleIn vivo (Athens, Greece)
Urinary Metabolites as Biomarkers of Early Radiation Cystitis in Patients With Prostate Cancer Undergoing Radiotherapy.
Article in In vivo (Athens, Greece). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Radiation biomarkers in body fluids: translational perspectives for precision radiotherapy-a narrative review.Translational cancer research · 2026Review
- Urinary Biomarkers for Radiation Cystitis: Current Insights and Future Directions.International journal of molecular sciences · 2026Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND/
aimTreatment-related bladder toxicities are a primary concern in the management of prostate cancer radiotherapy. This study aimed to identify urinary metabolites that can predict early radiation cystitis-related toxicities in patients undergoing radiotherapy for prostate cancer. PATIENTS AND
methodsPatients' clinical characteristics and urine samples were collected before, two weeks after, at the end, and three months after the initiation of radiotherapy and subsequently analyzed. Capillary electrophoresis-mass spectrometry and liquid chromatography-mass spectrometry were used for comprehensive quantification of urinary metabolites. Multivariate analysis was conducted to identify potential protective factors against the early toxicities of radiation cystitis.
resultsA total of 176 samples were obtained from 44 patients. Betaine, tartrate, N,N-dimethylglycine, and homocarnosine were identified as independent protective factors against early toxicities of radiation cystitis among various potential confounding metabolic factors. Comorbid diabetes mellitus was also identified as a protective factor.
conclusionBetaine, tartrate, N,N-dimethylglycine, and homocarnosine were identified as protective urinary metabolites against early radiation cystitis. Urinary metabolomic profiling may be a useful tool for investigating disease metabolism in metabolic disorders and cancers. Its ease of use and repeatability make it an optimal method for patient follow-up.
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