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Publications

Journal Article Epublish

PubMed: 41883995 DOI: 10.2147/CMAR.S573379

Adaptation of MALDI-TOF MS Technique for Tracking Changes in the Urinary Microbiome During and After Radiotherapy for Prostate Cancer.

Cancer Manag Res 18:573379

Authors: Michał Złoch, Ewelina Sibińska, Fernanda Monedeiro, Wioletta Miśta, Adrian Arendowski, Piotr Fijałkowski, Monika Pietrowska, Jolanta Mrochem-Kwarciak, Anna Jędrzejewska, Ewa Telka, Kinga Karoń, Małgorzata Rabsztyn, Paweł Pomastowski, Dorota Gabryś

Affiliations

  • Centre for Modern Interdisciplinary Technologies, Institute of Advanced Studies, Nicolaus Copernicus University in Torun, Torun, Poland.
  • Radiotherapy Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland.
  • Faculty of Chemistry, Rzeszów University of Technology, Rzeszów, Poland.
  • Clinical Proteomics Laboratory, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland.
  • Analytics and Clinical Biochemistry Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland.
  • Radiotherapy Department, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland. Clinical Proteomics Laboratory, Maria Sklodowska-Curie National Research Institute of Oncology, Gliwice Branch, Gliwice, Poland.

Abstract

PURPOSE

The urinary microbiome may influence the development of radiation-induced complications in prostate cancer. However, its dynamics during and after radiotherapy (RT) remain unclear. This study aimed to use matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to characterize and monitor urinary microbiome changes during RT for prostate cancer.

PATIENTS AND METHODS

Eighty-eight patients with prostate cancer who underwent RT were included. Midstream urine and blood samples were collected at six time points: before gold fiducial implantation (t1), at the start (t2) and end of RT (t3), and at 1, 4, and 7 months post-RT (t4-t6). Microorganisms were cultured under diverse conditions and identified by MALDI-TOF MS. Statistical analyses were used to assess the associations between microbial profiles, RT stages, and biochemical parameters in the urine and blood.

RESULTS

A total of 1773 microbial isolates were identified in 89% of urine samples, with 79% showing a polymicrobial composition. The microbiota was dominated by Staphylococcus (51.6%), Micrococcus, Enterococcus, Kocuria, and Corynebacterium. Biodiversity decreased at the end of RT but gradually recovered up to seven months post-treatment. Genera such as Actinomyces, Corynebacterium, Staphylococcus, and Streptococcus were significantly correlated with study time course, whereas the abundance of Kocuria rhizophila increased over time. Changes in microbiome composition were strongly associated with glucose levels in urine and blood.

CONCLUSION

RT triggers a dynamic response in the urinary microbiome, with an initial decline in diversity followed by progressive recolonization. Glucose levels in urine and blood significantly affect microbial composition, suggesting that metabolic factors modulate RT-related microbiome shifts. These findings highlight the interplay between RT, host metabolism, and urinary microbiota, supporting the potential value of glucose monitoring to maintain microbial balance after RT.

MeSH

Radiotherapy, Blood, Neoplasms, Prostate, Prostatic Neoplasms, Microbiota