Epigenome-wide analysis reveals potential biomarkers for radiation-induced toxicity risk in prostate cancer.

BACKGROUND

Prostate cancer is the second most common cancer globally, with radiation therapy (RT) being a key treatment for clinically localized and locally advanced cases. Given high survival rates, addressing long-term side effects of RT is crucial for preserving quality-of-life. Radiogenomics, the study of genetic variations affecting response to radiation, has primarily focussed on genomic biomarkers, while DNA methylation studies offer insights into RT responses. Although most research has centred on tumours, no epigenome-wide association studies have explored peripheral blood biomarkers of RT-induced toxicities in prostate cancer patients. Identifying such biomarkers could reveal molecular mechanisms underlying RT response and enable personalized treatment.

METHODS

We analysed 105 prostate cancer patients (52 cases and 53 controls). Cases developed grade ≥ 2 genitourinary and/or gastrointestinal late toxicity after 12 months of starting RT, whereas controls did not. An epigenome-wide association study of post-RT toxicities was performed using the Illumina MethylationEPIC BeadChip, adjusting for age and cell type composition. We constructed two methylation risk scores-one using differentially methylated positions (MRSsites) and another using differentially methylated regions (MRSregions)-as well as a Support Vector Machine-based methylation signature (SVMsites). We evaluated RT effects on biological age and stochastic epigenetic mutations within established radiation response pathways. Gene Ontology and pathway enrichment analyses were also performed.

RESULTS

Pre-RT methylation analysis identified 56 differentially methylated positions (adjusted p-value ≤ 0.05), and 6 differentially methylated regions (p-value ≤ 0.05) associated with the genes NTM, ACAP1, IL1RL2, VOOP1, AKR1E2, and an intergenic region on chromosome 13 related to Short/Long Interspersed Nuclear Elements. Both Methylation Risk Scores (MRSsites AUC = 0.87; MRSregions AUC = 0.89) and the 8-CpG Support Vector Machine signature (SVMsites AUC = 0.98) exhibited strong discriminatory accuracy in classifying patients in the discovery cohort. Gene ontology analysis revealed significant enrichment (adjusted p-value ≤ 0.05) of genes involved in DNA repair, inflammatory response, tissue repair, and oxidative stress response pathways.

CONCLUSIONS

Epigenetic biomarkers show potential for predicting severe long-term adverse effects of RT in prostate cancer patients. The identified methylation patterns provide valuable insights into toxicity mechanisms and may aid personalized treatment strategies. However, validation in independent cohorts is essential to confirm their predictive value and clinical applicability.