Urinary metabolomic signatures associated with early adverse events during volumetric modulated arc therapy for prostate cancer: A secondary analysis of a public dataset.
This study suggests that urinary metabolomics may help identify biomarkers for early urinary toxicities in prostate cancer treatment, but findings need validation in larger cohorts.
Where it sits
this study against the rest of the degarelix corpusSummary and findings
This study analyzed urinary metabolomic signatures in 11 patients undergoing volumetric modulated arc therapy (VMAT) for prostate cancer, specifically looking for associations with early urinary toxicities. Patients were categorized into those with Grade 1 urinary toxicities (n=7) and those without (n=4). The analysis identified several metabolites correlated with toxicity but did not report significant findings after correction for false discovery rate.
Abstract
Volumetric modulated arc therapy (VMAT) is an advanced radiotherapy technique for prostate cancer that improves dose conformity but is often accompanied by early urinary toxicities. Non-invasive biomarkers for predicting such adverse events remain limited. In the present study, a secondary analysis of a public urinary metabolomics dataset (MxP<sup>®</sup> Quant 500; 630 metabolites) from 11 patients treated with VMAT (76 Gy/38 fractions) was performed. Patients were grouped as patients with urinary toxicities (n=7; Grade 1) and those without (n=4). Patient-level Spearman's rank correlation coefficients (ρ) between the metabolite concentration and fraction number were calculated and summarized within each group. Overlaps in the top 60 positively correlated metabolites and bottom 60 negatively correlated metabolites across groups were identified and assessed using OmicsNet 2.0. Four metabolites [cholesteryl ester 20:4, taurodeoxycholic acid, triglyceride (TG) 18:0_32:2 and TG 18:3_34:1] were positively correlated in the toxicity group but negatively correlated in controls. Conversely, five metabolites, including phosphatidylcholines (PCs; PC aa C42:2 and PC ae C42:1), TG 16:0_38:1, fatty acid (FA) 20:2 and diglyceride 18:1_18:1, showed the opposite trend. Network analysis indicated impaired lipolysis, specifically the hydrolysis of TGs into FAs, involving carboxyl ester lipase and adipose TG lipase/hormone-sensitive lipase pathways. One patient with toxicity was on ursodeoxycholic acid, possibly influencing bile acid-related metabolites. Overall, early urinary adverse events in VMAT were associated with lipid metabolism dysregulation. No metabolites remained significant after false discovery rate correction, and this exploratory, hypothesis-generating analysis suggested that urinary metabolomics may serve as a non-invasive biomarker platform for toxicity prediction, warranting validation in larger cohorts.
Background
This paper addresses the need for non-invasive biomarkers to predict early urinary toxicities associated with volumetric modulated arc therapy (VMAT) for prostate cancer. Previous research has shown that VMAT can improve dose conformity but often leads to adverse urinary effects. Understanding metabolic changes could provide insights into toxicity prediction and management.
Methods
The study performed a secondary analysis of a public urinary metabolomics dataset involving 11 patients treated with VMAT at a dose of 76 Gy over 38 fractions. Patients were divided into two groups based on the presence of Grade 1 urinary toxicities. Spearman's rank correlation coefficients were calculated to assess relationships between metabolite concentrations and fraction number.
Results
The analysis identified four metabolites positively correlated with urinary toxicities in the affected group, while five metabolites showed the opposite correlation in controls. However, no metabolites remained significant after false discovery rate correction, indicating that the findings may not be robust.
Interpretation
While the study provides initial insights into potential metabolic signatures associated with urinary toxicities in VMAT, the lack of significant findings after correction raises questions about the clinical relevance of these results. The small sample size and exploratory nature of the analysis limit the ability to draw definitive conclusions or apply findings in practice.
Key findings
- Patients with urinary toxicities (n=7) showed positive correlations with four metabolites, including cholesteryl ester 20:4.
- In the control group (n=4), the same four metabolites were negatively correlated.
- Five metabolites, including phosphatidylcholines, showed the opposite trend between the two groups.
- No metabolites remained significant after false discovery rate correction.
Limitations
- small sample size (n=11)
- no significant findings after false discovery rate correction
- exploratory analysis, not definitive
- potential confounding by medication in one patient