Novel strategies for modulating the gut microbiome for cancer therapy

Cho, Young Seok; Han, Kai; Xu, Jin; Moon, James J.

doi:10.1016/j.addr.2024.115332

Cited by 1 publication

(1 citation statement)

References 199 publications

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“… 35 , 36 , 44 , 45 Furthermore, our findings contribute to the literature suggesting that microbial metabolites modulate immune pathways and tissue injury and repair mechanisms 46 and that the microbiome may impact the efficacy and toxicity of anti-cancer therapeutics, including radiotherapy. 47 The growing body of evidence illustrates the importance of metabolites in predicting RT-induced changes, encouraging future longitudinal studies of metabolomics-based modeling in RT-induced EASRs. As technological advancements in artificial intelligence continue, there may be increasing opportunities to leverage pre-RT metabolome profiles to develop predictive algorithms for EASRs.…”

Section: Discussionmentioning

confidence: 99%

Metabolomics in Radiotherapy-Induced Early Adverse Skin Reactions of Breast Cancer Patients

McMahon,

Lee,

Takita

et al. 2024

BCTT

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Background Early adverse skin reactions (EASRs) are common side effects of radiotherapy (RT) that impact the quality of life of breast cancer patients. This study used global metabolomics profiles of breast cancer populations to identify metabolic pathways and biomarkers significantly associated with RT-induced EASRs to identify potential targets for precision interventions. Methods We used a frequency-matched study design to identify pre-RT urine samples from 60 female breast cancer patients (30 with high and 30 with low EASRs) for metabolomic analysis by Metabolon Inc. using UPLC-MS/MS and GC-MS. Using MetaboAnalyst, we performed metabolomic data analysis and visualization on 84 candidate metabolites from 478 total compounds. We used the Oncology Nursing Society (ONS) Skin Toxicity Criteria (0–6) for EASRs assessment. Results Seven metabolic pathways were significantly associated with RT-induced EASRs, including alanine, aspartate, and glutamate metabolism (p = 0.0028), caffeine metabolism (p = 0.0360), pentose and glucuronate interconversions (p = 0.0028), glycine, serine, and threonine metabolism (p = 0.0360), beta-alanine metabolism (p = 0.0210), pantothenate and CoA biosynthesis (p = 0.0028), and glutathione metabolism (p = 0.0490). The alanine, aspartate, and glutamate metabolic pathway had the lowest false discovery rate (FDR)-adjusted p-value and the highest impact value of 0.60. Thirteen metabolite biomarkers were significantly associated with RT-induced EASRs. Conclusion Our data show that the alanine, aspartate, and glutamate metabolism pathways had the highest impact value on RT-induced EASRs. Future larger studies are warranted to validate our findings and facilitate targeted interventions for preventing or mitigating RT-induced EASRs, offering a promising direction for further research and clinical applications.

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