1 Department of Biochemistry, Cellular and Molecular Biology, School of Medicine, Georgetown University, Washington, District of Columbia.
2 TUBITAK Marmara Research Center, Institute of Gene Engineering and Biotechnology, Molecular Oncology Laboratory, Gebze, Kocaeli, Turkey.
OMICS. 2019 Apr;23(4):214-223. doi: 10.1089/omi.2019.0006.
Metabolomics offers new promise for research on prostate cancer (PCa) and its personalized treatment. Metabolomic profiling of radiation-treated PCa patients is particularly important to reveal their new metabolomic status, and evaluate the radiation effects. In addition, bioinformatics-integrated metabolomics-based approaches for disease profiling and assessment of therapy could help develop precision biomarkers in a context of PCa. We report mass spectrometry-based untargeted (global) serum metabolomics findings from patients with PCa ( = 55) before and after treatment with stereotactic body radiation therapy (SBRT), and intensity-modulated radiation therapy (IMRT) with SBRT, and using parsimony phylogenetic analysis. Importantly, the radiation-treated serum metabolome of patients represented a unique robust cluster on a cladogram that was distinct from the pre-RT metabolome. The altered radiation responsive serum metabolome was defined by predominant aberrations in the metabolic pathways of nitrogen, pyrimidine, purine, porphyrin, alanine, aspartate, glutamate, and glycerophospholipid. Our findings collectively suggest that global metabolomics integrated with parsimony phylogenetics offer a unique and robust systems biology analytical platform for powerful unbiased determination of radiotherapy (RT)-associated biosignatures in patients with PCa. These new observations call for future translational research for evaluation of metabolomic biomarkers in PCa prognosis specifically, and response to radiation treatment broadly. Radiation metabolomics is an emerging specialty of systems sciences and clinical medicine that warrants further research and educational initiatives.
代谢组学为前列腺癌(PCa)及其个性化治疗的研究提供了新的希望。对接受放射治疗的 PCa 患者进行代谢组学分析对于揭示其新的代谢组学状态和评估放射治疗效果尤为重要。此外,基于生物信息学整合的代谢组学方法可用于疾病分析和评估治疗效果,有助于在 PCa 背景下开发精准生物标志物。我们报告了基于质谱的非靶向(全局)血清代谢组学研究结果,该研究纳入了 55 例接受立体定向体部放射治疗(SBRT)和 SBRT 联合强度调制放射治疗(IMRT)前后的 PCa 患者,并采用简约系统发育分析。重要的是,经过放射治疗的患者的血清代谢组在系统发育树上形成了一个独特而稳健的集群,与放射治疗前的代谢组明显不同。受辐射影响的血清代谢组发生变化,表现在氮、嘧啶、嘌呤、卟啉、丙氨酸、天冬氨酸、谷氨酸和甘油磷脂代谢途径中的主要异常。我们的研究结果表明,将全局代谢组学与简约系统发育学相结合,为有力、无偏地确定接受放疗的 PCa 患者的生物标志物提供了一个独特而稳健的系统生物学分析平台。这些新发现呼吁未来进行转化研究,以评估代谢组学标志物在 PCa 预后,特别是对放射治疗反应方面的作用。放射代谢组学是系统科学和临床医学的新兴专业,值得进一步开展研究和教育活动。