Liu Manlu, Zhu Yanlong, McIlwain Sean J, Deng Haotian, Brasier Allan R, Ge Ying, Kimple Michelle E, Baschnagel Andrew M
Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USA.
Department of Cell and Regenerative Biology, School of Medicine and Public Health, University of Wisconsin, Madison, WI 53726, USA.
Metabolites. 2025 May 20;15(5):340. doi: 10.3390/metabo15050340.
: The current staging of non-small cell lung cancer (NSCLC) relies on conventional imaging, which lacks the sensitivity to detect micrometastatic disease. The functional assessment of NSCLC progression may provide independent information to enhance the prediction of metastatic risk. The objective of this study was to determine if we could identify a metabolomic signature predictive of metastasis in patients with NSCLC treated with definitive radiation. : Plasma samples were collected prospectively from patients enrolled in a clinical trial with non-metastatic NSCLC treated with definitive radiation. Metabolites were extracted, and mass spectrometry-based analysis was performed using a flow injection electrospray (FIE)-Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) method. Early metastasis was defined as metastasis within 1 year of radiation treatment. : The study cohort included 28 patients. FIE-FITCR produced highly reproducible profiles in technical replicates. A total of 51 metabolic features were identified to be different in patients with early metastasis compared to patients without early metastasis (all adjusted -values < 0.05, Welch's -test), including glycerophospholipids, sphingolipids, and fatty acyls. In the follow-up samples collected after the initiation of chemotherapy and radiation treatment, a total of 174 metabolic features were significantly altered in patients who developed early metastasis compared to those who did not. : We identified several distinct changes in the metabolic profiles of patients with NSCLC who developed metastatic disease within 1 year of definitive radiation. These findings highlight the potential of metabolomic profiling as a predictive tool for assessing metastatic risk in NSCLC.
非小细胞肺癌（NSCLC）的当前分期依赖于传统影像学检查，而传统影像学检查缺乏检测微转移疾病的敏感性。NSCLC进展的功能评估可能会提供独立信息，以增强对转移风险的预测。本研究的目的是确定我们能否识别出一种代谢组学特征，用于预测接受根治性放疗的NSCLC患者的转移情况。：前瞻性地收集了参加一项针对非转移性NSCLC接受根治性放疗的临床试验患者的血浆样本。提取代谢物，并使用流动注射电喷雾（FIE）-傅里叶变换离子回旋共振（FTICR）质谱（MS）方法进行基于质谱的分析。早期转移定义为放疗后1年内发生的转移。：研究队列包括28名患者。FIE-FITCR在技术重复中产生了高度可重复的图谱。与无早期转移的患者相比，共有51种代谢特征在有早期转移的患者中存在差异（所有校正P值<0.05，Welch's t检验），包括甘油磷脂、鞘脂和脂肪酰基。在化疗和放疗开始后收集的随访样本中，与未发生早期转移的患者相比，发生早期转移的患者共有174种代谢特征发生了显著改变。：我们在接受根治性放疗后1年内发生转移的NSCLC患者的代谢谱中发现了几个明显的变化。这些发现突出了代谢组学分析作为评估NSCLC转移风险的预测工具的潜力。
