Huang Yida, Lin Huimin, Shi Jiahao, Chen Yifan, Sang Qi, Wang Ruimin, Liu Wanshan, Wu Jiao, Li Yanyan, Xu Xiaoyu, Ding Chunmeng, Yang Shouzhi, Zhang Juxiang, Jia Renbing, Fan Xianqun, Qian Kun, Zhou Yixiong
State Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai 200030, P. R. China.
Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200127, P. R. China.
Proc Natl Acad Sci U S A. 2025 Aug 5;122(31):e2506345122. doi: 10.1073/pnas.2506345122. Epub 2025 Jul 31.
Ocular adnexal lymphoma (OAL) is the most common orbital malignancy in adults. Advanced tools for precise diagnosis and prognosis of OAL are in demand. Here, the nanoparticle-enhanced laser desorption/ionization mass spectrometry was applied for the construction of OAL-associated serum metabolic patterns (SMPs) from 239 participants (104 OAL and 135 non-OAL). Through machine learning, the diagnostic performance with an area-under-the-curve (AUC) of 0.901 was achieved for OAL based on SMPs. Furthermore, a diagnostic metabolic panel was constructed with an AUC of 0.875. Moreover, a prognosis scoring system was built and its desirable prediction efficacy for progression-free survival of OAL was confirmed ( < 0.05). Specifically, the decreased serum alanine level was found to play both vital roles in the diagnosis and prognosis of OAL, and we demonstrated that uptake of alanine promotes glycolysis and cell growth in lymphoma cells. Our study highlights the value of the serum metabolite biomarkers in the clinical management of OAL.
眼附属器淋巴瘤（OAL）是成人中最常见的眼眶恶性肿瘤。需要先进的工具来精确诊断和预测OAL的预后。在此，应用纳米颗粒增强激光解吸/电离质谱法，从239名参与者（104例OAL和135例非OAL）构建与OAL相关的血清代谢模式（SMP）。通过机器学习，基于SMP对OAL的诊断性能实现了曲线下面积（AUC）为0.901。此外，构建了一个诊断代谢组，AUC为0.875。此外，建立了一个预后评分系统，并证实了其对OAL无进展生存期的良好预测效能（<0.05）。具体而言，发现血清丙氨酸水平降低在OAL的诊断和预后中均起重要作用，并且我们证明丙氨酸摄取促进淋巴瘤细胞的糖酵解和细胞生长。我们的研究突出了血清代谢物生物标志物在OAL临床管理中的价值。
