The Fifth People's Hospital of Shanghai, Shanghai Key Laboratory of Medical Epigenetics, The International Co-laboratory of Medical Epigenetics and Metabolism, Ministry of Science and Technology, Institutes of Biomedical Sciences, Fudan University, Shanghai, 200032, China.
Department of Neurosurgery, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.
Talanta. 2022 Apr 1;240:123159. doi: 10.1016/j.talanta.2021.123159. Epub 2021 Dec 20.
Protein biomarkers of intracranial aneurysm (IA) are essential for early detection and prediction of its rupture to facilitate the diagnosis and clinical management of the disease, monitor treatment response and detect recurrence. Here, we developed a comprehensive strategy for IA biomarker discovery by analyzing tissues from an animal model (n = 4) and serum from human patients (n = 60) using isobaric tandem mass tags-based quantitative proteomics. A total of 4811 and 562 proteins were identified from aneurysm tissue and serum samples, respectively. The 223 candidate protein biomarkers were further validated in an independent serum cohort (n = 30) by multiple reaction monitoring analysis. Combined with a logistic regression model, we built a diagnostic classifier P2 (FCN2 & RARRES2) to differentiate IA from healthy controls with accuracy of 93.3%, as well as a diagnostic classifier P7 (ADAM12, APOL3, F9, C3, CEACAM1, ICAM3, KLHDC7A) to classify ruptured IA from unruptured IA with accuracy of 95.0%. Taken together, our results suggest a valuable strategy for biomarker discovery and patient stratification in IA.
颅内动脉瘤 (IA) 的蛋白质生物标志物对于早期检测和预测其破裂至关重要，有助于疾病的诊断和临床管理，监测治疗反应和检测复发。在这里，我们通过分析动物模型（n=4）的组织和人类患者（n=60）的血清，使用基于等压串联质量标签的定量蛋白质组学，开发了一种全面的 IA 生物标志物发现策略。从动脉瘤组织和血清样本中分别鉴定出 4811 种和 562 种蛋白质。通过多重反应监测分析，进一步在独立的血清队列（n=30）中验证了 223 种候选蛋白生物标志物。结合逻辑回归模型，我们构建了一个诊断分类器 P2（FCN2 和 RARRES2），用于将 IA 与健康对照区分开来，准确率为 93.3%，还构建了一个诊断分类器 P7（ADAM12、APOL3、F9、C3、CEACAM1、ICAM3、KLHDC7A），用于区分破裂性 IA 和未破裂性 IA，准确率为 95.0%。总之，我们的研究结果为 IA 的生物标志物发现和患者分层提供了一种有价值的策略。
