利用高分辨质谱法测量干燥血浆微量样本中的 3-O-甲基多巴：诊断高危神经母细胞瘤患者的工具。

IF 3.2 3区医学 Q2 MEDICAL LABORATORY TECHNOLOGY

Clinica Chimica Acta Pub Date : 2024-10-16 DOI:10.1016/j.cca.2024.120005

Margherita Biondi , Sebastiano Barco , Davide Cangelosi , Alessia Cafaro , Martina Morini , Federica Pigliasco , Lucilla Rossi , Fabrizio Mancin , Massimo Conte , Alberto Garaventa , Giuliana Cangemi

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引用次数: 0

摘要

背景：诊断时的风险评估对神经母细胞瘤（NB）至关重要，以便为高危患者提供最及时、最适当的治疗。3-O-甲基多巴（3-OMD）是左旋多巴的直接代谢产物，是一种很有前景的神经母细胞瘤诊断生物标志物，可对高危患者进行分层：方法：我们在赛默飞世尔科技公司的 Orbitrap Exploris 120 上使用液相色谱-高分辨质谱（LC-HRMS）技术开发并验证了从干燥血浆样本（DPS）和血浆中测定 3-OMD 的方法：从少量（50 mL）血浆和 DPS（从 30 mL 血浆中提取）中测得的 3-OMD 浓度范围为 7.8-4000 ng/mL，该方法准确且重现性好。血浆和 DPS 中测得的 3-OMD 浓度高度相关（R = 0.99 95 %CI 0.993-0.996）。3-OMD 水平在 L1 和 M 阶段以及 L1 和 L2 阶段之间存在差异（p 值结论：3-OMD 在 L1 和 M 阶段以及 L1 和 L2 阶段之间存在差异：3-OMD被证实是高风险NB的一种有趣的生物标志物。所描述的方法对涉及多个部位的进一步前瞻性研究具有附加价值。3-OMD 在 DPS 中的稳定性便于运输和室温储存。

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Measurement of 3-O-methyldopa from dried plasma microsamples by high-resolution mass spectrometry: A tool for the diagnosis of patients with high-risk neuroblastoma

Background

Risk assessment at diagnosis is crucial for neuroblastoma (NB) in order to address patients at high-risk to the most timely and appropriate treatments. 3-O-methyldopa (3-OMD), a direct metabolite of L-Dopa, is a promising biomarker of NB at diagnosis able to stratify high-risk patients.

Methods

We show the development and validation of a method for measuring 3-OMD from dried plasma samples (DPS) and plasma using liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) on a Thermo Fisher Scientific Orbitrap Exploris 120.

Results

The method was accurate and reproducible in the range 7.8–4000 ng/mL, from small amounts (50 mL) of plasma and DPS (obtained starting from 30 mL plasma). 3-OMD concentrations measured in plasma and DPS were highly correlated (R = 0.99 95 %CI 0.993–0.996). Differences of 3-OMD levels across stages L1 and M and L1 and L2 (p-value < 0.05) were statistically significant. Receiving Operator Curve (ROC) analysis showed that 3-OMD was able to discriminate patients at high-risk with high sensitivity and specificity both from plasma or DPS (AUC = 0.8295 %CI 0.71–0.94, P < 0.0001).

Conclusions

3-OMD is confirmed as an interesting biomarker of high-risk NB. The described method is an added value for further prospective studies involving multiple sites. The stability of 3-OMD in DPS allows for easy shipment and storage at room temperature.

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来源期刊

Clinica Chimica Acta 医学-医学实验技术

CiteScore

10.10

自引率

2.00%

发文量

1268

审稿时长

23 days

期刊介绍： The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.