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血浆蛋白生物标志物谱分析揭示了急性白血病、淋巴瘤患者与对照者之间的主要差异。

Plasma protein biomarker profiling reveals major differences between acute leukaemia, lymphoma patients and controls.

机构信息

Department of Immunology, Genetics & Pathology, Uppsala University, Uppsala, Sweden; Centre for Research and Development, Uppsala University/Region Gävleborg, Sweden.

Department of Immunology, Genetics & Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden.

出版信息

N Biotechnol. 2022 Nov 25;71:21-29. doi: 10.1016/j.nbt.2022.06.005. Epub 2022 Jun 29.

DOI:10.1016/j.nbt.2022.06.005
PMID:35779858
Abstract

Aiming to accommodate the unmet need for easily accessible biomarkers with a focus on biological differences between haematological diseases, the diagnostic value of plasma proteins in acute leukaemias and lymphomas was investigated. A multiplex proximity extension assay (PEA) was used to analyze 183 proteins in diagnostic plasma samples from 251 acute leukaemia and lymphoma patients and compared with samples from 60 healthy controls. Multivariate modelling using partial least square discriminant analysis revealed highly significant differences between distinct disease subgroups and controls. The model allowed explicit distinction between leukaemia and lymphoma, with few patients misclassified. Acute leukaemia samples had higher levels of proteins associated with haemostasis, inflammation, cell differentiation and cell-matrix integration, whereas lymphoma samples demonstrated higher levels of proteins known to be associated with tumour microenvironment and lymphoma dissemination. PEA technology can be used to screen for large number of plasma protein biomarkers in low µL sample volumes, enabling the distinction between controls, acute leukaemias and lymphomas. Plasma protein profiling could help gain insights into the pathophysiology of acute leukaemia and lymphoma and the technique may be a valuable tool in the diagnosis of these diseases.

摘要

为了满足对易于获取的生物标志物的需求,重点关注血液系统疾病之间的生物学差异,本研究调查了血浆蛋白在急性白血病和淋巴瘤中的诊断价值。使用多重邻近延伸分析(PEA)检测了 251 例急性白血病和淋巴瘤患者的诊断血浆样本中的 183 种蛋白,并与 60 例健康对照者的样本进行比较。使用偏最小二乘判别分析进行的多变量建模显示,不同疾病亚组与对照组之间存在显著差异。该模型能够明确区分白血病和淋巴瘤,少数患者被错误分类。急性白血病样本中与止血、炎症、细胞分化和细胞-基质整合相关的蛋白水平较高,而淋巴瘤样本中与肿瘤微环境和淋巴瘤播散相关的蛋白水平较高。PEA 技术可用于筛选大量低 µL 样本量的血浆蛋白生物标志物,从而区分对照组、急性白血病和淋巴瘤。血浆蛋白谱分析有助于深入了解急性白血病和淋巴瘤的病理生理学,该技术可能是这些疾病诊断的有用工具。

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