Llamas-Urbano Adrián, Martínez-Moreno Julio Manuel, Pérez-Sánchez Carlos, Barbarroja Nuria
Cobiomic Bioscience SL, EBT UCO/IMIBIC, Cordoba, Spain.
Maimonides Institute for Research in Biomedicine of Cordoba (IMIBIC)/Reina Sofia University Hospital/University of Cordoba (UCO), Córdoba, Spain.
Methods Mol Biol. 2025;2929:171-193. doi: 10.1007/978-1-0716-4595-6_14.
Advancements in proteomics and biomarker discovery require technologies capable of high-throughput, multiplexed, and minimally invasive protein detection. The Proximity Extension Assay (PEA), developed by Olink Proteomics, meets these demands by integrating dual-recognition immunoassays with quantitative PCR (qPCR), enabling the precise quantification of multiple proteins with exceptional sensitivity and specificity. While PEA is commonly applied to serum and plasma, its adaptability allows for the analysis of alternative biological matrices, including cerebrospinal fluid, urine, synovial fluid, bone marrow, amniotic fluid, blister fluid, conditioned media, interstitial fluid, and extracellular vesicles, among others. These matrices offer valuable opportunities for biomarker discovery, precision medicine, and translational research, particularly in diseases where conventional sampling is challenging. This chapter details the methodological considerations required for processing these alternative biofluids, ensuring their compatibility with PEA technology. It provides best practices for sample collection, processing, and quality control to maximize the accuracy and reproducibility of proteomic analyses. Additionally, it highlights PEA's ability to detect low-abundance proteins, which is critical for identifying novel biomarkers in complex biological samples.
蛋白质组学和生物标志物发现领域的进展需要能够进行高通量、多重和微创蛋白质检测的技术。由Olink Proteomics公司开发的邻位延伸分析(PEA)通过将双识别免疫分析与定量PCR(qPCR)相结合,满足了这些需求,能够以极高的灵敏度和特异性对多种蛋白质进行精确量化。虽然PEA通常应用于血清和血浆,但它的适应性使其能够分析其他生物基质,包括脑脊液、尿液、滑液、骨髓、羊水、水疱液、条件培养基、间质液和细胞外囊泡等。这些基质为生物标志物发现、精准医学和转化研究提供了宝贵机会,尤其是在传统采样具有挑战性的疾病中。本章详细介绍了处理这些替代生物流体所需的方法学考量,确保它们与PEA技术兼容。它提供了样本采集、处理和质量控制的最佳实践,以最大限度地提高蛋白质组学分析的准确性和可重复性。此外,它还强调了PEA检测低丰度蛋白质的能力,这对于在复杂生物样本中识别新型生物标志物至关重要。