Bowel Cancer & Biomarker Laboratory, School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, St Leonards, NSW, Australia.
Centre for Inflammation, Centenary Institute, Camperdown, NSW, Australia.
Methods Mol Biol. 2024;2823:241-251. doi: 10.1007/978-1-0716-3922-1_15.
Biofluids such as blood plasma are rich reservoirs of potential biomarkers for disease diagnosis, prognosis, and prediction of treatment response. However, mass spectrometry analysis of circulating plasma proteins remains challenging. The introduction of data-independent acquisition mass spectrometry (DIA-MS) is an important step toward addressing detection of less abundant plasma proteins. Numerous plasma peptide MS/MS spectral library datasets produced from extensive plasma fractionation are accessible from public archives, and these can be repurposed as spectral reference libraries to increase the depth of proteomic analysis when DIA-MS is used. Here we describe the workflow that relies on reusing the existing spectral reference libraries by populating them with locally obtained peptide MS/MS data acquired by DIA-MS. This approach was demonstrated effectively to identify putative plasma biomarkers of response to neoadjuvant chemotherapy in the setting of pancreatic ductal adenocarcinoma (PDAC) (O'Rourke et al., J Proteomics 231:103998, 2021).
生物流体(如血浆)是疾病诊断、预后和治疗反应预测的潜在生物标志物的丰富来源。然而,循环血浆蛋白的质谱分析仍然具有挑战性。非依赖性采集质谱(DIA-MS)的引入是解决检测较少丰度血浆蛋白的重要步骤。从广泛的血浆分级分离产生的大量血浆肽 MS/MS 光谱库数据集可从公共档案中获得,并且当使用 DIA-MS 时,这些数据集可被重新用作光谱参考库,以增加蛋白质组学分析的深度。在这里,我们描述了一种依赖于通过 DIA-MS 获得的局部肽 MS/MS 数据填充现有光谱参考库来重用它们的工作流程。这种方法在胰腺导管腺癌 (PDAC) 中对新辅助化疗反应的潜在血浆生物标志物的鉴定中得到了有效证明(O'Rourke 等人,J Proteomics 231:103998, 2021)。