脑脊液 (CSF) 是发现与儿科中枢神经系统恶性肿瘤预后相关的生物标志物和开发治疗靶点的关键基质。然而，儿童中蛋白质浓度的广泛范围和与年龄相关的差异使得此类发现具有挑战性。此外，儿科脑脊液样本通常很少，并且首先优先用于临床目的。目前的工作重点是优化蛋白质组分析工作流程的每个步骤，以便从可用于研究目的的有限 CSF 资源中提取尽可能详细的蛋白质组信息。该策略包括应用连续超速离心来富集细胞外囊泡 (EV)，此外还分析少量原始 CSF，从而可以对 400 μL CSF 中的 1351 种蛋白质（相对于原始 CSF 的 55%）进行定量。当包含光谱库时，总共可以定量 2103 种蛋白质 (240%)。工作流程针对 CSF 输入量、胰蛋白酶消化方法、梯度长度、质谱数据采集方法和数据库搜索策略进行了优化，以量化尽可能多的蛋白质。完全优化的工作流程包括蛋白质聚集捕获 (PAC) 消化，与数据无关的采集（DIA，21 分钟梯度）相结合，仅从 400 μL CSF 中即可定量 2989 种独特的蛋白质，与之前相比，蛋白质增加了 340%原始脑脊液的胰蛋白酶消化物分析。

The cerebrospinal fluid (CSF) is a key matrix for discovery of biomarkers relevant for prognosis and the development of therapeutic targets in pediatric central nervous system malignancies. However, the wide range of protein concentrations and age-related differences in children makes such discoveries challenging. In addition, pediatric CSF samples are often sparse and first prioritized for clinical purposes. The present work focused on optimizing each step of the proteome analysis workflow to extract the most detailed proteome information possible from the limited CSF resources available for research purposes. The strategy included applying sequential ultracentrifugation to enrich for extracellular vesicles (EV) in addition to analysis of a small volume of raw CSF, which allowed quantification of 1351 proteins (+55% relative to raw CSF) from 400 μL CSF. When including a spectral library, a total of 2103 proteins (+240%) could be quantified. The workflow was optimized for CSF input volume, tryptic digestion method, gradient length, mass spectrometry data acquisition method and database search strategy to quantify as many proteins a possible. The fully optimized workflow included protein aggregation capture (PAC) digestion, paired with data-independent acquisition (DIA, 21 min gradient) and allowed 2989 unique proteins to be quantified from only 400 μL CSF, which is a 340% increase in proteins compared to analysis of a tryptic digest of raw CSF.