Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99354, United States.
Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon 97239, United States.
J Am Soc Mass Spectrom. 2022 Jan 5;33(1):17-30. doi: 10.1021/jasms.1c00169. Epub 2021 Nov 23.
Global and phosphoproteome profiling has demonstrated great utility for the analysis of clinical specimens. One barrier to the broad clinical application of proteomic profiling is the large amount of biological material required, particularly for phosphoproteomics─currently on the order of 25 mg wet tissue weight. For hematopoietic cancers such as acute myeloid leukemia (AML), the sample requirement is ≥10 million peripheral blood mononuclear cells (PBMCs). Across large study cohorts, this requirement will exceed what is obtainable for many individual patients/time points. For this reason, we were interested in the impact of differential peptide loading across multiplex channels on proteomic data quality. To achieve this, we tested a range of channel loading amounts (approximately the material obtainable from 5E5, 1E6, 2.5E6, 5E6, and 1E7 AML patient cells) to assess proteome coverage, quantification precision, and peptide/phosphopeptide detection in experiments utilizing isobaric tandem mass tag (TMT) labeling. As expected, fewer missing values were observed in TMT channels with higher peptide loading amounts compared to lower loadings. Moreover, channels with a lower loading have greater quantitative variability than channels with higher loadings. A statistical analysis showed that decreased loading amounts result in an increase in the type I error rate. We then examined the impact of differential loading on the detection of known differences between distinct AML cell lines. Similar patterns of increased data missingness and higher quantitative variability were observed as loading was decreased resulting in fewer statistical differences; however, we found good agreement in features identified as differential, demonstrating the value of this approach.
全球和磷酸化蛋白质组学分析已被证明在分析临床标本方面具有很大的作用。蛋白质组学分析广泛应用的一个障碍是需要大量的生物材料,特别是对于磷酸化蛋白质组学来说,目前大约需要 25 毫克湿组织重量。对于急性髓细胞白血病 (AML) 等血液系统癌症,样本需求≥1000 万个外周血单核细胞 (PBMC)。在大型研究队列中,这一需求将超过许多个体患者/时间点的可获得量。出于这个原因,我们对多通道中差异肽加载对蛋白质组学数据质量的影响感兴趣。为了实现这一目标,我们测试了一系列通道加载量(大约可从 5E5、1E6、2.5E6、5E6 和 1E7 AML 患者细胞中获得),以评估利用等重同位素标记的串联质量标签 (TMT) 标记实验中的蛋白质组覆盖度、定量精度和肽/磷酸肽检测。正如预期的那样,与低负载相比,高肽负载的 TMT 通道中观察到的缺失值更少。此外,与高负载相比,负载较低的通道具有更大的定量可变性。统计分析表明,减少加载量会导致 I 型错误率增加。然后,我们研究了差异加载对不同 AML 细胞系之间已知差异检测的影响。随着负载的降低,数据缺失和更高的定量可变性增加,导致更少的统计差异;然而,我们发现差异特征的识别具有良好的一致性,这证明了这种方法的价值。