Evaluation of Differential Peptide Loading on Tandem Mass Tag-Based Proteomic and Phosphoproteomic Data Quality

Abstract

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.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

“…In spite of the detrimental effect of the ion suppression on the accuracy, TMT-based quantification provides a higher precision than label-free quantification [ 202 , 203 , 204 , 206 ]. TMTs, in addition to protein quantification, increase the detection sensitivity of certain highly hydrophilic analytes, such as phosphopeptides [ 207 , 208 ]. TMTs are widely applied in oncoproteomics analysis [ 205 , 209 , 210 , 211 , 212 , 213 ].…”

Mapping the proteogenomic landscape enables prediction of drug response in acute myeloid leukemia

“…In this study, we explored the extent to which the molecular landscape, determined by genomic, transcriptomic, and proteomic measurements, can provide insight into ex vivo drug response. We applied our in-depth global and phosphoproteomic pipeline, developed under the NCI CPTAC program, 34 , 43 , 44 to a subset of 210 patients within the Beat AML cohort, which had been previously characterized via whole-exome sequencing, RNA sequencing, and ex vivo drug sensitivity measurements of 145 small-molecule inhibitors. 11 , 12 We integrated the transcriptomics, proteomics, and phosphoproteomics to identify four distinct proteogenomic subtypes of patients using non-negative matrix factorization.…”