4.5 Article

Assessment of SRM, MRM3, and DIA for the targeted analysis of phosphorylation dynamics in non-small cell lung cancer

Journal

PROTEOMICS
Volume 16, Issue 15-16, Pages 2193-2205

Publisher

WILEY-BLACKWELL
DOI: 10.1002/pmic.201500453

Keywords

Data-independent acquisition; MRM3; Protein phosphorylation; Quantitative proteomics; Selected reaction monitoring; Technology

Funding

  1. Netherlands Organization for Scientific Research (NWO) through a VIDI grant [723.012.102, 723.013.008]
  2. Netherlands Organization for Scientific Research (NWO) as part of the National Roadmap Large-scale Research Facilities of the Netherlands [184.032.201]

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Hypothesis-driven MS-based targeted proteomics has gained great popularity in a relatively short timespan. Next to the widely established selected reaction monitoring (SRM) workflow, data-independent acquisition (DIA), also referred to as sequential window acquisition of all theoretical spectra (SWATH) was introduced as a high-throughput targeted proteomics method. DIA facilitates increased proteome coverage, however, does not yet reach the sensitivity obtained with SRM. Therefore, a well-informed method selection is crucial for designing a successful targeted proteomics experiment. This is especially the case when targeting less conventional peptides such as those that contain PTMs, as these peptides do not always adhere to the optimal fragmentation considerations for targeted assays. Here, we provide insight into the performance of DIA, SRM, and MRM cubed (MRM3) in the analysis of phosphorylation dynamics throughout the phosphoinositide 3-kinase mechanistic target of rapamycin (PI3K-mTOR) and mitogen-activated protein kinase (MAPK) signaling network. We observe indeed that DIA is less sensitive when compared to SRM, however demonstrates increased flexibility, by postanalysis selection of alternative phosphopeptide precursors. Additionally, we demonstrate the added benefit of MRM3, allowing the quantification of two poorly accessible phosphosites. In total, targeted proteomics enabled the quantification of 42 PI3K-mTOR and MAPK phosphosites, gaining a so far unachieved in-depth view mTOR signaling events linked to tyrosine kinase inhibitor resistance in non-small cell lung cancer.

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