High-Throughput Global Phosphoproteomic Profiling Using Phospho Heavy-Labeled-Spiketide FAIMS Stepped-CV DDA (pHASED)

Abstract

Global high-throughput profiling of oncogenic signaling pathways by phosphoproteomics is increasingly being applied to cancer specimens. Such quantitative unbiased phosphoproteomic profiling of cancer cells identifies oncogenic signaling cascades that drive disease initiation and progression; pathways that are often invisible to genomics sequencing strategies. Therefore, phosphoproteomic profiling has immense potential for informing individualized anti-cancer treatments. However, complicated and extensive sample preparation protocols, coupled with intricate chromatographic separation techniques that are necessary to achieve adequate phosphoproteomic depth, limits the clinical utility of these techniques. Traditionally, phosphoproteomics is performed using isobaric tagged based quantitation coupled with TiO2 enrichment and offline prefractionation prior to nLC-MS/MS. However, the use of isobaric tags and offline HPLC limits the applicability of phosphoproteomics for the analysis of individual patient samples in real-time. To address these limitations, here we have optimized a new protocol, phospho-Heavy-labeled-spiketide FAIMS Stepped-CV DDA (pHASED). pHASED maintained phosphoproteomic coverage yet decreased sample preparation time and complexity by eliminating the variability associated with offline prefractionation. pHASED employed online phosphoproteome deconvolution using high-field asymmetric waveform ion mobility spectrometry (FAIMS) and internal phosphopeptide standards to provide accurate label-free quantitation data. Compared with our traditional tandem mass tag (TMT) phosphoproteomics workflow and optimized using isogenic FLT3-mutant acute myeloid leukemia (AML) cell line models (n=18/workflow), pHASED halved total sample preparation, and running time (TMT=10 days, pHASED=5 days) and doubled the depth of phosphoproteomic coverage in real-time (phosphopeptides = 7,694 pHASED, 3,861 TMT). pHASED coupled with bioinformatic analysis predicted differential activation of the DNA damage and repair ATM signaling pathway in sorafenib-resistant AML cell line models, uncovering a potential therapeutic opportunity that was validated using cytotoxicity assays. Herein, we optimized a rapid, reproducible, and flexible protocol for the characterization of complex cancer phosphoproteomes in real-time, highlighting the potential for phosphoproteomics to aid in the improvement of clinical treatment strategies.