Additional file 2 of Phospho-heavy-labeled-spiketide FAIMS stepped-CV DDA (pHASED) provides real-time phosphoproteomics data to aid in cancer drug selection

Additional file 3: Table S1. SBDS heavy-labeled phosphorylated peptide standards. Table S2. Common and unique phosphoproteins identified across all four CVs based on PSM acquisition. Table S3. High confidence modification sites identified in LFQ (p < 0.01). Table S4. High confidence modification sites identified in pHASED (p < 0.01). Table S5. Unique and common phosphoproteins identified in LFQ and pHASED datasets. Table S6. Phosphorylated master protein kinases identified in LFQ dataset (p < 0.01). Table S7. Phosphorylated master protein kinases identified in pHASED dataset (p < 0.01). Table S8. FLT3-D835 mutations associated with resistance to tyrosine kinase FLT3 inhibitors. Table S9. Kinase-Substrate analysis of LFQ dataset for resistant cells in comparison to FLT3-ITD (log2 fold change ± 0.5). Table S10. Kinase-Substrate analysis of pHASED dataset for resistant cells in comparison to FLT3-ITD (log2 fold change ± 0.5). Table S11. Canonical pathways identified as significantly associated with LFQ dataset for resistant cells in comparison to FLT3-ITD. Table S12. Canonical pathways identified as significantly associated with pHASED dataset for resistant cells in comparison to FLT3-ITD. Table S13. Kinase activity inferred by KSEA analysis of phosphorylation changes in pHASED dataset (log2 ± 0.5, p ≤ 0.05) for resistant cells in comparison to FLT3-ITD. Table S14. Mutation-specific response to sorafenib. IC50 compared to FLT3-ITD. Table S15. Bliss Synergy scores for sorafenib in combination with KU-60019 at different doses. Table S16. Unique ATM substrates identified with increased phosphorylation (log2 ≥ 0.5) in pHASED dataset for resistant cells in comparison to FLT3-ITD. Table S17. Vector mutations in FLT3 gene.