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. 2021 May 1;81(9):2495-2509.
doi: 10.1158/0008-5472.CAN-20-3804. Epub 2021 Jan 28.

High-Density, Targeted Monitoring of Tyrosine Phosphorylation Reveals Activated Signaling Networks in Human Tumors

Affiliations

High-Density, Targeted Monitoring of Tyrosine Phosphorylation Reveals Activated Signaling Networks in Human Tumors

Lauren E Stopfer et al. Cancer Res. .

Abstract

Tyrosine phosphorylation (pTyr) plays a pivotal role in signal transduction and is commonly dysregulated in cancer. As a result, profiling tumor pTyr levels may reveal therapeutic insights critical to combating disease. Existing discovery and targeted mass spectrometry-based methods used to monitor pTyr networks involve a tradeoff between broad coverage of the pTyr network, reproducibility in target identification across analyses, and accurate quantification. To address these limitations, we developed a targeted approach, termed "SureQuant pTyr," coupling low input pTyr enrichment with a panel of isotopically labeled internal standard peptides to guide data acquisition of low-abundance tyrosine phosphopeptides. SureQuant pTyr allowed for reliable quantification of several hundred commonly dysregulated pTyr targets with high quantitative accuracy, improving the robustness and usability of targeted mass spectrometry assays. We established the clinical applicability of SureQuant pTyr by profiling pTyr signaling levels in human colorectal tumors using minimal sample input, characterizing patient-specific oncogenic-driving mechanisms. While in some cases pTyr profiles aligned with previously reported proteomic, genomic, and transcriptomic molecular characterizations, we highlighted instances of new insights gained using pTyr characterization and emphasized the complementary nature of pTyr measurements with traditional biomarkers for improving patient stratification and identifying therapeutic targets. The turn-key nature of this approach opens the door to rapid and reproducible pTyr profiling in research and clinical settings alike and enables pTyr-based measurements for applications in precision medicine. SIGNIFICANCE: SureQuant pTyr is a mass spectrometry-based targeted method that enables sensitive and selective targeted quantitation of several hundred low-abundance tyrosine phosphorylated peptides commonly dysregulated in cancer, including oncogenic signaling networks.

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Conflict of interest statement

COI: The authors declare no potential conflicts of interest.

Figures

Figure 1.
Figure 1.
Platform for targeted pTyr analysis with IS-guided acquisition. A, Human kinome tree with peptides selected for SureQuant pTyr analysis colored according to kinase group. B, Sample processing workflow for pTyr enrichment and analysis. C, Mass spectrometry acquisition method and analysis workflow for SureQuant pTyr IS-triggered quantitation.
Figure 2.
Figure 2.
High quantitative reproducibility is achieved with SureQuant pTyr. A, Experimental setup. IS-trigger peptides were added to three biological replicates of A549 cell lysate stimulated with epidermal growth factor (EGF). Enriched light (L) and heavy (H) pTyr peptides were analyzing using SureQuant pTyr acquisition. B, MS/MS spectra from analysis #3 of the heavy (left) and light (right) CTTND1 peptide, SLDNN[pY]STPNER-pY904, at peak intensity, where [pY] denotes the residue position with pTyr modification. Monitored product ions are uniquely colored and labeled with b/y ion. C, Ion intensity over time for the 6 heavy (upper) and light (lower) product ions from CTTND1 pY904 in analysis #3. Each MS/MS event is represented by a point. D, Integrated peak area intensities for each product ion in C. Bar color corresponds to analysis #. E, Ratios of light to heavy signal intensity (L/H) of CTTND1 pY904 for each analysis, where each point represents the L/H value of a single product ion. Solid line and error bars represent the mean and standard deviation, respectively. F, Correlation of (L/H) signals across 127 peptides between analysis #1 and #2 (r2=0.96, black) and analysis #1 and #3 (r2=0.97, grey). G, Log2 fold change values, relative to the mean peptide abundance at the 0-minute timepoint, of pTyr peptides for three data acquisition methods: PRM (black), TMT-labeled DDA (grey) and SureQuant pTyr (blue). Significant differences in quantitation between PRM and TMT-DDA vs. SQ pTyr are represented as *p<0.05 (Dunnett’s multiple comparisons test). Each sample includes n=3 biological replicates, error bars represent the standard deviation.
Figure 3.
Figure 3.
Targeted pTyr analysis highlights CRC tumor heterogeneity. A, Peptides identified and quantified across 31 tumors. B, Distribution of tumor L:H ratios with peptides rank ordered from highest to lowest maximum abundance. Annotated peptides labeled by source protein and residue position with pTyr modification have the maximum and minimum abundances. C, Light to heavy signal intensity ratios (L/H) for ErbB3 peptide (black), SLEATDSAFDNPD[pY]WHSR, and EGFR peptide (red), GSTAENAE[pY]LR, where [pY] denotes the residue position with pTyr modification. D, Peptide and tumor hierarchical clustering (distance metric = correlation), where pTyr abundance values are z-score normalized light to heavy signal ratios. E, Tumors plotted by principal component 1 (PC1) and PC2 score, colored according to unified multi-omics subtype. F, Significantly enriched reactome pathways from the top 20 peptides derived from unique proteins on PC1 (top, black) and PC2 (bottom, grey). Significance values are FDR adjusted.
Figure 4.
Figure 4.
Differential pTyr levels identify tumors with significant pathway enrichment. A, Hierarchical clustering based on the correlation coefficients between phosphosites across all tumors (distance metric = correlation). B-E, Protein-protein interaction network of peptides within cluster 1 (B), cluster 2 (C) and cluster 3 (D-E). Node color(s) maps peptides to enriched pathway(s). F Significantly enriched pathways among tumors using tumor-specific pathway enrichment analysis. G Significantly enriched kinase-substrate interactions within tumors. Significance (p-value) and directionality indicated by color, FDR q-value < 0.25 for all enrichment analyses. Tumors without any significant enrichment are not shown.
Figure 5.
Figure 5.
EGFR phosphorylation levels identify candidates for anti-EGFR therapy. A, Enrichment plots (left) of ErbB signaling pathway in T25 (purple) and T9 (teal). Peptide rank (x-axis) versus pTyr abundance is plotted on the left y-axis, and the running enrichment score is plotted on the right y-axis. Each hit signifies a pTyr source protein present in the ErbB signaling pathway library. All pTyr peptides identified in the ErbB signaling pathway and their corresponding pTyr abundance (right), with ErbB family receptors annotated in bold. pTyr abundance values are z-score normalized light to heavy signal ratios. B, Z-score normalized pTyr abundance (pTyr), protein expression (protein) and transcript expression (RNA-seq) levels of ErbB signaling pathway members. C, Correlation between pTyr abundance and protein (red) or transcript (blue) expression of ErbB signaling pathway members. Protein and transcript abundance values are z-score normalized. Correlation coefficients for pTyr vs. protein for T9, T16, and T22 are r2= 0.06, 0.05, 0.29, respectively. Correlation coefficients for pTyr vs. gene expression for T9, T16, T22, and T25 are r2= 0.35, 0.01, 0.38, and 0.43, respectively. Protein expression data for T25 was unavailable. D, Normalized enrichment score (NES) for positively enriched reactome pathways in T9 using RNA-seq data. *= p<0.05, **= p<0.01, FDR q-value < 0.05 for all. E, Correlation between all pTyr sites in the full matrix and corresponding protein expression (top, r2=0.025) and gene expression (bottom, r2=0.026) levels. All values are z-score normalized. F, Cumulative pTyr signal, calculated as the ratio of tumor light to heavy pTyr signal (x) to the mean light to heavy signal (μ) across tumors, log2 transformed for two EGFR phosphopeptides rank ordered from highest to lowest signal. Tumor specific annotations are indicated by color, and pY1148 and pY1173 denote the EGFR residue position with pTyr modification.
Figure 6.
Figure 6.
pTyr signatures of T cell signaling pathway peptides. A, pTyr signal of T-cell signaling peptides, calculated as the ratio of tumor light to heavy pTyr signal (x) to the mean light to heavy signal (μ), for T8 and T9. Phosphorylation levels on the signaling diagram (colored circles) correspond to T8, and pY denotes the residue position with pTyr modification. B, Cumulative CD3ζ pTyr levels (light to heavy signal) from three CD3ζ pTyr peptides. Tumor-specific biomarker statuses are indicated by color. C, Gene set enrichment analysis (GSEA) plots for IFN-γ response, with gene rank (x-axis) versus running enrichment score (y-axis). Each hit signifies a gene present in the gene set. D, Normalized enrichment scores (NES) from GSEA for selected significantly enriched pathways *p<0.05, **p<0.01, q<0.25 for all. E, Z-scored normalized protein and transcript expression levels of antigen presentation genes. F, GSEA NES for antigen processing and presentation gene ontology gene set (GO:0019882), *p<0.05, **p<0.01, q<0.25 for all. G, Immune score of tumors from Vasaikar et al., * = positively enriched # = negatively enriched in pTyr T cell signaling peptides. H, Unique pTyr peptides with significant positive correlation to immune score (p < 0.05). I, Correlation between immune score and the L/H signal of CD3ζ-pY111, r2 = 0.19.

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References

    1. White FM, Wolf-Yadlin A. Methods for the Analysis of Protein Phosphorylation–Mediated Cellular Signaling Networks. Annu Rev Anal Chem. Annual Reviews; 2016;9:295–315. - PubMed
    1. Lemmon MA, Schlessinger J. Cell signaling by receptor tyrosine kinases. Cell. 2010. page 1117–34. - PMC - PubMed
    1. Groves JT, Kuriyan J. Molecular mechanisms in signal transduction at the membrane. Nat. Struct. Mol. Biol. Howard Hughes Medical Institute; 2010. page 659–65. - PMC - PubMed
    1. Hunter T, Sefton BM. Transforming gene product of Rous sarcoma virus phosphorylates tyrosine. Proc Natl Acad Sci U S A. 1980;77:1311–5. - PMC - PubMed
    1. Lawrence RT, Searle BC, Llovet A, Villén J. Plug-and-play analysis of the human phosphoproteome by targeted high-resolution mass spectrometry. Nat Methods. Nature Publishing Group; 2016;13:431–4. - PMC - PubMed

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