Proteomic Discovery and Validation of Novel Fluid Biomarkers for Improved Patient Selection and Prediction of Clinical Outcomes in Alzheimer's Disease Patient Cohorts.

Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline. The two cardinal neuropathological hallmarks of AD include the buildup of cerebral ß amyloid (Aß) plaques and neurofibrillary tangles of hyperphosphorylated tau. The current disease-modifying treatments are still not effective enough to lower the rate of cognitive decline. There is an urgent need to identify early detection and disease progression biomarkers that can facilitate AD drug development. The current established readouts based on the expression levels of amyloid beta, tau, and phospho-tau have shown many discrepancies in patient samples when linked to disease progression. There is an urgent need to identify diagnostic and disease progression biomarkers from blood, cerebrospinal fluid (CSF), or other biofluids that can facilitate the early detection of the disease and provide pharmacodynamic readouts for new drugs being tested in clinical trials. Advances in proteomic approaches using state-of-the-art mass spectrometry are now being increasingly applied to study AD disease mechanisms and identify drug targets and novel disease biomarkers. In this report, we describe the application of quantitative proteomic approaches for understanding AD pathophysiology, summarize the current knowledge gained from proteomic investigations of AD, and discuss the development and validation of new predictive and diagnostic disease biomarkers.

Characterization of Citrullination Sites in Neutrophils and Mast Cells Activated by Ionomycin via Integration of Mass Spectrometry and Machine Learning.

Citrullination is an important post-translational modification implicated in many diseases including rheumatoid arthritis (RA), Alzheimer's disease, and cancer. Neutrophil and mast cells have different expression profiles for protein-arginine deiminases (PADs), and ionomycin-induced activation makes them an ideal cellular model to study proteins susceptible to citrullination. We performed high-resolution mass spectrometry and stringent data filtration to identify citrullination sites in neutrophil and mast cells treated with and without ionomycin. We identified a total of 833 validated citrullination sites on 395 proteins. Several of these citrullinated proteins are important components of pathways involved in innate immune responses. Using this benchmark primary sequence data set, we developed machine learning models to predict citrullination in neutrophil and mast cell proteins. We show that our models predict citrullination likelihood with 0.735 and 0.766 AUCs (area under the receiver operating characteristic curves), respectively, on independent validation sets. In summary, this study provides the largest number of validated citrullination sites in neutrophil and mast cell proteins. The use of our novel motif analysis approach to predict citrullination sites will facilitate the discovery of novel protein substrates of protein-arginine deiminases (PADs), which may be key to understanding immunopathologies of various diseases.

Quantitative Mass Spectrometry to Interrogate Proteomic Heterogeneity in Metastatic Lung Adenocarcinoma and Validate a Novel Somatic Mutation CDK12-G879V.

Lung cancer is the leading cause of cancer death in both men and women. Tumor heterogeneity is an impediment to targeted treatment of all cancers, including lung cancer. Here, we sought to characterize tumor proteome and phosphoproteome changes by longitudinal, prospective collection of tumor tissue from an exceptional responder lung adenocarcinoma patient who survived with metastatic lung adenocarcinoma for over seven years while undergoing HER2-directed therapy in combination with chemotherapy. We employed "Super-SILAC" and TMT labeling strategies to quantify the proteome and phosphoproteome of a lung metastatic site and eight distinct metastatic progressive lymph nodes collected during these seven years, including five lymph nodes procured at autopsy. We identified specific signaling networks enriched in lung compared with the lymph node metastatic sites. We correlated the changes in protein abundance with changes in copy number alteration (CNA) and transcript expression. ERBB2/HER2 protein expression was higher in lung, consistent with a higher degree of ERBB2 amplification in lung compared with the lymph node metastatic sites. To further interrogate the mass spectrometry data, a patient-specific database was built by incorporating all the somatic and germline variants identified by whole genome sequencing (WGS) of genomic DNA from the lung, one lymph node metastatic site and blood. An extensive validation pipeline was built to confirm variant peptides. We validated 360 spectra corresponding to 55 germline and 6 somatic variant peptides. Targeted MRM assays revealed two novel variant somatic peptides, CDK12-G879V and FASN-R1439Q, expressed in lung and lymph node metastatic sites, respectively. The CDK12-G879V mutation likely results in a nonfunctional CDK12 kinase and chemotherapy susceptibility in lung metastatic sites. Knockdown of CDK12 in lung adenocarcinoma cells increased chemotherapy sensitivity which was rescued by wild type, but not CDK12-G879V expression, consistent with the complete resolution of the lung metastatic sites in this patient.

Dataset describing the development, optimization and application of SRM/MRM based targeted proteomics strategy for quantification of potential biomarkers of EGFR TKI sensitivity.

The data presented here describes the use of targeted proteomic assays to quantify potential biomarkers of Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) sensitivity in lung adenocarcinoma and is related to the research article: "Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma" [1]. This article describes the data associated with liquid chromatography coupled to multiple reaction monitoring (LC-MRM) method development which includes selection of an optimal transition list, retention time prediction and building of reverse calibration curves. Sample preparation and optimization which includes phosphotyrosine peptide enrichment via a combination of pan-phosphotyrosine antibodies is described. The dataset also consists of figures, tables and Excel files describing the quantitative results of testing these optimized methods in two lung adenocarcinoma cell lines with EGFR mutations.

Quantitative targeted proteomic analysis of potential markers of tyrosine kinase inhibitor (TKI) sensitivity in EGFR mutated lung adenocarcinoma.

Lung cancer causes the highest mortality among all cancers. Patients harboring kinase domain mutations in the epidermal growth factor receptor (EGFR) respond to EGFR tyrosine kinase inhibitors (TKIs), however, acquired resistance always develops. Moreover, 30-40% of patients with EGFR mutations exhibit primary resistance. Hence, there is an unmet need for additional biomarkers of TKI sensitivity that complement EGFR mutation testing and predict treatment response. We previously identified phosphopeptides whose phosphorylation is inhibited upon treatment with EGFR TKIs, erlotinib and afatinib in TKI sensitive cells, but not in resistant cells. These phosphosites are potential biomarkers of TKI sensitivity. Here, we sought to develop modified immuno-multiple reaction monitoring (immuno-MRM)-based quantitation assays for select phosphosites including EGFR-pY1197, pY1172, pY998, AHNAK-pY160, pY715, DAPP1-pY139, CAV1-pY14, INPPL1-pY1135, NEDD9-pY164, NF1-pY2579, and STAT5A-pY694. These sites were significantly hypophosphorylated by erlotinib and a 3rd generation EGFR TKI, osimertinib, in TKI-sensitive H3255 cells, which harbor the TKI-sensitizing EGFRL858R mutation. However, in H1975 cells, which harbor the TKI-resistant EGFRL858R/T790M mutant, osimertinib, but not erlotinib, could significantly inhibit phosphorylation of EGFR-pY-1197, STAT5A-pY694 and CAV1-pY14, suggesting these sites also predict response in TKI-resistant cells. We could further validate EGFR-pY-1197 as a biomarker of TKI sensitivity by developing a calibration curve-based modified immuno-MRM assay. SIGNIFICANCE: In this report, we have shown the development and optimization of MRM assays coupled with global phosphotyrosine enrichment (modified immuno-MRM) for a list of 11 phosphotyrosine peptides. Our optimized assays identified the targets reproducibly in biological samples with good selectivity. We also developed and characterized quantitation methods to determine endogenous abundance of these targets and correlated the results of the relative quantification with amounts estimated from the calibration curves. This approach represents a way to validate and verify biomarker candidates discovered from large-scale global phospho-proteomics analysis. The application of these modified immuno-MRM assays in lung adenocarcinoma cells provides proof-of concept for the feasibility of clinical applications. These assays may be used in prospective clinical studies of EGFR TKI treatment of EGFR mutant lung cancer to correlate treatment response and other clinical endpoints.

Quantitative Tyrosine Phosphoproteomics of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitor-treated Lung Adenocarcinoma Cells Reveals Potential Novel Biomarkers of Therapeutic Response.

Mutations in the Epidermal growth factor receptor (EGFR) kinase domain, such as the L858R missense mutation and deletions spanning the conserved sequence 747LREA750, are sensitive to tyrosine kinase inhibitors (TKIs). The gatekeeper site residue mutation, T790M accounts for around 60% of acquired resistance to EGFR TKIs. The first generation EGFR TKIs, erlotinib and gefitinib, and the second generation inhibitor, afatinib are FDA approved for initial treatment of EGFR mutated lung adenocarcinoma. The predominant biomarker of EGFR TKI responsiveness is the presence of EGFR TKI-sensitizing mutations. However, 30-40% of patients with EGFR mutations exhibit primary resistance to these TKIs, underscoring the unmet need of identifying additional biomarkers of treatment response. Here, we sought to characterize the dynamics of tyrosine phosphorylation upon EGFR TKI treatment of mutant EGFR-driven human lung adenocarcinoma cell lines with varying sensitivity to EGFR TKIs, erlotinib and afatinib. We employed stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative mass spectrometry to identify and quantify tyrosine phosphorylated peptides. The proportion of tyrosine phosphorylated sites that had reduced phosphorylation upon erlotinib or afatinib treatment correlated with the degree of TKI-sensitivity. Afatinib, an irreversible EGFR TKI, more effectively inhibited tyrosine phosphorylation of a majority of the substrates. The phosphosites with phosphorylation SILAC ratios that correlated with the TKI-sensitivity of the cell lines include sites on kinases, such as EGFR-Y1197 and MAPK7-Y221, and adaptor proteins, such as SHC1-Y349/350, ERRFI1-Y394, GAB1-Y689, STAT5A-Y694, DLG3-Y705, and DAPP1-Y139, suggesting these are potential biomarkers of TKI sensitivity. DAPP1, is a novel target of mutant EGFR signaling and Y-139 is the major site of DAPP1 tyrosine phosphorylation. We also uncovered several off-target effects of these TKIs, such as MST1R-Y1238/Y1239 and MET-Y1252/1253. This study provides unique insight into the TKI-mediated modulation of mutant EGFR signaling, which can be applied to the development of biomarkers of EGFR TKI response.

Glycosylation characterization of therapeutic mAbs by top- and middle-down mass spectrometry.

A reference monoclonal antibody IgG1 and a fusion IgG protein were analyzed by top- and middle-down mass spectrometry with multiple fragmentation techniques including electron transfer dissociation (ETD) and matrix-assisted laser desorption ionization in-source decay (MALDI-ISD) to investigate heterogeneity of glycosylated protein species. Specifically, glycan structure, sites, relative abundance levels, and termini structural conformation were investigated by use of Fourier transform ion cyclotron resonance (FT-ICR) or high performance liquid chromatography electrospray ionization (HPLC-ESI) linked to an Orbitrap. Incorporating a limited enzymatic digestion by immunoglobulin G-degrading enzyme Streptococcus pyogenes (IdeS) with MALDI-ISD analysis extended sequence coverage of the internal region of the proteins without pre-fractionation. The data in this article is associated with the research article published in Journal of Proteomics (Tran et al., 2015) [1].

Comprehensive glycosylation profiling of IgG and IgG-fusion proteins by top-down MS with multiple fragmentation techniques.

We employed top- and middle-down analyses with multiple fragmentation techniques including electron transfer dissociation (ETD), electron capture dissociation (ECD), and matrix-assisted laser desorption ionization in-source decay (MALDI-ISD) for characterization of a reference monoclonal antibody (mAb) IgG1 and a fusion IgG protein. Fourier transform ion cyclotron resonance (FT-ICR) or high performance liquid chromatography electrospray ionization (HPLC-ESI) on an Orbitrap was employed. These experiments provided a comprehensive view on the protein species; especially for different glycosylation level in these two proteins, which showed good agreement with oligosaccharide profiling. Top- and middle-down MS provided additional information regarding glycosylation sites and different combinational protein species that were not available from oligosaccharide mapping or conventional bottom-up analysis. Finally, incorporating a limited enzymatic digestion by immunoglobulin G-degrading enzyme of Streptococcus pyogene (IdeS) with MALDI-ISD analysis enabled extended sequence coverage of the internal region of protein without pre-fractionation. BIOLOGICAL SIGNIFICANCE: Oligosaccharide profiling together with top- and middle-down methods enabled: 1) detection of heterogeneous glycosylated protein species and sites in intact IgG1 and fusion proteins with high mass accuracy, 2) estimation of relative abundance levels of protein species in the sample, 3) confirmation of the protein termini structural information, and 4) improved sequence coverage by MALDI-ISD analysis for the internal regions of the proteins without sample pre-fractionation.