Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN₂ vs immediate flash freezing (iFF) in LN₂ on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN₂ vs immediate flash freezing (iFF) in LN₂ on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen

Quantitative Analysis of Signaling Networks across Differentially Embedded Tumors Highlights Interpatient Heterogeneity in Human Glioblastoma

Glioblastoma multiforme (GBM) is the most aggressive malignant primary brain tumor, with a dismal mean survival even with the current standard of care. Although in vitro cell systems can provide mechanistic insight into the regulatory networks governing GBM cell proliferation and migration, clinical samples provide a more physiologically relevant view of oncogenic signaling networks. However, clinical samples are not widely available and may be embedded for histopathologic analysis. With the goal of accurately identifying activated signaling networks in GBM tumor samples, we investigated the impact of embedding in optimal cutting temperature (OCT) compound followed by flash freezing in LN₂ vs immediate flash freezing (iFF) in LN₂ on protein expression and phosphorylation-mediated signaling networks. Quantitative proteomic and phosphoproteomic analysis of 8 pairs of tumor specimens revealed minimal impact of the different sample processing strategies and highlighted the large interpatient heterogeneity present in these tumors. Correlation analyses of the differentially processed tumor sections identified activated signaling networks present in selected tumors and revealed the differential expression of transcription, translation, and degradation associated proteins. This study demonstrates the capability of quantitative mass spectrometry for identification of in vivo oncogenic signaling networks from human tumor specimens that were either OCT-embedded or immediately flash-frozen

Phosphoproteomic Analysis of Rat Liver by High Capacity IMAC and LC−MS/MS

Proper liver function is crucial for metabolism control and to clear toxic substances from the bloodstream. Many small-molecule therapeutics accumulate in the liver, negatively impacting liver function and often resulting in hepatotoxicity and cell death. Several analytical methods are currently utilized to evaluate hepatotoxicity and monitor liver function. To date, none of these methods have specifically targeted protein phosphorylation-mediated signal transduction pathways which should be altered in response to toxic effects of small molecule therapeutics. To develop novel assays to probe specific signaling pathways in the liver, identification and quantification of specific protein phosphorylation sites in this complex organ is necessary. Here, we have utilized an optimized immobilized metal affinity chromatography (IMAC) protocol to enrich phosphorylated peptides from a tryptic digest of proteins isolated from whole liver lysate. LC−MS/MS analysis of IMAC-enriched peptides resulted in the identification of more than 300 phosphorylation sites from over 200 proteins in rat liver, a significant advance over previously published analyses of the liver phosphoproteome. Previously characterized phosphorylation sites and potentially novel sites were identified in the current study, including sites on proteins implicated in metabolism regulation, transcription, translation, and canonical signaling pathways. Moreover, protein phosphorylation analysis was performed without prior fractionation of the sample, enabling analysis of small sample amounts while minimizing analysis time, potentially allowing for high-throughput assays to be performed with this methodology. From these data, it appears that this methodology can be used to identify new phosphorylation sites and, in combination with a stable isotope-labeling step, to investigate the effects of liver diseases, cancer and evaluate potential toxicology of new drug substances.Keywords: IMAC • liver • mass spectrometry • phosphorylation • proteomic

Quantitative acetyllysine profiling of HepG2 cells stimulated with insulin.

<p><b>A.</b> Heat map representing the log₂ fold-change relative to the unstimulated condition of the 43 acetylation sites quantified. Colored bars to the right of the heatmap indicate clusters. <b>B.</b> Acetylation dynamics on sites identified on histone H3. <b>C.</b> Acetylation dynamics on sites identified on remodeling and splicing factor 1.</p

Quantitative acetyllysine profiling of A549 cells stimulated with EGF or IGF-1.

<p><b>A.</b> Heat map of log2 fold-change relative to the unstimulated condition of the 90 acetylation sites quantified. Colored bars at the right indicate the clusters. <b>B.</b> Comparison of acetylation dynamics on GAPDH. <b>C.</b> Comparison of acetylation dynamics on histone H4, Lys⁶ and Lys⁹. <b>D.</b> EGF-stimulated Histone H3 Lys¹⁴ acetylation dynamics analyzed by mass spectrometry and western blotting. <b>E.</b> Acetylation dynamics quantified by SILAC on GAPDH Lys¹⁹⁴. <b>F.</b> Acetylation dynamics quantified by SILAC on GAPDH Lys²⁶³.</p

Quantitative phosphotyrosine profiling of A549 cells treated with the lysine deacetylase inhibitor, TSA, with or without EGF stimulation.

<p><b>A.</b> The four phosphotyrosine sites significantly (<i>p<0</i>.<i>05</i>) differentially phosphorylated between A549 cells treated with TSA or DMSO. Average phosphorylation +/- standard error are shown. <b>B.</b> The fold change ratio in response to TSA treatment mapped to a visual representation of proteins involved in kinase signaling, scaffolding, and cell adhesion. Each circle represents a unique phosphorylation site identified on the protein. Sites are color coded to characterize the relative effect of TSA pre-treatment on the EGF response. Proteins are labeled by their gene name. A larger version of the figure with labeled phosphorylation sites is available in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126242#pone.0126242.s007" target="_blank">S7 Fig</a>.</p

Global Phosphoproteome of HT-29 Human Colon Adenocarcinoma Cells

Phosphorylation events in cellular signaling cascades triggered by a variety of cellular stimuli modulate protein function, leading to diverse cellular outcomes including cell division, growth, death, and differentiation. Abnormal regulation of protein phosphorylation due to mutation or overexpression of signaling proteins often results in various disease states. We provide here a list of protein phosphorylation sites identified from HT-29 human colon adenocarcinoma cell line by immobilized metal affinity chromatography (IMAC) combined with liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis. In this study, proteins extracted from HT-29 whole cell lysates were digested with trypsin and carboxylate groups on the resulting peptides were converted to methyl esters. Derivatized phosphorylated peptides were enriched using Fe3+-chelated metal affinity resin. Phosphopeptides retained by IMAC were separated by high performance liquid chromatography (HPLC) and analyzed by electrospray ionization-quadrupole-time-of-flight (ESI-Q-TOF) mass spectrometry. We identified 238 phosphorylation sites, 213 of which could be conclusively localized to a single residue, from 116 proteins by searching MS/MS spectra against the human protein database using MASCOT. Peptide identification and phosphorylation site assignment were confirmed by manual inspection of the MS/MS spectra. Many of the phosphorylation sites identified in our results have not been described previously in the scientific literature. We attempted to ascribe functionality to the sites identified in this work by searching for potential kinase motifs with Scansite (http://scansite.mit.edu) and obtaining information on kinase substrate selectivity from Pattern Explorer (http://scansite.mit.edu/pe). The list of protein phosphorylation sites identified in the present experiment provides broad information on phosphorylated proteins under normal (asynchronous) cell culture conditions. Sites identified in this study may be utilized as surrogate bio-markers to assess the activity of selected kinases and signaling pathways from different cell states and exogenous stimuli. Keywords: phosphoproteome • IMAC • HT-29 • scansite • pattern explore

Phosphotyrosine Profiling of NSCLC Cells in Response to EGF and HGF Reveals Network Specific Mediators of Invasion

Growth factor signaling is deregulated in cancer and often leads to invasion, yet receptor tyrosine kinase signaling pathways driving invasion under different growth factor conditions are not well understood. To identify specific signaling molecules regulating invasion of A549 non-small cell lung carcinoma (NSCLC) cells downstream of the epidermal growth factor receptor (EGFR) and Met, quantitative site-specific mass spectrometric analysis of tyrosine phosphorylation was performed following epidermal growth factor (EGF) or hepatocyte growth factor (HGF) stimulation, at three different growth factor concentrations and at two time points. Through this analysis, the temporal and concentration dependent phosphorylation profiles were obtained for 131 and 139 sites downstream of EGF and HGF stimulation, respectively. To characterize the effect of these signaling network alterations, we quantified 3D cell migration/invasion through Matrigel. Partial least-squares regression (PLSR) analysis was performed to identify the tyrosine phosphorylation sites most strongly correlated with EGF and/or HGF mediated invasion. Potential common and specific signaling events required for driving invasion downstream of EGFR and Met were identified using either a combined or two independent PLSR models, based on the quantitative EGF or HGF data. Our data highlight the integration and compartmentalization of signaling required for invasion in cancer

Phosphotyrosine Profiling of NSCLC Cells in Response to EGF and HGF Reveals Network Specific Mediators of Invasion

Growth factor signaling is deregulated in cancer and often leads to invasion, yet receptor tyrosine kinase signaling pathways driving invasion under different growth factor conditions are not well understood. To identify specific signaling molecules regulating invasion of A549 non-small cell lung carcinoma (NSCLC) cells downstream of the epidermal growth factor receptor (EGFR) and Met, quantitative site-specific mass spectrometric analysis of tyrosine phosphorylation was performed following epidermal growth factor (EGF) or hepatocyte growth factor (HGF) stimulation, at three different growth factor concentrations and at two time points. Through this analysis, the temporal and concentration dependent phosphorylation profiles were obtained for 131 and 139 sites downstream of EGF and HGF stimulation, respectively. To characterize the effect of these signaling network alterations, we quantified 3D cell migration/invasion through Matrigel. Partial least-squares regression (PLSR) analysis was performed to identify the tyrosine phosphorylation sites most strongly correlated with EGF and/or HGF mediated invasion. Potential common and specific signaling events required for driving invasion downstream of EGFR and Met were identified using either a combined or two independent PLSR models, based on the quantitative EGF or HGF data. Our data highlight the integration and compartmentalization of signaling required for invasion in cancer