Proteogenomic characterization of pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer with poor patient survival. Toward understanding the underlying molecular alterations that drive PDAC oncogenesis, we conducted comprehensive proteogenomic analysis of 140 pancreatic cancers, 67 normal adjacent tissues, and 9 normal pancreatic ductal tissues. Proteomic, phosphoproteomic, and glycoproteomic analyses were used to characterize proteins and their modifications. In addition, whole-genome sequencing, whole-exome sequencing, methylation, RNA sequencing (RNA-seq), and microRNA sequencing (miRNA-seq) were performed on the same tissues to facilitate an integrated proteogenomic analysis and determine the impact of genomic alterations on protein expression, signaling pathways, and post-translational modifications. To ensure robust downstream analyses, tumor neoplastic cellularity was assessed via multiple orthogonal strategies using molecular features and verified via pathological estimation of tumor cellularity based on histological review. This integrated proteogenomic characterization of PDAC will serve as a valuable resource for the community, paving the way for early detection and identification of novel therapeutic targets.

Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

To elucidate the deregulated functional modules that drive clear cell renal cell carcinoma (ccRCC), we performed comprehensive genomic, epigenomic, transcriptomic, proteomic, and phosphoproteomic characterization of treatment-naive ccRCC and paired normal adjacent tissue samples. Genomic analyses identified a distinct molecular subgroup associated with genomic instability. Integration of proteogenomic measurements uniquely identified protein dysregulation of cellular mechanisms impacted by genomic alterations, including oxidative phosphorylation-related metabolism, protein translation processes, and phospho-signaling modules. To assess the degree of immune infiltration in individual tumors, we identified microenvironment cell signatures that delineated four immune-based ccRCC subtypes characterized by distinct cellular pathways. This study reports a large-scale proteogenomic analysis of ccRCC to discern the functional impact of genomic alterations and provides evidence for rational treatment selection stemming from ccRCC pathobiology.

MS-PyCloud: A Cloud Computing-Based Pipeline for Proteomic and Glycoproteomic Data Analyses.

Rapid development and wide adoption of mass spectrometry-based glycoproteomic technologies have empowered scientists to study proteins and protein glycosylation in complex samples on a large scale. This progress has also created unprecedented challenges for individual laboratories to store, manage, and analyze proteomic and glycoproteomic data, both in the cost for proprietary software and high-performance computing and in the long processing time that discourages on-the-fly changes of data processing settings required in explorative and discovery analysis. We developed an open-source, cloud computing-based pipeline, MS-PyCloud, with graphical user interface (GUI), for proteomic and glycoproteomic data analysis. The major components of this pipeline include data file integrity validation, MS/MS database search for spectral assignments to peptide sequences, false discovery rate estimation, protein inference, quantitation of global protein levels, and specific glycan-modified glycopeptides as well as other modification-specific peptides such as phosphorylation, acetylation, and ubiquitination. To ensure the transparency and reproducibility of data analysis, MS-PyCloud includes open-source software tools with comprehensive testing and versioning for spectrum assignments. Leveraging public cloud computing infrastructure via Amazon Web Services (AWS), MS-PyCloud scales seamlessly based on analysis demand to achieve fast and efficient performance. Application of the pipeline to the analysis of large-scale LC-MS/MS data sets demonstrated the effectiveness and high performance of MS-PyCloud. The software can be downloaded at https://github.com/huizhanglab-jhu/ms-pycloud.

Community evaluation of glycoproteomics informatics solutions reveals high-performance search strategies for serum glycopeptide analysis.

Glycoproteomics is a powerful yet analytically challenging research tool. Software packages aiding the interpretation of complex glycopeptide tandem mass spectra have appeared, but their relative performance remains untested. Conducted through the HUPO Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates solutions for system-wide glycopeptide analysis. The same mass spectrometrybased glycoproteomics datasets from human serum were shared with participants and the relative team performance for N- and O-glycopeptide data analysis was comprehensively established by orthogonal performance tests. Although the results were variable, several high-performance glycoproteomics informatics strategies were identified. Deep analysis of the data revealed key performance-associated search parameters and led to recommendations for improved 'high-coverage' and 'high-accuracy' glycoproteomics search solutions. This study concludes that diverse software packages for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies and specifies key variables that will guide future software developments and assist informatics decision-making in glycoproteomics.

Deep eutectic solvent self-assembled reverse nanomicelles for transdermal delivery of sparingly soluble drugs.

BACKGROUND: Transdermal delivery of sparingly soluble drugs is challenging due to their low solubility and poor permeability. Deep eutectic solvent (DES)/or ionic liquid (IL)-mediated nanocarriers are attracting increasing attention. However, most of them require the addition of auxiliary materials (such as surfactants or organic solvents) to maintain the stability of formulations, which may cause skin irritation and potential toxicity. RESULTS: We fabricated an amphiphilic DES using natural oxymatrine and lauric acid and constructed a novel self-assembled reverse nanomicelle system (DES-RM) based on the features of this DES. Synthesized DESs showed the broad liquid window and significantly solubilized a series of sparingly soluble drugs, and quantitative structure-activity relationship (QSAR) models with good prediction ability were further built. The experimental and molecular dynamics simulation elucidated that the self-assembly of DES-RM was adjusted by noncovalent intermolecular forces. Choosing triamcinolone acetonide (TA) as a model drug, the skin penetration studies revealed that DES-RM significantly enhanced TA penetration and retention in comparison with their corresponding DES and oil. Furthermore, in vivo animal experiments demonstrated that TA@DES-RM exhibited good anti-psoriasis therapeutic efficacy as well as biocompatibility. CONCLUSIONS: The present study offers innovative insights into the optimal design of micellar nanodelivery system based on DES combining experiments and computational simulations and provides a promising strategy for developing efficient transdermal delivery systems for sparingly soluble drugs.

Characterization of In Vivo Protein Complexes via Chemical Cross-Linking and Mass Spectrometry.

Cells perform various functions by proteins via protein complexes. Characterization of protein complexes is critical to understanding their biological and clinical significance and has been one of the major efforts of functional proteomics. To date, most protein complexes are characterized by the in vitro system from protein extracts after the cells or tissues are lysed, and it has been challenging to determine which of these protein complexes are formed in intact cells. Herein, we report an approach to preserve protein complexes using in vivo cross-linking, followed by size exclusion chromatography and data-independent acquisition mass spectrometry. This approach enables the characterization of in vivo protein complexes from cells or tissues, which allows the determination of protein complexes in clinical research. More importantly, the described approach can identify protein complexes that are not detected by the in vitro system, which provide unique protein function information.

Neoplastic cell enrichment of tumor tissues using coring and laser microdissection for proteomic and genomic analyses of pancreatic ductal adenocarcinoma.

BACKGROUND: The identification of differentially expressed tumor-associated proteins and genomic alterations driving neoplasia is critical in the development of clinical assays to detect cancers and forms the foundation for understanding cancer biology. One of the challenges in the analysis of pancreatic ductal adenocarcinoma (PDAC) is the low neoplastic cellularity and heterogeneous composition of bulk tumors. To enrich neoplastic cells from bulk tumor tissue, coring, and laser microdissection (LMD) sampling techniques have been employed. In this study, we assessed the protein and KRAS mutation changes associated with samples obtained by these enrichment techniques and evaluated the fraction of neoplastic cells in PDAC for proteomic and genomic analyses. METHODS: Three fresh frozen PDAC tumors and their tumor-matched normal adjacent tissues (NATs) were obtained from three sampling techniques using bulk, coring, and LMD; and analyzed by TMT-based quantitative proteomics. The protein profiles and characterizations of differentially expressed proteins in three sampling groups were determined. These three PDACs and samples of five additional PDACs obtained by the same three sampling techniques were also subjected to genomic analysis to characterize KRAS mutations. RESULTS: The neoplastic cellularity of eight PDACs ranged from less than 10% to over 80% based on morphological review. Distinctive proteomic patterns and abundances of certain tumor-associated proteins were revealed when comparing the tumors and NATs by different sampling techniques. Coring and bulk tissues had comparable proteome profiles, while LMD samples had the most distinct proteome composition compared to bulk tissues. Further genomic analysis of bulk, cored, or LMD samples demonstrated that KRAS mutations were significantly enriched in LMD samples while coring was less effective in enriching for KRAS mutations when bulk tissues contained a relatively low neoplastic cellularity. CONCLUSIONS: In addition to bulk tissues, samples from LMD and coring techniques can be used for proteogenomic studies. The greatest enrichment of neoplastic cellularity is obtained with the LMD technique.

Data-Independent Acquisition-Based Mass Spectrometry (DIA-MS) for Quantitative Analysis of Intact N-Linked Glycopeptides.

N-linked protein glycosylation is a key regulator in various biological functions. Previous studies have shown that aberrant glycosylation is associated with many diseases. Therefore, it is essential to elucidate protein modifications of glycosylation by quantitatively profiling intact N-linked glycopeptides. Data-independent acquisition (DIA) mass spectrometry (MS) is a cost-effective, flexible, and high-throughput method for global proteomics. However, substantial challenges are still present in the quantitative analysis of intact glycopeptides with high accuracy at high throughput. In this study, we have established a novel integrated platform for the DIA analysis of intact glycopeptides isolated from complex samples. The established analysis platform utilizes a well-designed DIA-MS method for raw data collection, a spectral library constructed specifically for intact glycopeptide quantification providing accurate results by the inclusion of Y ions for quantification and filtering of quantified intact glycopeptides with low-quality MS2 spectra automatically using a set of criteria. Intact glycopeptides isolated from human serum were used to evaluate the performance of the integrated platform. By utilizing 100 isolation windows for DIA data acquisition, a well-constructed human serum spectral library containing 1123 nonredundant intact glycopeptides with Y ions, and automated data inspection, 620 intact glycopeptides were quantified with high confidence from DIA-MS. In summary, our integrated platform can serve as a reliable quantitative tool for characterizing intact glycopeptides isolated from complex biological samples to assist our understanding of biological functions of N-linked glycosylation.

OmicsOne: associate omics data with phenotypes in one-click.

BACKGROUND: The rapid advancements of high throughput "omics" technologies have brought a massive amount of data to process during and after experiments. Multi-omic analysis facilitates a deeper interrogation of a dataset and the discovery of interesting genes, proteins, lipids, glycans, metabolites, or pathways related to the corresponding phenotypes in a study. Many individual software tools have been developed for data analysis and visualization. However, it still lacks an efficient way to investigate the phenotypes with multiple omics data. Here, we present OmicsOne as an interactive web-based framework for rapid phenotype association analysis of multi-omic data by integrating quality control, statistical analysis, and interactive data visualization on 'one-click'. MATERIALS AND METHODS: OmicsOne was applied on the previously published proteomic and glycoproteomic data sets of high-grade serous ovarian carcinoma (HGSOC) and the published proteome data set of lung squamous cell carcinoma (LSCC) to confirm its performance. The data was analyzed through six main functional modules implemented in OmicsOne: (1) phenotype profiling, (2) data preprocessing and quality control, (3) knowledge annotation, (4) phenotype associated features discovery, (5) correlation and regression model analysis for phenotype association analysis on individual features, and (6) enrichment analysis for phenotype association analysis on interested feature sets. RESULTS: We developed an integrated software solution, OmicsOne, for the phenotype association analysis on multi-omics data sets. The application of OmicsOne on the public data set of ovarian cancer data showed that the software could confirm the previous observations consistently and discover new evidence for HNRNPU and a glycopeptide of HYOU1 as potential biomarkers for HGSOC data sets. The performance of OmicsOne was further demonstrated in the Tumor and NAT comparison study on the proteome data set of LSCC. CONCLUSIONS: OmicsOne can effectively simplify data analysis and reveal the significant associations between phenotypes and potential biomarkers, including genes, proteins, and glycopeptides, in minutes to assist users to understand aberrant biological processes.

Impact of Increased FUT8 Expression on the Extracellular Vesicle Proteome in Prostate Cancer Cells.

Extracellular vesicles (EVs) are involved in intercellular communication, transporting proteins and nucleic acids to proximal and distal regions. There is evidence of glycosylation influencing protein routing into EVs; however, the impact of aberrant cellular glycotransferase expression on EV protein profiles has yet to be evaluated. In this study, we paired extracellular vesicle characterization and quantitative proteomics to determine the systemic impact of altered α(1,6)fucosyltranferase (FUT8) expression on prostate cancer-derived EVs. Our results showed that increased cellular expression of FUT8 could reduce the number of vesicles secreted by prostate cancer cells as well as increase the abundance of proteins associated with cell motility and prostate cancer metastasis. In addition, overexpression of FUT8 resulted in altered glycans on select EV-derived glycoproteins. This study presents the first evidence of altered cellular glycosylation impacting EV protein profiles and provides further rationale for exploring the functional role of glycosylation in EV biogenesis and biology.

Intact Glycopeptide Analysis of Influenza A/H1N1/09 Neuraminidase Revealing the Effects of Host and Glycosite Location on Site-Specific Glycan Structures.

Influenza H1N1 virus has posed a serious threat to human health. The glycosylation of neuraminidase (NA) could affect the infectivity and virulence of the influenza virus, but detailed site-specific glycosylation information of NA is still missing. In this study, intact glycopeptide analysis is performed on an influenza NA (A/H1N1/California/2009) that is expressed in human 293T and insect Hi-5 cells. The data indicate that three of four potential N-linked glycosylation sites are glycosylated, including one partial glycosylation site from both cell lines. The NA expressed in human cells has more complex glycans than that of insect cells, suggesting the importance of selecting an appropriate expression system for the production of functional glycoproteins. Different types of glycans are identified from different glycosites of NA expressed in human cells, which implies the site-dependence of glycosylation on NA. This study provides valuable information for the research of influenza virus as well as the functions of viral protein glycosylation.

Deciphering the Roles of N-Glycans on Collagen-Platelet Interactions.

Collagen is a potent agonist for platelet activation, presenting itself as a key contributor to coagulation via interactions with platelet glycoproteins. The fine details dictating platelet-collagen interactions are poorly understood. In particular, glycosylation could be a key determinant in the platelet-collagen interaction. Here, we report an affinity purification coupled to a mass spectrometry-based approach to elucidate the function of N-glycans in dictating platelet-collagen interactions. By integrative proteomic and glycoproteomic analysis of collagen-platelet interactive proteins with N-glycan manipulation, we demonstrate that the interaction of platelet adhesive receptors with collagen is highly N-glycan regulated, with glycans on many receptors playing positive roles in collagen binding, with glycans on other platelet glycoproteins exhibiting inhibitory roles on the binding to collagen. Our results significantly enhance our understanding of the details of glycans influencing the platelet-collagen interaction.

Simple Tip-Based Sample Processing Method for Urinary Proteomic Analysis.

Mass spectrometry-based urinary proteomics is one of the most attractive strategies to discover proteins for diagnosis, prognosis, monitoring, or prediction of therapeutic responses of urological diseases involving the kidney, prostate, and bladder; however, interfering compounds found in urine necessitate sample preparation strategies that are currently not suitable for urinary proteomics in the clinical setting. Herein, we describe the C4-tip method, comprising a simple, automated strategy utilizing a reverse-phase resin tip-based format and "on-tip" digestion to examine the urine proteome. We first determined the optimal conditions for protein isolation and protease digestion on the C4-tip using the standard protein bovine fetuin. Next, we applied the C4-tip method to urinary proteomics, identifying a total of 813 protein groups using LC-MS/MS, with identified proteins from the C4-tip method displaying a similar distribution of gene ontology (GO) cellular component assignments compared to identified proteins from an ultrafiltration preparation method. Finally, we assessed the reproducibility of the C4-tip method, revealing a high Spearman correlation R-value for shared proteins identified across all tips. Together, we have shown the C4-tip method to be a simple, robust method for high-throughput analysis of the urinary proteome by mass spectrometry in the clinical setting.

Mapping the O-glycoproteome using site-specific extraction of O-linked glycopeptides (EXoO).

Protein glycosylation is one of the most abundant post-translational modifications. However, detailed analysis of O-linked glycosylation, a major type of protein glycosylation, has been severely impeded by the scarcity of suitable methodologies. Here, a chemoenzymatic method is introduced for the site-specific extraction of O-linked glycopeptides (EXoO), which enabled the mapping of over 3,000 O-linked glycosylation sites and definition of their glycans on over 1,000 proteins in human kidney tissues, T cells, and serum. This large-scale localization of O-linked glycosylation sites demonstrated that EXoO is an effective method for defining the site-specific O-linked glycoproteome in different types of sample. Detailed structural analysis of the sites identified revealed conserved motifs and topological orientations facing extracellular space, the cell surface, the lumen of the Golgi, and the endoplasmic reticulum (ER). EXoO was also able to reveal significant differences in the O-linked glycoproteome of tumor and normal kidney tissues pointing to its broader use in clinical diagnostics and therapeutics.

N-GlycositeAtlas: a database resource for mass spectrometry-based human N-linked glycoprotein and glycosylation site mapping.

BACKGROUND: N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. The large-scale characterization of N-linked glycoproteins accomplished by mass spectrometry-based glycoproteomics has provided valuable insights into the interdependence of glycoprotein structure and protein function. However, these studies focused mainly on the analysis of specific sample type, and lack the integration of glycoproteomic data from different tissues, body fluids or cell types. METHODS: In this study, we collected the human glycosite-containing peptides identified through their de-glycosylated forms by mass spectrometry from over 100 publications and unpublished datasets generated from our laboratory. A database resource termed N-GlycositeAtlas was created and further used for the distribution analyses of glycoproteins among different human cells, tissues and body fluids. Finally, a web interface of N-GlycositeAtlas was created to maximize the utility and value of the database. RESULTS: The N-GlycositeAtlas database contains more than 30,000 glycosite-containing peptides (representing > 14,000 N-glycosylation sites) from more than 7200 N-glycoproteins from different biological sources including human-derived tissues, body fluids and cell lines from over 100 studies. CONCLUSIONS: The entire human N-glycoproteome database as well as 22 sub-databases associated with individual tissues or body fluids can be downloaded from the N-GlycositeAtlas website at http://nglycositeatlas.biomarkercenter.org.

Mapping human N-linked glycoproteins and glycosylation sites using mass spectrometry.

N-linked glycoprotein is a highly interesting class of proteins for clinical and biological research. Over the last decade, large-scale profiling of N-linked glycoproteins and glycosylation sites from biological and clinical samples has been achieved through mass spectrometry-based glycoproteomic approaches. In this paper, we reviewed the human glycoproteomic profiles that have been reported in more than 80 individual studies, and mainly focused on the N-glycoproteins and glycosylation sites identified through their deglycosylated forms of glycosite-containing peptides. According to our analyses, more than 30,000 glycosite-containing peptides and 7,000 human glycoproteins have been identified from five different body fluids, twelve human tissues (or related cell lines), and four special cell types. As the glycoproteomic data is still missing for many organs and tissues, a systematical glycoproteomic analysis of various human tissues and body fluids using a uniform platform is still needed for an integrated map of human N-glycoproteomes.

Evaluation of NCI-7 Cell Line Panel as a Reference Material for Clinical Proteomics.

Reference materials are vital to benchmarking the reproducibility of clinical tests and essential for monitoring laboratory performance for clinical proteomics. The reference material utilized for mass spectrometric analysis of the human proteome would ideally contain enough proteins to be suitably representative of the human proteome, as well as exhibit a stable protein composition in different batches of sample regeneration. Previously, The Clinical Proteomic Tumor Analysis Consortium (CPTAC) utilized a PDX-derived comparative reference (CompRef) materials for the longitudinal assessment of proteomic performance; however, inherent drawbacks of PDX-derived material, including extended time needed to grow tumors and high level of expertise needed, have resulted in efforts to identify a new source of CompRef material. In this study, we examined the utility of using a panel of seven cancer cell lines, NCI-7 Cell Line Panel, as a reference material for mass spectrometric analysis of human proteome. Our results showed that not only is the NCI-7 material suitable for benchmarking laboratory sample preparation methods, but also NCI-7 sample generation is highly reproducible at both the global and phosphoprotein levels. In addition, the predicted genomic and experimental coverage of the NCI-7 proteome suggests the NCI-7 material may also have applications as a universal standard proteomic reference.

Reanalysis of Global Proteomic and Phosphoproteomic Data Identified a Large Number of Glycopeptides.

Protein glycosylation plays fundamental roles in many cellular processes, and previous reports have shown dysregulation to be associated with several human diseases, including diabetes, cancer, and neurodegenerative disorders. Despite the vital role of glycosylation for proper protein function, the analysis of glycoproteins has been lagged behind to other protein modifications. In this study, we describe the reanalysis of global proteomic data from breast cancer xenograft tissues using recently developed software package GPQuest 2.0, revealing a large number of previously unidentified N-linked glycopeptides. More importantly, we found that using immobilized metal affinity chromatography (IMAC) technology for the enrichment of phosphopeptides had coenriched a substantial number of sialoglycopeptides, allowing for a large-scale analysis of sialoglycopeptides in conjunction with the analysis of phosphopeptides. Collectively, combined tandem mass spectrometry (MS/MS) analyses of global proteomic and phosphoproteomic data sets resulted in the identification of 6 724 N-linked glycopeptides from 617 glycoproteins derived from two breast cancer xenograft tissues. Next, we utilized GPQuest 2.0 for the reanalysis of global and phosphoproteomic data generated from 108 human breast cancer tissues that were previously analyzed by Clinical Proteomic Analysis Consortium (CPTAC). Reanalysis of the CPTAC data set resulted in the identification of 2 683 glycopeptides from the global proteomic data set and 4 554 glycopeptides from phosphoproteomic data set, respectively. Together, 11 292 N-linked glycopeptides corresponding to 1 731 N-linked glycosites from 883 human glycoproteins were identified from the two data sets. This analysis revealed an extensive number of glycopeptides hidden in the global and enriched in IMAC-based phosphopeptide-enriched proteomic data, information which would have remained unknown from the original study otherwise. The reanalysis described herein can be readily applied to identify glycopeptides from already existing data sets, providing insight into many important facets of protein glycosylation in different biological, physiological, and pathological processes.