Analytical Characterization for Similarity Assessment Between an Aflibercept Biosimilar SB15 and Reference Product (Eylea®).

INTRODUCTION: SB15 is a proposed biosimilar product of reference aflibercept (Eylea®), an approved biological drug product for retinal diseases including neovascular age-related macular degeneration (nAMD). This study aimed to assess the analytical similarity between SB15 and its commercially available reference product (RP) sourced from the United States (US-aflibercept) and European Union (EU-aflibercept) in terms of structural, physicochemical, and biological properties. METHODS: A panel of state-of-the-art analytical methods was used for the comprehensive characterization of SB15 and US/EU-aflibercept. In terms of the structural and physicochemical properties, primary structure; post-translational modifications (PTM); higher-order structure; purity and impurities; charge variants; and glycosylation were compared. In addition, biological characterization including mechanism of action (MoA)-related and Fc-related biological activities was conducted. RESULTS: Analytical similarity between SB15 and US/EU-aflibercept was demonstrated. The primary and higher-order structure of SB15 was confirmed to be comparable to that of US/EU-aflibercept. In addition, there were no meaningful differences in the physicochemical properties in terms of size and charge heterogeneity between SB15 and its RP. SB15 and RP were similar in biological activities including MoA-related binding activities, potencies, and Fc-related biological functions. Consequently, SB15 was confirmed to be highly similar to US/EU-aflibercept. CONCLUSIONS: Based on a comprehensive analytical similarity assessment of structural, physicochemical, and biological properties, SB15 was demonstrated to be highly similar to US/EU-aflibercept RP, supporting safe and effective use of SB15.

Proteogenomic landscape of human pancreatic ductal adenocarcinoma in an Asian population reveals tumor cell-enriched and immune-rich subtypes.

We report a proteogenomic analysis of pancreatic ductal adenocarcinoma (PDAC). Mutation-phosphorylation correlations identified signaling pathways associated with somatic mutations in significantly mutated genes. Messenger RNA-protein abundance correlations revealed potential prognostic biomarkers correlated with patient survival. Integrated clustering of mRNA, protein and phosphorylation data identified six PDAC subtypes. Cellular pathways represented by mRNA and protein signatures, defining the subtypes and compositions of cell types in the subtypes, characterized them as classical progenitor (TS1), squamous (TS2-4), immunogenic progenitor (IS1) and exocrine-like (IS2) subtypes. Compared with the mRNA data, protein and phosphorylation data further classified the squamous subtypes into activated stroma-enriched (TS2), invasive (TS3) and invasive-proliferative (TS4) squamous subtypes. Orthotopic mouse PDAC models revealed a higher number of pro-tumorigenic immune cells in TS4, inhibiting T cell proliferation. Our proteogenomic analysis provides significantly mutated genes/biomarkers, cellular pathways and cell types as potential therapeutic targets to improve stratification of patients with PDAC.

Label-Free Quantitative Proteome Profiling of Cerebrospinal Fluid from a Rat Stroke Model with Stem Cell Therapy.

Human adipose-derived mesenchymal stem cells (hAMSCs) are capable of immunomodulation and regeneration after neural injury. For these reasons, hAMSCs have been investigated as a promising stem cell candidate for stroke treatment. However, noninvasive experiments studying the effects of grafted stem cells in the host brain have not yet been reported. Cerebrospinal fluid (CSF), which can be collected without sacrificing the subject, is involved in physiological control of the brain and reflects the pathophysiology of various neurological disorders of the central nervous system (CNS). Following stem cell transplantation in a stroke model, quantitative analysis of CSF proteome changes can potentially reveal the therapeutic effect of stem cells on the host CNS. We examined hAMSC-secreted proteins obtained from serum-free culture medium by liquid chromatography-tandem mass spectrometry (LC-MS/MS), which identified several extracellular matrix proteins, supporting the well-known active paracrine function of hAMSCs. Subsequently, we performed label-free quantitative proteomic analysis on CSF samples from rat stroke models intravenously injected with hAMSC (experimental) or phosphate buffered saline (control). In total, 524 proteins were identified; among them, 125 and 91 proteins were increased and decreased with hAMSC treatment, respectively. Furthermore, gene set enrichment analysis revealed three proteins, 14-3-3 theta, MAG, and neurocan, that showed significant increases in the hAMSC-treated model; these proteins are core members of neurotrophin signaling, nerve growth factor (NGF) signaling, and glycosaminoglycan metabolism, respectively. Subsequent histological and neurologic function experiments validated proliferative neurogenesis in the hAMSC-treated stroke model. We conclude that (i) intravenous injection of hAMSCs can induce neurologic recovery in a rat stroke model and (ii) CSF may reflect the therapeutic effect of hAMSCs. Additionally, proteins as 14-3-3 theta, MAG, and neurocan could be considered as potential CSF biomarkers of neuroregeneration. These CSF proteome profiling results would be utilized as valuable resource in further stroke studies.

Blockers of Wnt3a, Wnt10a, or ß-Catenin Prevent Chemotherapy-Induced Neuropathic Pain In Vivo.

Although chemotherapy is a key cancer treatment, many chemotherapeutic drugs produce chronic neuropathic pain, called chemotherapy-induced neuropathic pain (CINP), which is a dose-limiting adverse effect. To date, there is no medicine that prevents CINP in cancer patients and survivors. We determined whether blockers of the canonical Wnt signaling pathway prevent CINP. Neuropathic pain was induced by intraperitoneal injection of paclitaxel (PAC) on four alternate days in male Sprague-Dawley rats or male Axin2-LacZ knock-in mice. XAV-939, LGK-974, and iCRT14, Wnt/ß-catenin blockers, were administered intraperitoneally as a single or multiple doses before or after injury. Mechanical allodynia, phosphoproteome profiling, Wnt ligands, and inflammatory mediators were measured by von Frey filament, phosphoproteomics, reverse transcription-polymerase chain reaction, and Western blot analysis. Localization of ß-catenin was determined by immunohistochemical analysis in the dorsal root ganglia (DRGs) in rats and human. Our phosphoproteome profiling of CINP rats revealed significant phosphorylation changes in Wnt signaling components. Importantly, repeated systemic injections of XAV-939 or LGK-974 prevented the development of CINP in rats. In addition, XAV-939, LGK-974, and iCRT14 ameliorated CINP. PAC increased Wnt3a and Wnt10a, activated ß-catenin in DRG, and increased monocyte chemoattractant protein-1 and interleukin-1ß in DRG. PAC also upregulated rAxin2 in mice. Furthermore, ß-catenin was expressed in neurons, including calcitonin gene-related protein-expressing neurons and satellite cells in rat and human DRG. In conclusion, chemotherapy increases Wnt3a, Wnt10a, and ß-catenin in DRG and their pharmacological blockers prevent and ameliorate CINP, suggesting a target for the prevention and treatment of CINP.

Prognostic plasma protein panel for Aß deposition in the brain in Alzheimer's disease.

Alzheimer's disease (AD) is the most common age-associated dementia. Many studies have sought to predict cerebral amyloid deposition, the major pathological hallmark of AD, using body fluids such as blood or cerebral spinal fluid (CSF). The use of blood in diagnostic procedures is widespread in medicine; however, existing blood biomarkers for AD remain unreliable. We sought to discover blood biomarkers that discriminate Aß deposition status in the brain. This study used 107 individuals who were cognitively normal (CN), 107 patients with mild cognitive impairment (MCI), and 40 AD patients with Pittsburg compound B positron emission tomography (PiB-PET) amyloid imaging data available. We found five plasma biomarker candidates via mass spectrometry (MS) based-proteomic analysis and validated these proteins using enzyme-linked immunosorbent assay (ELISA). Our integrated models were highly predictive of brain amyloid deposition, exhibiting 0.871 accuracy with 79% sensitivity and 84% specificity overall, and 0.836 accuracy with 68% sensitivity and 90% specificity in patients with MCI. These results indicated that a combination of proteomic-based blood proteins might be a possible biomarker set for predicting cerebral amyloid deposition.

Proteogenomic Characterization of Human Early-Onset Gastric Cancer.

We report proteogenomic analysis of diffuse gastric cancers (GCs) in young populations. Phosphoproteome data elucidated signaling pathways associated with somatic mutations based on mutation-phosphorylation correlations. Moreover, correlations between mRNA and protein abundances provided potential oncogenes and tumor suppressors associated with patient survival. Furthermore, integrated clustering of mRNA, protein, phosphorylation, and N-glycosylation data identified four subtypes of diffuse GCs. Distinguishing these subtypes was possible by proteomic data. Four subtypes were associated with proliferation, immune response, metabolism, and invasion, respectively; and associations of the subtypes with immune- and invasion-related pathways were identified mainly by phosphorylation and N-glycosylation data. Therefore, our proteogenomic analysis provides additional information beyond genomic analyses, which can improve understanding of cancer biology and patient stratification in diffuse GCs.

Efficient Exploitation of Separation Space in Two-Dimensional Liquid Chromatography System for Comprehensive and Efficient Proteomic Analyses.

Proteomics aims to achieve complete profiling of the protein content and protein modifications in cells, tissues, and biofluids and to quantitatively determine changes in their abundances. This information serves to elucidate cellular processes and signaling pathways and to identify candidate protein biomarkers and/or therapeutic targets. Analyses must therefore be both comprehensive and efficient. Here, we present a novel online two-dimensional reverse-phase/reverse-phase liquid chromatography separation platform, which is based on a newly developed online noncontiguous fractionating and concatenating device (NCFC fractionator). In bottom-up proteomics analyses of a complex proteome, this system provided significantly improved exploitation of the separation space of the two RPs, considerably increasing the numbers of peptides identified compared to a contiguous 2D-RP/RPLC method. The fully automated online 2D-NCFC-RP/RPLC system bypassed a number of labor-intensive manual processes required with the previously described offline 2D-NCFC RP/RPLC method, and thus, it offers minimal sample loss in a context of highly reproducible 2D-RP/RPLC experiments.

Comprehensive Proteome Profiling of Platelet Identified a Protein Profile Predictive of Responses to An Antiplatelet Agent Sarpogrelate.

Sarpogrelate is an antiplatelet agent widely used to treat arterial occlusive diseases. Evaluation of platelet aggregation is essential to monitor therapeutic effects of sarpogrelate. Currently, no molecular signatures are available to evaluate platelet aggregation. Here, we performed comprehensive proteome profiling of platelets collected from 18 subjects before and after sarpogrelate administration using LC-MS/MS analysis coupled with extensive fractionation. Of 5423 proteins detected, we identified 499 proteins affected by sarpogrelate and found that they strongly represented cellular processes related to platelet activation and aggregation, including cell activation, coagulation, and vesicle-mediated transports. Based on the network model of the proteins involved in these processes, we selected three proteins (cut-like homeobox 1; coagulation factor XIII, B polypeptide; and peptidylprolyl isomerase D) that reflect the platelet aggregation-related processes after confirming their alterations by sarpogrelate in independent samples using Western blotting. Our proteomic approach provided a protein profile predictive of therapeutic effects of sarpogrelate.

Integrated analysis of global proteome, phosphoproteome, and glycoproteome enables complementary interpretation of disease-related protein networks.

Multi-dimensional proteomic analyses provide different layers of protein information, including protein abundance and post-translational modifications. Here, we report an integrated analysis of protein expression, phosphorylation, and N-glycosylation by serial enrichments of phosphorylation and N-glycosylation (SEPG) from the same tissue samples. On average, the SEPG identified 142,106 unmodified peptides of 8,625 protein groups, 18,846 phosphopeptides (15,647 phosphosites), and 4,019 N-glycopeptides (2,634 N-glycosites) in tumor and adjacent normal tissues from three gastric cancer patients. The combined analysis of these data showed that the integrated analysis additively improved the coverages of gastric cancer-related protein networks; phosphoproteome and N-glycoproteome captured predominantly low abundant signal proteins, and membranous or secreted proteins, respectively, while global proteome provided abundances for general population of the proteome. Therefore, our results demonstrate that the SEPG can serve as an effective approach for multi-dimensional proteome analyses, and the holistic profiles of protein expression and PTMs enabled improved interpretation of disease-related networks by providing complementary information.

A simple dual online ultra-high pressure liquid chromatography system (sDO-UHPLC) for high throughput proteome analysis.

We report a new and simple design of a fully automated dual-online ultra-high pressure liquid chromatography system. The system employs only two nano-volume switching valves (a two-position four port valve and a two-position ten port valve) that direct solvent flows from two binary nano-pumps for parallel operation of two analytical columns and two solid phase extraction (SPE) columns. Despite the simple design, the sDO-UHPLC offers many advantageous features that include high duty cycle, back flushing sample injection for fast and narrow zone sample injection, online desalting, high separation resolution and high intra/inter-column reproducibility. This system was applied to analyze proteome samples not only in high throughput deep proteome profiling experiments but also in high throughput MRM experiments.

Estimating influence of cofragmentation on peptide quantification and identification in iTRAQ experiments by simulating multiplexed spectra.

Isobaric tag-based quantification such as iTRAQ and TMT is a promising approach to mass spectrometry-based quantification in proteomics as it provides wide proteome coverage with greatly increased experimental throughput. However, it is known to suffer from inaccurate quantification and identification of a target peptide due to cofragmentation of multiple peptides, which likely leads to under-estimation of differentially expressed peptides (DEPs). A simple method of filtering out cofragmented spectra with less than 100% precursor isolation purity (PIP) would decrease the coverage of iTRAQ/TMT experiments. In order to estimate the impact of cofragmentation on quantification and identification of iTRAQ-labeled peptide samples, we generated multiplexed spectra with varying degrees of PIP by mixing the two MS/MS spectra of 100% PIP obtained in global proteome profiling experiments on gastric tumor-normal tissue pair proteomes labeled by 4-plex iTRAQ. Despite cofragmentation, the simulation experiments showed that more than 99% of multiplexed spectra with PIP greater than 80% were correctly identified by three different database search engines-MODa, MS-GF+, and Proteome Discoverer. Using the multiplexed spectra that have been correctly identified, we estimated the effect of cofragmentation on peptide quantification. In 74% of the multiplexed spectra, however, the cancer-to-normal expression ratio was compressed, and a fair number of spectra showed the "ratio inflation" phenomenon. On the basis of the estimated distribution of distortions on quantification, we were able to calculate cutoff values for DEP detection from cofragmented spectra, which were corrected according to a specific PIP and probability of type I (or type II) error. When we applied these corrected cutoff values to real cofragmented spectra with PIP larger than or equal to 70%, we were able to identify reliable DEPs by removing about 25% of DEPs, which are highly likely to be false positives. Our experimental results provide useful insight into the effect of cofragmentation on isobaric tag-based quantification methods. The simulation procedure as well as the corrected cutoff calculation method could be adopted for quantifying the effect of cofragmentation and reducing false positives (or false negatives) in the DEP identification with general quantification experiments based on isobaric labeling techniques.

A fully automated dual-online multifunctional ultrahigh pressure liquid chromatography system for high-throughput proteomics analysis.

A fully automated dual-online multifunctional ultrahigh pressure liquid chromatography (DO-MULTI-UPLC) system has been developed for high throughput proteome analyses of complex peptide mixtures. The system employs two online solid phase extraction (SPE) columns (150µm inner diameter×3cm), two capillary reverse phase (RP) columns (75µm×100cm) and a strong cation exchange (SCX) column (150µm×15cm) on a single system utilizing one binary pump and one isocratic pump. With the automated operation of six switching valves, the selection of LC experiments between single-dimensional RPLC and online two-dimensional SCX/RPLC were achieved automatically, without manual intervention, while two RPLC columns were used independently and alternatively. By essentially removing the dead time for column equilibration between experiments, in either 1D mode or 2D experimental mode, the current system was demonstrated to increase the experimental throughput by about two folds, while keeping the inter-column reproducibility of peptide elution time in less than 1% of gradient time. The advantageous features of the proposed system were demonstrated by its application to proteome samples of varying complexities.

Fully automated multifunctional ultrahigh pressure liquid chromatography system for advanced proteome analyses.

A multifunctional liquid chromatography system that performs 1-dimensional, 2-dimensional (strong cation exchange/reverse phase liquid chromatography or SCX/RPLC) separations and online phosphopeptide enrichment using a single binary nanoflow pump has been developed. With a simple operation of a function selection valve equipped with a SCX column and a TiO2 (titanium dioxide) column, a fully automated selection of three different experiment modes was achieved. Because the current system uses essentially the same solvent flow paths, the same trap column, and the same separation column for reverse-phase separation of 1D, 2D, and online phosphopeptides enrichment experiments, the elution time information obtained from these experiments is in excellent agreement, which facilitates correlating peptide information from different experiments. The final reverse-phase separation of the three experiments is completely decoupled from all of the function selection processes; thereby salts or acids from SCX or TiO2 column do not affect the efficiency of the reverse-phase separation.