N-glycans from serum IgG and total serum glycoproteins specific for endometriosis.

Endometriosis is a chronic inflammatory gynaecological disease characterized by the growth of endometrial tissue outside the uterine cavity. There are currently no definitive non-invasive diagnostic tools. Glycosylation is the most common posttranslational modification of proteins and altered glycosylation has been found in many diseases, including chronic inflammatory conditions and cancer. Sialylation and galactosylation on serum IgG have previously been found to be altered in endometriosis and serum sialylation changed after Zoladex (Goserelin Acetate) therapy. Using IgG and whole serum glycoproteins, we investigated N-glycosylation in two clinical cohorts of women with and without endometriosis. PNGase F-digested serum samples were fluorescently labelled and N-glycans were profiled by ultra-performance liquid chromatography. Clinical data was collected to link glycomic findings with metabolic and hormonal profiles. Total serum glycoprotein and IgG glycosylation differed in patients with endometriosis compared to control cases. The most significantly altered was glycan peak 3 from IgG, containing bisected biantennary glycans, which was decreased in the endometriosis cohorts (p = 0.0000005-0.018). In conclusion, this is the first pilot study to identify changes in N-glycans from whole serum glycoproteins associated with endometriosis. A larger validation study is now warranted and such studies should include the follow-up of surgically and pharmacologically treated patients.

CHOmpact: A reduced metabolic model of Chinese hamster ovary cells with enhanced interpretability.

Metabolic modeling has emerged as a key tool for the characterization of biopharmaceutical cell culture processes. Metabolic models have also been instrumental in identifying genetic engineering targets and developing feeding strategies that optimize the growth and productivity of Chinese hamster ovary (CHO) cells. Despite their success, metabolic models of CHO cells still present considerable challenges. Genome-scale metabolic models (GeMs) of CHO cells are very large (>6000 reactions) and are difficult to constrain to yield physiologically consistent flux distributions. The large scale of GeMs also makes the interpretation of their outputs difficult. To address these challenges, we have developed CHOmpact, a reduced metabolic network that encompasses 101 metabolites linked through 144 reactions. Our compact reaction network allows us to deploy robust, nonlinear optimization and ensure that the computed flux distributions are physiologically consistent. Furthermore, our CHOmpact model delivers enhanced interpretability of simulation results and has allowed us to identify the mechanisms governing shifts in the anaplerotic consumption of asparagine and glutamate as well as an important mechanism of ammonia detoxification within mitochondria. CHOmpact, thus, addresses key challenges of large-scale metabolic models and will serve as a platform to develop dynamic metabolic models for the control and optimization of biopharmaceutical cell culture processes.

Glycosylation in Indolent, Significant and Aggressive Prostate Cancer by Automated High-Throughput N-Glycan Profiling.

The diagnosis and treatment of prostate cancer (PCa) is a major health-care concern worldwide. This cancer can manifest itself in many distinct forms and the transition from clinically indolent PCa to the more invasive aggressive form remains poorly understood. It is now universally accepted that glycan expression patterns change with the cellular modifications that accompany the onset of tumorigenesis. The aim of this study was to investigate if differential glycosylation patterns could distinguish between indolent, significant, and aggressive PCa. Whole serum N-glycan profiling was carried out on 117 prostate cancer patients' serum using our automated, high-throughput analysis platform for glycan-profiling which utilizes ultra-performance liquid chromatography (UPLC) to obtain high resolution separation of N-linked glycans released from the serum glycoproteins. We observed increases in hybrid, oligomannose, and biantennary digalactosylated monosialylated glycans (M5A1G1S1, M8, and A2G2S1), bisecting glycans (A2B, A2(6)BG1) and monoantennary glycans (A1), and decreases in triantennary trigalactosylated trisialylated glycans with and without core fucose (A3G3S3 and FA3G3S3) with PCa progression from indolent through significant and aggressive disease. These changes give us an insight into the disease pathogenesis and identify potential biomarkers for monitoring the PCa progression, however these need further confirmation studies.

A Robust and Versatile Automated Glycoanalytical Technology for Serum Antibodies and Acute Phase Proteins: Ovarian Cancer Case Study.

The direct association of the genome, transcriptome, metabolome, lipidome and proteome with the serum glycome has revealed systems of interconnected cellular pathways. The exact roles of individual glycoproteomes in the context of disease have yet to be elucidated. In a move toward personalized medicine, it is now becoming critical to understand disease pathogenesis, and the traits, stages, phenotypes and molecular features that accompany it, as the disruption of a whole system. To this end, we have developed an innovative technology on an automated platform, "GlycoSeqCap," which combines N-glycosylation data from six glycoproteins using a single source of human serum. Specifically, we multiplexed and optimized a successive serial capture and glycoanalysis of six purified glycoproteins, immunoglobulin G (IgG), immunoglobulin M (IgM), immunoglobulin A (IgA), transferrin (Trf), haptoglobin (Hpt) and alpha-1-antitrypsin (A1AT), from 50 µl of human serum. We provide the most comprehensive and in-depth glycan analysis of individual glycoproteins in a single source of human serum to date. To demonstrate the technological application in the context of a disease model, we performed a pilot study in an ovarian cancer cohort (n = 34) using discrimination and classification analyses to identify aberrant glycosylation. In our sample cohort, we exhibit improved selectivity and specificity over the currently used biomarker for ovarian cancer, CA125, for early stage ovarian cancer. This technology will establish a new state-of-the-art strategy for the characterization of individual serum glycoproteomes as a diagnostic and monitoring tool which represents a major step toward understanding the changes that take place during disease.

Small Molecule IL-36γ Antagonist as a Novel Therapeutic Approach for Plaque Psoriasis.

IL-36 cytokines are pro-inflammatory members of the IL-1 family that are upregulated in inflammatory disorders. Specifically, IL-36γ is highly expressed in active psoriatic lesions and can drive pro-inflammatory processes in 3D human skin equivalents supporting a role for this target in skin inflammation. Small molecule antagonists of interleukins have been historically challenging to generate. Nevertheless, we performed a small molecule high-throughput screen to identify IL-36 antagonists using a novel TR-FRET binding assay. Several compounds, including 2-oxypyrimidine containing structural analogs of the marketed endothelin receptor A antagonist Ambrisentan, were identified as hits from the screen. A-552 was identified as a the most potent antagonist of human IL-36γ, but not the closely related family member IL-36α, was capable of attenuating IL-36γ induced responses in mouse and human disease models. Additionally, x-ray crystallography studies identified key amino acid residues in the binding pocket present in human IL-36γ that are absent in human IL-36α. A-552 represents a first-in-class small molecule antagonist of IL-36 signaling that could be used as a chemical tool to further investigate the role of this pathway in inflammatory skin diseases such as psoriasis.

Circulating Markers of Inflammation Persist in Children and Adults With Giant Aneurysms After Kawasaki Disease.

BACKGROUND: The sequelae of Kawasaki disease (KD) vary widely with the greatest risk for future cardiovascular events among those who develop giant coronary artery aneurysms (CAA). We sought to define the molecular signature associated with different outcomes in pediatric and adult KD patients. METHODS: Molecular profiling was conducted using mass spectrometry-based shotgun proteomics, transcriptomics, and glycomics methods on 8 pediatric KD patients at the acute, subacute, and convalescent time points. Shotgun proteomics was performed on 9 KD adults with giant CAA and matched healthy controls. Plasma calprotectin was measured by ELISA in 28 pediatric KD patients 1 year post-KD, 70 adult KD patients, and 86 healthy adult volunteers. RESULTS: A characteristic molecular profile was seen in pediatric patients during the acute disease, which resolved at the subacute and convalescent periods in patients with no coronary artery sequelae but persisted in 2 patients who developed giant CAA. We, therefore, investigated persistence of inflammation in KD adults with giant CAA by shotgun proteomics that revealed a signature of active inflammation, immune regulation, and cell trafficking. Correlating results obtained using shotgun proteomics in the pediatric and adult KD cohorts identified elevated calprotectin levels in the plasma of patients with CAA. Investigation of expanded pediatric and adult KD cohorts revealed elevated levels of calprotectin in pediatric patients with giant CAA 1 year post-KD and in adult KD patients who developed giant CAA in childhood. CONCLUSIONS: Complex patterns of biomarkers of inflammation and cell trafficking can persist long after the acute phase of KD in patients with giant CAA. Elevated levels of plasma calprotectin months to decades after acute KD and infiltration of cells expressing S100A8 and A9 in vascular tissues suggest ongoing, subclinical inflammation. Calprotectin may serve as a biomarker to inform the management of KD patients following the acute illness.

Integrating biomarkers across omic platforms: an approach to improve stratification of patients with indolent and aggressive prostate cancer.

Classifying indolent prostate cancer represents a significant clinical challenge. We investigated whether integrating data from different omic platforms could identify a biomarker panel with improved performance compared to individual platforms alone. DNA methylation, transcripts, protein and glycosylation biomarkers were assessed in a single cohort of patients treated by radical prostatectomy. Novel multiblock statistical data integration approaches were used to deal with missing data and modelled via stepwise multinomial logistic regression, or LASSO. After applying leave-one-out cross-validation to each model, the probabilistic predictions of disease type for each individual panel were aggregated to improve prediction accuracy using all available information for a given patient. Through assessment of three performance parameters of area under the curve (AUC) values, calibration and decision curve analysis, the study identified an integrated biomarker panel which predicts disease type with a high level of accuracy, with Multi AUC value of 0.91 (0.89, 0.94) and Ordinal C-Index (ORC) value of 0.94 (0.91, 0.96), which was significantly improved compared to the values for the clinical panel alone of 0.67 (0.62, 0.72) Multi AUC and 0.72 (0.67, 0.78) ORC. Biomarker integration across different omic platforms significantly improves prediction accuracy. We provide a novel multiplatform approach for the analysis, determination and performance assessment of novel panels which can be applied to other diseases. With further refinement and validation, this panel could form a tool to help inform appropriate treatment strategies impacting on patient outcome in early stage prostate cancer.

Plasma N-glycans in colorectal cancer risk.

Aberrant glycosylation has been associated with a number of diseases including cancer. Our aim was to elucidate changes in whole plasma N-glycosylation between colorectal cancer (CRC) cases and controls in one of the largest cohorts of its kind. A set of 633 CRC patients and 478 age and gender matched controls was analysed. Additionally, patients were stratified into four CRC stages. Moreover, N-glycan analysis was carried out in plasma of 40 patients collected prior to the initial diagnosis of CRC. Statistically significant differences were observed in the plasma N-glycome at all stages of CRC, this included a highly significant decrease in relation to the core fucosylated bi-antennary glycans F(6)A2G2 and F(6)A2G2S(6)1 (P < 0.0009). Stage 1 showed a unique biomarker signature compared to stages 2, 3 and 4. There were indications that at risk groups could be identified from the glycome (retrospective AUC = 0.77 and prospective AUC = 0.65). N-glycome biomarkers related to the pathogenic progress of the disease would be a considerable asset in a clinical setting and it could enable novel therapeutics to be developed to target the disease in patients at risk of progression.

Emerging Approaches for the Identification of Protein Targets of Small Molecules - A Practitioners' Perspective.

Small-molecule (SM) leads in the early drug discovery pipeline are progressed primarily based on potency against the intended target(s) and selectivity against a very narrow slice of the proteome. So, why is there a tendency to wait until SMs are matured before probing for a deeper mechanistic understanding? For one, there is a concern about the interpretation of complex -omic data outputs and the resources needed to test these hypotheses. However, with recent advances in broad endpoint profiling assays that have companion reference databases and refined technology integration strategies, we argue that data complexity can translate into meaningful decision-making. This same strategy can also prioritize phenotypic screening hits to increase the likelihood of accessing unprecedented target space. In this Perspective. we will highlight a cohesive process that supports SM hit prosecution, providing a data-driven rationale and a suite of methods for direct identification of SM targets driving relevant biological end points.

N-glycan signatures identified in tumor interstitial fluid and serum of breast cancer patients: association with tumor biology and clinical outcome.

Particular N-glycan structures are known to be associated with breast malignancies by coordinating various regulatory events within the tumor and corresponding microenvironment, thus implying that N-glycan patterns may be used for cancer stratification and as predictive or prognostic biomarkers. However, the association between N-glycans secreted by breast tumor and corresponding clinical relevance remain to be elucidated. We profiled N-glycans by HILIC UPLC across a discovery dataset composed of tumor interstitial fluids (TIF, n = 85), paired normal interstitial fluids (NIF, n = 54) and serum samples (n = 28) followed by independent evaluation, with the ultimate goal of identifying tumor-related N-glycan patterns in blood of patients with breast cancer. The segregation of N-linked oligosaccharides revealed 33 compositions, which exhibited differential abundances between TIF and NIF. TIFs were depleted of bisecting N-glycans, which are known to play essential roles in tumor suppression. An increased level of simple high mannose N-glycans in TIF strongly correlated with the presence of tumor infiltrating lymphocytes within tumor. At the same time, a low level of highly complex N-glycans in TIF inversely correlated with the presence of infiltrating lymphocytes within tumor. Survival analysis showed that patients exhibiting increased TIF abundance of GP24 had better outcomes, whereas low levels of GP10, GP23, GP38, and coreF were associated with poor prognosis. Levels of GP1, GP8, GP9, GP14, GP23, GP28, GP37, GP38, and coreF were significantly correlated between TIF and paired serum samples. Cross-validation analysis using an independent serum dataset supported the observed correlation between TIF and serum, for five of nine N-glycan groups: GP8, GP9, GP14, GP23, and coreF. Collectively, our results imply that profiling of N-glycans from proximal breast tumor fluids is a promising strategy for determining tumor-derived glyco-signature(s) in the blood. N-glycans structures validated in our study may serve as novel biomarkers to improve the diagnostic and prognostic stratification of patients with breast cancer.

LC/MS-based Intact IgG and Released Glycan Analysis for Bioprocessing Applications.

Robust plate based antibody glycan analysis platforms are urgently needed for biopharmaceutical development and manufacturing as well as for clinical biomarker research. A 96-well plate based workflow has been developed to analyze both intact IgG antibodies and released N-glycans using an Orbitrap Fusion Mass Spectrometer and an LC/MS method on the Waters UNIFI platform. Here, such a workflow including protein A purification, PNGaseF digestion, 2-AB labeling, and SPE clean-up is described. The measured IgG glycan profile is consistent with that obtained from non-plate based method and commercial kit and has the advantage of less hands-on time. Also the application of the workflow in cell culture monitoring and clonal selection work is demonstrated. Apart from checking the major glycan structure changes among clones, post translational modifications (PTMs) such as C-terminal lysine residue clipping and N-terminal pyroglutamic acid formation can also be deduced from the workflow.

Quantitative ligand and receptor binding studies reveal the mechanism of interleukin-36 (IL-36) pathway activation.

IL-36 cytokines signal through the IL-36 receptor (IL-36R) and a shared subunit, IL-1RAcP (IL-1 receptor accessory protein). The activation mechanism for the IL-36 pathway is proposed to be similar to that of IL-1 in that an IL-36R agonist (IL-36α, IL-36ß, or IL-36γ) forms a binary complex with IL-36R, which then recruits IL-1RAcP. Recent studies have shown that IL-36R interacts with IL-1RAcP even in the absence of an agonist. To elucidate the IL-36 activation mechanism, we considered all possible binding events for IL-36 ligands/receptors and examined these events in direct binding assays. Our results indicated that the agonists bind the IL-36R extracellular domain with micromolar affinity but do not detectably bind IL-1RAcP. Using surface plasmon resonance (SPR), we found that IL-1RAcP also does not bind IL-36R when no agonist is present. In the presence of IL-36α, however, IL-1RAcP bound IL-36R strongly. These results suggested that the main pathway to the IL-36R·IL-36α·IL-1RAcP ternary complex is through the IL-36R·IL-36α binary complex, which recruits IL-1RAcP. We could not measure the binding affinity of IL-36R to IL-1RAcP directly, so we engineered a fragment crystallizable-linked construct to induce IL-36R·IL-1RAcP heterodimerization and predicted the binding affinity during a complete thermodynamic cycle to be 74 µm The SPR analysis also indicated that the IL-36R antagonist IL-36Ra binds IL-36R with higher affinity and a much slower off rate than the IL-36R agonists, shedding light on IL-36 pathway inhibition. Our results reveal the landscape of IL-36 ligand and receptor interactions, improving our understanding of IL-36 pathway activation and inhibition.

Cell-Surface Receptor-Ligand Interaction Analysis with Homogeneous Time-Resolved FRET and Metabolic Glycan Engineering: Application to Transmembrane and GPI-Anchored Receptors.

Ligand-binding assays are the linchpin of drug discovery and medicinal chemistry. Cell-surface receptors and their ligands have traditionally been characterized by radioligand-binding assays, which have low temporal and spatial resolution and entail safety risks. Here, we report a powerful alternative (GlycoFRET), where terbium-labeled fluorescent reporters are irreversibly attached to receptors by metabolic glycan engineering. For the first time, we show time-resolved fluorescence resonance energy transfer between receptor glycans and fluorescently labeled ligands. We describe GlycoFRET for a GPI-anchored receptor, a G-protein-coupled receptor, and a heterodimeric cytokine receptor in living cells with excellent sensitivity and high signal-to-background ratios. In contrast to previously described methods, GlycoFRET does not require genetic engineering or antibodies to label receptors. Given that all cell-surface receptors are glycosylated, we expect that GlycoFRET can be generalized with applications in chemical biology and biotechnology, such as target engagement, receptor pharmacology, and high-throughput screening.

High-throughput characterization of the functional impact of IgG Fc glycan aberrancy in juvenile idiopathic arthritis.

Juvenile idiopathic arthritis (JIA) encompasses all forms of chronic idiopathic arthritis that arise before age 16. Previous studies have found JIA to be associated with lower Fc galactosylation of circulating IgG, but the overall spectrum of glycan changes and the net impact on IgG function are unknown. Using ultra performance liquid chromatography (UPLC), we compared IgG glycosylation in 54 subjects with recent-onset untreated JIA with 98 healthy pediatric controls, paired to biophysical profiling of affinity for 20 IgG receptors using a high-throughput multiplexed microsphere assay. Patients with JIA exhibited an increase in hypogalactosylated and hyposialylated IgG glycans, but no change in fucosylation or bisection, together with alteration in the spectrum of IgG ligand binding. Supervised machine learning demonstrated a robust capacity to discriminate JIA subjects from controls using either glycosylation or binding data. The binding signature was driven predominantly by enhanced affinity for Fc receptor like protein 5 (FcRL5), a noncanonical Fc receptor expressed on B cells. Affinity for FcRL5 correlated inversely with galactosylation and sialylation, a relationship confirmed through enzymatic manipulation. These results demonstrate the capacity of combined structural and biophysical IgG phenotyping to define the overall functional impact of IgG glycan changes and implicate FcRL5 as a potential cellular sensor of IgG glycosylation.

Serum N-glycome alterations in breast cancer during multimodal treatment and follow-up.

Using our recently developed high-throughput automated platform, N-glycans from all serum glycoproteins from patients with breast cancer were analysed at diagnosis, after neoadjuvant chemotherapy, surgery, radiotherapy and up to 3 years after surgery. Surprisingly, alterations in the serum N-glycome after chemotherapy were pro-inflammatory with an increase in glycan structures associated with cancer. Surgery, on the other hand, induced anti-inflammatory changes in the serum N-glycome, towards a noncancerous phenotype. At the time of first follow-up, glycosylation in patients with affected lymph nodes changed towards a malignant phenotype. C-reactive protein showed a different pattern, increasing after first line of neoadjuvant chemotherapy, then decreasing throughout treatment until 1 year after surgery. This may reflect a switch from acute to chronic inflammation, where chronic inflammation is reflected in the serum after the acute phase response subsides. In conclusion, we here present the first time-course serum N-glycome profiling of patients with breast cancer during and after treatment. We identify significant glycosylation changes with chemotherapy, surgery and follow-up, reflecting the host response to therapy and tumour removal.

Development of inverse electron demand Diels-Alder ligation and TR-FRET assays for the determination of ligand-protein target occupancy in live cells.

Determination of target engagement following drug administration under physiological conditions is essential for understanding clinical outcomes of therapeutic candidates. While the list of potential techniques that enable studies of target engagement is continuously expanding, identification of the best method to evaluate interactions between a ligand and its cellular binding partner(s) remains far from straightforward. We developed and compared the applicability of two label-based techniques; inverse electron demand Diels-Alder (IED-DA) ligation-based pull-down and TR-FRET assays for in-cell determination of target occupancy of c-Src kinase and p38-α kinase by the reversible inhibitor Dasatinib. Significantly, none of the assays required engineering proteins-of-interest. Moreover, cellular TR-FRET assay emerged as a very promising platform for the determination of target occupancy of specific protein in a high-throughput manner. Our studies suggest that both IED-DA assay and TR-FRET assay should be considered as methods of choice for the determination of target engagement of small molecule protein binders in live cells.

Advances in analytical methodologies to guide bioprocess engineering for bio-therapeutics.

This study was performed to monitor the glycoform distribution of a recombinant antibody fusion protein expressed in CHO cells over the course of fed-batch bioreactor runs using high-throughput methods to accurately determine the glycosylation status of the cell culture and its product. Three different bioreactors running similar conditions were analysed at the same five time-points using the advanced methods described here. N-glycans from cell and secreted glycoproteins from CHO cells were analysed by HILIC-UPLC and MS, and the total glycosylation (both N- and O-linked glycans) secreted from the CHO cells were analysed by lectin microarrays. Cell glycoproteins contained mostly high mannose type N-linked glycans with some complex glycans; sialic acid was α-(2,3)-linked, galactose ß-(1,4)-linked, with core fucose. Glycans attached to secreted glycoproteins were mostly complex with sialic acid α-(2,3)-linked, galactose ß-(1,4)-linked, with mostly core fucose. There were no significant differences noted among the bioreactors in either the cell pellets or supernatants using the HILIC-UPLC method and only minor differences at the early time-points of days 1 and 3 by the lectin microarray method. In comparing different time-points, significant decreases in sialylation and branching with time were observed for glycans attached to both cell and secreted glycoproteins. Additionally, there was a significant decrease over time in high mannose type N-glycans from the cell glycoproteins. A combination of the complementary methods HILIC-UPLC and lectin microarrays could provide a powerful and rapid HTP profiling tool capable of yielding qualitative and quantitative data for a defined biopharmaceutical process, which would allow valuable near 'real-time' monitoring of the biopharmaceutical product.

High-Throughput Analysis of the Plasma N-Glycome by UHPLC.

The understanding of glycosylation alterations in health and disease has evolved significantly and glycans are considered to be relevant biomarker candidates. High-throughput analytical technologies capable of generating high-quality, large-scale glycoprofiling data are in high demand. Here, we describe an automated sample preparation workflow and analysis of N-linked glycans from plasma samples using hydrophilic interaction liquid chromatography with fluorescence detection on an ultrahigh-performance liquid chromatography (UHPLC) instrument. Samples are prepared in 96-well plates and the workflow features rapid glycoprotein denaturation, enzymatic glycan release, glycan purification on solid-supported hydrazide, fluorescent labeling, and post-labeling cleanup with solid-phase extraction. The development of a novel approach for plasma N-glycan analysis and its implementation on a robotic platform significantly reduces the time required for sample preparation and minimizes technical variation. It is anticipated that the developed method will contribute to expanding high-throughput capabilities to analyze protein glycosylation.

Pregnancy-Associated Changes of IgG and Serum N-Glycosylation in Camel (Camelus dromedarius).

The dromedary camel (Camelus dromedarius) is an agriculturally important species of high economic value but of low reproductive efficiency. Serum and IgG N-glycosylation are affected by physiological and pathogenic changes and might therefore be a useful diagnostic tool in camel livestock management. This study presents the first comprehensive annotation of the N-glycome from dromedary camel serum as well as their single-domain and conventional antibodies and its subsequent application for camel pregnancy diagnostics. N-glycans were released by PNGaseF, labeled with 2-aminobenzamide (2-AB), and analyzed by hydrophilic interaction liquid chromatography with fluorescent detection (HILIC-UPLC-FLD), enzymatic sequencing and mass spectrometry (MS). The use of a high-throughput robotic platform for sample preparation allowed the rapid generation of glycomics data from pregnant (n = 8) and nonpregnant (n = 8) camels of the Majaheem and Wadha breed. IgG N-glycans dominate the glycan profile of camel serum and present a mixture of core-fucosylated and noncore-fucosylated N-glycans which can contain N-glycolylneuraminic and N-acetylneuraminic acid. Significant pregnancy-associated but breed-independent increases in galactosylation, core-fucosylation, sialylation, and decreases in serum O-acetylation were observed. The monitoring of IgG and serum N-glycosylation presents an attractive complementary test for camel pregnancy diagnostics and presents an interesting tool for biomarker discovery in camel health and breeding.