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A broad-based interlaboratory study of glycosylation profiles of a reference and modified IgG antibody involving 103 reports from 76 laboratories., Graphical Abstract Highlights A broad-based interlaboratory study of the glycosylation of a reference antibody: NISTmAb. 103 reports were received from 76 diverse laboratories worldwide. Analysis involved two samples, the NISTmAb and an enzymatically modified sample, enabling within-lab separation of random and systematic errors using the “Youden two-sample” method. Consensus values were derived and similar performance across all experimental methods was noted., Glycosylation is a topic of intense current interest in the development of biopharmaceuticals because it is related to drug safety and efficacy. This work describes results of an interlaboratory study on the glycosylation of the Primary Sample (PS) of NISTmAb, a monoclonal antibody reference material. Seventy-six laboratories from industry, university, research, government, and hospital sectors in Europe, North America, Asia, and Australia submitted a total of 103 reports on glycan distributions. The principal objective of this study was to report and compare results for the full range of analytical methods presently used in the glycosylation analysis of mAbs. Therefore, participation was unrestricted, with laboratories choosing their own measurement techniques. Protein glycosylation was determined in various ways, including at the level of intact mAb, protein fragments, glycopeptides, or released glycans, using a wide variety of methods for derivatization, separation, identification, and quantification. Consequently, the diversity of results was enormous, with the number of glycan compositions identified by each laboratory ranging from 4 to 48. In total, one hundred sixteen glycan compositions were reported, of which 57 compositions could be assigned consensus abundance values. These consensus medians provide community-derived values for NISTmAb PS. Agreement with the consensus medians did not depend on the specific method or laboratory type. The study provides a view of the current state-of-the-art for biologic glycosylation measurement and suggests a clear need for harmonization of glycosylation analysis methods.

Circadian clocks keep time via ~ 24 h transcriptional feedback loops. In Drosophila, CLOCK-CYCLE (CLK-CYC) activators and PERIOD-TIMELESS (PER-TIM) repressors are feedback loop components whose transcriptional status varies over a circadian cycle. Although changes in the state of activators and repressors has been characterized, how their status is translated to transcriptional activity is not understood. We used mass spectrometry to identify proteins that interact with GFP-tagged CLK (GFP-CLK) in fly heads at different times of day. Many expected and novel interacting proteins were detected, of which several interacted rhythmically and were potential regulators of protein levels, activity or transcriptional output. Genes encoding these proteins were tested to determine if they altered circadian behavior via RNAi knockdown in clock cells. The NIPPED-A protein, a scaffold for the SAGA and Tip60 histone modifying complexes, interacts with GFP-CLK as transcription is activated, and reducing Nipped-A expression lengthens circadian period. RNAi analysis of other SAGA complex components shows that the SAGA histone deubiquitination (DUB) module lengthened period similarly to Nipped-A RNAi knockdown and weakened rhythmicity, whereas reducing Tip60 HAT expression drastically weakened rhythmicity. These results suggest that CLK-CYC binds NIPPED-A early in the day to promote transcription through SAGA DUB and Tip60 HAT activity.

To enable the molecular-level characterization of MHC- associated peptides for neoantigen discovery and identification of antigenic peptides on biotherapeutics, we have developed optimized workflows that allow the identification of MHC- presented epitopes. MHC Class I and II function to display peptide fragments of processed self and foreign proteins (antigens) on the cell surface for inspection by T cells (CD8+ cytotoxic T cells for Class I, and CD4+ helper T cells for Class II). Recognition of foreign antigens by T cell receptors triggers an immediate T-cell activation and expansion, resulting in the immune response. Characterizing these antigens is paramount to understanding the immunogenicity of proteins (e.g., biotherapeutic proteins) and generating tools for targeted cell destruction (e.g., cancer immunotherapy). Tumor neoantigens result from somatic mutations during oncogenesis and have immense immunotherapeutic value. Genomic sequencing of cancer tumor tissues combined with bioinformatics has enabled the identification of tumor specific mutations and in silico prediction of MHC-associated neoantigenic peptides. Often the results of the prediction algorithms are discordant with actual binding information. Neoantigen prediction by gene sequencing and in silico approaches can be complemented and further validated by empirical MHC peptide sequencing. Of interest to BioPharma is that biotherapeutics have the potential to exhibit immunogenicity, resulting in the expression of antidrug antibodies, which reduce drug load and effectiveness. Even though most protein therapeutics are humanized, single-nucleotide polymorphisms in endogenous related proteins can be the source of the immunogenic response. Thus, it is imperative to identify the biotherapeutic derived epitopes presented by MHC Class II to T helper cells with the goal of modifying the drug to remove the antigenic peptides without reducing efficacy. It also can lead to a personalized approach with multiple versions of the same drug mapped to the appropriate patient haplotype to insure efficacy without immunogenic response. The molecular-level characterization of peptides associated with MHC Class I and II requires MHC enrichment by immunoprecipitation, an unbiased peptide elution, and analysis by mass spectrometry. Here we present case studies of our recent work applying workflows for the analysis of peptides associated with Class I and Class II MHC molecules. Using human cell lines (HCT116 and Colo205), we present optimized methods for cell treatment/growth and lysis conditions, MHC immunoaffinity purification, peptide enrichment, mass spectrometry and data processing for sensitive and specific analysis of MHC-associated peptides. These assays have utility to improve prediction of neoantigen identification and mitigate risk of biotherapeutic immunogenicity. Citation Format: Michael Pisano, Paul Del Rizzo, James Mobley, Kamal Houssain, Bill Ho, Richard Jones, David Allen, Ravi Amunugama, Michael Ford. MS-based HLA peptide discovery: Tumor neoantigens and biotherapeutic T-cell epitopes [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B28.

Immuno-oncology describes therapeutic approaches exploiting the body's immune system to fight cancer. One approach involves educating the immune-system to recognize and destroy tumor cells by targeting tumor-specific neoantigens. Neoantigens are antigens presented by tumors but not recognized by the immune-system. Identification of Neoantigens is therefore an active area of research and development. The major histocompatibility complex (MHC) plays a crucial role in antigen presentation. Peptides generated by protein degradation in the cytosol are presented, non-covalently bound to MHC Class I molecules, on the surface of cells for inspection by T-lymphocytes. Cytotoxic T lymphocytes (CTL) recognize peptides presented by MHC Class I. The recognition of peptide antigens presented by MHC Class I results in the destruction of the presenting cell by the CTL. Characterization of peptides associated with MHC Class I molecules requires a targeted protein complex enrichment, an unbiased peptide elution and finally a peptide analysis method. Here we present the latest results from our work optimizing and performing a workflow for the analysis of peptides associated with Class I MHC molecules. Citation Format: Michael J. Ford, Richard C. Jones, Ravi Amunugama, David Allen, Paul Del Rizzo, James Mobley, Michael Pisano. Optimization of methods for the analysis of class I MHC peptides by mass spectrometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 577.

The major histocompatibility complex (MHC) is a region of highly polymorphic genes encoding for glycoproteins (MHC molecules) that form part of the cell-mediated branch of the acquired immune system. In the cytosol, cellular self and foreign (non-self) proteins are constantly being degraded; it is the peptides generated that are presented, non-covalently bound to MHC molecules, on the surface of cells for inspection by cytotoxic T-lymphocytes (CTLs). Nonrecognition of the presented peptide ultimately leads to cell destruction. Characterizing the factors associated with nonrecognition is an attractive proposition for anyone interested in generating tools for targeted cell destruction. In the field of oncology the obvious application then is the targeted destruction of cancerous cells. To enable the molecular level characterization of peptides associated with molecules of the major histocompatibility complex requires a targeted protein complex enrichment, an unbiased peptide elution and finally a peptide analysis method. Most frequently an immunoprecipitation is used to isolate the target complex. The peptide elution is performed under conditions minimizing protein contamination and finally peptide analysis is accomplished by mass spectrometry. Here we present a case study of our recent work optimizing and performing a workflow for the analysis of peptides associated with Class I and Class II MHC molecules. The goal of the assay optimization was to minimize the amount of antibody required for the assay, to minimize the amount of biological material needed from which the complex is isolated and to achieve the optimum sensitivity towards the peptides of interest. Citation Format: Michael Ford, Richard Jones, David Allen, Ravi Amunugama, Paul Del Rizzo, Michael Pisano, James Mobley, Paul Domanski, Bill Ho, Daniel Bochar, Melissa Holt. Mass spectrometric characterization of peptides associated with molecules of the major histocompatibility complex [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr B80.

A neoantigen is a patient-specific tumor antigen resulting from mutations during oncogenesis (1). Advances in genome sequencing of cancer tumor tissues combined with bioinformatics have enabled the identification of tumor specific mutations and the prediction of the peptides that will be presented by the MHC complex. The presented peptides are recognized as foreign by the immune system and can be used to discriminate cancerous from normal cells. Neoantigen prediction by gene sequencing and in silico approaches can be strengthened and further supported by mass spectrometry. The molecular level characterization of peptides associated with molecules of the major histocompatibility complex requires a targeted protein complex enrichment, an unbiased peptide elution, and finally a peptide analysis method. We use immunoaffinity to isolate the target complex, elute the peptides under conditions minimizing protein contamination and finally analyze the peptides by mass spectrometry. Here we present a case studies of our recent work applying workflows for the analysis of peptides associated with both Class I and Class II MHC molecules. Combining state-of-the-art mass spectrometry and bioinformatics, we demonstrate the utility of this approach for neoantigen identification and quantitation. Reference: 1. Sun et al. Cancer Lett 2017;392:17-25. Citation Format: Michael J. Ford, Richard Jones, David Allen, Ravi Amunugama, Michael Pisano, James Mobley, Paul Domanski, Bill Ho, Daniel Bochar, Melissa Holt. Mass spectrometry as a tool for MHC class I and II neoantigen discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5717.

The major histocompatibility complex (MHC) is a region of highly polymorphic genes encoding for glycoproteins (MHC molecules) that form part of the cell-mediated branch of the acquired immune system. In the cytosol, cellular self and foreign (non-self) proteins are constantly being degraded; it is the peptides generated that are presented, non-covalently bound to MHC molecules, on the surface of cells for inspection by cytotoxic T-lymphocytes (CTLs). Non-recognition of the presented peptide ultimately leads to cell destruction. Characterizing the factors associated with non-recognition is an attractive proposition for anyone interested in generating tools for targeted cell destruction. In the field of oncology the obvious application then is the targeted destruction of cancerous cells. To enable the molecular level characterization of peptides associated with molecules of the major histocompatibility complex requires a targeted protein complex enrichment, an unbiased peptide elution and finally a peptide analysis method. Most frequently an immunoprecipitation is used to isolate the target complex. The peptide elution is performed under conditions minimizing protein contamination and finally peptide analysis is accomplished by mass spectrometry. Here we present a case study of our recent work optimizing and performing a workflow for the analysis of peptides associated with Class I and Class II MHC molecules.

The major histocompatibility complex (MHC) is a region of highly polymorphic genes encoding for glycoproteins (MHC molecules) that form part of the cell-mediated branch of the acquired immune system. In the cytosol, cellular self and foreign (non-self) proteins are constantly being degraded; it is the peptides generated that are presented, non-covalently bound to MHC molecules, on the surface of cells for inspection by cytotoxic T-lymphocytes (CTLs). Non recognition of the presented peptide ultimately leads to cell destruction. Characterizing the factors associated with Non recognition is an attractive proposition for anyone interested in generating tools for targeted cell destruction. In the field of oncology the obvious application then is the targeted destruction of cancerous cells. To enable the molecular level characterization of peptides associated with molecules of the major histocompatibility complex requires a targeted protein complex enrichment, an unbiased peptide elution and finally a peptide analysis method. Most frequently an immunoprecipitation is used to isolate the target complex. The peptide elution is performed under conditions minimizing protein contamination and finally peptide analysis is accomplished by mass spectrometry. Here we present a case study of our recent work optimizing and performing a workflow for the analysis of peptides associated with Class I MHC molecules. The goal of the assay optimization was to minimize the amount of antibody required for the assay, to minimize the amount of biological material needed from which the complex is isolated and to achieve the optimum sensitivity towards the hitherto unknown target peptides. Citation Format: Michael Ford, Richard Jones, David Allen, Ravi Amunugama, Paul Del Rizzo, Michael Pisano, James Mobley, Paul Domanski, Bill Ho, Daniel Bochar. Mass spectrometric characterization of peptides associated with molecules of the major histocompatibility complex [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1673. doi:10.1158/1538-7445.AM2017-1673

The Identification and validation of drug targets is an industry wide challenge. There is a very clear and urgent need for technologies that can identify the interaction partners of small molecules. Chemical proteomics is one technology that has attracted attention as a solution to the drug target identification problem. Here we present a new approach utilizing a chloroalkane (CA) moiety capture handle, which can be chemically attached to small molecules to isolate their respective protein partners. In general derivatization of small molecules with the CA moiety does not impact their cell permeability and has limited impact on potency, allowing for phenotypic assays of the derivatized compound to be performed. The retention of cell permeability also allows for the capture process to be performed from live cells treated with the CA-compound. This process is also compatible with competition assays, which can be used to evaluate and compare other compounds exhibiting a similar mode of action. Here we present a study using Dasatinib-CA, a modified kinase inhibitor and potent anti-cancer drug which binds to a broad range of kinases. First we performed target enrichment experiments by incubating K562 cells with the modified Dasatinib (Dasatinib-CA). Cells were lysed and the Dasatinib-CA, together with the bound targets, was rapidly captured onto magnetic resin coated with HaloTag. Unmodified compound was used to competitively elute putative interacting proteins. Secondly using the same assay format we evaluated the relative target affinities of Dasatinib-CA versus competing molecules. Competition assays were performed by incubating multiple mixtures of Dasatinib analogues and Dasatinib-CA at varying relative concentrations. Eluted proteins were processed using SDS-PAGE and in-gel digestion. For target identification experiments peptides were analyzed using label free mass spectrometry. For the competition assays digested material was labeled with Tandem Mass Tags (TMT) 10plex reagents. Peptides were analyzed using nanoscale LC-MS/MS coupled with a Q Exactive mass spectrometer (Thermo). Protein identification and quantitation was performed with MaxQuant (MaxQuant.org) and data validation and visualization was performed using Perseus (Perseus-framework.org). Using this approach we identified over 30 kinases, including known membrane associated and membrane protein targets. This work presented here highlights a new method for chemical proteomics and demonstrates utility of the platform to enable target identification and to evaluate competitor molecules. Citation Format: Michael Ford, Richard Jones, Ravi Amunugama, Danette Daniels, Rachel Ohana, Sergiy Levin, Thomas Kirkland, Marjeta Urh, Keith Wood. A chemoproteomics strategy for target identification and lead compound optimization using chloroalkane derivatized compounds. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr C158.

Chemoproteomic technologies enable the quantitative and qualitative profiling of small molecule protein interactions. Here we report a new approach utilizing a chloroalkane (CA) capture tag which can be chemically attached to small molecules to enable the isolation of their respective protein targets through selective capture onto an immobilized HaloTag protein. We have combined our chemoproteomics workflow with multiplexed chemical labeling methods to enable the analysis of dose dependent target engagement studies in a single LC-MS/MS experiment. Here we demonstrate this workflow using BIRB796-CA, a modified kinase inhibitor. Target enrichment experiments were performed by incubating HEK293 cells with the BIRB-CA. Cells were then lysed and the BIRB-CA, together with the bound targets, was rapidly captured onto immobilized HaloTag protein. Unmodified compound was used to competitively elute putative interacting proteins. To study dose dependent effects on the protein interaction profile, cells were incubated with multiple mixtures of BIRB and BIRB-CA at varying relative concentrations. The eluted proteins were processed using SDS-PAGE and in-gel digestion. Digested material was labeled with Tandem Mass Tags (TMT) 10plex reagents and analyzed using nanoscale LC-MS/MS coupled with a Q Exactive mass spectrometer (Thermo). Protein identification was performed with MaxQuant (MaxQuant.org) and data validation and visualization was performed using Perseus (Perseus-framework.org). We tested this chemoproteomics workflow using the interaction of MAP kinases (MAPK) with BIRB796, an allosteric kinase inhibitor. Treatment of LPS simulated THP-1 cells with BIRB796 and BIRB-CA revealed minimal impact of the CA modification on the inhibition of TNFα secretion. The interaction of BIRB-CA with known BIRB targets MAPK13, MAPK12, MAPK9 and MAPK14 has been confirmed using label free quantitative proteomic profiling. We have optimized the TMT labeling method for minimal losses and sample processing steps. We are applying the TMT method to BIRB-CA and control pull downs and extending this workflow to include the BIRB/BIRB-CA titration samples. Here we will use post-acquisition data processing of the BIRB/BIRB-CA titration pull down data to assess compound binding characteristics with the inferred extension to compounds with unknown binding specificities. Citation Format: Michael Ford, Richard Jones, Ravi Amunugama, Danette Daniels, Rachel Ohana, Sergiy Levin, Thomas Kirkland, Marjeta Urh, Keith Wood. Chemoproteomic profiling for target identification using chloroalkane derivatized compounds. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2015 Nov 5-9; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2015;14(12 Suppl 2):Abstract nr B161.

Chemoproteomic profiling is the qualitative and quantitative study of small molecule protein interactions using mass spectrometry. Chemoproteomics approaches typically involve four steps 1) modification of the bait drug molecules with the addition of an affinity tag, e.g. biotin, 2) incubation of the bait molecule with cells, cell lysates or tissue homogenates, 3) recovery of the bait molecule using the added affinity mechanism, e.g. streptavidin and 4) identification of proteins interacting with the bait molecule by liquid chromatography and tandem mass spectrometry (LC-MS/MS). To obtain value from chemoproteomics experiments any identified small molecule protein interactions need to be representative of the underlying biology and not artifacts of the chemoproteomics process. Chemoproteomic workflows offer a relatively simple method to generate a large volume of extremely valuable data about the behavior of a molecule, its analogs and its competitors. As such the number of samples generated for analysis can be significant. One method for maintaining throughput in chemoproteomics workflows is multiplexed proteomics with chemical labeling. This approach enables the pooling of multiple experimental conditions for analysis in a single LC-MS/MS experiment thus helping to reduce potential bottle necks associated with instrument capacity. Here we report a multiplexed chemoproteomics workflow based on a novel chloroalkane (CA) ligand that minimally affects compound potency and cell permeability using a p38 MAPKinase inhibitor. We show changes in protein interaction profiles by titrating cells with different mixtures of parent inhibitor + modified inhibitor-CA compound at varying relative concentrations. These changes in profiles can be monitored using cells transfected with NanoLuc fusion proteins of known inhibitor targets and show increasing capture correlated with increasing concentrations of modified inhibitor CA-compound. Overall interactions profiles can be more thoroughly analyzed by chemical labeling and combing this approach with 8plex iTRAQ labeling techniques. This multiplexing approach allows for many titrations points to be studies at once, yielding information about the dynamics of interactions between small molecules and their protein targets. The ability to study these differences after treatment of live cells aids in the understanding of the differing interaction targets of many given small molecule inhibitor. Citation Format: Michael Ford, Richard Jones, Ravi Amunugama, Danette Daniels, Rachel Ohana, Thomas Kirkland, Marjeta Urh. Multiplexed chemoproteomic profiling as a tool to decipher the intracellular interactions between proteins and small molecules. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2439. doi:10.1158/1538-7445.AM2015-2439