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In cancer cells, the process of epithelial-mesenchymal transition (EMT) confers migratory and invasive capacity, resistance to apoptosis, drug resistance, evasion of host immune surveillance and tumor stem cell traits. Cells undergoing EMT may represent tumor cells with metastatic potential. Characterizing the EMT secretome may identify biomarkers to monitor EMT in tumor progression and provide a prognostic signature to predict patient survival. Utilizing a transforming growth factor-β-induced cell culture model of EMT, we quantitatively profiled differentially secreted proteins, by GeLC-tandem mass spectrometry. Integrating with the corresponding transcriptome, we derived an EMT-associated secretory phenotype (EASP) comprising of proteins that were differentially upregulated both at protein and mRNA levels. Four independent primary tumor-derived gene expression data sets of lung cancers were used for survival analysis by the random survival forests (RSF) method. Analysis of 97-gene EASP expression in human lung adenocarcinoma tumors revealed strong positive correlations with lymph node metastasis, advanced tumor stage and histological grade. RSF analysis built on a training set (n = 442), including age, sex and stage as variables, stratified three independent lung cancer data sets into low-, medium- and high-risk groups with significant differences in overall survival. We further refined EASP to a 20 gene signature (rEASP) based on variable importance scores from RSF analysis. Similar to EASP, rEASP predicted survival of both adenocarcinoma and squamous carcinoma patients. More importantly, it predicted survival in the early-stage cancers. These results demonstrate that integrative analysis of the critical biological process of EMT provides mechanism-based and clinically relevant biomarkers with significant prognostic value.

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.

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 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