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<p><p>LAT is a transmembrane adaptor protein that is critical for the emanation of signals downstream of the TCR. Following TCR engagement, LAT is phosphorylated on multiple tyrosine residues, allowing it to serve as a scaffold for a multi-protein signaling complex. Mutation of tyrosine 136 on LAT abrogates binding of PLC-&#947;1. The disruption of this interaction has severe consequences on TCR-mediated calcium signaling and MAPK activation. Mice harboring a mutation at this tyrosine, LATY136F (LAT<super>m/m</super>) mice, have drastically impaired thymocyte development; however, CD4<super>+</super> T cells in the periphery rapidly expand and instigate a fatal lymphoproliferative syndrome. In order to bypass the severe developmental defects exhibited in LAT<super>m/m</super> mice, our laboratory previously developed a conditional knock-in mouse line in which the mutated LAT allele is expressed in mature T cells following deletion of a floxed wildtype LAT allele (ERCre<super>+</super>LAT<super>f/m</super> mice). LAT<super>f/m</super> mice develop a similar lymphoproliferative syndrome as LAT<super>m/m</super> mice. We used both of these mouse models to analyze the contribution of two other proteins that are essential for TCR-mediated signaling, RasGRP1 and Gads, in LAT-mediated autoimmunity. </p><p><p>Analysis of LAT<super>m/m</super>RasGRP1<super>-/-</super> mice demonstrated that the additional deletion of RasGRP1 increased the thymocyte development block and, as a result, young mice contained markedly reduced T cell populations. However, by four months of age, a lymphoproliferative disease had developed in these mice. To bypass the severe developmental block, we analyzed LAT<super>f/m</super>RasGRP1<super>-/-</super> mice and observed that they developed disease similarly to LAT<super>f/m</super> mice. We also assessed the effect of Gads deletion in both mouse models of LAT disease. LAT<super>m/m</super>Gads<super>-/-</super> mice had an even more dramatic block in the DN stage of thymocyte development compared to LAT<super>m/m</super> controls, although by four months of age CD4<super>+</super> T cells had expanded. Following deletion of the wildtype LAT allele, LAT<super>f/m</super>Gads<super>-/-</super> mice also developed disease. Our results indicated that LAT-mediated autoimmunity can occur independently of the critical T cell signaling components RasGRP1 and Gads. </p><p><p>In addition, we more closely examined RasGRP1-mediated Erk activation in T cells. RasGRP1 is a Ras-guanyl nucleotide exchange factor that is required for positive selection of thymocytes, activation of T cells, and control of T cell mediated-autoimmunity. While the importance of various RasGRP1 structural domains has previously been explored, RasGRP1 also contains a tail domain of unknown function. To elucidate the physiological role of this domain, we generated knock-in mice expressing RasGRP1 without the tail domain, RasGRP1<super>d/d</super> mice. Analysis of these mice demonstrated that deletion of the tail domain led to impaired T cell development but, with age, CD4<super>+</super> T cells expanded and auto-antibodies were produced. RasGRP1<super>d/d</super> thymocytes were unable to activate Erk and underwent aberrant thymic selection processes. Mechanistically, the tail-deleted form of RasGRP1 was not able to traffic to the cell membrane following stimulation, indicating a potential reason for its inability to activate Erk. While the DAG-binding C1 domain of RasGRP1 has long been recognized as an important factor mediating Erk activation, our data revealed the physiological relevance of the tail domain of RasGRP1 in the control of Erk signaling.</p> / Dissertation

Altered signaling pathways, which are mediated by post-translational modifications and changes in protein expression levels, are key regulators of cancer initiation, progression, and therapeutic escape. Many aspects of cancer progression, including early carcinogenesis and immediate response to drug treatment, are beyond the scope of genetic profiling and non-invasive monitoring techniques. Global protein profiling of cancer cell line models, tumor tissues, and biofluids (e.g. serum or urine) using mass spectrometry-based proteomics produces novel biological insights, which support improved patient outcomes. Recent technological advances resulting in next-generation mass spectrometry instrumentation and improved bioinformatics workflows have led to unprecedented measurement reproducibility as well as increased depth and coverage of the human proteome. It is now possible to interrogate the cancer proteome with quantitative proteomics to identify prognostic cancer biomarkers, stratify patients for treatment, identify new therapeutic targets, and elucidate drug resistance mechanisms. There are, however, numerous challenges associated with protein measurements. Biological samples have a high level of complexity and wide dynamic range, which is even more pronounced in samples used for non-invasive disease monitoring, such as serum. Cancer biomarkers are generally found in low abundance compared to other serum proteins, particularly at early stages of disease where cancer detection would make the biggest impact on improving patient survival. Additionally, the large-scale datasets generally require bioinformatics expertise to produce useful biological insights. These difficulties converge to create obstacles for down-stream clinical translation. This dissertation research demonstrates how proteomics is applied to develop new resources and generate novel workflows to improve protein quantification in complex biosamples, which could improve translation of cancer research to benefit patient care. The studies described in this dissertation move from assessment of quantitative mass spectrometry platforms, to analytical assay development and validation, and ending with personalized biomarker development applied to patient samples. As an example, four different quantitative mass spectrometry acquisition platforms are explored and comparisons of their ability to quantify low abundance peptides in a complex background are explored. Lung cancers frequently have aberrant signaling resulting in increased kinase activity and targetable signaling hubs; kinase inhibitors have been successfully developed and implemented clinically. Therefore, changes in amounts of kinase peptides in the complex background of peptides from all ATP-utilizing enzymes in a lung cancer cell line model after kinase inhibitor treatment was selected as a model system. Traditional mass spectrometry platforms, data dependent acquisition and multiple reaction monitoring, are compared to the two newer methods, data independent acquisition and parallel reaction monitoring. Relative quantification is performed across the four methods and analytical performance as well as downstream applications, including drug target identification and elucidation of signaling changes. Liquid chromatography – multiple reaction monitoring (LC-MRM) was selected for development of multiplexed quantitative assays based on superior sensitivity and fast analysis times, allowing for larger peptide panels. Method comparison results also provide guidelines for quantitative proteomics platform selection for translational cancer researchers. Next, a multiplexed quantitative LC-MRM assay targeting a panel of 30 RAS signaling proteins was developed and described. Over 30% of all human cancers have a RAS mutation and these cancers are generally aggressive and limited treatment options, leading to poor patient prognosis. Many targeted inhibitors have successfully shut down RAS signaling, leading to tumor regression, however, acquired drug resistance is common. The multiplexed LC-MRM assays characterized and validated are a publically available resource for cancer researchers to interrogate the RAS signal transduction network. Feasibility has been demonstrated in cell line models in order to identify signaling changes that confer BRAF inhibitor resistance and biomarkers of sensitivity to treatment. This analytical LC-MRM panel could support meaningful development of new therapeutic options and identification of companion biomarkers, with the end goal of improving patient outcomes. Multiplexed LC-MRM assays developed for personalized disease biomarkers using an integrated multi-omics approach are described for Multiple Myeloma, an incurable malignancy with poor patient outcomes. This disease is characterized by clonal expansion of the plasma cells in the bone marrow, which secrete a monoclonal immunoglobulin, or M-protein. Clinical treatment decisions are based on multiple semi-quantitative assays that require manual evaluation. In the clinic, minimal residual disease quantification methods, including multi-parameter flow cytometry and immunohistochemistry, are applied to bone marrow aspirates, which is a highly invasive technique that does not provide a systemic evaluation of the disease. To address these issues, we hypothesized that unique variable region peptides could be identified and LC-MRM assays developed specific to each patient’s M-protein to improve specificity and sensitivity in non-invasive disease monitoring. A proteogenomics approach was used to design personalized assays for each patient to monitor their disease progression, which demonstrate improved specificity and up to a 500-fold increase in sensitivity compared to current clinical methods. Assays can be developed from marrow aspirates collected when the patient was at residual disease stage, which is useful if no sample with high disease burden is available. The patient-specific tests are also multiplexed with constant region peptide assays that monitor all immunoglobulin heavy and light chain classes, which could reduce analysis to a single test. In conclusion, highly sensitive patient-specific assays have been developed that could change the paradigm for patient evaluation and clinical decision-making, increasing the ability of clinicians to continue first line therapy in the hopes of achieving a cure, or to intervene at an earlier time point in disease recurrence. This study also provides a blueprint for future development of personalized diagnostics, which could be applied to biomarkers of other cancer types. Overall, these studies demonstrate how quantitative proteomics can be used to support translational cancer research, from the impact of different mass spectrometry platforms on elucidating signaling changes and drug targets to the characterization of multiplexed LC-MRM assays applied to cell line models for translational research purposes and in patient serum samples optimized for clinical translation. We believe that mass spectrometry-based proteomics is poised to play a pivotal role in personalized diagnostics to support implementation of precision medicine, an effort that will improve the quality and efficiency of patient care.

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