• Applications of Quantitative Proteomics and Phosphoproteomics to Study the Development of Resistance to Targeted Therapy in Cancer

      Awasthi, Shivangi; Shapiro, Paul, Ph.D.; Goodlett, David Robinson, 1960-; Guha, Udayan (2018)
      Targeted inhibition of protein kinases is a major approach to treat cancer. However, the effectiveness of kinase inhibitors is limited due to intrinsic and acquired resistance mechanisms that promote the progression and survival of cancer cells. The objective of this dissertation is to use liquid chromatography coupled to mass spectrometry (LC MS) based quantitative proteomics to identify potential biomarkers of resistance and response to molecularly targeted therapies in cutaneous melanoma and lung adenocarcinoma in vitro. For the first part of this thesis, I conducted a proteomic analysis of the acquired drug resistance to extracellular signal-regulated kinase (ERK1/2) pathway inhibitors in a melanoma cell line model. A combination of immunoblot assays, global label-free bottom-up proteomics, phosphoproteomics and pathway analysis was used to characterize the differential protein expression in drug resistant melanoma cells. Examination of the quantitative data pointed to an invasive and metastatic phenotypic signature in the resistant cells. We also identified and verified the overexpression of β-catenin and Caveolin-1 (CAV-1) in MEK1/2 and ERK1/2 inhibitor resistant cells. These findings suggest that these proteins have a role in the development of resistance and may represent novel targets for co-therapy. For the second part of this thesis, I have utilized a multiple reaction monitoring (MRM) based targeted proteomic technique to verify previously identified potential biomarkers of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) response in lung adenocarcinoma. Published global phosphoproteomic data were used to select a list of phosphotyrosine peptides (pY) and MRM based relative and absolute quantitative methods were developed to measure their expression in TKI sensitive and resistant lung adenocarcinoma cells. Modified immuno-MRM assays were optimized using heavy labelled synthetic peptide standards which identified the targets with good reproducibility and repeatability. The results indicated that of the 11 chosen sites, EGFR-pY1197 can be used as potential biomarker of EGFR TKI sensitivity, regardless of the EGFR TKI used. Overall these data advance our understanding of the mechanisms of targeted therapy resistance and highlight candidate biomarkers of resistance and sensitivity.
    • Rapid Diagnosis of Microbial Infection via Mass Spectrometric Phenotyping

      Liang, Tao; Goodlett, David Robinson, 1960-; 0000-0001-9883-3999 (2018)
      Microbial infection is a perpetual public threat, causing more than 15 million annual deaths worldwide. Clinical microbiology laboratories currently rely on bacterial culture-based methods for microbial diagnosis to identify causative pathogens, which is time-consuming and labor-intensive. This drives the development of novel diagnostics to identify pathogens accurately and more rapidly. Mass spectrometry (MS) now plays a vital role in clinical diagnosis due to its high accuracy, high specificity, rapidity and high- throughput capability. In this thesis, we present a multi-faceted mass spectrometry approach for rapid microbial infection diagnosis. We first used a novel sample transfer technique, surface acoustic wave nebulization (SAWN) for bacterial membrane lipid analysis, specifically lipid A. Analytical performance of different SAWN chips was characterized, and the optimized SAWN chip was used for bacterial phenotyping. Results showed that lipid A mass spectra from different bacterial species can be differentiated by dot product analysis, in turn, demonstrating feasibility of using SAWN for rapid bacterial identification. We next developed a rapid sodium acetate (SA) based method for lipid extraction, which greatly improved our lipid-based library for pathogen identification by reducing the process time to less than an hour. Importantly, the novel SA method maintained the key components of the reported lipid library method for bacterial identification. Namely, these were the ability to detect 1) antibiotic resistance, 2) microbes direct from biological fluids without culture, and 3) single microbes in polymicrobial samples. This platform can be a complementary approach to the commercialized protein-based systems to improve patient outcomes. The last objective of this thesis is to understand the proteome change in response to lipopolysaccharide stimulus in the context of sepsis, which will facilitate the discovery of new biomarkers for sepsis diagnosis. Shotgun label-free quantification proteomics results showed that 27 new sepsis-related proteins were found among 182 significantly changed proteins in the septic mouse group. A longitudinal, but not pair-wise, data analysis strategy overcame inherent heterogeneity detected twice as many significant changes using each mouse's data as its own control sample. Overall, the advances made in this thesis have broad implications in MS-based rapid diagnosis of microbial infections.