<div> Advancements in cancer treatments have increased rapidly in recent years, but cures remain elusive. Surgical tumor resection is a central treatment for many solid malignancies. Residual tumor at surgical margins leads to tumor recurrence. Novel tools for assessing residual tumor at surgical margins could improve surgical outcomes by helping to maximize the extent of resection. Ambient ionization-mass spectrometry (MS) methods generate and analyze ions from minimally prepared samples in near-real-time (e.g. seconds to minutes). These methods leverage the high sensitivity and specificity of mass spectrometry for analyzing gas phase ions and generating those ions quickly and with minimal sample preparation. Recent work has shown that differential profiles of ions, corresponding to phospholipids and small metabolites, are detected from cancerous and their respective normal tissue with ambient ionization-MS methods. When properly implemented, ambient ionization-MS could be used to assess for tumor at surgical margins and provide a molecular diagnosis during surgery. </div><div><br></div><div>The research herein reports efforts in developing rapid intraoperative ambient ionization-MS methods for the molecular assessment of cancerous tissues. Touch spray (TS) ionization and desorption electrospray ionization (DESI) were utilized to analyze kidney cancer and brain cancer.</div><div><br></div><div> As a demonstration of the applicability of TS-MS to provide diagnostic information from fresh surgical tissues, TS-MS was used to rapidly analyze renal cell carcinoma and healthy renal tissue biopsies obtained from human subjects undergoing nephrectomy surgery. Differential phospholipid profiles were identified using principal component analysis (PCA), and the significant ions were characterized using multiple stages of mass spectrometry and high resolution/exact mass MS. The same TS-MS analyzed renal tissues were subsequently analyzed with DESI-MS imaging to corroborate the TS-MS results, and the significant DESI-MS ions were also characterized with MS.</div><div><br></div><div>Significant efforts were made in developing and evaluating a standalone intraoperative DESI-MS system for analyzing brain tissue biopsies during brain tumor surgery. The intraoperative DESI-MS system consists of a linear trap quadrupole mass spectrometer placed on a custom-machined cart that contains all hardware for operating the mass spectrometer. This instrument was operated in the neurosurgical suites at Indiana University School of Medicine to rapidly analyze brain tissue biopsies obtained from glioma resection surgeries. A DESI-MS library of normal brain tissue and glioma was used to statistically classify the brain tissue biopsies collected in the operating room. Multivariate statistical methodologies were employed to predict the disease state and tumor cell percentage of the samples. A DESI-MS assay for detecting 2-hydroxyglutarate (2HG), the oncometabolic product of the isocitrate dehydrogenase (IDH) mutation (a key glioma prognostic marker), was developed and applied to determine the IDH mutation status during the surgical resection. The strengths, weaknesses, and areas of future work in this field are discussed. </div><div><br></div>

<p>Microglia are a population of specialized, tissue-resident immune cells that make up around 10% of total cells in our brain. They actively prune neuronal synapses, engulf cellular debris, and misfolded protein aggregates such as the Alzheimer’s Disease (AD)-associated amyloid-beta (Aβ) by the process of phagocytosis. During AD, microglia are unable to phagocytose Aβ, perhaps due to the several disease-associated changes affecting their normal function. Functional molecules such as lipids and metabolites also influence microglial behavior but have primarily remained uncharacterized to date. The overarching question of this work is, <i>How do microglia become dysfunctional in chronic inflammation</i>? To this end, we developed new chemical tools to better understand and investigate the microglial response to Aβ <i>in vitro</i> and <i>in vivo</i>. Specifically, we introduce three new tools. (1) Recombinant human Aβ was developed via a rapid, refined, and robust method for expressing, purifying, and characterizing the protein. (2) A pH-sensitive fluorophore conjugate of Aβ (called Aβ^pH) was developed to identify and separate Aβ-specific phagocytic and non-phagocytic glial cells <i>ex vivo</i> and <i>in vivo</i>. (3) New lysosomal, mitochondrial, and nuclei-targeting pH-activable fluorescent probes (called LysoShine, MitoShine, and NucShine, respectively) to visualize subcellular organelles in live microglia. Next, we asked, <i>What changes occur to the global lipid and metabolite profiles of microglia in the presence of Aβ in vitro and in vivo</i>? We screened 1500 lipids comprising 10 lipid classes and 700 metabolites in microglia exposed to Aβ. We found significant changes in specific lipid classes with acute and prolonged Aβ exposure. We also identified a lipid-related protein that was differentially regulated due to Aβ <i>in vivo</i>. This new lipid reprogramming mechanism “turned on” in the presence of cellular stress was also present in microglia in the brains of the 5xFAD mouse model, suggesting a generic response to inflammation and toxicity. It is well known that activated microglia induce reactive astrocytes during inflammation. Therefore, we asked, <i>What changes in proteins, lipids, and metabolites occur in astrocytes due to their reactive state? </i>We provide a comprehensive characterization of reactive astrocytes comprising 3660 proteins, 1500 lipids, and 700 metabolites. These microglia and astrocytes datasets will be available to the scientific community as a web application. We propose a final model wherein the molecules secreted by reactive astrocytes may also induce lipid-related changes to the microglial cell state in inflammation. In conclusion, this thesis highlights chemical neuroimmunology as the new frontier of neuroscience propelled by the development of new chemical tools and techniques to characterize glial cell states and function in neurodegeneration.</p>

<p>My research has focused on the development and translation of ambient ionization mass spectrometry (MS)-based platforms in clinical and surgical settings, specifically in the area of brain cancer diagnostics and surgical decision making. Ambient ionization MS methods, such as those described herein, generate and analyze gas phase ions with high sensitivity and specificity from minimally prepared samples in near-real-time, on the order of seconds to minutes, rendering them well suited to point-of-care applications. We used ambient ionization MS methods, specifically desorption electrospray ionization mass spectrometry (DESI-MS) and extraction nanoelectrospray ionization mass spectrometry (nESI-MS) to molecularly characterize brain cancer biopsies. The characterization was made using diagnostic compounds identified as markers of disease state, tissue composition, tumor type, and genotype in human brain tissue. Methods were developed and validated offline in the laboratory and translated to clinical and surgical settings, thereby generating chemical information on prognostic features intraoperatively and providing valuable information that would be otherwise unavailable. We believe that, with approval, the methodologies described can assist physicians and improve patient outcomes by providing analytical tools and molecular information that can inform surgical decision making and adjuvant treatment strategies, complementing and not interfering with standard of care protocols.</p> <p><br></p> <p>We have successfully demonstrated the use of desorption electrospray ionization mass spectrometry (DESI-MS) for the expedient molecular assessment of human glioma tissue biopsies based on lipid profiles and prognostic metabolites, both at the tumor core and near surgical margins, in two small-scale, clinical studies. Maximal surgical resection of gliomas that avoids non-infiltrated tissue is associated with survival benefit in patients with glioma. The infiltrative nature of gliomas, as well as their morphological and genetic diversity, renders treatment difficult and demands an integrated imaging and diagnostic approach during surgery to guide clinicians in achieving maximal tumor resection. Further, the estimation of tumor cell percentage (TCP), a measure of tumor infiltration at surgical margins, is not routinely assessed intraoperatively. </p> <p>We have previously shown that rapid, offline molecular assessment of tumor infiltration in tissue biopsies is possible and believe that the same assessment performed intraoperatively in biopsied tissue near surgical margins could improve resection and better inform patient management strategies, including postoperative radiotherapy. Using a DESI-MS spectral library of normal brain tissue and glioma biopsies to generate a statistical model to classify brain tissue biopsies intraoperatively, multivariate statistical approaches were used to predict the disease state and tumor cell percentage (TCP) of each biopsy, thereby providing an measure of tumor infiltration at surgical margins via molecular indicators. In addition to assessment of tumor infiltration, we have developed DESI-MS assays for detecting the oncometabolite 2-Hydroxyglutarate (2HG) to detect isocitrate dehydrogenase (IDH) mutations in gliomas intraoperatively. Knowledge of IDH genotypes at the time of surgical resection could improve patient outcomes, as more aggressive tumor resection of IDH-mutated gliomas is associated with increased survival. While assessments of IDH genotype are typically not available until days after surgery, we have demonstrated the ability to provide this information is less than five minutes. An intraoperative DESI-MS system has successfully been used in a proof-of-concept clinical study and intraoperative performance validation of this platform is ongoing. The findings of these two studies as well as strengths, weaknesses, and areas of improvement for upcoming future iterations of the research are discussed.</p> <p><br></p> <p>Point-of-care applications necessitate the adaptation of MS methodologies to smaller devices. Miniature mass spectrometers (Mini MS) boast small footprints, simple operation, and low power consumption, noise levels, and cost, making them attractive candidates for point-of-care use. In a small-scale clinical study, we demonstrated the first application of a Mini MS for determination of IDH mutation status in gliomas intraoperatively. This study paves a path forward for the application of Mini MS in the OR. With its small footprint and low power consumption and noise level, this application of miniature mass spectrometers represents a simple and cost-effective platform for an important intraoperative measurement. </p> <p><br></p> <p>While MS-based methods of tissue analysis can detect molecular features of interest and rapidly produce large quantities of data, their inherent speed is rarely utilized because they are traditionally coupled with time-consuming separation techniques (e.g., chromatography). Ambient ionization MS, specifically DESI-MS, is well suited for high-throughput applications due to its lack of sample preparation and purification techniques. In an attempt to rapidly characterize microarrays of tissue biopsies, we developed a high-throughput DESI-MS (HT-DESI-MS) method for the rapid characterization of disease state, human brain tumor type, glioma classification, and detection of IDH mutations in tissue microarrays (TMA) of banked and fresh human brain tissue biopsies. We anticipate that HT-DESI-MS analysis of TMAs could become a standard tool for the generation of spectral libraries for sample classification, the identification of biomarkers through large-scale studies, the correlation of molecular features with anatomical features when coupled to digital pathology, and the assessment of drug efficacy. </p>

<p>Urine-based biomarkers offer numerous advantages for clinical analysis, including non-invasive collection, a suitable sample source for longitudinal disease monitoring, a better screenshot of disease heterogeneity, higher sample volumes, faster processing times, and lower rejection rates and costs. They will be extremely useful in a clinical trial context, which can be applied alone or in combination with other methods as long as they demonstrate clear reproducibility across cohorts. While biofluids such as urine present enormous challenges with a wide dynamic range and extreme complex typically dominated by a few highly abundant proteins, we have demonstrated that the analytical issue can be efficiently addressed by focusing on extracellular vesicles (EVs), tiny packages released by all kinds of cells. These tiny packages contain different kinds of molecules from inside the cells. Here, we established a robust EV isolation and characterization platform to screen and validate Parkinson’s Disease (PD) and Renal Cell Carcinoma (RCC) biomarkers from urine. PD is a progressive neurological disorder affecting body movement because some brain cells stop producing dopamine. PD is often not diagnosed until it has advanced, making early detection crucial. We investigated urinary EVs from 138 individuals to enable early detection and found several proteins involved in PD development that could be biological indicators for early disease detection. Several biochemical techniques were applied to verify our findings. In the second project, we attempted to develop a novel diagnostic technique for early intervention of RCC. Here, we made our efforts to develop a quantitative method based on data-independent acquisition (DIA) mass spectrometry to analyze urinary EV phosphoproteomics for non-invasive RCC biomarker screening. Combined with our in-house EVtrap method for EV isolation and PolyMAC enrichment of phosphopeptides, we quantified 2,584 unique phosphosites. We observed unique upregulated phosphosites and pathways differentiating healthy control (HC), chronic kidney disease (CKD), low-grade, and high-grade clear cell RCC. These applications have a significant promise for early PD and RCC diagnosis and monitoring based on actual functional proteins with urine as the source. These studies might provide a viable path to developing urinary EV-based disease diagnosis.</p>