Developments in ambient mass spectrometry imaging and its applications in biomedical research and cancer diagnosis
My dissertation research has focused on developing and applying innovative mass spectrometry methods to the biomedical field, specifically in the area of cancer detection and intraoperative surgical-guidance. We used desorption electrospray ionization (DESI-MS) imaging to chemically characterize different types of cancers. The characterization was performed using particular chemical compounds found to be markers of disease through chemical imaging of human biopsy tissue. In particular, we have focused on investigating human genitourinary cancers, such as prostate, bladder and kidney, as well as human brain cancers. Our goal now is to translate this technology as validated in the laboratory to clinical and surgical settings, offering chemical information on disease state that could increase patient survival and improve disease management. We believe that this methodology can assist clinicians by offering analytical tools and molecular information that can provide improved intraoperative diagnosis of tumors and their margins, augmenting but not interfering with established surgical workflow. We have successfully shown that DESI-MS enables fast, accurate diagnosis and grading of human cancers based on lipid profiles, and have developed statistical classifiers based on molecular data. DESI-MS also provides valuable information on tumor cell concentration in tissue and on tumor margin position, especially in the case of human brain cancers. In addition to diagnostic capabilities, we have been able to contribute new knowledge on lipid expression in human cancers. Many of the studies included in this dissertation involved identification and structural characterization of various lipids by tandem MS analysis. For example, we detected cholesterol sulfate (CS) as a potential biomarker for prostate cancer. These studies have evolved and in collaboration with scientists in the Purdue Cancer Center we have now identified the enzyme cholesterol sulfotransferase 2B1b as a novel regulator of a malignant phenotype in prostate cancer. We are now also investigating the possibility of detecting CS and other lipid markers in urine samples as a non-invasive method for prostate cancer diagnosis. In human brain cancers, we have detected distinctive variations in lipid profiles related to malignancy, such as higher abundance of lipid phosphatidylserine (40:4) in high grade oligodendroglioma subtype, information which is potentially important for better understanding the biochemical processes related to cancer development. It is remarkable how the changes in lipid profiles observed in DESI-MS data provide reliable and accurate information on tumor subtype and grade. We are currently revising and expanding the classifier to include other types of brain tumors, such as meningiomas and metastatic brain tumors, and normal brain tissue with the goal of further improving diagnostic capabilities. We have also recently identified the oncometabolite 2-hydroxygluterate (2HG) directly from tissue by negative ion mode DESI-MS imaging in human gliomas; overproduction and accumulation of 2HG has been recently associated with a genetic mutation of the isocitrate dehydrogenase 1 (IDH1) enzyme, an indicator of increased survival rates for glioma patients. The exceptional ability to rapidly detect 2HG from tissue by DESI will add to the diagnostic capabilities of the technology by providing valuable prognostic information to surgeon and patient, as well as additional information on tumor margins. The development of novel methodologies and capabilities for tissue analysis by DESI-MS has also been pursued. The capability for full 3D molecular image construction using DESI-MS imaging was developed, allowing direct correlation and easy visualization of endogenous compounds in substructures of an entire organ, as demonstrated for a mouse brain. More recently, new solvent systems were developed which allow for a new capability for DESI-MS imaging - non-destructive tissue analysis. Sequential analysis, using for example immunohistochemistry or MALDI, can now be performed on the same tissue section previously imaged by DESI-MS. This allows lipid and metabolite information obtained by DESI-MS to be unambiguously correlated to protein and morphological information. This progress has greatly expanded the applications of DESI technology, especially in the biological field, and provides means for better understanding the molecular information derived from tissue. Moreover, this development also allows DESI-MS imaging to be now fully integrated into the pathological procedures, in clinical and surgical practice. (Abstract shortened by UMI.)
Cooks, Purdue University.
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