Advancements in ambient ionization mass spectrometry towards improved ovarian cancer research and diagnosis

Ovarian cancer is a highly aggressive disease accounting for the majority of deaths from gynecological malignancies. Investigating the molecular mechanisms driving disease development and progression can improve early detection and drive the introduction of novel treatment strategies to ameliorate patient outcomes. Enhancing the accuracy and efficiency of ovarian cancer surgeries by introducing molecular information to rapidly assess tissue samples and guide cancer excision could also offer significant benefits to the management of ovarian cancer. Ambient ionization mass spectrometry (MS) methods are capable of obtaining biomolecule information directly from tissue samples with minimal sample preparation requirements and experimental simplicity, providing a suitable platform to conduct these investigations. Desorption electrospray ionization (DESI) was introduced in 2004 as the first ambient ionization MS technique and has been widely applied to investigate healthy and cancerous human tissue sections towards identifying potential cancer molecular markers and developing predictive statistical models towards improved cancer diagnosis. Alternative ambient ionization methods utilizing direct liquid extraction-based mechanisms have also been developed to improve the analytical capabilities of ambient ionization MS and expand applications in tissue analysis and cancer diagnosis. Overall, this dissertation presents the application and development of ambient ionization MS methods for ovarian cancer research and improved diagnostics. First, the use of DESI-MS to distinguish between malignant and borderline ovarian tumors, as well as determine metabolic markers associated with disease aggressiveness is described. Going beyond cancer diagnosis, we next apply DESI-MS to identify trends in metabolic composition resulting from the expression of the fatty acid binding protein (FABP4) gene, a molecular determinant of ovarian cancer metastasis and residual disease post-surgery. An alternative liquid extraction-based ambient ionization MS approach is also described in this dissertation to improve spatial control in MS imaging and profiling applications from biological tissue sections. The capabilities of this method are tested with various biological samples, including ovarian cancer tissue. Finally, we discuss the development of an ambient MS technology, the MasSpec Pen, envisioned for nondestructive, rapid, ex vivo and in vivo assessment of surgical specimens. We demonstrate the capabilities of this system to provide accurate diagnoses from ovarian fresh-frozen specimens ex vivo across different sample sets, utilizing various healthy and ovarian cancer tissue types and mass spectrometry platforms.