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Abstract
Skin cancer is the most common cancer known to humans, worldwide. Current detection and treatment of skin cancers remains challenging and time-consuming, as detection relies on stepwise protocols involving visual inspection, optical inspection by a device known as a dermatoscopy, and subsequent excision or punch biopsy for histopathological analysis. Furthermore, cutaneous melanoma (melanoma of the skin) can visually mimic other cutaneous lesions, leading to some degree of difficulty in classification of melanoma subtypes, necessitating a large number of biopsies to be taken. Various studies have indicated 24 out of every 25 biopsies performed for a suspected melanoma are confirmed to be benign post-biopsy, leading to a large amount of unnecessary biopsies. There thus exists a need for development of novel detection technologies for more rapid, less subjective, yet highly specific characterization of skin cancers at the pre-biopsy stage.
Mass spectrometry (MS) is an analytical technique becoming increasingly important in clinical research. MS allows for tissue identification and disease site categorization based on molecular characterization of tissues. Through addition of an ambient ionization laser source known as a Picosecond InfraRed Laser (PIRL), rapid and accurate classifications of skin cancers may be realized. Throughout the research presented in this thesis on banked ex vivo human skin cancers as well as in murine models, once a mass spectrometry molecular signature model has been built from a library of known samples, PIRL-MS may be used to diagnose unknown skin cancers rapidly, within just 5-10 seconds of sampling and analysis time with high sensitivity and specificity. In this thesis, I apply PIRL-MS to skin cancers to enable for rapid, sensitive and specific detection of skin cancers prior to the biopsy stage.
