Picosecond Infrared Laser Mass Spectrometry Identifies a Metabolite Array for 10 s Diagnosis of Select Skin Cancer Types: A Proof-of-Concept Feasibility Study.

Abstract

Currently, a large number of skin biopsies are taken for each true skin cancer case detected, creating a need for a rapid, high sensitivity, and specificity skin cancer detection tool to reduce the number of unnecessary biopsies taken from benign tissue. Picosecond infrared laser mass spectrometry (PIRL-MS) using a hand-held sampling probe is reported to detect and classify melanoma, squamous cell carcinoma, and normal skin with average sensitivity and specificity values of 86-95% and 91-98%, respectively (at a 95% confidence level) solely requiring 10 s or less of total data collection and analysis time. Classifications are not adversely affected by specimen's quantity of melanin pigments and are mediated by a number of metabolic lipids, further identified herein as potential biomarkers for skin cancer-type differentiation, 19 of which were sufficient here (as a fully characterized metabolite array) to provide high specificity and sensitivity classification of skin cancer types. In situ detection was demonstrated in an intradermal melanoma mouse model wherein in vivo sampling did not cause significant discomfort. PIRL-MS sampling is further shown to be compatible with downstream gross histopathologic evaluations despite loss of tissue from the immediate laser sampling site(s) and can be configured using selective laser pulses to avoid thermal damage to normal skin. Therefore, PIRL-MS may be employed as a decision-support tool to reduce both the subjectivity of clinical diagnosis and the number of unnecessary biopsies currently required for skin cancer screening.