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BACKGROUND: Accurate tissue diagnosis during ovarian cancer surgery is critical to maximize cancer excision and define treatment options. Yet, current methods for intraoperative tissue evaluation can be time intensive and subjective. We have developed a handheld and biocompatible device coupled to a mass spectrometer, the MasSpec Pen, which uses a discrete water droplet for molecular extraction and rapid tissue diagnosis. Here we evaluated the performance of this technology for ovarian cancer diagnosis across different sample sets, tissue types, and mass spectrometry systems.
METHODS: MasSpec Pen analyses were performed on 192 ovarian, fallopian tube, and peritoneum tissue samples. Samples were evaluated by expert pathologists to confirm diagnosis. Performance using an Orbitrap and a linear ion trap mass spectrometer was tested. Statistical models were generated using machine learning and evaluated using validation and test sets.
RESULTS: High performance for high-grade serous carcinoma (n = 131; clinical sensitivity, 96.7%; specificity, 95.7%) and overall cancer (n = 138; clinical sensitivity, 94.0%; specificity, 94.4%) diagnoses was achieved using Orbitrap data. Variations in the mass spectra from normal tissue, low-grade, and high-grade serous ovarian cancers were observed. Discrimination between cancer and fallopian tube or peritoneum tissues was also achieved with accuracies of 92.6% and 87.9%, respectively, and 100% clinical specificity for both. Using ion trap data, excellent results for high-grade serous cancer vs normal ovarian differentiation (n = 40; clinical sensitivity, 100%; specificity, 100%) were obtained.
CONCLUSIONS: The MasSpec Pen, together with machine learning, provides robust molecular models for ovarian serous cancer prediction and thus has potential for clinical use for rapid and accurate ovarian cancer diagnosis.
©2019 American Association for Clinical Chemistry
Ovarian cancer is a highly lethal disease and the fifth leading cause of all cancer-related deaths in women (1, 2). Accurate diagnosis and stratification of ovarian cancer is important to develop personalized treatment approaches (3). High-grade serous carcinomas (HGSC)6 and low-grade serous carcinomas (LGSC) are common subtypes of ovarian cancers, with the latter accounting for just a small proportion of cases. HGSCs show aggressive features including rapid growth and invasive behavior, whereas LGSCs follow a more indolent course (4). Cytoreductive surgery in combination with chemotherapy is the primary course of treatment for HGSC and essential to maximize patient survival. However, the timing of cytoreductive surgery is of...