Abstract 678: A 10-second lipidomic based approach to diagnose common spinal tumor types with picosecond infrared laser mass spectrometry

Abstract Intradural extramedullary spinal neoplasms account for ∼40% of all diagnosed spinal tumors. Of that, meningioma and schwannoma are the most common. However, improving the surgical outcomes for these spinal neoplasms requires precise intraoperative diagnosis provided by highly trained neuropathologists. Through a retrospective study of n=257 patient specimens, we demonstrate that 10-second picosecond infrared laser mass spectrometry (PIRL-MS) can robustly and objectively diagnose commonly occurring spinal tumor types with the sensitivity and specificity values of (93±1)% and (97±2)%, respectively. This classification utilizes n=41 cellular lipids including phosphatidylcholines, sphingomyelins, phosphatidylethanolamines, and ceramides, whose identities were established using high-resolution tandem mass spectrometry. The identified lipids form a ‘molecular array’ for robust diagnosis of meningioma and schwannoma tumors by non-pathologists in a manner like genomic, transcriptomic, or methylomic arrays used to diagnose brain cancer types, albeit on a faster timescale of seconds as opposed to hours. Furthermore, when subjected to the presence of additional intradural extramedullary spinal tumor types in the differential diagnosis, the generalizability and robustness of the identified molecular array rendered correct classification even in the presence of data not seen previously by the model. PIRL-MS mediated pathology stratifies the resection risk such that complete removal of certain spinal neoplasms such as meningioma tumors with dural excision could be justified to improve the surgical outcomes. Thus, providing informed surgical care even in the absence of intraoperative consults, addressing the human resource limitations in settings that are understaffed in neuropathology. Here, the current state of PIRL-MS device development allows operation by anyone with basic laboratory skills. Citation Format: Alexa Fiorante, Michael Woolman, David Munoz, Taira Kiyota, Lan Anna Ye, Yasamine Farahmand, Darah Vlaminck, Francis Talbot, Sunit Das, Gelareh Zadeh, Howard Ginsberg, Ahmed Aman, Arash Zarrine-Afsar. A 10-second lipidomic based approach to diagnose common spinal tumor types with picosecond infrared laser mass spectrometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 678.