Ambient MS Based Analytical Platform for Identification of Brain Tumor Tissues

Igor Popov, Department of Molecular and Biological Physics, Moscow Institute of Physics and Technology, Dolgoprudny, Russia
Evgeny Zhvansky, Department Of Molecular And Biological Physics, Moscow Institute Of Physics And Technology, Moscow, Russia
Nikita Levin, Laboratory Of Ion And Molecular Physics, Moscow Institute Of Physics And Technology, Moscow, Russia
Vsevolod Shurkhay, Burdenko Neurosurgical Institute, Moscow, Russia
Maria Indeykina, Laboratory Of Mass Spectrometry Of Biomacromolecules, Emanuel Institute Of Biochemical Physics, Moscow, Russia
Alexey Kononikhin, Department Of Molecular And Biological Physics, Moscow Institute Of Physics And Technology, Moscow, Russia
Yury Kostyukevich, Department Of Molecular And Biological Physics, Moscow Institute Of Physics And Technology, Moscow, Russia
Alexander Potapov, Burdenko Neurosurgical Institute, Moscow, Russia
Eugene Nikolaev, Department Of Molecular And Biological Physics, Moscow Institute Of Physics And Technology, Moscow, Russia

Rapid and reliable tumor tissue identification during surgical operations is a challenging problem. Especially in neurosurgery, where the tissue is formlessness and precision of tumor/normal tissue border determination is extremely important. Ambient ionization mass spectrometry based on situ fingerprinting of tissue is an attractive solution.

A special spray-from-tissue ambient ionization method was developed. In this source liquid extraction is immediately followed by ionization. For preliminary characterization of method and formation of database more than 200 tumor samples were analyzed. For each sample, mass spectra were measured in both FTICR and in ion trap mode. MS/MS was used for deeper analysis and identification. Final validation of database profiles was performed using ultrahigh resolution FTICR.

It was demonstrated that MS profile analysis of brain tissue samples gives sufficient information for the identification of tissue and the type of pathology as well as for theirs combination. One of the most important methodological results of the database accumulation stage of the project is the conclusion that in the boundary regions of each tumor the MS profiles can be represented as a linear combination of two and more profiles from different types of cells (necrotic tissue with necrotized vessels, necrotic tissue with tumor stain, tumor with necrosis (with a predominance of tumor tissue), necrotized tumor (with a predominance of necrotic masses), parts of tumor cells). In our work we demonstrate the possibility to use high and ultrahigh resolution data (accurate mass and fine isotopic structure of mass spectra) to identify lipids, metabolites and other compounds giving molecular signatures of the whole tissue.