ИСТИНА

Introduction One of the problems in neurosurgery is tumor border monitoring, which can be solved with real time mass-spectrometry analysis. Mass-spectrum profile of brain samples is rather similar to one of a complex mixture, which can consist of overlapping peaks, corresponding to different molecules. Lack of time during on-line analysis renders use of reliable molecule identification difficult, which leads to uncertainty in molecules identification and consequently unreliable classification of tissue type. Additional criteria for peaks identification in spectra would significantly improve the accuracy of classification. We analyze possible applications of high and ultrahigh resolution MS methods for brain tumor profiling based on our experience of investigation of more than 100 tumor samples. Methods All biological samples were collected from dissected tissues (brain tumors) during neurosurgical operations in the N. N. Burdenko Scientific Research Neurosurgery Institute. Two experiment design were used for search for additional criterion of molecular identification. First, high resolution mass-spectrometer Thermo LTQ FT Ultra was used. It is equipped with the novel ion source based on direct-spray-from-tissue ionization method in which liquid extraction is immediately followed by ESI. With this setup about 300 mass-spectra were measured during about 5 minutes in each experiment. The isotopic fine structure was obtained by Bruker Apex Ultra FTICR with ultrahigh resolution. In this case primarily methanol extraction of lipids from tissue samples was used. Preliminary Data While mass-spectra are being measured during long time (several minutes), change (evolution) of the mass-spectrometric profile is taking place, what makes difficult to use the profile for future automated classification. In addition, same complexities appear in classification of unknown tissue sample. These problems can be solved with additional descriptors allowing identification of components that forms profiles. The preliminary results suggest that analysis of intensities of peaks can give additional information about molecules corresponding peaks in spectra. Number of carbon atoms in molecule was determined in each scan from intensity of monoisotopic and first isotopic peak ratio taking into account natural isotopic distribution of 13C. About 300 high resolution mass-spectra for each biological sample were obtained during continuous extraction. Results of carbon atom number calculation show rather large dispersion: about 6 atoms for 40 carbons at average. But averaging reveals a statistically significant result. The error in calculations depends on ion current. Despite ICR uncertainty in intensity, the averaged carbon atoms number in molecule coincides rather well with determined from previously identified chemical formula. Second method of identification of molecules in methanol extracts with ultrahigh resolution mass-spectrometry could be applied in another case: for example, to nitrogen atoms detection in molecule. This is useful if possible chemical formulas differ from each other by less than two carbon atoms. This method also allows calculations of not only the number of carbon atoms in molecule but all the atoms with natural isotopic distribution. Amount of these atoms in a molecule is not very precise if calculated by peaks intensities because of the differences in intensity and concentration of isotopic molecules. This is the problem of FT ICR mass-spectra, which can be solved by more accurate raw signal processing. Novel Aspect Novel method of chemical formula determination by using information from isotopic distribution in tissue identification by mass spectrometry is presented.