ИСТИНА

Introduction Recent applications of mass spectrometry, and especially ambient mass spectrometry methods that do not require time-consuming sample preparation, have been successfully demonstrated to be capable of discriminating various tumors and unaffected brain tissues. However, delineating the tumor margins and optimal resection volume during surgery is not as straightforward due to various patterns of tumor growth and tumor cell infiltration. The most basic parameter describing resected tissue is tumorous cell percentage (TCP), which is determined by the routine histological evaluation during surgery. This work is an attempt to correlate mass spectrometry data with histology to determine TCP using rapid ambient molecular profiling. Methods Tissue samples of glial tumors were provided by N.N. Burdenko National Scientific and Practical Center for Neurosurgery. Samples were analyzed with Inline Cartridge Extraction (ICE) using Thermo LTQ XL mass spectrometer located in a clinic or LTQ XL Orbitrap located in a remote laboratory. All samples subjected to analysis were also histologically annotated in order to determine TCP. Obtained data were processed using in-lab software. Preliminary Data Since histological evaluation (using hematoxylin and eosin staining) and ICE both are destructive methods of analysis, there was a necessity to develop protocols to match histological data to molecular profiles. As the sample volume of resected brain tumor tissue is relatively small, it complicates the simultaneous mass spectrometry profiling and histological evaluation, especially in the case of highly heterogeneous grade IV tumors. Therefore several protocols were developed to dissect resected tissues on subsamples intended to mass spectrometry analysis and histological evaluation. As a result, it became possible to match determined TCP to profiles and apply the regression algorithms to determine significant features. Different algorithms were cross-validated, and it was demonstrated that TCP could be determined with less than 20% error. Novel Aspect The combination of original tissue dissection strategies and data analysis algorithms allows TCP determination in glial tumor samples.