Assessment of variation of inline cartridge extraction mass spectra

Abstract

Recently, mass-spectrometry methods show its utility in tumor boundary location.The effect of differences between research and clinical protocols such as low-and high-resolution measurements and sample storage have to be understood and taken into account to transfer methods from bench to bedside. In this study, we demonstrate a simple way to compare mass spectra obtained by different experimental protocols, assess its quality, and check for the presence of outliers and batch effect in the dataset. We compare the mass spectra of both fresh and frozen-thawed astrocytic brain tumor samples obtained with the inline cartridge extraction prior to electrospray ionization. Our results reveal the importance of both positive and negative ion mode mass spectrometry for getting reliable information about sample diversity. We show that positive mode highlights the difference between protocols of mass spectra measurement, such as fresh and frozen-thawed samples, whereas negative mode better characterizes the histological difference between samples. We also show how the use of similarity spectrum matrix helps to identify the proper choice of the measurement parameters, so data collection would be kept reliable, and analysis would be correct and meaningful. K E Y W O R D Sbrain tumor, data conversion, inline cartridge extraction, low-and high-resolution comparison, spectra stability and reproducibility | INTRODUCTIONFast tissue profiling methods for mass spectrometers allowed developing methods of rapid analysis of biological substances. [1][2][3][4][5][6][7] There are a lot of attempts to incorporate mass spectrometry into the clinical routine for surgery assistance purposes. [8][9][10][11][12] Mass spectra of complex mixtures of biological molecules, even those whose mass is up to 1000 Da, is still rather a difficult task, because of the enormous diversity of molecules contained in biological tissues. 13,14 Despite the common practice of LC-MS/MS to be used as an instrument for accurate identification of complex mixture components, it could not be used as a routine technique for rapid analyses. 15 Therefore, rapid analyses

Analysis of ion currents in mass spectrometric profiles using glioblastoma tissue

“…The effects associated with the geometry of the sample and its internal heterogeneity are visible in the negative ion mode. This confirms earlier observations that positive ions better describe inter-patient variability, while negative ions reflect intra-sample variability 29 . Thus, all pairs of ions between that have a significant correlation value can be divided into three groups:…”

“…Mass spectra were processed in a similar way to previously described [23][24][25][26][27][28][29][30] . So, mass spectra were converted to vectors with 1m/z binning width and were normalized to total ion current.…”

“…So, mass spectra were converted to vectors with 1m/z binning width and were normalized to total ion current. Previously we calculated similarity spectra matrices (SSM) 29,30 , where each matrix element was calculated as a cosine measure between two mass spectra (vectors), and these mass spectra (scans) were taken from a whole measurement. Thus, SSM demonstrated the similarity between scans of single measurement and/or different measurements.…”

“…For mass spectrometric profiling of the samples, extraction using an integrated cartridge (ICE) 28 was used, followed by electrospray ionization. Mass spectra were measured according to a previously developed protocol 29 . In this work, we used only low-resolution spectra in the range of 100-2000 m/z in both polarities.…”

Comparison of Dimensionality Reduction Methods in Mass Spectra of Astrocytoma and Glioblastoma Tissues

“…All spectra were measured in the m/z 100 -2000 ranges. The exact description of the experimental protocol was published previously 25 . Usually, 3 fragments from each dissected tissue sample from the same single patient were measured with each instrument for taking into account and evaluating inner biological variability.…”