In this work, we demonstrate a new approach for assessing the stability and reproducibility of mass spectra obtained via ambient ionization methods. This method is suitable for both comparing experiments during which only one mass spectrum is measured and for evaluating the internal homogeneity of mass spectra collected over a period of time. The approach uses Pearson’s r coefficient and the cosine measure to compare the spectra. It is based on the visualization of dissimilarities between measurements, thus leading to the analysis of dissimilarity patterns. The cosine measure and correlations are compared to obtain better metrics for spectra homogeneity. The method filters out unreliable scans to prevent the analyzed sample from being wrongly characterized. The applicability of the method is demonstrated on a set of brain tumor samples. The developed method could be employed in neurosurgical applications, where mass spectrometry is used to monitor the intraoperative tumor border.

Cells metabolism alteration is the new hallmark of cancer, as well as an important method for carcinogenesis investigation. It is well known that the malignant cells switch to aerobic glycolysis pathway occurring also in healthy proliferating cells. Recently, it was shown that in malignant cells de novo synthesis of the intracellular fatty acid replaces dietary fatty acids which change the lipid composition of cancer cells noticeably. These alterations in energy metabolism and structural lipid production explain the high proliferation rate of malignant tissues. However, metabolic reprogramming affects not only lipid metabolism but many of the metabolic pathways in the cell. 2-hydroxyglutarate was considered as cancer cell biomarker and its presence is associated with oxidative stress influencing the mitochondria functions. Among the variety of metabolite detection methods, mass spectrometry stands out as the most effective method for simultaneous identification and quantification of the metabolites. As the metabolic reprogramming is tightly connected with epigenetics and signaling modifications, the evaluation of metabolite alterations in cells is a promising approach to investigate the carcinogenesis which is necessary for improving current diagnostic capabilities and therapeutic capabilities. In this paper, we overview recent studies on metabolic alteration and oncometabolites, especially concerning brain cancer and mass spectrometry approaches which are now in use for the investigation of the metabolic pathway.

The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.

It has previously been reported that different conformations of oligonucleotides may be detected using a gas-phase hydrogen/deuterium (H/D) exchange performed in the collision cell of a mass spectrometer. The presence of different conformers was postulated based on the bimodal shape of the deuterium distribution and on the ion mobility spectrometry data. Here we implement an in-electrospray ionization source H/D exchange to detect the different conformations of oligonucleotides in the region of ion formation. We observed that the number of H/D exchanges depends considerably on the temperature of the desolvating capillary and varies from 25% at 50°C to 80% at 450°C, but no bimodality in the shape of the deuterium distribution was observed. Such results indicate that in the region of ion formation different conformations of oligonucleotide ions rapidly interconvert one into another.

• Strategy for thresholding and denoising spectra for conversion is proposed. • Intelligent thresholding to maximize number of shared peaks in different resolutions. • Algorithm unifies high- and low-resolution mass spectra is presented. • Algorithm facilitates the translation of mass spectrometric assays to clinical use.