Feature selection algorithm for spray-from-tissue mass spectrometry

Lipid Profiles of Human Brain Tumors Obtained by High-Resolution Negative Mode Ambient Mass Spectrometry

Alterations in cell metabolism, including changes in lipid composition occurring during malignancy, are well characterized for various tumor types. However, a significant part of studies that deal with brain tumors have been performed using cell cultures and animal models. Here, we present a dataset of 124 high-resolution negative ionization mode lipid profiles of human brain tumors resected during neurosurgery. The dataset is supplemented with 38 non-tumor pathological brain tissue samples resected during elective surgery. The change in lipid composition alterations of brain tumors enables the possibility of discriminating between malignant and healthy tissues with the implementation of ambient mass spectrometry. On the other hand, the collection of clinical samples allows the comparison of the metabolism alteration patterns in animal models or in vitro models with natural tumor samples ex vivo. The presented dataset is intended to be a data sample for bioinformaticians to test various data analysis techniques with ambient mass spectrometry profiles, or to be a source of clinically relevant data for lipidomic research in oncology.

Inline cartridge extraction for rapid brain tumor tissue identification by molecular profiling

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.

Metrics for evaluating the stability and reproducibility of mass spectra

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.

[The role of lipid metabolism disorders, atypical isoforms of protein kinase C, and mutational status of cytosolic and mitochondrial forms of isocitrate dehydrogenase in carcinogenesis of glial tumors]

The relationship between molecular genetic and metabolic disorders is one of the challenges of modern oncology. In this review, we consider lipid metabolism and its changes as one of the factors of oncogenesis of glial tumors. Also, we demonstrate that the genome and the metabolome are interconnected by a large number of links, and the metabolic pathways, during their reorganization, are able to drastically affect the genetic structure of the cell and, in particular, cause its tumor transformation. Our own observations and analysis of the literature data allow us to conclude that mass spectrometry is a highly accurate current method for assessing metabolic disorders at the cellular level. The use of mass spectrometry during surgery allows the neurosurgeon to obtain real-time data on the level of specific molecular markers in the resected tissue, thereby bringing intraoperative navigation techniques to the molecular level. The generation of molecular fingerprints for each tumor significantly complements the available neuroimaging, molecular genetic, and immunohistochemical data.