Differential Plasma Metabolites between High- and Low-Grade Meningioma Cases

From Lipid Signatures to Cellular Responses: Unraveling the Complexity of Melanoma and Furthering Its Diagnosis and Treatment

Recent advancements in mass spectrometry have significantly enhanced our understanding of complex lipid profiles, opening new avenues for oncological diagnostics. This review highlights the importance of lipidomics in the comprehension of certain metabolic pathways and its potential for the detection and characterization of various cancers, in particular melanoma. Through detailed case studies, we demonstrate how lipidomic analysis has led to significant breakthroughs in the identification and understanding of cancer types and its potential for detecting unique biomarkers that are instrumental in its diagnosis. Additionally, this review addresses the technical challenges and future perspectives of these methodologies, including their potential expansion and refinement for clinical applications. The discussion underscores the critical role of lipidomic profiling in advancing cancer diagnostics, proposing a new paradigm in how we approach this devastating disease, with particular emphasis on its application in comparative oncology.

Metabolomic biomarkers in liquid biopsy: accurate cancer diagnosis and prognosis monitoring

Liquid biopsy, a novel detection method, has recently become an active research area in clinical cancer owing to its unique advantages. Studies on circulating free DNA, circulating tumor cells, and exosomes obtained by liquid biopsy have shown great advances and they have entered clinical practice as new cancer biomarkers. The metabolism of the body is dynamic as cancer originates and progresses. Metabolic abnormalities caused by cancer can be detected in the blood, sputum, urine, and other biological fluids via systemic or local circulation. A considerable number of recent studies have focused on the roles of metabolic molecules in cancer. The purpose of this review is to provide an overview of metabolic markers from various biological fluids in the latest clinical studies, which may contribute to cancer screening and diagnosis, differentiation of cancer typing, grading and staging, and prediction of therapeutic response and prognosis.

Comparative Analysis of Amino Acid Profiles in Patients with Glioblastoma and Meningioma Using Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry (LC-ESI-MS/MS)

Brain tumors account for 1% of all cancers diagnosed de novo. Due to the specificity of the anatomical area in which they grow, they can cause significant neurological disorders and lead to poor functional status and disability. Regardless of the results of biochemical markers of intracranial neoplasms, they are currently of no diagnostic significance. The aim of the study was to use LC-ESI-MS/MS in conjunction with multivariate statistical analyses to examine changes in amino acid metabolic profiles between patients with glioblastoma, meningioma, and a group of patients treated for osteoarthritis of the spine as a control group. Comparative analysis of amino acids between patients with glioblastoma, meningioma, and the control group allowed for the identification of statistically significant differences in the amino acid profile, including both exogenous and endogenous amino acids. The amino acids that showed statistically significant differences (lysine, histidine, α-aminoadipic acid, phenylalanine) were evaluated for diagnostic usefulness based on the ROC curve. The best results were obtained for phenylalanine. Classification trees were used to build a model allowing for the correct classification of patients into the study group (patients with glioblastoma multiforme) and the control group, in which cysteine turned out to be the most important amino acid in the decision-making algorithm. Our results indicate amino acids that may prove valuable, used alone or in combination, toward improving the diagnosis of patients with glioma and meningioma. To better assess the potential utility of these markers, their performance requires further validation in a larger cohort of samples.

Metabolomics Approach Reveals Important Glioblastoma Plasma Biomarkers for Tumor Biology

Glioblastoma (GB) is the most aggressive and frequent primary malignant tumor of the central nervous system and is associated with poor overall survival even after treatment. To better understand tumor biochemical alterations and broaden the potential targets of GB, this study aimed to evaluate differential plasma biomarkers between GB patients and healthy individuals using metabolomics analysis. Plasma samples from both groups were analyzed via untargeted metabolomics using direct injection with an electrospray ionization source and an LTQ mass spectrometer. GB biomarkers were selected via Partial Least Squares Discriminant and Fold-Change analyses and were identified using tandem mass spectrometry with in silico fragmentation, consultation of metabolomics databases, and a literature search. Seven GB biomarkers were identified, some of which were unprecedented biomarkers for GB, including arginylproline (m/z 294), 5-hydroxymethyluracil (m/z 143), and N-acylphosphatidylethanolamine (m/z 982). Notably, four other metabolites were identified. The roles of all seven metabolites in epigenetic modulation, energy metabolism, protein catabolism or folding processes, and signaling pathways that activate cell proliferation and invasion were elucidated. Overall, the findings of this study highlight new molecular targets to guide future investigations on GB. These molecular targets can also be further evaluated to derive their potential as biomedical analytical tools for peripheral blood samples.