Most cancers develop upon the accumulation of genetic alterations that provoke and sustain the transformed phenotype. Several metabolomic approaches now allow for the global assessment of intermediate metabolites, generating profound insights into the metabolic rewiring associated with malignant transformation. The metabolomic profiling of neoplastic lesions growing in mice, irrespective of their origin, can provide invaluable information on the mechanisms underlying oncogenesis, tumor progression, and response to therapy. Moreover, the metabolomic profiling of tumors growing in mice may result in the identification of novel diagnostic or prognostic biomarkers, which is of great clinical significance. Several methods can be applied to the metabolomic profiling of neoplastic lesions in mice, including mass spectrometry-based techniques (e.g., gas chromatography-, capillary electrophoresis-, or liquid chromatography-coupled mass spectrometry) as well as nuclear magnetic resonance. Here, we compare and discuss the advantages and disadvantages of all these techniques to provide a concise and reliable guide for readers interested in this active area of investigation.
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http://dx.doi.org/10.1016/B978-0-12-801329-8.00013-1 | DOI Listing |
Prostate Int
September 2024
Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China.
Background: The causal associations and potential mechanisms between prostatic diseases, the predominant male urological disorders, and the course of COVID-19 remain unclear.
Methods: A two-sample Mendelian randomization (MR) analysis was performed to evaluate causal associations between prostate cancer, benign prostatic hyperplasia, and prostatitis and different COVID-19 outcomes (SARS-CoV-2 infection, hospitalized COVID-19, and severe COVID-19). Reverse MR, linkage disequilibrium score regression, and Bayesian colocalization analyses were subsequently performed to strengthen the identified causal relationships.
Heliyon
January 2025
Children's Brain Tumour Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, UK.
Isocitrate dehydrogenase wild-type glioblastoma (GBM) is characterised by a heterogeneous genetic landscape resulting from dynamic competition between tumour subclones to survive selective pressures. Improvements in metabolite identification and metabolome coverage have led to increased interest in clinically relevant applications of metabolomics. Here, we use liquid chromatography-mass spectrometry and gene expression microarray to profile integrated intratumour metabolic heterogeneity, as a direct functional readout of adaptive responses of subclones to the tumour microenvironment.
View Article and Find Full Text PDFCancer Manag Res
January 2025
Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, People's Republic of China.
Objective: Our research has pinpointed the gut microbiome's role in the progression of various pathological types of non-small cell lung cancer (NSCLC). Nonetheless, the characteristics of the gut microbiome and its metabolites across different clinical stages of NSCLC are yet to be fully understood. The current study seeks to explore the distinctive gut flora and metabolite profiles of NSCLC patients across varying TNM stages.
View Article and Find Full Text PDFCrit Care
January 2025
Department of Critical Care Medicine, Cumming School of Medicine, Health Research Innovation Center (HRIC), University of Calgary, Room 4C64, 3280 Hospital Drive N.W., Calgary, AB, T2N 4Z6, Canada.
Background: Traumatic brain injury (TBI) is a major public health concern worldwide, contributing to high rates of injury-related death and disability. Severe traumatic brain injury (sTBI), although it accounts for only 10% of all TBI cases, results in a mortality rate of 30-40% and a significant burden of disability in those that survive. This study explored the potential of metabolomics in the diagnosis of sTBI and explored the potential of metabolomics to examine probable primary and secondary brain injury in sTBI.
View Article and Find Full Text PDFNat Methods
January 2025
Statistical Center for Single-Cell and Spatial Genomics, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Spatial molecular profiling has provided biomedical researchers valuable opportunities to better understand the relationship between cellular localization and tissue function. Effectively modeling multimodal spatial omics data is crucial for understanding tissue complexity and underlying biology. Furthermore, improvements in spatial resolution have led to the advent of technologies that can generate spatial molecular data with subcellular resolution, requiring the development of computationally efficient methods that can handle the resulting large-scale datasets.
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