Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics

Introduction: Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics. Objectives: Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs. Methods: A literature search of the current relevant primary research was performed. Results: Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance. Conclusion: Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies

Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method

Direct infusion nanoelectrospray Fourier transform ion cyclotron resonance mass spectrometry (DI nESI FT-ICR MS)offers high mass accuracy and resolution for analyzing complex metabolite mixtures. High dynamic range across a wide mass range, however, can only be achieved at the expense of mass accuracy, since the large numbers of ions entering the ICR detector induce adverse spacecharge effects. Here we report an optimized strategy for wide-scan DI nESI FT-ICR MS that increases dynamic range but maintains high mass accuracy. It comprises the collection if multiple adjacent selected ion monitoring (SIM) windows that are stitched together using novel algorithms. The final SIM-stitching method, derived from several optimization experiments, comprises 21 adjoining SIM windows each of width m/z 30 (from m/z 70 to 500; adjacent windows overlap by m/z 10) with an automated gain control (AGC) target of 1 105 charges. SIMstitching and wide-scan range (WSR; Thermo Electron)were compared using a defined standard to assess mass accuracy and a liver extract to assess peak count and dynamic range. SIM-stitching decreased the maximum mass error by 1.3- and 4.3-fold, and increased the peak count by 5.3- and 1.8-fold, versus WSR (AGC targets of 1 x 105 and 5 x 105, respectively). SIM-stitching achieved an rms mass error of 0.18 ppm and detected over 3000 peaks in liver extract. This novel approach increases metabolome coverage, has very high mass accuracy, and at 5.5 min/sample is conducive for high- throughput metabolomics

Characterisation of the dynamic nature of lipids throughout the lifespan of genetically identical female and male Daphnia magna

Lipids play a significant role in regulation of health and disease. To enhance our understanding of the role of lipids in regulation of lifespan and healthspan additional studies are required. Here, UHPLC-MS/MS lipidomics was used to measure dynamic changes in lipid composition as a function of age and gender in genetically identical male and female Daphnia magna with different average lifespans. We demonstrate statistically significant age-related changes in triglycerides (TG), diglycerides (DG), phosphatidylcholine, phosphatidylethanolamine, ceramide and sphingomyelin lipid groups, for example, in males, 17.04% of TG lipid species decline with age whilst 37.86% increase in relative intensity with age. In females, 23.16% decrease and 25.31% increase in relative intensity with age. Most interestingly, the rate and direction of change can differ between genetically identical female and male Daphnia magna, which could be the cause and/or the consequence of the different average lifespans between the two genetically identical genders. This study provides a benchmark dataset to understand how lipids alter as a function of age in genetically identical female and male species with different average lifespan and ageing rate.Peer reviewe

Combined bezafibrate, medroxyprogesterone acetate and valproic acid treatment inhibits osteosarcoma cell growth without adversely affecting normal mesenchymal stem cells.

This document is the Accepted Manuscript version of a published work that appeared in final form in Bioscience Reports. To access the final edited and published work see http://dx.doi.org/10.1042/BSR20202505Drug repurposing is a cost effective means of targeting new therapies for cancer. We have examined the effects of the repurposed drugs, bezafibrate, medroxyprogesterone acetate and valproic acid on human osteosarcoma cells, i.e., SAOS2 and MG63 compared with their normal cell counterparts, i.e. mesenchymal stem/stromal cells (MSCs). Cell growth, viability and migration were measured by biochemical assay and live cell imaging, whilst levels of lipid-synthesising enzymes were measured by immunoblotting cell extracts. These drug treatments inhibited the growth and survival of SAOS2 and MG63 cells most effectively when used in combination (termed V-BAP). In contrast, V-BAP treated MSCs remained viable with only moderately reduced cell proliferation. V-BAP treatment also inhibited migratory cell phenotypes. MG63 and SAOS2 cells expressed much greater levels of fatty acid synthase and stearoyl CoA desaturase 1 than MSCs, but these elevated enzyme levels significantly decreased in the V-BAP treated osteosarcoma cells prior to cell death. Hence, we have identified a repurposed drug combination that selectively inhibits the growth and survival of human osteosarcoma cells in association with altered lipid metabolism without adversely affecting their non-transformed cell counterparts

Aromatic metabolites from the coelomic fluid of Eisenia earthworm species

Earthworms from the genus Eisenia express coelomic fluid when under severe stress. This coelomic fluid contains a complex mixture of small-molecule metabolites, including aromatic metabolites which are known to be species-specific, yet their actual identities remain unknown. We have aimed to characterize selected high-concentration coelomic fluid metabolites. The major aromatic compound in Eisenia veneta coelomic fluid is the rare metabolite a-nicotinamide riboside; and the major aromatic compound for Eisenia fetida is closely related to the (already characterized) metabolite of Eisenia andrei, which consists of two aromatic quinazoline-2,4-dione ring structures linked by N-acetylspermine. The biological function(s) of these metabolites in earthworms is unknown, but we hypothesize that they represent remnants of larger molecules, possibly bacterial in origin, that are recalcitrant to metabolism by earthworm enzymes. (C) 2016 The Authors. Published by Elsevier Masson SAS

Suitability of Dried Blood Spots for Accelerating Veterinary Biobank Collections and Identifying Metabolomics Biomarkers With Minimal Resources

Biomarker discovery using biobank samples collected from veterinary clinics would deliver insights into the diverse population of pets and accelerate diagnostic development. The acquisition, preparation, processing, and storage of biofluid samples in sufficient volumes and at a quality suitable for later analysis with most suitable discovery methods remain challenging. Metabolomics analysis is a valuable approach to detect health/disease phenotypes. Pre-processing changes during preparation of plasma/serum samples may induce variability that may be overcome using dried blood spots (DBSs). We report a proof of principle study by metabolite fingerprinting applying UHPLC-MS of plasma and DBSs acquired from healthy adult dogs and cats (age range 1-9 years), representing each of 4 dog breeds (Labrador retriever, Beagle, Petit Basset Griffon Vendeen, and Norfolk terrier) and the British domestic shorthair cat (n = 10 per group). Blood samples (20 and 40 μL) for DBSs were loaded onto filter paper, air-dried at room temperature (3 h), and sealed and stored (4°C for ~72 h) prior to storage at -80°C. Plasma from the same blood draw (250 μL) was prepared and stored at -80°C within 1 h of sampling. Metabolite fingerprinting of the DBSs and plasma produced similar numbers of metabolite features that had similar abilities to discriminate between biological classes and correctly assign blinded samples. These provide evidence that DBSs, sampled in a manner amenable to application in in-clinic/in-field processing, are a suitable sample for biomarker discovery using UHPLC-MS metabolomics. Further, given appropriate owner consent, the volumes tested (20-40 μL) make the acquisition of remnant blood from blood samples drawn for other reasons available for biobanking and other research activities. Together, this makes possible large-scale biobanking of veterinary samples, gaining sufficient material sooner and enabling quicker identification of biomarkers of interest

Metabolomics Reveals Target and Off-Target Toxicities of a Model Organophosphate Pesticide to Roach (Rutilus rutilus): Implications for Biomonitoring

No description supplie