Liquid Chromatography-based Mass Spectrometry Research Articles

A conserved metabolic signature associated with response to fast-acting anti-malarial agents.

In malaria drug discovery, understanding the mode of action of lead compounds is important as it helps in predicting the potential emergence of drug resistance in the field when these drugs are eventually deployed. In this study, we have employed metabolomics technologies to characterize the potential targets of anti-malarial drug candidates in the developmental pipeline at NITD. We show that NITD fast-acting leads belonging to spiroindolone and imidazothiadiazole class induce a common biochemical theme in drug-exposed malaria parasites which is similar to another fast-acting, clinically available drug, DHA. These biochemical features which are absent in a slower acting NITD lead (GNF17) point to hemoglobin digestion and inhibition of the pyrimidine pathway as potential action points for these drugs. These biochemical themes can be used to identify and inform on the mode of action of fast drug candidates of similar profiles in future drug discovery programs.

17th International Conference on Malignant Lymphoma, Palazzo dei Congressi, Lugano, Switzerland, 13 - 17 June, 2023.

Introduction: Peripheral T-cell lymphomas (PTCL) are a rare and heterogeneous group of malignancies that share a unifying feature of epigenetic dysregulation. Recent evidence suggests that PTCL, unlike other forms of cancer or even lymphoma, exhibits a marked vulnerability to hypomethylating agents (HMAs) alone and especially in combination with HDAC inhibitors. HMAs like azacitidine (AZA) and decitabine (DAC) have been shown to reverse transcriptional repression secondary to hypermethylation. Cladribine (CLAD) is FDA-approved for the treatment of hairy cell leukemia and is postulated to inhibit both DNA and histone methylation. Here, we sought to define the mechanistic differences between different DNA HMAs in order to inform a rationale on the optimal combinations that might exploit the epigenetic vulnerabilities of PTCL. Methods: Cell viability, caspase activity assay, and western blotting (WB) were performed on a panel of T-cell lymphoma cell lines to identify the effects of AZA/DAC/CLAD on cell survival, apoptosis, and DNA methyltransferase (DNMT) levels. Liquid chromatography-based mass spectrometry (LC-MS) was done to quantify 5-methyl cytosine (5-mC) levels. Results: Cell viability analysis confirmed that the dose and time-dependent sensitivity of the six PTCL cell lines differed following exposure to AZA/DAC/CLAD, where CLAD showed the lowest IC50 value (0.1–1 µM) across all cell lines, followed by AZA (IC50: 1–10 µM), and DAC had the least effect on cell viability (IC50: >100 µM, except T-ALL). A differential threshold of caspase activation was observed across the PTCL cell lines where CLAD showed the most superior caspase activity leading to the highest apoptotic potential. However, WB analysis showed that after 24 hours of treatment, DNMT1 and DNMT3A protein levels were significantly depleted at low concentrations of DAC (<0.01 µM) compared to AZA whereas CLAD did not affect the DNMT1 and DNMT3A levels. LC-MS-based quantification of 5-mC showed a similar relationship in methylation, with initial changes observed at doses >0.01 μM of DAC and >0.1 μM of AZA/CLAD. Taking the short half-life of AZA/DAC into account, cell viability assays with daily addition of AZA/DAC showed increased cell cytotoxicity for AZA/DAC treated samples, which was comparable to CLAD. Ongoing analyses of gene expression and metabolism of the universal methyl donor S-adenosylmethionine (SAM) will help to understand the mechanistic difference between these HMAs. Conclusions: These data suggest that the HMAs have a distinct mechanism of action for hypomethylation. While AZA/DAC induces hypomethylation by depletion of DNMTs, CLAD acts in a DNMT depletion-independent pathway. A mechanistic understanding of AZA/DAC/CLAD will inform how best to use them in clinic as well as assist in the strategic development of biological correlates to further support their therapeutic application. The research was funded by: Translational Orphan Blood Cancer Research Initiative Fund and RO1 # FD-R-006814-01. Keywords: Genomics, Epigenomics, and Other -Omics, Molecular Targeted Therapies No conflicts of interests pertinent to the abstract.

Untargeted and targeted metabolomics to understand plant growth regulation and evolution in Wollemi pine (Wollemia nobilis)

Wollemi pine ( Wollemia nobilis (Jones, Hill, Allen)) is a living fossil, known only through fossil records until its 1994 discovery in Australia. Wollemi Pine is closely related to Norfolk Island pine ( Araucaria heterophylla (Salisb.) Franco), making it an interesting system to study metabolic evolution. We employed untargeted liquid chromatography mass spectrometry-based (LC-MS) metabolomics, with chemometrics, pathway analysis, and our novel plant growth regulator (PGR) putative identification tool (HormonomicsDB), to explore the metabolomes of both species. We identified PGR conjugates and found cytokinin, zeatin, and brassinosteroid pathways to be overrepresented in Wollemi pine tissues, suggesting these PGRs play an important role in its survival. Melatonin, a proposed ancient and stress-related PGR, was not identified in untargeted analysis of either species. Based on our untargeted results, we employed targeted LC-MS to quantify brassinolide and confirm the absence or presence of melatonin in Wollemi and Norfolk Island pine. Both species had similar concentrations of brassinolide, while Wollemi pine had significantly higher melatonin levels than Norfolk Island pine. High levels of melatonin and brassinolide in Wollemi pine supports the hypothesis that these are ancient PGRs that conferred an evolutionary advantage in Wollemi, allowing it to persist.

Secretome analysis identified extracellular superoxide dismutase and catalase of Macrophomina phaseolina.

Macrophomina phaseolina, a necrotrophic fungal pathogen is known to cause charcoal rot disease in food crops, pulse crops, oil crops and cotton and fibre crops. Necrotrophic fungi survive on dead plant tissue. It is well known that reactive oxygen species (ROS) are produced by the host plant during plant-pathogen interaction. However, it is still unclear how M. phaseolina can overcome the ROS-induced cellular damage. To mimic the invasion of M. phaseolina inside the plant cell wall, we developed solid substrate fermentation where M. phaseolina spore suspension was inoculated on a wheat bran bed and incubated for vegetative growth. To analyse the secretome of M. phaseolina after different day interval, its secretory material was collected and concentrated. Both superoxide dismutase (SOD) and catalase were detected in the secretome by zymogram. The presence of SOD and catalase was further confirmed by liquid chromatography based mass spectrometry. The physicochemical properties of M. phaseolina catalase in terms of stability towards pH, temperature, metal ions and chaotropic agent and inhibitors indicated its fitness at different environmental conditions. Apart from the production of catalase in SSF, the studies on this particular microorganism may also have significance in necrotrophic fungal pathogen and their susceptible host plant interaction.

Myo-Inositol Levels in the Dorsal Hippocampus Serve as Glial Prognostic Marker of Mild Cognitive Impairment in Mice.

Dementia is a devastating age-related disorder. Its therapy would largely benefit from the identification of susceptible subjects at early, prodromal stages of the disease. To search for such prognostic markers of cognitive impairment, we studied spatial navigation in male BALBc vs. B6N mice in combination with in vivo magnetic resonance spectroscopy (1H-MRS). BALBc mice consistently showed higher escape latencies than B6N mice, both in the Water Cross Maze (WCM) and the Morris water maze (MWM). These performance deficits coincided with higher levels of myo-inositol (mIns) in the dorsal hippocampus before and after training. Subsequent biochemical analyses of hippocampal specimens by capillary immunodetection and liquid chromatography mass spectrometry-based (LC/MS) metabolomics revealed a higher abundance of glial markers (IBA-1, S100B, and GFAP) as well as distinct alterations in metabolites including a decrease in vitamins (pantothenic acid and nicotinamide), neurotransmitters (acetylcholine), their metabolites (glutamine), and acetyl-L-carnitine. Supplementation of low abundant acetyl-L-carnitine via the drinking water, however, failed to revert the behavioral deficits shown by BALBc mice. Based on our data we suggest (i) BALBc mice as an animal model and (ii) hippocampal mIns levels as a prognostic marker of mild cognitive impairment (MCI), due to (iii) local changes in microglia and astrocyte activity, which may (iv) result in decreased concentrations of promnesic molecules.

High-defined quantitative snapshots of the ganglioside lipidome using high resolution ion mobility SLIM assisted shotgun lipidomics

Defects in sphingolipid metabolism have emerged as a common link across neurodegenerative disorders, and a deeper understanding of the lipid content in preclinical models and patient specimens offers opportunities for development of new therapeutic targets and biomarkers. Sphingolipid metabolic pathways include the formation of glycosphingolipid species that branch into staggeringly complex structural heterogeneity within the globoside and ganglioside sub-lipidomes. Characterization of these sub-lipidomes has typically relied on liquid chromatography-mass spectrometry-based (LC-MS) approaches, but such assays are challenging and resource intensive due to the close structural heterogeneity, the presence of isobaric and isomeric species, and broad dynamic range of endogenous glycosphingolipids. Here, we apply Structures for Lossless Ion Manipulations (SLIM)-based High Resolution Ion Mobility (HRIM)-MS to enable rapid, repeatable, quantitative assays with deep structural information sufficient to resolve endogenous brain gangliosides at the level of individual molecular species. Analyses were performed using a prototype SLIM-MS instrument equipped with a 13-m serpentine path which enabled resolution of closely related isomeric analytes such as GD1a d36:1 and GD1b d36:1 based on recorded mass-to-charge (m/z) and arrival times. To demonstrate the power of our methodology, brain extracts derived from wild-type mice hemi-brains were analyzed by HRIM-MS using flow injection analyses (FIA) without the need for additional separation by liquid chromatography. Endogenous ganglioside species were readily resolved, identified, and quantified by FIA-SLIM-MS analyses within 2 min per sample. Thus, the FIA-SLIM-MS platform enables robust quantification across a broad range of lipid species in biological specimens in a standardized assay format that is readily scalable to support studies with large sample numbers.

Development of a Protein‐based Human Identification Capability from a Single Hair

Shed human hair (lacking root nuclear DNA) frequently contributes important information to forensic investigations involving human identification. Detection of genetic variation observed in amino acid sequences of hair proteins provides a new suite of identity markers that augment microscopic hair analysis and mitochondrial DNA sequencing. In this study, a new method that completely dissolves single hairs using a combination of heat, ultrasonication, and surfactants was developed. Dissolved proteins were digested and genetically variant peptide (GVP) profiles were obtained for single hairs (25mm) via high-resolution nanoflow liquid chromatography-based mass spectrometry and a novel exome-driven bioinformatic approach. Overall, 6519 unique peptides were identified and a total of 57 GVPs were confirmed. Random match probabilities ranged between 2.6×10-2 and 6.0×10-9 . The new bioinformatic strategy and ability to analyze GVPs in forensically relevant samples sizes demonstrate applicability of this approach to distinguish individuals in forensic contexts.

Proteomic Profiling of the Dystrophin-Deficient Brain.

Duchenne muscular dystrophy is a highly progressive neuromuscular disorder caused by primary abnormalities in the Dmd gene encoding the membrane cytoskeletal protein dystrophin. Dystrophinopathies are multi-systems disorders that are characterized by severe skeletal muscle wasting, with loss of independent ambulation in the early teenage years, followed by cardio-respiratory complications and premature death. Nonprogressive cognitive impairments are estimated to affect approximately one-third of dystrophic children. To identify the molecular mechanisms behind the impaired brain function in dystrophinopathy, liquid chromatography-based mass spectrometry offers an unbiased and technology-driven approach. In this chapter, we give a detailed description of a label-free mass spectrometric method to investigate proteome-wide changes in the dystrophin-deficient brain from a genetic mouse model of Duchenne muscular dystrophy.

Intestinal Metabolites Are Profoundly Altered in the Context of HLA-B27 Expression and Functionally Modulate Disease in a Rat Model of Spondyloarthritis.

HLA-B27-associated spondyloarthritides are associated with an altered intestinal microbiota and bowel inflammation. We undertook this study to identify HLA-B27-dependent changes in both host and microbial metabolites in the HLA-B27/β2 -microglobulin (β2 m)-transgenic rat and to determine whether microbiota-derived metabolites could impact disease in this major model of spondyloarthritis. Cecal contents were collected from Fischer 344 33-3 HLA-B27/β2 m-transgenic rats and wild-type controls at 6 weeks (before disease) and 16 weeks (with active bowel inflammation). Metabolomic profiling was performed by high-throughput gas and liquid chromatography-based mass spectrometry. HLA-B27/β2 m-transgenic rats were treated with the microbial metabolites propionate or butyrate in drinking water for 10 weeks, and disease activity was subsequently assessed. Our screen identified 582 metabolites, of which more than half were significantly altered by HLA-B27 expression at 16 weeks. Both microbial and host metabolites were altered, with multiple pathways affected, including those for amino acid, carbohydrate, xenobiotic, and medium-chain fatty acid metabolism. Differences were even observed at 6 weeks, with up-regulation of histidine, tyrosine, spermidine, N-acetylmuramate, and glycerate in HLA-B27/β2 m-transgenic rats. Administration of the short-chain fatty acid propionate significantly attenuated HLA-B27-associated inflammatory disease, although this was not associated with increased FoxP3+ T cell induction or with altered expression of the immunomodulatory cytokines interleukin-10 (IL-10) or IL-33 or of the tight junction protein zonula occludens 1. HLA-B27 expression was also associated with altered host expression of messenger RNA for the microbial metabolite receptors free fatty acid receptor 2 (FFAR2), FFAR3, and niacin receptor 1. HLA-B27 expression profoundly impacts the intestinal metabolome, with changes evident in rats even at age 6 weeks. Critically, we demonstrate that a microbial metabolite, propionate, attenuates development of HLA-B27-associated inflammatory disease. These and other microbiota-derived bioactive mediators may provide novel treatment modalities in HLA-B27-associated spondyloarthritides.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics.

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH. The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort. DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH. (1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc.

Identification of a Set of Conserved Eukaryotic Internal Retention Time Standards for Data-independent Acquisition Mass Spectrometry

Accurate knowledge of retention time (RT) in liquid chromatography-based mass spectrometry data facilitates peptide identification, quantification, and multiplexing in targeted and discovery-based workflows. Retention time prediction is particularly important for peptide analysis in emerging data-independent acquisition (DIA) experiments such as SWATH-MS. The indexed RT approach, iRT, uses synthetic spiked-in peptide standards (SiRT) to set RT to a unit-less scale, allowing for normalization of peptide RT between different samples and chromatographic set-ups. The obligatory use of SiRTs can be costly and complicates comparisons and data integration if standards are not included in every sample. Reliance on SiRTs also prevents the inclusion of archived mass spectrometry data for generation of the peptide assay libraries central to targeted DIA-MS data analysis. We have identified a set of peptide sequences that are conserved across most eukaryotic species, termed Common internal Retention Time standards (CiRT). In a series of tests to support the appropriateness of the CiRT-based method, we show: (1) the CiRT peptides normalized RT in human, yeast, and mouse cell lysate derived peptide assay libraries and enabled merging of archived libraries for expanded DIA-MS quantitative applications; (2) CiRTs predicted RT in SWATH-MS data within a 2-min margin of error for the majority of peptides; and (3) normalization of RT using the CiRT peptides enabled the accurate SWATH-MS-based quantification of 340 synthetic isotopically labeled peptides that were spiked into either human or yeast cell lysate. To automate and facilitate the use of these CiRT peptide lists or other custom user-defined internal RT reference peptides in DIA workflows, an algorithm was designed to automatically select a high-quality subset of datapoints for robust linear alignment of RT for use. Implementations of this algorithm are available for the OpenSWATH and Skyline platforms. Thus, CiRT peptides can be used alone or as a complement to SiRTs for RT normalization across peptide spectral libraries and in quantitative DIA-MS studies.

Plasma ceramides are elevated in overweight Holstein dairy cows experiencing greater lipolysis and insulin resistance during the transition from late pregnancy to early lactation

Insulin resistance is a homeorhetic adaptation to parturition in dairy cows transitioning from late pregnancy to early lactation. An increase in prepartum adiposity can predispose periparturient cows to greater lipolysis and insulin resistance, thus increasing the risk for metabolic disease. Mechanisms mediating the development of insulin resistance in overweight peripartal dairy cows may depend on ceramide metabolism. The sphingolipid ceramide accumulates in plasma and tissues of overweight monogastric animals, and facilitates saturated fatty acid-induced insulin resistance. Considering this evidence, we hypothesized that plasma ceramides would be elevated in periparturient dairy cattle and that these sphingolipids would correlate with the magnitude of lipolysis and insulin resistance. To test our central hypothesis, multiparous Holstein cows were allocated into 2 groups according to their body condition score (BCS) at d −30 prepartum: lean (BCS <3.0; n=10) or overweight (BCS >4.0; n=11). Blood samples were collected at d −45, −30, −15, and −7, relative to expected parturition, and at d 4 postpartum. Plasma glucose, insulin, nonesterified fatty acids (NEFA), and β-hydroxybutyrate (BHBA) concentrations were measured, and insulin sensitivity was estimated. The concentrations of individual plasma ceramide and glycosylated ceramide were determined using liquid chromatography-based mass spectrometry. Results demonstrated that greater adiposity was associated with a greater loss in body condition during late pregnancy. Overweight cows had greater circulating concentrations of glucose, insulin, and NEFA, and lower insulin sensitivity relative to lean cows. We detected 30 different sphingolipids across 6 lipid classes with acyl chains ranging from 16 to 26 carbons. The most abundant plasma sphingolipids detected were C24:0-ceramide, C24:0-monohexosylceramide, and C16:0-lactosylceramide. Plasma concentrations of total ceramide and monohexosylceramide increased as lactation approached, and saturated ceramide and monohexosylceramide were elevated in cows with greater adiposity relative to those with a lean phenotype. Plasma ceramides (e.g., C24:0-ceramide) were positively correlated with plasma NEFA and inversely correlated with insulin sensitivity. Our data demonstrate a remodeled plasma sphingolipidome in dairy cows transitioning from late pregnancy to lactation characterized by a concomitant increase in plasma ceramides with the development of peripartal insulin resistance.

Proteomic profile of an acute partial bladder outlet obstruction.

Partial bladder outlet obstruction (pBOO) is a ubiquitous problem in urology. From posterior urethral valves to prostatic hypertrophy, pBOO results in significant morbidity and mortality. However, the pathophysiology is not completely understood. Proteomics uses mass spectrometry to accurately quantify change in tissue protein concentration. Therefore, we have applied proteomic analysis to a rodent model to assess for protein changes after a surgically induced pBOO. We hypothesize that proteomic analysis after an acute obstruction will determine the most prevalent initial protein response and, potentially, novel molecular pathways. Sprague Dawley rats underwent a surgically induced pBOO (n = 3 per group) for 3, 7, or 14 days. Bladders were assessed for weight and urodynamic parameters. Proteomics used liquid-chromatography based mass spectrometry. Polymerase chain reaction (PCR) was performed on tissue samples to confirm increased mRNA transcription. Bladder weight and capacity increased over the experimental period, but no changes were seen in bladder pressure. Statistically significant increases in protein quantities were seen in 3 proteins related to endoplasmic reticulum stress: GRP-78 (3.66-fold), RhoA (1.90-fold), and RhoA-GDP (1.95-fold), and 2 cytoskeleton molecules: actin (1.7-fold) and tubulin a/b (3.01-fold). Decorin and lumican, members of the small leucine rich proteoglycan (SLRP) family, were also elevated (0.35- and 0.34-fold, respectively). Real-time PCR data confirmed protein elevation. Our experiment confirms that molecular changes occur very soon after the initiation of pBOO, and implicates several molecular pathways. We believe these insights may provide insight into novel prevention and treatment strategies targeted at the pathophysiology of pBOO.

Proteome Analysis of Mouse Adipose Tissue and Colon Tissue using a Novel Integrated Data Processing Pipeline

Abstract: Liquid chromatography based mass spectrometry (LC-MS) is a key technology for analyzing highly complex anddynamic proteome samples. With highly accurate and sensitive LC-MS analysis of complex proteome samples, efficient dataprocessing is another critical issue to obtain more information from LC-MS data. A typical proteomic data processing starts wit hprotein database search engine which assigns peptide sequences to MS/MS spectra and finds proteins. Although several searchengines, such as SEQUEST and MASCOT, have been widely used, there is no unique standard way to interpret MS/MS spectraof peptides. Each search engine has pros and cons depending on types of mass spectrometers and physicochemical properties ofpeptides. In this study, we describe a novel data process pipeline which identifies more peptides and proteins by correcting pre-cursor ion mass numbers and unifying multi search engines results. The pipeline utilizes two open-source software, i PE-MMRfor mass number correction, and iProphet to combine several search results. The integrated pipeline identified 25% more pro-teins in mouse epididymal adipose tissue compared with the conventional method. Also the pipeline was validated using controland colitis induced colon tissue. The results of the present study shows that the integrated pipeline can efficiently identifyincreased number of proteins compared to the conventional method which can be a breakthrough in identification of a potentialbiomarker candidate.Key words: iPE-MMR, iProphet, Q-TOF, TPP

Clustering with position-specific constraints on variance: Applying redescending M-estimators to label-free LC-MS data analysis

BackgroundClustering is a widely applicable pattern recognition method for discovering groups of similar observations in data. While there are a large variety of clustering algorithms, very few of these can enforce constraints on the variation of attributes for data points included in a given cluster. In particular, a clustering algorithm that can limit variation within a cluster according to that cluster's position (centroid location) can produce effective and optimal results in many important applications ranging from clustering of silicon pixels or calorimeter cells in high-energy physics to label-free liquid chromatography based mass spectrometry (LC-MS) data analysis in proteomics and metabolomics.ResultsWe present MEDEA (M-Estimator with DEterministic Annealing), an M-estimator based, new unsupervised algorithm that is designed to enforce position-specific constraints on variance during the clustering process. The utility of MEDEA is demonstrated by applying it to the problem of "peak matching"--identifying the common LC-MS peaks across multiple samples--in proteomic biomarker discovery. Using real-life datasets, we show that MEDEA not only outperforms current state-of-the-art model-based clustering methods, but also results in an implementation that is significantly more efficient, and hence applicable to much larger LC-MS data sets.ConclusionsMEDEA is an effective and efficient solution to the problem of peak matching in label-free LC-MS data. The program implementing the MEDEA algorithm, including datasets, clustering results, and supplementary information is available from the author website at http://www.hephy.at/user/fru/medea/.

Metabolomic Analysis of Resveratrol-Induced Effects in the Human Breast Cancer Cell Lines MCF-7 and MDA-MB-231

Resveratrol is a naturally occurring anticancer compound present in grapes and wine with antiproliferative properties against breast cancer cells and xenografts. Our objective was to investigate the metabolic alterations that characterize the effects of resveratrol in the human breast cancer cell lines MCF-7 and MDA-MB-231 using high-throughput liquid chromatography-based mass spectrometry. In both cell lines, growth inhibition was dose dependent and accompanied by substantial metabolic changes. For all 21 amino acids analyzed levels increased more than 100-fold at a resveratrol dose of 100 μM with far lower concentrations in MDA-MB-231 compared to MCF-7 cells. Among the biogenic amines and modified amino acids (n = 16) resveratrol increased the synthesis of serotonin, kynurenine, and spermindine in both cell lines up to 61-fold indicating that resveratrol strongly interacts with cellular biogenic amine metabolism. Among the eicosanoids and oxidized polyunsaturated fatty acids (n = 17) a pronounced increase in arachidonic acid and its metabolite 12S-HETE was observed in MDA-MB-231 and to a lesser extent in MCF-7 cells, indicating release from cell membrane phospholipids upon activation of phospholipase A₂ and subsequent metabolism by 12-lipoxygenase. In conclusion, metabolomic analysis elucidated several small molecules as markers for the response of breast cancer cells to resveratrol.