The Lipid Metabolism as Target and Modulator of BOLD-100 Anticancer Activity: Crosstalk with Histone Acetylation.

The leading first-in-class ruthenium-complex BOLD-100 currently undergoes clinical phase-II anticancer evaluation. Recently, BOLD-100 is identified as anti-Warburg compound. The present study shows that also deregulated lipid metabolism parameters characterize acquired BOLD-100-resistant colon and pancreatic carcinoma cells. Acute BOLD-100 treatment reduces lipid droplet contents of BOLD-100-sensitive but not -resistant cells. Despite enhanced glycolysis fueling lipid accumulation, BOLD-100-resistant cells reveal diminished lactate secretion based on monocarboxylate transporter 1 (MCT1) loss mediated by a frame-shift mutation in the MCT1 chaperone basigin. Glycolysis and lipid catabolism converge in the production of protein/histone acetylation substrate acetyl-coenzymeA (CoA). Mass spectrometric and nuclear magnetic resonance analyses uncover spontaneous cell-free BOLD-100-CoA adduct formation suggesting acetyl-CoA depletion as mechanism bridging BOLD-100-induced lipid metabolism alterations and histone acetylation-mediated gene expression deregulation. Indeed, BOLD-100 treatment decreases histone acetylation selectively in sensitive cells. Pharmacological targeting confirms histone de-acetylation as central mode-of-action of BOLD-100 and metabolic programs stabilizing histone acetylation as relevant Achilles' heel of acquired BOLD-100-resistant cell and xenograft models. Accordingly, histone gene expression changes also predict intrinsic BOLD-100 responsiveness. Summarizing, BOLD-100 is identified as epigenetically active substance acting via targeting several onco-metabolic pathways. Identification of the lipid metabolism as driver of acquired BOLD-100 resistance opens novel strategies to tackle therapy failure.

Power of mzRAPP-Based Performance Assessments in MS1-Based Nontargeted Feature Detection.

When performing chromatography-mass spectrometry-based nontargeted metabolomics, or exposomics, one of the key steps in the analysis is to obtain MS1-based feature tables. Inapt parameter settings in feature detection will result in missing or wrong quantitative values and might ultimately lead to downstream incorrect biological interpretations. However, until recently, no strategies to assess the completeness and abundance accuracy of feature tables were available. Here, we show that mzRAPP enables the generation of benchmark peak lists by using an internal set of known molecules in the analyzed data set. Using the benchmark, the completeness and abundance accuracy of feature tables can be assessed in an automated pipeline. We demonstrate that our approach adds to other commonly applied quality assurance methods such as manual or automatized parameter optimization techniques or removal of false-positive signals. Moreover, we show that as few as 10 benchmark molecules can already allow for representative performance metrics to further improve quantitative biological understanding.

The Anticancer Ruthenium Compound BOLD-100 Targets Glycolysis and Generates a Metabolic Vulnerability towards Glucose Deprivation.

Cellular energy metabolism is reprogrammed in cancer to fuel proliferation. In oncological therapy, treatment resistance remains an obstacle and is frequently linked to metabolic perturbations. Identifying metabolic changes as vulnerabilities opens up novel approaches for the prevention or targeting of acquired therapy resistance. Insights into metabolic alterations underlying ruthenium-based chemotherapy resistance remain widely elusive. In this study, colon cancer HCT116 and pancreatic cancer Capan-1 cells were selected for resistance against the clinically evaluated ruthenium complex sodium trans-[tetrachlorobis(1H-indazole)ruthenate(III)] (BOLD-100). Gene expression profiling identified transcriptional deregulation of carbohydrate metabolism as a response to BOLD-100 and in resistance against the drug. Mechanistically, acquired BOLD-100 resistance is linked to elevated glucose uptake and an increased lysosomal compartment, based on a defect in downstream autophagy execution. Congruently, metabolomics suggested stronger glycolytic activity, in agreement with the distinct hypersensitivity of BOLD-100-resistant cells to 2-deoxy-d-glucose (2-DG). In resistant cells, 2-DG induced stronger metabolic perturbations associated with ER stress induction and cytoplasmic lysosome deregulation. The combination with 2-DG enhanced BOLD-100 activity against HCT116 and Capan-1 cells and reverted acquired BOLD-100 resistance by synergistic cell death induction and autophagy disturbance. This newly identified enhanced glycolytic activity as a metabolic vulnerability in BOLD-100 resistance suggests the targeting of glycolysis as a promising strategy to support BOLD-100 anticancer activity.

Thermodynamic Genome-Scale Metabolic Modeling of Metallodrug Resistance in Colorectal Cancer.

BACKGROUND: Mass spectrometry-based metabolomics approaches provide an immense opportunity to enhance our understanding of the mechanisms that underpin the cellular reprogramming of cancers. Accurate comparative metabolic profiling of heterogeneous conditions, however, is still a challenge. METHODS: Measuring both intracellular and extracellular metabolite concentrations, we constrain four instances of a thermodynamic genome-scale metabolic model of the HCT116 colorectal carcinoma cell line to compare the metabolic flux profiles of cells that are either sensitive or resistant to ruthenium- or platinum-based treatments with BOLD-100/KP1339 and oxaliplatin, respectively. RESULTS: Normalizing according to growth rate and normalizing resistant cells according to their respective sensitive controls, we are able to dissect metabolic responses specific to the drug and to the resistance states. We find the normalization steps to be crucial in the interpretation of the metabolomics data and show that the metabolic reprogramming in resistant cells is limited to a select number of pathways. CONCLUSIONS: Here, we elucidate the key importance of normalization steps in the interpretation of metabolomics data, allowing us to uncover drug-specific metabolic reprogramming during acquired metal-drug resistance.

Morpho-metabotyping the oxidative stress response.

Oxidative stress and reactive oxygen species (ROS) are central to many physiological and pathophysiological processes. However, due to multiple technical challenges, it is hard to capture a comprehensive readout of the cell, involving both biochemical and functional status. We addressed this problem by developing a fully parallelized workflow for metabolomics (providing absolute quantities for > 100 metabolites including TCA cycle, pentose phosphate pathway, purine metabolism, glutathione metabolism, cysteine and methionine metabolism, glycolysis and gluconeogenesis) and live cell imaging microscopy. The correlative imaging strategy was applied to study morphological and metabolic adaptation of cancer cells upon short-term hydrogen peroxide (H2O2) exposure in vitro. The combination provided rich metabolic information at the endpoint of exposure together with imaging of mitochondrial effects. As a response, superoxide concentrations were elevated with a strong mitochondrial localization, and multi-parametric image analysis revealed a shift towards fragmentation. In line with this, metabolism reflected both the impaired mitochondrial function and shifts to support the first-line cellular defense and compensate for energy loss. The presented workflow combining high-end technologies demonstrates the applicability for the study of short-term oxidative stress, but it can be suitable for the in-depth study of various short-term oxidative and other cellular stress-related phenomena.

STAT3-dependent analysis reveals PDK4 as independent predictor of recurrence in prostate cancer.

Prostate cancer (PCa) has a broad spectrum of clinical behavior; hence, biomarkers are urgently needed for risk stratification. Here, we aim to find potential biomarkers for risk stratification, by utilizing a gene co-expression network of transcriptomics data in addition to laser-microdissected proteomics from human and murine prostate FFPE samples. We show up-regulation of oxidative phosphorylation (OXPHOS) in PCa on the transcriptomic level and up-regulation of the TCA cycle/OXPHOS on the proteomic level, which is inversely correlated to STAT3 expression. We hereby identify gene expression of pyruvate dehydrogenase kinase 4 (PDK4), a key regulator of the TCA cycle, as a promising independent prognostic marker in PCa. PDK4 predicts disease recurrence independent of diagnostic risk factors such as grading, staging, and PSA level. Therefore, low PDK4 is a promising marker for PCa with dismal prognosis.

Single Spheroid Metabolomics: Optimizing Sample Preparation of Three-Dimensional Multicellular Tumor Spheroids.

Tumor spheroids are important model systems due to the capability of capturing in vivo tumor complexity. In this work, the experimental design of metabolomics workflows using three-dimensional multicellular tumor spheroid (3D MTS) models is addressed. Non-scaffold based cultures of the HCT116 colon carcinoma cell line delivered highly reproducible MTSs with regard to size and other key parameters (such as protein content and fraction of viable cells) as a prerequisite. Carefully optimizing the multiple steps of sample preparation, the developed procedure enabled us to probe the metabolome of single MTSs (diameter range 790 ± 22 µm) in a highly repeatable manner at a considerable throughput. The final protocol consisted of rapid washing of the spheroids on the cultivation plate, followed by cold methanol extraction. 13C enriched internal standards, added upon extraction, were key to obtaining the excellent analytical figures of merit. Targeted metabolomics provided absolute concentrations with average biological repeatabilities of <20% probing MTSs individually. In a proof of principle study, MTSs were exposed to two metal-based anticancer drugs, oxaliplatin and the investigational anticancer drug KP1339 (sodium trans-[tetrachloridobis(1H-indazole)ruthenate(III)]), which exhibit distinctly different modes of action. This difference could be recapitulated in individual metabolic shifts observed from replicate single MTSs. Therefore, biological variation among single spheroids can be assessed using the presented analytical strategy, applicable for in-depth anticancer drug metabolite profiling.

The Power of LC-MS Based Multiomics: Exploring Adipogenic Differentiation of Human Mesenchymal Stem/Stromal Cells.

The molecular study of fat cell development in the human body is essential for our understanding of obesity and related diseases. Mesenchymal stem/stromal cells (MSC) are the ideal source to study fat formation as they are the progenitors of adipocytes. In this work, we used human MSCs, received from surgery waste, and differentiated them into fat adipocytes. The combination of several layers of information coming from lipidomics, metabolomics and proteomics enabled network analysis of the biochemical pathways in adipogenesis. Simultaneous analysis of metabolites, lipids, and proteins in cell culture is challenging due to the compound's chemical difference, so most studies involve separate analysis with unimolecular strategies. In this study, we employed a multimolecular approach using a two-phase extraction to monitor the crosstalk between lipid metabolism and protein-based signaling in a single sample (~105 cells). We developed an innovative analytical workflow including standardization with in-house produced 13C isotopically labeled compounds, hyphenated high-end mass spectrometry (high-resolution Orbitrap MS), and chromatography (HILIC, RP) for simultaneous untargeted screening and targeted quantification. Metabolite and lipid concentrations ranged over three to four orders of magnitude and were detected down to the low fmol (absolute on column) level. Biological validation and data interpretation of the multiomics workflow was performed based on proteomics network reconstruction, metabolic modelling (MetaboAnalyst 4.0), and pathway analysis (OmicsNet). Comparing MSCs and adipocytes, we observed significant regulation of different metabolites and lipids such as triglycerides, gangliosides, and carnitine with 113 fully reprogrammed pathways. The observed changes are in accordance with literature findings dealing with adipogenic differentiation of MSC. These results are a proof of principle for the power of multimolecular extraction combined with orthogonal LC-MS assays and network construction. Considering the analytical and biological validation performed in this study, we conclude that the proposed multiomics workflow is ideally suited for comprehensive follow-up studies on adipogenesis and is fit for purpose for different applications with a high potential to understand the complex pathophysiology of diseases.

Preclinical studies on metal based anticancer drugs as enabled by integrated metallomics and metabolomics.

Resistance development is a major obstacle for platinum-based chemotherapy, with the anticancer drug oxaliplatin being no exception. Acquired resistance is often associated with altered drug accumulation. In this work we introduce a novel -omics workflow enabling the parallel study of platinum drug uptake and its distribution between nucleus/protein and small molecule fraction along with metabolic changes after different treatment time points. This integrated metallomics/metabolomics approach is facilitated by a tailored sample preparation workflow suitable for preclinical studies on adherent cancer cell models. Inductively coupled plasma mass spectrometry monitors the platinum drug, while the metabolomics tool-set is provided by hydrophilic interaction liquid chromatography combined with high-resolution Orbitrap mass spectrometry. The implemented method covers biochemical key pathways of cancer cell metabolism as shown by a panel of >130 metabolite standards. Furthermore, the addition of yeast-based 13C-enriched internal standards upon extraction enabled a novel targeted/untargeted analysis strategy. In this study we used our method to compare an oxaliplatin sensitive human colon cancer cell line (HCT116) and its corresponding resistant model. In the acquired oxaliplatin resistant cells distinct differences in oxaliplatin accumulation correlated with differences in metabolomic rearrangements. Using this multi-omics approach for platinum-treated samples facilitates the generation of novel hypotheses regarding the susceptibility and resistance towards oxaliplatin.

High-resolution laser ablation inductively coupled plasma mass spectrometry used to study transport of metallic nanoparticles through collagen-rich microstructures in fibroblast multicellular spheroids.

We have efficiently produced collagen-rich microstructures in fibroblast multicellular spheroids (MCSs) as a three-dimensional in vitro tissue analog to investigate silver (Ag) nanoparticle (NP) penetration. The MCS production was examined by changing the seeding cell number (500 to 40,000 cells) and the growth period (1 to 10 days). MCSs were incubated with Ag NP suspensions with a concentration of 5 µg mL-1 for 24 h. For this study, laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used to visualize Ag NP localization quantitatively. Thin sections of MCSs were analyzed by LA-ICP-MS with a laser spot size of 8 µm to image distributions of 109Ag, 31P, 63Cu, 66Zn, and 79Br. A calibration using a NP suspension was applied to convert the measured Ag intensity into the number of NPs present. The determined numbers of NPs ranged from 30 to 7200 particles in an outer rim of MCS. The particle distribution was clearly correlated with the presence of 31P and 66Zn and was localized in the outer rim of proliferating cells with a width that was equal to about twice the diameter of single cells. Moreover, abundant collagens were found in the outer rim of MCSs. For only the highest seeding cell number, NPs were completely captured at the outer rim, in a natural barrier reducing particle transport, whereas Eosin (79Br) used as a probe of small molecules penetrated into the core of MCSs already after 1 min of exposure. Graphical abstract Fibroblast MCS could build up the barrier only for nanoparticles.