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Lipid droplets, the dynamic organelles that store Triglycerides (TG) and cholesterol esters (CE), are highly accumulated in colon cancer cells. This work studies the TG and CE subspecies profile in colon carcinoma cell lines, SW480 derived from primary tumor, and SW620 derived from a metastasis of the same tumor. It was previously reported that the total TG and CE content is dramatically higher in SW620 cells; however, TG and CE subspecies profile has not been investigated in detail. The work presented here confirms that the total TG and CE Content is significantly higher in the SW620 cells. Moreover, the fatty acid (FA) composition of TG is significantly altered in the SW620 cells, with significant decrease in the abundance of saturated triglycerides. This resulted in a significantly decreased TG saturation index in the SW620 cells. The saturation index of CE was also significantly decreased in the SW620 cells.
MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid Cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentrationdependent changes in nutrient use, nutrient depletion, metabolic tracing employing 13C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer
metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells.
Background: Prevention of metastatic invasion is one of the main challenges in the treatment of alveolar rhabdomyosarcoma. Still the therapeutic options are limited. Therefore, an anti-tumor screening was initiated focusing on the anti-metastatic and anti-invasion properties of selected medicinal plant extracts and phytoestrogens, already known to be effective in the prevention and treatment of different cancer entities.
Methods: Treatment effects were first evaluated by cell viability, migration, invasion, and colony forming assays on the alveolar rhabdomyosarcoma cell line RH-30 in comparison with healthy primary cells.
Results: Initial anti-tumor screenings of all substances analyzed in this study, identified the plant extract of Vincetoxicum arnottianum (VSM) as the most promising candidate, harboring the highest anti-metastatic potential. Those significant anti-motility properties were proven by a reduced ability for migration (60%), invasion (99%) and colony formation (61%) under 48 h exposure to 25 μg/ml VSM. The restricted motility features were due to an induction of the stabilization of the cytoskeleton – actin fibers were 2.5-fold longer and were spanning the entire cell. Decreased proliferation (PCNA, AMT, GCSH) and altered metastasis (e. g. SGPL1, CXCR4, stathmin) marker expression on transcript and protein level confirmed the significant lowered tumorigenicity under VSM treatment. Finally, significant alterations in the cell metabolism were detected for
25 metabolites, with levels of uracil, N-acetyl serine and propanoyl phosphate harboring the greatest alterations. Compared to the conventional therapy with cisplatin, VSM treated cells demonstrated a similar metabolic shutdown of the primary cell metabolism. Primary control cells were not affected by the VSM treatment.
Conclusions: This study revealed the VSM root extract as a potential, new migrastatic drug candidate for the putative treatment of pediatric alveolar rhabdomyosarcoma with actin filament stabilizing properties and accompanied by a marginal effect on the vitality of primary cells.
T cells need to adapt their cellular metabolism for effector cell differentiation. This relies on alterations in mitochondrial physiology. Which signals and molecules regulate those alterations remains unclear. We recently reported, that the mitochondrial protein TCAIM inhibits activation-induced changes in mitochondrial morphology and function and thus, CD effector T cell formation. Using conditional TCAIM knock-in (KI) and knockout (KO) mice, w now show that it also applies to CD8+ T cells and more importantly, delineate the molecular processes in mitochondria by which TCAIM controls effector cell differentiation. TCAIM KI resulted in reduced activation-induced HIF1α protein expression. Metabolomics and transcriptional data in combination with mathematical flux modeling revealed an impaired induction of anabolic pathways, especially of the mevalonate pathway and cholesterol biosynthesis in TCAIM KI CD8+ T cells. Addition of cholesterol completely rescued HIF1α protein expression, activation and proliferation of TCAIM KI CD8+ T cells. At the molecular level, TCAIM delayed activation-induced mitochondria-ER contact (MERC) formation by binding to MERC promoting proteins such as RMD3 and VDAC2. In summary, we demonstrate that TCAIM suppresses effector cell differentiation by inhibiting MERC formation, which induce HIF1α-mediated increase in cellular metabolism and cholesterol biosynthesis.
Metabolomics, the analysis of potentially all small molecules within a biological system, has become a valuable tool for biomarker identification and the elucidation of biological processes. While metabolites are often present in complex mixtures at extremely different concentrations, the dynamic range of available analytical methods to capture this variance is generally limited. Here, we show that gas chromatography coupled to atmospheric pressure chemical ionization mass spectrometry (GC-APCI-MS), a state of the art analytical technology applied in metabolomics analyses, shows an average linear range (LR) of 2.39 orders of magnitude for a set of 62 metabolites from a representative compound mixture. We further developed a computational tool to extend this dynamic range on average by more than 1 order of magnitude, demonstrated with a dilution series of the compound mixture, using robust and automatic reconstruction of intensity values exceeding the detection limit. The tool is freely available as an R package (CorrectOverloadedPeaks) from CRAN (https://cran.r-project.org/) and can be incorporated in a metabolomics data processing pipeline facilitating large screening assays.
Metabolomics
(2024)