The biochemistry of cancer cells diverges significantly from normal cells as a result of a comprehensive reprogramming of metabolic pathways. A major factor influencing cancer metabolism is hypoxia, which is mediated by HIF1α and HIF2α. HIF1α represents one of the principal regulators of metabolism and energetic balance in cancer cells through its regulation of glycolysis, glycogen synthesis, Krebs cycle and the pentose phosphate shunt. However, less is known about the role of HIF1α in modulating lipid metabolism. Lipids serve cancer cells to provide molecules acting as oncogenic signals, energetic reserve, precursors for new membrane synthesis and to balance redox biological reactions. To study the role of HIF1α in these processes, we used HCT116 colorectal cancer cells expressing endogenous HIF1α and cells in which the hif1α gene was deleted to characterize HIF1α-dependent and independent effects on hypoxia regulated lipid metabolites. Untargeted metabolomics integrated with proteomics revealed that hypoxia induced many changes in lipids metabolites. Enzymatic steps in fatty acid synthesis and the Kennedy pathway were modified in a HIF1α-dependent fashion. Palmitate, stearate, PLD3 and PAFC16 were regulated in a HIF-independent manner. Our results demonstrate the impact of hypoxia on lipid metabolites, of which a distinct subset is regulated by HIF1α.

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Self-assembling chemotherapeutic agents are mixtures of relatively nontoxic precursors that can combine chemically under physiological conditions to form products with greater cytotoxic and/or antimicrobial activity than either of the precursors. Combinations that form products more rapidly in or near the target (tumor, pathogen, virally infected cell) than in normal tissues will exhibit target-selective synergism, thus exhibiting an antitarget selectivity that is greater than the selectivities of the product (e.g., a hydrazone) and of either precursor (e.g., a hydrazine derivative or ketone) used singly. This paper describes the target-selective cytotoxic synergism of a cationic aldehyde (A) and a cationic acylhydrazine (B) containing a triarylalkylphosphonium moiety against Ehrlich ascites carcinoma cells (ELA) in culture, in addition to reviewing previous work on self-assembling cytotoxins. The synergism between A and B is carcinoma selective when the ELA cells (the target) are compared to CV-1, an untransformed African green monkey kidney epithelial line. Like tetraphenylphosphonium and rhodamine 123, which are selectively concentrated in ELA cells relative to CV-1, A, B and the hydrazone C resulting from their reaction are lipophilic delocalized cations that selectively inhibit ELA growth relative to CV-1 growth. The hydrazone C is more growth inhibitory than either A or B for both cell lines. A combination of A with an unreactive analogue of B and a combination of B with an unreactive analogue of A did not synergistically inhibit ELA proliferation. The degree of synergism is greater against the ELA cells than against the CV-1 cells. These data, together with hydrazone formation kinetics, suggest that A and B are both concentrated together selectively inside the ELA due to the transmembrane potentials, reacting inside the ELA cells at a higher velocity than inside the CV-1 cells to form the more growth-inhibitory hydrazone C.

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Running titlePurine nucleotide metabolism regulates MICA expression Keywords Immunology, Warburg effect, Purine, Natural killer cells (NK cells), Metabolism, NKG2D ligands, Purine metabolism, Glucose metabolism, Immunometabolism, Immunosurveillance Abstract Expression of the cell surface glycoprotein MHC class I polypeptide-related sequence A (MICA) is induced in dangerous, abnormal or 'stressed' cells, including cancer cells, virus-infected cells and rapidly proliferating cells. MICA is recognized by the activating immune cell receptor NKG2D, providing a mechanism by which immune cells can identify and potentially eliminate pathological cells. Immune recognition through NKG2D is implicated in cancer, atherosclerosis, transplant rejection and inflammatory diseases such as rheumatoid arthritis. Despite the wide range of potential therapeutic applications of MICA manipulation, the factors that control MICA expression are unclear. Here we use metabolic interventions and metabolomic analyses to show that the transition from quiescent cellular metabolism to a 'Warburg' or biosynthetic metabolic state induces MICA expression. Specifically, we show that glucose transport into the cell and active glycolytic metabolism are necessary to upregulate MICA expression. Active purine synthesis is necessary to support this effect of glucose, and increases in purine nucleotide levels are sufficient to induce MICA expression.Metabolic induction of MICA expression directly influences NKG2D-dependent cytotoxicity by immune cells. These findings support a model of MICA regulation whereby the purine metabolic activity of individual cells is reflected by cell surface MICA expression and is the subject of surveillance by NKG2D receptor-expressing immune cells.

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The Reproducibility Project: Cancer Biology seeks to address growing concerns about reproducibility in scientific research by conducting replications of 50 papers in the field of cancer biology published between 2010 and 2012. This Registered report describes the proposed replication plan of key experiments from ‘Transcriptional amplification in tumor cells with elevated c-Myc’ by Lin et al. (2012), published in Cell in 2012. The experiments that will be replicated are those reported in Figures 3E and 3F. In these experiments, elevated levels of c-Myc in the P493-6 cell model of Burkitt's lymphoma results in an increase of the total level of RNA using UV/VIS spectrophotometry (Figure 3E; Lin et al., 2012) and on the mRNA levels/cell for a large set of genes using digital gene expression technology (Figure 3F; Lin et al., 2012). The Reproducibility Project: Cancer Biology is a collaboration between the Center for Open Science and Science Exchange, and the results of the replications will be published in eLife.DOI: http://dx.doi.org/10.7554/eLife.04024.001

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