Noninvasive Liquid Diet Delivery of Stable Isotopes into Mouse Models for Deep Metabolic Network Tracing

Delivering isotopic tracers for metabolic studies in rodents without overt stress is challenging. Current methods achieve low label enrichment in proteins and lipids. Here, we report noninvasive introduction of 13C6-glucose via a stress-free, ad libitum liquid diet. Using NMR and ion chromatography-mass spectrometry, we quantify extensive 13C enrichment in products of glycolysis, the Krebs cycle, the pentose phosphate pathway, nucleobases, UDP-sugars, glycogen, lipids, and proteins in mouse tissues during 12 to 48 h of 13C6-glucose feeding. Applying this approach to patient-derived lung tumor xenografts (PDTX), we show that the liver supplies glucose-derived Gln via the blood to the PDTX to fuel Glu and glutathione synthesis while gluconeogenesis occurs in the PDTX. Comparison of PDTX with ex vivo tumor cultures and arsenic-transformed lung cells versus xenografts reveals differential glucose metabolism that could reflect distinct tumor microenvironment. We further found differences in glucose metabolism between the primary PDTX and distant lymph node metastases

Converting a breast cancer microarray signature into a high-throughput diagnostic test

BACKGROUND: A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. RESULTS: To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001). CONCLUSION: In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients

Circulating Fatty Acids Associated with Advanced Liver Fibrosis and Hepatocellular Carcinoma in South Texas Hispanics

Background: Hispanics in South Texas have high rates of hepatocellular carcinoma (HCC) and nonalcoholic fatty liver disease (NAFLD). Liver fibrosis severity is the strongest predictive factor of NAFLD progression to HCC. We examined the association between free fatty acids (FA) and advanced liver fibrosis or HCC in this population. Methods: We quantified 45 FAs in plasma of 116 subjects of the Cameron County Hispanic Cohort, 15 Hispanics with HCC, and 56 first/second-degree relatives of Hispanics with HCC. Liver fibrosis was assessed by FibroScan. Results: Advanced liver fibrosis was significantly associated with low expression of very long chain (VLC) saturated FAs (SFA), odd chain SFAs, and VLC n-3 polyunsaturated FAs [PUFA; AOR; 95% confidence interval (CI), 10.4 (3.7-29.6); P \u3c 0.001; 5.7 (2.2-15.2); P \u3c 0.001; and 3.7 (1.5-9.3); P = 0.005]. VLC n3-PUFAs significantly improved the performance of the noninvasive markers for advanced fibrosis - APRI, FIB-4, and NFS. Plasma concentrations of VLC SFAs and VLC n-3 PUFAs were further reduced in patients with HCC. Low concentrations of these FAs were also observed in relatives of patients with HCC and in subjects with the PNPLA3 rs738409 homozygous genotype. Conclusions: Low plasma concentrations of VLC n-3 PUFAs and VLC SFAs were strongly associated with advanced liver fibrosis and HCC in this population. Genetic factors were associated with low concentrations of these FAs as well. Impact: These results have implications in identifying those at risk for liver fibrosis progression to HCC and in screening this population for advanced fibrosis. They also prompt the evaluation of VLC n-3 PUFA or VLC SFA supplementation to prevent cirrhosis and HCC

AMPK Is Essential to Balance Glycolysis and Mitochondrial Metabolism to Control T-ALL Cell Stress and Survival

T cell acute lymphoblastic leukemia (T-ALL) is an aggressive malignancy associated with Notch pathway mutations. While both normal activated and leukemic T cells can utilize aerobic glycolysis to support proliferation, it is unclear to what extent these cell populations are metabolically similar and if differences reveal T-ALL vulnerabilities. Here we show that aerobic glycolysis is surprisingly less active in T-ALL cells than proliferating normal T cells and that T-ALL cells are metabolically distinct. Oncogenic Notch promoted glycolysis but also induced metabolic stress that activated 5' AMP-activated kinase (AMPK). Unlike stimulated T cells, AMPK actively restrained aerobic glycolysis in T-ALL cells through inhibition of mTORC1 while promoting oxidative metabolism and mitochondrial Complex I activity. Importantly, AMPK deficiency or inhibition of Complex I led to T-ALL cell death and reduced disease burden. Thus, AMPK simultaneously inhibits anabolic growth signaling and is essential to promote mitochondrial pathways that mitigate metabolic stress and apoptosis in T-ALL

Organization of Enzyme Concentration across the Metabolic Network in Cancer Cells

<div><p>Rapid advances in mass spectrometry have allowed for estimates of absolute concentrations across entire proteomes, permitting the interrogation of many important biological questions. Here, we focus on a quantitative aspect of human cancer cell metabolism that has been limited by a paucity of available data on the abundance of metabolic enzymes. We integrate data from recent measurements of absolute protein concentration to analyze the statistics of protein abundance across the human metabolic network. At a global level, we find that the enzymes in glycolysis comprise approximately half of the total amount of metabolic proteins and can constitute up to 10% of the entire proteome. We then use this analysis to investigate several outstanding problems in cancer metabolism, including the diversion of glycolytic flux for biosynthesis, the relative contribution of nitrogen assimilating pathways, and the origin of cellular redox potential. We find many consistencies with current models, identify several inconsistencies, and find generalities that extend beyond current understanding. Together our results demonstrate that a relatively simple analysis of the abundance of metabolic enzymes was able to reveal many insights into the organization of the human cancer cell metabolic network.</p></div

Global profile of glycolytic enzyme concentrations across all cell lines.

<p><b>(a)</b> Distribution of cell protein copy (CPC) values for all glycolytic/gluconeogenic proteins across all cell lines. For each protein the median, standard deviations, max, and min are indicated. <b>(b)</b> Probability distribution function of CPC values for all metabolic proteins and the glycolytic/gluconeogenic subset—different subsets are denoted by different colors. Values were binned with a bin difference of 10^0.2 and the relative frequency, or percentage of values falling into that bin, were plotted. <b>(c)</b> Distribution of 11 glycolytic proteins in a sequential pathway order. Center dot indicates average CPC value for each protein with bars indicating the max and min measurements across all cell lines. <b>(d)</b> Pathway diagram of glycolysis activity. Blue squares indicate branching into other biological pathways, blue hexagons indicate intermediate metabolites, and purple circles indicate reacting enzymes. Size of purple circle is proportional to the average CPC value for that enzyme across all cell lines.</p

Cofactor and protein concentration analysis within the human metabolic protein network.

<p>Network diagram of glycolysis illustrating the abundance of aminotransferases and enzymes that utilize NAD(P)/NAD(P)H as a cofactor. The size of the nodes corresponds to the average abundance of the proteins.</p

Distribution of metabolic proteome percentage across all cell lines for various pathways.

<p>For each distribution the median, standard deviations, max, and min are indicated. Inset contains a magnified look at the pathways with the highest percentages of the metabolic proteome.</p

Branch point analysis across the human metabolic protein network.

<p><b>(a)</b> Diagram clarifying method for computing various Branch Divergence scores in 2 different circumstances. Orange squares indicate reactant and product metabolites with blue ovals indicating the reacting enzymes. <b>(b)</b> Histogram of Branch Divergence Scores based on top 2 values. Each bin is lower end inclusive with a bin size of 0.1. <b>(c)</b> Histogram of Branch Divergence Scores based on top 3 values. Each bin is lower end inclusive with a bin size of 0.1. <b>(d)</b> Plot indicating the p-values for pathways that have significantly different counts in one-sided and equally distributed pathways (defined as a p-value < 0.05). <b>(e)</b> Ratio of one-sided counts to equally distributed counts for significant pathways.</p

Global intracellular distribution of metabolic protein concentrations across all cell lines.

<p><b>(a)</b> Pie chart diagraming the total percentage of metabolic proteins across all cell lines. Metabolic proteins are differentiated by a different color inset. <b>(b)</b> Probability distribution function of cell protein copy (CPC) values for all proteins and the metabolic subset—different subsets are denoted by different colors. Log₁₀ values were binned with a bin difference of 10^0.3 and the relative frequency, or percentage of values falling into that bin, were plotted.</p