• We used molecular dynamics, saturation mutagenesis, and enzymologic screening to develop a glutaminase-free mutant (Q59L) L-ASP.• We then used Q59L to show that glutaminase activity is not required for L-ASP activity against ASNS-negative cancer cells.L-Asparaginase (L-ASP) is a key component of therapy for acute lymphoblastic leukemia. Its mechanism of action, however, is still poorly understood, in part because of its dual asparaginase and glutaminase activities. Here, we show that L-ASP's glutaminase activity is not always required for the enzyme's anticancer effect. We first used molecular dynamics simulations of the clinically standard Escherichia coli L-ASP to predict what mutated forms could be engineered to retain activity against asparagine but not glutamine. Dynamic mapping of enzyme substrate contacts identified Q59 as a promising mutagenesis target for that purpose. Saturation mutagenesis followed by enzymatic screening identified Q59L as a variant that retains asparaginase activity but shows undetectable glutaminase activity. Unlike wild-type L-ASP, Q59L is inactive against cancer cells that express measurable asparagine synthetase (ASNS). Q59L is potently active, however, against ASNS-negative cells. Those observations indicate that the glutaminase activity of L-ASP is necessary for anticancer activity against ASNS-positive cell types but not ASNS-negative cell types.Because the clinical toxicity of L-ASP is thought to stem from its glutaminase activity, these findings suggest the hypothesis that glutaminase-negative variants of L-ASP would provide larger therapeutic indices than wild-type L-ASP for ASNS-negative cancers. (Blood. 2014;123(23):3596-3606) Introduction L-Asparaginase (L-ASP) is an enzyme drug used in combination with vincristine and a glucocorticoid (eg, dexamethasone) to treat acute lymphoblastic leukemia (ALL).1,2 We 3-6 and others 7 have reported a rationale for testing L-ASP against low-asparagine synthetase (ASNS) solid tumors as well. L-ASP's primary known enzymatic activity is deamidation of asparagine to aspartic acid and ammonia, but it also deamidates glutamine to glutamic acid and ammonia, although with lower affinity and lower maximal rate. L-ASP therapy is often limited by toxic side effects that are generally attributed to the glutaminase activity. 8,9 Those side effects often preclude completion of the full treatment regimen, resulting in poor outcome. 10 The question that arises, however, is whether the therapeutic index of L-ASP could be increased by decreasing its glutaminase activity 8,9 or whether that would also decrease the anticancer effect commensurately.One side of the debate hypothesizes that L-ASP's therapeutic index can be improved by increasing glutaminase activity. In support of that hypothesis, data collected over the last decade have suggested that glutaminase activity generally increases the efficacy of L-ASP and is sometimes required to achieve an anticancer effect. Those studies have reported asparaginase activity to be expendable. [11][12][13][...

Metabolomics is a rapidly advancing field, and much of our understanding of the subject has come from research on cell lines. However, the results and interpretation of such studies depend on appropriate normalization of the data; ineffective or poorly chosen normalization methods can lead to frankly erroneous conclusions. That is a recurrent challenge because robust, reliable methods for normalization of data from cells have not been established. In this study, we have compared several methods for normalization of metabolomic data from cell extracts. Total protein concentration, cell count, and DNA concentration exhibited strong linear correlations with seeded cell number, but DNA concentration was found to be the most generally useful method for the following reasons: 1) DNA concentration showed the greatest consistency across a range of cell numbers; 2) DNA concentration was the closest to proportional with cell number; 3) DNA samples could be collected from the same dish as the metabolites; and 4) cell lines that grew in clumps were difficult to count accurately. We therefore conclude that DNA concentration is a widely applicable method for normalizing metabolomic data from adherent cell lines.

Advances in metabolomics, particularly for research on cancer, have increased the demand for accurate, highly sensitive methods for measuring glutamine (Gln) and glutamic acid (Glu) in cell cultures and other biological samples. N-terminal Gln and Glu residues in proteins or peptides have been reported to cyclize to pyroglutamic acid (pGlu) during liquid chromatography (LC)-mass spectrometry (MS) analysis, but cyclization of free Gln and Glu to free pGlu during LC-MS analysis has not been well-characterized. Using an LC-MS/MS protocol that we developed to separate Gln, Glu, and pGlu, we found that free Gln and Glu cyclize to pGlu in the electrospray ionization source, revealing a previously uncharacterized artifact in metabolomic studies. Analysis of Gln standards over a concentration range from 0.39 to 200 μM indicated that a minimum of 33% and maximum of almost 100% of Gln was converted to pGlu in the ionization source, with the extent of conversion dependent on fragmentor voltage. We conclude that the sensitivity and accuracy of Gln, Glu, and pGlu quantitation by electrospray ionization-based mass spectrometry can be improved dramatically by using (i) chromatographic conditions that adequately separate the three metabolites, (ii) isotopic internal standards to correct for in-source pGlu formation, and (iii) user-optimized fragmentor voltage for acquisition of the MS spectra. These findings have immediate impact on metabolomics and metabolism research using LC-MS technologies.

The peroxidation of arachidonic acid (AA) catalyzed by cyclooxygenase (COX) is a well known free radical-mediated process that forms many bioactive products. Due to a lack of appropriate methodologies, however, no comprehensive structural evidence has been found previously for the formation of COX-mediated and AA-derived free radicals. Here we have used a combination of LC/ESR and LC/MS with a spin trap, α-[4-pyridyl-1-oxide]-N-tert-butyl nitrone (POBN), to characterize the carbon-centered radicals formed from COX-catalyzed AA peroxidation in vitro, including cellular peroxidation in human prostate cancer cells (PC-3). Three types of radicals with numerous isomers were trapped by POBN as ESR-active peaks and MS-active ions of m/z 296, m/z 448, and m/z 548, all stemming from PGF2-type alkoxyl radicals. One of these was a novel radical centered on the carbon-carbon double bond nearest the PGF ring, caused by an unusual β-scission of PGF2-type alkoxyl radicals. The complementary non-radical product was 1-hexanol, another novel β-scission product, instead of the more common aldehyde. The characterization of these novel products formed from in vitro peroxidation provides a new mechanistic insight into COX-catalyzed AA peroxidation in cancer biology.

Smoking is a major risk factor for the development of Bladder Cancer (BLCA); however, the functional consequences of the carcinogens in tobacco smoke and BLCA-associated metabolic alterations remains poorly defined. We assessed the metabolic profiles in BLCA smokers and non-smokers, and identified the key alterations in their metabolism. Liquid Chromatography – Mass Spectrometry (LC-MS), and bioinformatic analysis were performed to determine the metabolome associated with BLCA smokers and were further validated in cell line models. Smokers with BLCA were found to have elevated levels of methylated metabolites, polycyclic aromatic hydrocarbons (PAHs), DNA adducts and DNA damage. DNA methyltransferase 1 (DNMT1) expression was significantly higher in smokers than non-smokers with BLCA. An integromics approach, using multiple patient cohorts, revealed strong associations between smokers and high-grade BLCA. In vitro exposure to the tobacco smoke carcinogens, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and benzo[a]pyrene (BaP) led to increase in levels of methylated metabolites, DNA adducts, and extensive DNA damage in BLCA cells. Co-treatment of BLCA cells with these carcinogens and the methylation inhibitor 5-aza-2′-deoxycytidine (AZA) rewired the methylated metabolites, DNA adducts, DNA damage. These findings were confirmed through the isotopic labeled metabolic flux analysis. Screens using smoke associated metabolites and DNA adducts could provide robust biomarkers and improve individual risk prediction in BLCA smokers. Non-invasive predictive biomarkers that can stratify the risk of developing BLCA in smokers could aid in early detection and treatment.