bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2019‒07‒14
28 papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research

  1. Clin Nutr. 2019 Jun 26. pii: S0261-5614(19)30268-7. [Epub ahead of print]
      BACKGROUND & AIMS: Metabolic syndrome (MetS) induces major disturbances in plasma metabolome, reflecting abnormalities of several metabolic pathways. Recent evidences have demonstrated that the consumption of dairy products may protect from MetS, but the mechanisms remains unknown. The present study aimed at identify how the consumption of different types of dairy products could modify the changes in plasma metabolome during MetS.METHODS: In this observational study, we analyzed how the consumption of dairy products could modify the perturbations in the plasma metabolome induced by MetS in a sample of 298 participants (61 with MetS) from the French MONA LISA survey. Metabolomic profiling was analyzed with UPLC-MS/MS.
    RESULTS: Subjects with MetS exhibited major changes in plasma metabolome. Significant differences in plasma levels of branched chain amino acids, gamma-glutamyl amino acids, and metabolites from arginine and proline metabolism were observed between healthy control and Mets subjects. Plasma levels of many lipid species were increased with MetS (mono- and diacylglycerols, eicosanoids, lysophospholipids and lysoplasmalogens), with corresponding decreases in short chain fatty acids and plasmalogens. The consumption of dairy products, notably with a low fat content (milk and fresh dairy products), altered metabolite profiles in plasma from MetS subjects. Specifically, increasing consumption of dairy products promoted accumulation of plasma C15:0 fatty acid and was inversely associated to some circulating lysophospholipids, sphingolipids, gamma-glutamyl amino acids, leukotriene B4 and lysoplasmalogens.
    CONCLUSIONS: the consumption of low fat dairy products could mitigate some of the variations induced by MetS.
    Keywords:  Clinical parameters; Dairy products; Humans; Lipidomic; Metabolic syndrome; Untargeted metabolomics
  2. Metabolomics. 2019 Jul 09. 15(7): 103
      INTRODUCTION: We previously developed a tandem mass spectrometry-based label-free targeted metabolomics analysis framework coupled to two distinct chromatographic methods, reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC), with dynamic multiple reaction monitoring (dMRM) for simultaneous detection of over 200 metabolites to study core metabolic pathways.OBJECTIVES: We aim to analyze a large-scale heterogeneous data compendium generated from our LC-MS/MS platform with both RPLC and HILIC methods to systematically assess measurement quality in biological replicate groups and to investigate metabolite abundance changes and patterns across different biological conditions.
    METHODS: Our metabolomics framework was applied in a wide range of experimental systems including cancer cell lines, tumors, extracellular media, primary cells, immune cells, organoids, organs (e.g. pancreata), tissues, and sera from human and mice. We also developed computational and statistical analysis pipelines, which include hierarchical clustering, replicate-group CV analysis, correlation analysis, and case-control paired analysis.
    RESULTS: We generated a compendium of 42 heterogeneous deidentified datasets with 635 samples using both RPLC and HILIC methods. There exist metabolite signatures that correspond to various phenotypes of the heterogeneous datasets, involved in several metabolic pathways. The RPLC method shows overall better reproducibility than the HILIC method for most metabolites including polar amino acids. Correlation analysis reveals high confidence metabolites irrespective of experimental systems such as methionine, phenylalanine, and taurine. We also identify homocystine, reduced glutathione, and phosphoenolpyruvic acid as highly dynamic metabolites across all case-control paired samples.
    CONCLUSIONS: Our study is expected to serve as a resource and a reference point for a systematic analysis of label-free LC-MS/MS targeted metabolomics data in both RPLC and HILIC methods with dMRM.
    Keywords:  Amino acids; HILIC; LC–MS/MS; Measurement reliability; Metabolite dynamics; RPLC; Targeted metabolomics
  3. J Proteome Res. 2019 Jul 10.
      High-grade serous carcinoma (HGSC) is the most common and deadliest ovarian cancer (OC) type, accounting for 70-80% of OC deaths. This high mortality is largely due to late diagnosis. Early detection is thus crucial to reduce mortality, yet the tumor pathogenesis of HGSC remains poorly understood, making early detection exceedingly difficult. Faithfully and reliably representing the clinical nature of human HGSC, a recently developed triple-knockout (TKO) mouse model offers a unique opportunity to examine the entire disease spectrum of HGSC. Metabolic alterations were investigated by applying ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to serum samples collected from these mice at premalignant, early, and advanced stages of HGSC. This comprehensive analysis revealed a panel of 29 serum metabolites that distinguished mice with HGSC from controls and mice with uterine tumors with over 95% accuracy. Meanwhile, our panel could further distinguish early-stage HGSC from controls with 100% accuracy and from advanced-stage HGSC with over 90% accuracy. Important identified metabolites included phospholipids, sphingomyelins, sterols, N-acyltaurine, oligopeptides, bilirubin, 2(3)-hydroxysebacic acids, uridine, N-acetylneuraminic acid, and pyrazine derivatives. Overall, our study provides insights into dysregulated metabolism associated with HGSC development and progression, and serves as a useful guide toward early detection.
    Keywords:  biomarkers; carcinoma; high-grade serous ovarian cancer; mouse model; ultra-performance liquid chromatography−mass spectrometry; untargeted metabolomics
  4. Carcinogenesis. 2019 Jul 08. pii: bgz128. [Epub ahead of print]
      Racial/ethnic disparities have a significant impact on bladder cancer outcomes with African-American patients demonstrating inferior survival over European-American patients. We hypothesized that epigenetic difference in methylation of tumor DNA is an underlying cause of this survival health disparity. We analyzed bladder tumors from African-American and European-American patients using reduced representation bisulfite sequencing (RRBS) to annotate differentially methylated DNA regions. Liquid chromatography-mass spectrometry (LC-MS/MS) based metabolomics and flux studies were performed to examine metabolic pathways that showed significant association to the discovered DNA methylation patterns. RRBS analysis showed frequent hypermethylated CpG islands in African-American patients. Further analysis showed that these hypermethylated CpG islands patients are commonly located in the promoter regions of xenobiotic enzymes that are involved in suppressing bladder cancer progression. On follow up, LC-MS/MS revealed accumulation of glucuronic acid, S-adenosylhomocysteine and a decrease in S-adenosylmethionine, corroborating findings from the RRBS and mRNA expression analysis indicating increased glucuronidation and methylation capacities in African-American patients. Flux analysis experiments with 13C labelled glucose in cultured African-American bladder cancer cells confirmed these findings. Collectively, our studies revealed robust differences in methylation-related metabolism and expression of enzymes regulating xenobiotic metabolism in African American patients indicates that race/ethnic differences in tumor biology may exist in bladder cancer.
    Keywords:  Bladder Cancer; Epigenetics; Health disparity; Metabolomics; and Xenobiotic metabolism
  5. J Pharmacol Exp Ther. 2019 Jul 12. pii: jpet.119.258947. [Epub ahead of print]
      It is well recognized that many cancers are "addicted" to a constant supply of fatty acids (FAs) and exhibit brisk de novo FA synthesis. Upregulation of a key lipogenic enzyme, fatty acid synthase (FASN), is a near-universal feature of human cancers and their precursor lesions, and has been associated with chemoresistance, tumor metastasis, and diminished patient survival. FASN inhibition has been shown to be effective in killing cancer cells, but progress in the field has been hindered by off-target effects and poor pharmaceutical properties of candidate compounds. Our initial hit (1) was identified from a high-throughput screening effort by the Sanford-Burnham Center for Chemical Genomics using purified FASN thioesterase domain (FASN-TE). Despite being a potent inhibitor of purified FASN-TE, 1 proved highly unstable in mouse plasma and only weakly cytotoxic to breast cancer (BC) cells in vitro. An iterative process of synthesis, cytotoxicity testing, and plasma stability assessment was used to identify a new lead (41). This lead is more cytotoxic against multiple BC cell lines than (-)-trans-C75, the literature standard for inhibiting FASN, is stable in mouse plasma, and shows negligible cytotoxic effects against non-tumorigenic mammary epithelial cells. Compound 41 also has drug-like physical properties based on Lipinski's Rules and is therefore a valuable new lead for targeting fatty acid synthesis to exploit the requirement of tumor cells for fatty acids. SIGNIFICANCE STATEMENT: An iterative process of synthesis and biological testing was used to identify a novel thioesterase domain FASN inhibitor that has drug-like properties, is more cytotoxic to breast cancer cells than the widely used (-)-trans-C75, and has negligible effects on the growth and proliferation of non-cancerous mammary epithelial cells. Our studies have both confirmed the value of using potent and selective FASN inhibitors in the treatment of BC cells and shown that the availability of exogenous lipoproteins may impact both cancer cell FA metabolism and survival.
    Keywords:  breast cancer; cancer; drug discovery; lipids; palmitic acid
  6. Anal Chem. 2019 Jul 12.
      Glycosylation is one of the most important post-translational modifications essential for modulating biological functions on cellular surfaces and within cells. Glycan structures are not predictable from the genome since their biosynthesis is non-template driven and subject to multiple sequential and competitive glycosyltransferases/glycosidases. From a structural viewpoint, their analysis presents a particular challenge in terms of sensitivity and structural characterization. Porous graphitized carbon liquid chromatography coupled mass spectrometry (PGCLC-MS) is arguably the gold-standard for the structural characterization of glycoconjugates, especially complex mixtures typical in biological samples. This high performance is due in large part to chromatographic separation of isomers and the information delivered by collision induced fragmentation of each glycan in the mass spectrometer. More recently, ion mobility mass spectrometry (IM-MS) has emerged as an effective tool for gas-phase separation of isomeric oligosaccharides that has been demonstrated with small oligosaccharides and N-glycans. Here, we present a direct comparison of the IM- and LC-separation of O-glycans from porcine gastric and human salivary mucins. Our results identify structures, which are resolved by PGCLC and/or IM, validating the combination of the two methods. Taken together, the incorporation of both techniques into a single platform would be powerful and undoubtedly valuable for determining the full glycome of unknown samples.
  7. Mol Cell Proteomics. 2019 Jul 08. pii: mcp.RA118.001232. [Epub ahead of print]
      Tumors are heterogeneous tissues with different types of cells such as cancer cells, fibroblasts, and lymphocytes. While the morphological features of tumors are critical for cancer diagnosis and prognosis, the underlying molecular events and genes for tumor morphology are far from being clear. With the advancement in computational pathology and accumulation of large amount of cancer samples with matched molecular and histopathology data, researchers can carry out integrative analysis to investigate this issue. In this study, we systematically examine the relationships between morphological features and various molecular data in breast cancers. Specifically, we identified 73 breast cancer patients from the TCGA and CPTAC projects matched whole slide images, RNA-seq, and proteomic data. By calculating 100 different morphological features and correlating them with the transcriptomic and proteomic data, we inferred four major biological processes associated with various interpretable morphological features. These processes include metabolism, cell cycle, immune response, and extracellular matrix development, which are all hallmarks of cancers and the associated morphological features are related to area, density, and shapes of epithelial cells, fibroblasts, and lymphocytes. In addition, protein specific biological processes were inferred solely from proteomic data, suggesting the importance of proteomic data in obtaining a holistic understanding of the molecular basis for tumor tissue morphology. Furthermore, survival analysis yielded specific morphological features related to patient prognosis, which have a strong association with important molecular events based on our analysis. Overall, our study demonstrated the power for integrating multiple types of biological data for cancer samples in generating new hypothesis as well as identifying potential biomarkers predicting patient outcome. Future work includes causal analysis to identify key regulators for cancer tissue development and validating the findings using more independent datasets.
    Keywords:  Breast cancer; Cell cycle*; Computational pathology; Imaging genomics; Immune response; Morphology; Omics; Proteogenomics; Systems biology*; Tumor microenvironment*
  8. Cancers (Basel). 2019 Jul 05. pii: E948. [Epub ahead of print]11(7):
      A distinctive feature of cancer cells of various origins involves alterations of the composition of lipids, with significant enrichment in monounsaturated fatty acids. These molecules, in addition to being structural components of newly formed cell membranes of intensely proliferating cancer cells, support tumorigenic signaling. An increase in the expression of stearoyl-CoA desaturase 1 (SCD1), the enzyme that converts saturated fatty acids to ∆9-monounsaturated fatty acids, has been observed in a wide range of cancer cells, and this increase is correlated with cancer aggressiveness and poor outcomes for patients. Studies have demonstrated the involvement of SCD1 in the promotion of cancer cell proliferation, migration, metastasis, and tumor growth. Many studies have reported a role for this lipogenic factor in maintaining the characteristics of cancer stem cells (i.e., the population of cells that contributes to cancer progression and resistance to chemotherapy). Importantly, both the products of SCD1 activity and its direct impact on tumorigenic pathways have been demonstrated. Based on these findings, SCD1 appears to be a significant player in the development of malignant disease and may be a promising target for anticancer therapy. Numerous chemical compounds that exert inhibitory effects on SCD1 have been developed and preclinically tested. The present review summarizes our current knowledge of the ways in which SCD1 contributes to the progression of cancer and discusses opportunities and challenges of using SCD1 inhibitors for the treatment of cancer.
    Keywords:  SCD1 inhibitors; lipid metabolism; monounsaturated fatty acids; stearoyl-CoA desaturase 1 (SCD1); targeted therapy
  9. Mol Clin Oncol. 2019 Jul;11(1): 3-14
      Accurate diagnosis of colorectal cancer (CRC) relies on the use of invasive tools such as colonoscopy and sigmoidoscopy. Non-invasive tools are less sensitive in detecting the disease, particularly in the early stage. A number of researchers have used metabolomics analyses on serum/plasma samples of patients with CRC compared with normal healthy individuals in an effort to identify biomarkers for CRC. The aim of the present review is to compare reported serum metabolomics profiles of CRC and to identify common metabolites affected among these studies. A literature search was performed to include any experimental studies on global metabolomics profile of CRC using serum/plasma samples published up to March 2018. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool was used to assess the quality of the studies reviewed. In total, nine studies were included. The studies used various analytical platforms and were performed on different populations. A pathway enrichment analysis was performed using the data from all the studies under review. The most affected pathways identified were protein biosynthesis, urea cycle, ammonia recycling, alanine metabolism, glutathione metabolism and citric acid cycle. The metabolomics analysis revealed levels of metabolites of glycolysis, tricarboxylic acid cycle, anaerobic respiration, protein, lipid and glutathione metabolism were significantly different between cancer and control samples. Although the majority of differentiating metabolites identified were different in the different studies, there were several metabolites that were common. These metabolites include pyruvic acid, glucose, lactic acid, malic acid, fumaric acid, 3-hydroxybutyric acid, tryptophan, phenylalanine, tyrosine, creatinine and ornithine. The consistent dysregulation of these metabolites among the different studies suggest the possibility of common diagnostic biomarkers for CRC.
    Keywords:  biomarkers; colorectal cancer; metabolomics; pathways; serum
  10. Mol Cell Proteomics. 2019 Jul 09. pii: mcp.RA118.001221. [Epub ahead of print]
      Protein biomarkers for epithelial ovarian cancer are critical for the early detection of the cancer to improve patient prognosis and for the clinical management of the disease to monitor treatment response and to detect recurrences. Unfortunately, the discovery of protein biomarkers is hampered by the limited availability of reliable and sensitive assays needed for the reproducible quantification of proteins in complex biological matrices such as blood plasma. In recent years, targeted mass spectrometry, exemplified by Selected Reaction Monitoring (SRM) has emerged as a method, capable of overcoming this limitation. Here, we present a comprehensive SRM-based strategy for developing plasma-based protein biomarkers for epithelial ovarian cancer and illustrate how the SRM platform, when combined with rigorous experimental design and statistical analysis, can result in detection of predictive analytes.Our biomarker development strategy first involved a discovery-driven proteomic effort to derive potential N-glycoprotein biomarker candidates for plasma-based detection of human ovarian cancer from a genetically engineered mouse model of endometrioid ovarian cancer, which accurately recapitulates the human disease. Next, 65 candidate markers selected from proteins of different abundance in the discovery dataset were reproducibly quantified with SRM assays across a large cohort of over 200 plasma samples from ovarian cancer patients and healthy controls. Finally, these measurements were used to derive a 5-protein signature for distinguishing individuals with epithelial ovarian cancer from healthy controls. The sensitivity of the candidate biomarker signature in combination with CA125 ELISA-based measurements currently used in clinic, exceeded that of CA125 ELISA-based measurements alone. The SRM-based strategy in this study is broadly applicable. It can be used in any study that requires accurate and reproducible quantification of selected proteins in a high-throughput and multiplexed fashion.
    Keywords:  Cancer biomarker(s); Ovarian cancer; Plasma or serum analysis; Quantification; Selected reaction monitoring; Statistics; Targeted mass spectrometry
  11. Endocr Rev. 2019 Jul 11. pii: er.2018-00262. [Epub ahead of print]
      Steroid biosynthesis and metabolism is reflected by the serum steroid metabolome and, in even more detail, by the 24-hour urine steroid metabolome, which can provide unique insights into alterations of steroid flow and output indicative of underlying conditions. Mass spectrometry-based steroid metabolome profiling has allowed for the identification of unique multi-steroid signatures associated with disorders of steroid biosynthesis and metabolism that can be used for personalized approaches to diagnosis, differential diagnosis and prognostic prediction. In addition, steroid metabolome analysis has been used successfully as a discovery tool, for the identification of novel steroidogenic disorders and pathways as well as revealing insights into the pathophysiology of adrenal disease. Increased availability and technological advances in mass spectrometry-based methodologies have refocused attention on steroid metabolome profiling and facilitated the development of high-throughput steroid profiling methods soon to reach clinical practice. Furthermore, steroid metabolomics, the combination of mass spectrometry-based steroid analysis with machine learning-based approaches, has facilitated the development of powerful customized diagnostic approaches. In this review, we provide a comprehensive up-to-date overview of the utility of steroid metabolome analysis for the diagnosis and management of inborn disorders of steroidogenesis and autonomous adrenal steroid excess in the context of adrenal tumors.
  12. Sci Rep. 2019 Jul 08. 9(1): 9822
      Ultra-performance liquid chromatography - mass spectrometry (UPLC-MS) is widely used for untargeted metabolomics in biomedical research. To optimize the quality and precision of UPLC-MS metabolomic analysis, evaluation of blank samples for the elimination of background features is required. Although blanks are usually run either at the beginning or at the end of a sequence of samples, a systematic analysis of their effect of the instrument performance has not been properly documented. Using the analysis of two common bio-fluids (plasma and urine), we describe how the injection of blank samples within a sequence of samples may affect both the chromatographic and MS detection performance depending on several factors, including the sample matrix and the physicochemical properties of the metabolites of interest. The analysis of blanks and post-blank conditioning samples using t-tests, PCA and guided-PCA provides useful information for the elimination of background UPLC-MS features, the identification of column carry over and the selection of the number of samples required to achieve a stable performance.
  13. Cell Rep. 2019 Jul 09. pii: S2211-1247(19)30792-2. [Epub ahead of print]28(2): 512-525.e6
      Drug resistance is a significant hindrance to effective cancer treatment. Although resistance mechanisms of epidermal growth factor receptor (EGFR) mutant cancer cells to lethal EGFR tyrosine kinase inhibitors (TKI) treatment have been investigated intensively, how cancer cells orchestrate adaptive response under sublethal drug challenge remains largely unknown. Here, we find that 2-h sublethal TKI treatment elicits a transient drug-tolerant state in EGFR mutant lung cancer cells. Continuous sublethal treatment reinforces this tolerance and eventually establishes long-term TKI resistance. This adaptive process involves H3K9 demethylation-mediated upregulation of branched-chain amino acid aminotransferase 1 (BCAT1) and subsequent metabolic reprogramming, which promotes TKI resistance through attenuating reactive oxygen species (ROS) accumulation. Combination treatment with TKI- and ROS-inducing reagents overcomes this drug resistance in preclinical mouse models. Clinical information analyses support the correlation of BCAT1 expression with the EGFR TKI response. Our findings reveal the importance of BCAT1-engaged metabolism reprogramming in TKI resistance in lung cancer.
    Keywords:  BCAT1; EGFR tyrosine kinase inhibitors; branched-chain amino acids; drug resistance; lung cancer; metabolic reprogramming
  14. Cell Chem Biol. 2019 Jul 02. pii: S2451-9456(19)30205-3. [Epub ahead of print]
      Human cancers require fatty acid synthase (FASN)-dependent de novo long-chain fatty acid synthesis for proliferation. FASN is therefore an attractive drug target, but fast technologies for reliable label-free cellular compound profiling are lacking. Recently, MALDI-mass spectrometry (MALDI-MS) has emerged as an effective technology for discovery of recombinant protein target inhibitors. Here we present an automated, mechanistic MALDI-MS cell assay, which monitors accumulation of the FASN substrate, malonyl-coenzyme A (CoA), in whole cells with limited sample preparation. Profiling of inhibitors, including unpublished compounds, identified compound 1 as the most potent FASN inhibitor (1 nM in A549 cells) discovered to date. Moreover, cellular MALDI-MS assays enable parallel profiling of additional pathway metabolites. Surprisingly, several compounds triggered cytidine 5'-diphosphocholine (CDP-choline) but not malonyl-CoA accumulation indicating that they inhibit diacylglycerol generation but not FASN activity. Taken together, our study suggests that MALDI-MS cell assays may become important tools in drug profiling that provide additional mechanistic insights concerning compound action on metabolic pathways.
    Keywords:  MALDI-mass spectrometry; drug discovery; fatty acid synthase; inhibition; lipid synthesis; malonyl-CoA; mechanistic cell assay; metabolite markers
  15. Eur J Mass Spectrom (Chichester). 2019 Jul 09. 1469066719862423
      Metanephrine and normetanephrine are measured in blood plasma to diagnose different diseases. Simpler sample preparation procedures are preferred but tend to yield less purified extracts. Therefore, thorough investigation of matrix effects is required. In this work, several sample preparation methods and chromatographic modes were compared for liquid chromatography tandem mass spectrometric (with electrospray ionization; LC-ESI-MS/MS) analysis of metanephrine and normetanephrine in blood plasma. Protein precipitation with methanol was found to be sufficient for sample preparation and pentafluorophenyl column provided adequate chromatographic separation. A new cheaper and less labor-intensive approach is proposed where necessary quantitation limits are achieved through a sample preparation containing only protein precipitation and dilution of the sample extract. Matrix effects for different sample preparation methods and the use of isotope-labeled internal standards were evaluated. Unusual interference to D3-labeled internal standard of normetanephrine was discovered - signal of interfering compound increased while the matrix effects were reduced by dilution, e.g. dilution eliminates matrix suppression on interfering compound. The results stress the need to monitor interfering compounds and evaluate matrix effects at every step of method development. Matrix effects and interferences can be different for analytes and their corresponding isotopically labeled internal standards. This means that the use of isotopically labeled internal standards cannot guarantee accuracy of obtained results. New method allows quantification of the low nanomolar concentrations of metanephrine and normetanephrine in plasma samples.
    Keywords:  Metanephrines; isotopically labeled internal standard; liquid chromatography; mass spectrometry; matrix effects
  16. Med Sci (Basel). 2019 Jul 10. pii: E78. [Epub ahead of print]7(7):
      The most appropriate steroids to measure for the diagnosis of hyperandrogenism in polycystic ovary syndrome (PCOS) are still open to debate but should preferably be measured using a high-quality method such as liquid chromatography tandem mass spectrometry (LC-MS/MS). Measurement of testosterone is recommended in all of the current clinical guidelines but other steroids, such as androstenedione and dehydroepiandrosterone sulfate (DHEAS), have also been shown to be useful in diagnosing PCOS and may give additional information on metabolic risk. The 11-oxygenated steroids, and in particular 11KT derived mainly from the adrenal gland, are also increasing in prominence and have been shown to be the dominant androgens in this condition. Polycystic ovary syndrome is a complex syndrome and it is not surprising that each of the clinical phenotypes are associated with different patterns of steroid hormones; it is likely that steroid profiling with LC-MS/MS may be better at identifying hyperandrogensim in each of these phenotypes. Research into PCOS has been hampered by the small sample size of clinical studies previously undertaken and larger studies, preferably using LC-MS/MS profiling of steroids, are needed.
    Keywords:  11-ketotestosterone; androgens; liquid chromatography tandem mass spectrometry (LC-MS/MS); polycystic ovary syndrome (PCOS); testosterone
  17. J Chromatogr A. 2019 Jun 27. pii: S0021-9673(19)30665-X. [Epub ahead of print]
      A comprehensive Collision Cross Section (CCS) library was obtained via Travelling Wave Ion Guide mobility measurements through direct infusion (DI). The library consists of CCS and Mass Spectral (MS) data in negative and positive ElectroSpray Ionisation (ESI) mode for 463 and 479 endogenous metabolites, respectively. For both ionisation modes combined, TWCCSN2 data were obtained for 542 non-redundant metabolites. These data were acquired on two different ion mobility enabled orthogonal acceleration QToF MS systems in two different laboratories, with the majority of the resulting TWCCSN2 values (from detected compounds) found to be within 1% of one another. Validation of these results against two independent, external TWCCSN2 data sources and predicted TWCCSN2 values indicated to be within 1-2% of these other values. The same metabolites were then analysed using a rapid reversed-phase ultra (high) performance liquid chromatographic (U(H)PLC) separation combined with IM and MS (IM-MS) thus providing retention time (tr), m/z and TWCCSN2 values (with the latter compared with the DI-IM-MS data). Analytes for which TWCCSN2 values were obtained by U(H)PLC-IM-MS showed good agreement with the results obtained from DI-IM-MS. The repeatability of the TWCCSN2 values obtained for these metabolites on the different ion mobility QToF systems, using either DI or LC, encouraged the further evaluation of the U(H)PLC-IM-MS approach via the analysis of samples of rat urine, from control and methotrexate-treated animals, in order to assess the potential of the approach for metabolite identification and profiling in metabolic phenotyping studies. Based on the database derived from the standards 63 metabolites were identified in rat urine, using positive ESI, based on the combination of tr, TWCCSN2 and MS data.
    Keywords:  Collision cross section; Ion mobility spectrometry; Metabolic phenotyping; Metabolomics; Metabonomics
  18. Lipids Health Dis. 2019 Jul 08. 18(1): 151
      BACKGROUND: Free fatty acid (FFA) accumulation in proximal tubules plays a fundamental role in the progress of kidney disease. Here, we reported a rare case with undetectable serum FFAs and further evaluated the changes of serum FFAs in patients with chronic renal failure (CRF).METHODS: We analyzed the clinical data of a rare case and 574 CRF patients. The mRNA expression of lipoprotein lipase (LPL), hepatic lipase (HL) and fatty acid synthase (FASN) were determined in the rare case and 30 age-matched healthy males with qPCR.
    RESULTS: This rare case had serious proteinuria, hyperglycemia, lipid disorders and bilateral renal glomerular filtration dysfunction. Compared with healthy males, this case showed a 1.49-fold increase of LPL expression (P < 0.01), a 3.38-fold reduction of HL expression (P < 0.001), and no significant change of FASN expression (P > 0.05). In total, 21.6% of CRF patients showed abnormal FFAs. Biochemical parameters such as blood urea nitrogen (BUN) and creatinine (CREA) significantly differed among groups with low-, normal- or high-level-FFAs. Moreover, serum FFAs was found to be associated with BUN. FFAs decreased in the group with higher BUN (> 17.4 mmol/L) and in the group with lower estimated glomerular filtration rate (eGFR) (< 15 mL/min/1.73m2).
    CONCLUSIONS: The proteinuria, HL low expression and renal function failure may contribute to the FFA reduction, which might imply that the renal function is severely damaged.
    Keywords:  Chronic renal failure; Free fatty acids; Glucose metabolism; Lipid metabolism; Proteinuria
  19. Anal Bioanal Chem. 2019 Jul 06.
      Dysregulated lipid species are linked to various disease pathologies and implicated as potential biomarkers for type 1 diabetes (T1D). However, it is challenging to comprehensively profile the blood specimen lipidome with full structural details of every lipid molecule. The commonly used reversed-phase liquid chromatography-tandem mass spectrometry (RPLC-MS/MS)-based lipidomics approach is powerful for the separation of individual lipid species, but lipids belonging to different classes may still co-elute and result in ion suppression and misidentification of lipids. Using offline mixed-mode and RPLC-based two-dimensional separations coupled with MS/MS, a comprehensive lipidomic profiling was performed on human sera pooled from healthy and T1D subjects. The elution order of lipid molecular species on RPLC showed good correlations to the total number of carbons in fatty acyl chains and total number of double bonds. This observation together with fatty acyl methyl ester analysis was used to enhance the confidence of identified lipid species. The final T1D serum lipid library database contains 753 lipid molecular species with accurate mass and RPLC retention time uniquely annotated for each of the species. This comprehensive human serum lipid library can serve as a database for high-throughput RPLC-MS-based lipidomic analysis of blood samples related to T1D and other childhood diseases. Graphical abstract.
    Keywords:  Accurate mass and time tag; Human serum lipidome; Lipid profiling; Mixed-mode LC; RPLC-MS/MS; Type 1 diabetes
  20. Sci Rep. 2019 Jul 08. 9(1): 9816
      Tissue amino acid profiles depend on the cell types and extracellular components that constitute the tissue, and their functions and activities. We aimed to characterize the tissue amino acid profiles in several types of pancreatic tumors and lesions. We examined tissue amino acid profiles in 311 patients with pancreatic tumors or lesions. We used newly developed LC-MS/MS methods to obtain the profiles, which were compared with clinicopathological data. Each tumor or lesion presented a characteristic tissue amino acid profile. Certain amino acids were markedly altered during the multistep pancreatic carcinogenesis and pancreatic ductal adenocarcinoma (PDAC) progression. A tissue amino acid index (TAAI) was developed based on the amino acids that were notably changed during both carcinogenesis and cancer progression. Univariate and multivariate survival analyses revealed that PDAC patients with a high TAAI exhibited a significantly shorter survival rate, and these findings were validated using a second cohort. We suggest that tissue amino acid profiles are characteristic for normal tissue type, tumor histological type, and pathological lesion, and are representative of the cancer grade or progression stage in multistep carcinogenesis and of malignant characteristics. The TAAI could serve as an independent prognosticator for patients with PDAC.
  21. World J Gastroenterol. 2019 Jun 28. 25(24): 3009-3020
      Nonalcoholic fatty liver disease (NAFLD) is a heterogeneous and complex disease that is imprecisely diagnosed by liver biopsy. NAFLD covers a spectrum that ranges from simple steatosis, nonalcoholic steatohepatitis (NASH) with varying degrees of fibrosis, to cirrhosis, which is a major risk factor for hepatocellular carcinoma. Lifestyle and eating habit changes during the last century have made NAFLD the most common liver disease linked to obesity, type 2 diabetes mellitus and dyslipidemia, with a global prevalence of 25%. NAFLD arises when the uptake of fatty acids (FA) and triglycerides (TG) from circulation and de novo lipogenesis saturate the rate of FA β-oxidation and very-low density lipoprotein (VLDL)-TG export. Deranged lipid metabolism is also associated with NAFLD progression from steatosis to NASH, and therefore, alterations in liver and serum lipidomic signatures are good indicators of the disease's development and progression. This review focuses on the importance of the classification of NAFLD patients into different subtypes, corresponding to the main alteration(s) in the major pathways that regulate FA homeostasis leading, in each case, to the initiation and progression of NASH. This concept also supports the targeted intervention as a key approach to maximize therapeutic efficacy and opens the door to the development of precise NASH treatments.
    Keywords:  Lipid metabolism; Lipidomics; Methionine adenosyltransferase; Multiomics; Nonalcoholic steatohepatitis; One-carbon metabolism; Precision medicine; S-adenosylmethionine; Steatosis; Very low-density lipoproteins
  22. Anal Chem. 2019 Jul 12.
      Judicious selection of mass spectrometry (MS) acquisition parameters is essential for effectively profiling the broad diversity and dynamic range of biomolecules. Typically, acquisition parameters are individually optimized to maximally characterize analytes from each new sample matrix. This time-consuming process often ignores the synergistic relationship between MS method parameters, producing sub-optimal results. Here we detail the creation of an algorithm which accurately simulates LC-MS/MS lipidomic data acquisition performance for a benchtop quadrupole-Orbitrap MS system. By coupling this simulation tool with a genetic algorithm for constrained parameter optimization, we demonstrate the efficient identification of LC-MS/MS method parameter sets individually suited for specific sample matrices. Finally, we utilize the in silico simulation to examine how continued developments in MS speed and sensitivity will further increase the power of MS lipidomics as a vital tool for impactful biochemical analysis.
  23. JCI Insight. 2019 Jul 11. pii: 128438. [Epub ahead of print]4(13):
      BACKGROUNDStatins have pleiotropic effects on lipid metabolism. The relationship between these effects and future cardiovascular events is unknown. We characterized the changes in lipids upon pravastatin treatment and defined the relationship with risk reduction for future cardiovascular events.METHODSPlasma lipids (n = 342) were measured in baseline and 1-year follow-up samples from a Long-Term Intervention with Pravastatin in Ischaemic Disease (LIPID) study subcohort (n = 4991). The associations of changes in lipids with treatment and cardiovascular outcomes were investigated using linear and Cox regression. The effect of treatment on future cardiovascular outcomes was examined by the relative risk reduction (RRR).RESULTSPravastatin treatment was associated with changes in 206 lipids. Species containing arachidonic acid were positively associated while phosphatidylinositol species were negatively associated with pravastatin treatment. The RRR from pravastatin treatment for cardiovascular events decreased from 23.5% to 16.6% after adjustment for clinical risk factors and change in LDL-cholesterol (LDL-C) and to 3.0% after further adjustment for the change in the lipid ratio PI(36:2)/PC(38:4). Change in PI(36:2)/PC(38:4) mediated 58% of the treatment effect. Stratification of patients into quartiles of change in PI(36:2)/PC(38:4) indicated no benefit of pravastatin in the fourth quartile.CONCLUSIONThe change in PI(36:2)/PC(38:4) predicted benefit from pravastatin, independent of change in LDL-C, demonstrating its potential as a biomarker for monitoring the clinical benefit of statin treatment in secondary prevention.TRIAL REGISTRATIONAustralian New Zealand Clinical Trials Registry identifier ACTRN12616000535471.FUNDINGBristol-Myers Squibb; NHMRC grants 211086, 358395, and 1029754; NHMRC program grant 1149987; NHMRC fellowship 108026; and the Operational Infrastructure Support Program of the Victorian government of Australia.
    Keywords:  Cardiovascular disease; Cholesterol; Clinical Trials; Clinical practice; Metabolism
  24. Cancer Cell. 2019 Jul 08. pii: S1535-6108(19)30294-6. [Epub ahead of print]36(1): 84-99.e8
      To identify therapeutic targets in acute myeloid leukemia (AML), we chemically interrogated 200 sequenced primary specimens. Mubritinib, a known ERBB2 inhibitor, elicited strong anti-leukemic effects in vitro and in vivo. In the context of AML, mubritinib functions through ubiquinone-dependent inhibition of electron transport chain (ETC) complex I activity. Resistance to mubritinib characterized normal CD34+ hematopoietic cells and chemotherapy-sensitive AMLs, which displayed transcriptomic hallmarks of hypoxia. Conversely, sensitivity correlated with mitochondrial function-related gene expression levels and characterized a large subset of chemotherapy-resistant AMLs with oxidative phosphorylation (OXPHOS) hyperactivity. Altogether, our work thus identifies an ETC complex I inhibitor and reveals the genetic landscape of OXPHOS dependency in AML.
    Keywords:  NADH dehydrogenase inhibitor; acute myeloid leukemia; electron transport chain complex I; metabolism; mitochondrial respiration; oxidative phosphorylation; personalized medicine; therapeutic target
  25. Clin Cancer Res. 2019 Jul 12. pii: clincanres.0189.2019. [Epub ahead of print]
      PURPOSE: Atypical teratoid/rhabdoid tumors are aggressive infantile brain tumors with poor survival. Recent advancements have highlighted significant molecular heterogeneity in AT/RT with an aggressive subgroup featuring over-expression of the MYC proto-oncogene. We perform the first comprehensive metabolic profiling of patient-derived AT/RT cell lines to identify therapeutic susceptibilities in high MYC-expressing AT/RT.EXPERIMENTAL DESIGN: Metabolites were extracted from AT/RT cell lines and separated in ultra-high performance liquid chromatography mass spectrometry (UHPLC-MS). Glutamine metabolic inhibition with 6-diazo-5-oxo-L-norleucine (DON) was tested with growth and cell death assays and survival studies in orthotopic mouse models of AT/RT. Metabolic flux analysis was completed to identify combination therapies to act synergistically to improve survival in high MYC AT/RT.
    RESULTS: Unbiased metabolic profiling of AT/RT cell models identified a unique dependence of high MYC AT/RT on glutamine for survival. The glutamine analogue, DON, selectively targeted high MYC cell lines - slowing cell growth, inducing apoptosis, and extending survival in orthotopic mouse models of AT/RT. Metabolic flux experiments with isotopically labeled glutamine revealed DON inhibition of glutathione synthesis. DON combined with carboplatin further slowed cell growth, induced apoptosis, and extended survival in orthotopic mouse models of high MYC AT/RT.
    CONCLUSIONS: Unbiased metabolic profiling of AT/RT identified susceptibility of high MYC AT/RT to glutamine metabolic inhibition with DON therapy. DON inhibited glutamine-dependent synthesis of glutathione and synergized with carboplatin to extend survival in high MYC AT/RT. These findings can rapidly translate into new clinical trials to improve survival in high MYC AT/RT.
  26. Semin Cancer Biol. 2019 Jul 08. pii: S1044-579X(19)30044-6. [Epub ahead of print]
      In the recent decade, cutting edge molecular and proteomic analysis platforms revolutionized biomarkers discovery in cancers. Melanoma is the prototype with over 51,100 biomarkers discovered and investigated thus far. These biomarkers include tissue based tumor cell and tumor microenvironment biomarkers and circulating biomarkers including tumor DNA (cf-DNA), mir-RNA, proteins and metabolites. These biomarkers provide invaluable information for diagnosis, prognosis and play an important role in prediction of treatment response. In this review, we summarize the most recent discoveries in each of these biomarker categories. We will discuss the challenges in their implementation and standardization and conclude with some perspectives in melanoma biomarker research.
    Keywords:  epigenetic biomarker; melanoma; metabolomics; mir-RNA; proteomics; serum biomarker
  27. Front Pharmacol. 2019 ;10 709
      Reynoutria multiflora (Thunb.) Moldenke (He Shou Wu) has been used for about 20 centuries as a Chinese medicinal herb for its activities of anticancer, anti-hyperlipidemia, and anti-aging. Previously, we found that He Shou Wu ethanol extract could induce apoptosis in hepatocellular carcinoma cells, and we also screened its active components. In this study, we investigated whether lowering lipid metabolism of emodin, a main active component in He Shou Wu, was associated with inhibitory effects in hepatocellular carcinoma cells. The correlation of apoptosis induction and lipid metabolism was investigated. The intrinsic apoptotic cell death, lipid production, and their signaling pathways were investigated in emodin-treated human hepatocellular carcinoma cells Bel-7402. The data showed that emodin triggered apoptosis in Bel-7402 cells. The mitochondrial membrane potential (ΔΨm) was reduced in emodin-treated Bel-7402 cells. We also found that emodin activated the expression of intrinsic apoptosis signaling pathway-related proteins, cleaved-caspase 9 and 3, Apaf 1, cytochrome c (CYTC), apoptosis-inducing factor, endonuclease G, Bax, and Bcl-2. Furthermore, the level of triglycerides and desaturation of fatty acids was reduced in Bel-7402 cells when exposed to emodin. Furthermore, the expression level of messenger RNA (mRNA) and protein of sterol regulatory element binding protein 1 (SREBP1) as well as its downstream signaling pathway and the synthesis and the desaturation of fatty acid metabolism-associated proteins (adenosine triphosphate citrate lyase, acetyl-CoA carboxylase alpha, fatty acid synthase (FASN), and stearoyl-CoA desaturase D) were also decreased. Notably, knock-out of SREBP1 in Bel-7402 cells was also found to induce less intrinsic apoptosis than did emodin. In conclusion, these results indicated that emodin could induce apoptosis in an SREBP1-dependent and SREBP1-independent manner in hepatocellular carcinoma cells.
    Keywords:  SREBP1; emodin; hepatocellular carcinoma cells; intrinsic apoptosis; lipid metabolism
  28. Proteomics. 2019 Jul 10. e1900070
      Direct infusion-based shotgun lipidomics is one of the most powerful and useful tools in comprehensive analysis of lipid species from lipid extracts of various biological samples with high accuracy/precision. However, despite of many advantages, the classical shotgun lipidomics suffers some general dogmas of limitations, such as ion suppression, ambiguous identification of isobaric/isomeric lipid species, and ion source-generated artifacts, restraining the applications in analysis of low abundance lipid species, particularly those less ionizable or isomers that yield almost identical fragmentation patterns. This article reviews on the strategies (such as modifier addition, prefractionation, chemical derivatization, charge feature utilization, etc.) that have been employed to improve/eliminate these limitations in modern shotgun lipidomics approaches (e.g., high mass resolution mass spectrometry-based and multi-dimensional mass spectrometry-based shotgun lipidomics). Therefore, with the enhancement of these strategies for shotgun lipidomics, comprehensive analysis of lipid species including isomeric/isobaric species can be achieved in a more accurate and effective manner, greatly substantiating the aberrant lipid metabolism, signaling trafficking, and homeostasis under pathological conditions. This article is protected by copyright. All rights reserved.
    Keywords:  In-source fragmentation; Ion suppression; Isobaric/isomeric species; Multi-dimensional mass spectrometry; Shotgun lipidomics