bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒07‒12
33 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Nature. 2020 Jul 08.
      The mitochondrial electron transport chain (ETC) is necessary for tumour growth1-6 and its inhibition has demonstrated anti-tumour efficacy in combination with targeted therapies7-9. Furthermore, human brain and lung tumours display robust glucose oxidation by mitochondria10,11. However, it is unclear why a functional ETC is necessary for tumour growth in vivo. ETC function is coupled to the generation of ATP-that is, oxidative phosphorylation and the production of metabolites by the tricarboxylic acid (TCA) cycle. Mitochondrial complexes I and II donate electrons to ubiquinone, resulting in the generation of ubiquinol and the regeneration of the NAD+ and FAD cofactors, and complex III oxidizes ubiquinol back to ubiquinone, which also serves as an electron acceptor for dihydroorotate dehydrogenase (DHODH)-an enzyme necessary for de novo pyrimidine synthesis. Here we show impaired tumour growth in cancer cells that lack mitochondrial complex III. This phenotype was rescued by ectopic expression of Ciona intestinalis alternative oxidase (AOX)12, which also oxidizes ubiquinol to ubiquinone. Loss of mitochondrial complex I, II or DHODH diminished the tumour growth of AOX-expressing cancer cells deficient in mitochondrial complex III, which highlights the necessity of ubiquinone as an electron acceptor for tumour growth. Cancer cells that lack mitochondrial complex III but can regenerate NAD+ by expression of the NADH oxidase from Lactobacillus brevis (LbNOX)13 targeted to the mitochondria or cytosol were still unable to grow tumours. This suggests that regeneration of NAD+ is not sufficient to drive tumour growth in vivo. Collectively, our findings indicate that tumour growth requires the ETC to oxidize ubiquinol, which is essential to drive the oxidative TCA cycle and DHODH activity.
  2. Trends Analyt Chem. 2019 Nov;pii: 115330. [Epub ahead of print]120
      Shotgun lipidomics is one of the most powerful tools in analysis of cellular lipidomes in lipidomics, which directly analyzes lipids from lipid extracts of diverse biological samples with high accuracy/precision. However, despite its great advances in high throughput analysis of cellular lipidomes, low coverage of poorly ionized lipids, especially those species in very low abundance, and some types of isomers within complex lipid extracts by shotgun lipidomics remains a huge challenge. In the past few years, many strategies have been developed to enhance shotgun lipidomics for comprehensive analysis of lipid species. Chemical derivatization represents one of the most attractive and effective strategies, already receiving considerable attention. This review focuses on novel advanced derivatization strategies for enhancing shotgun lipidomics. It is anticipated that with the development of enhanced strategies, shotgun lipidomics can make greater contributions to biological and biomedical research.
    Keywords:  Bis(monoacylglycero) phosphate; chemical derivatization; multi-dimensional mass spectrometry; plasmalogen; polyphosphoinositides; shotgun lipidomics
  3. J Exp Med. 2020 Sep 07. pii: e20192389. [Epub ahead of print]217(9):
      Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis, and new therapies are needed. Altered metabolism is a cancer vulnerability, and several metabolic pathways have been shown to promote PDAC. However, the changes in cholesterol metabolism and their role during PDAC progression remain largely unknown. Here we used organoid and mouse models to determine the drivers of altered cholesterol metabolism in PDAC and the consequences of its disruption on tumor progression. We identified sterol O-acyltransferase 1 (SOAT1) as a key player in sustaining the mevalonate pathway by converting cholesterol to inert cholesterol esters, thereby preventing the negative feedback elicited by unesterified cholesterol. Genetic targeting of Soat1 impairs cell proliferation in vitro and tumor progression in vivo and reveals a mevalonate pathway dependency in p53 mutant PDAC cells that have undergone p53 loss of heterozygosity (LOH). In contrast, pancreatic organoids lacking p53 mutation and p53 LOH are insensitive to SOAT1 loss, indicating a potential therapeutic window for inhibiting SOAT1 in PDAC.
  4. Anal Chem. 2020 Jul 10.
      The unbiased selection of peptide precursors makes data-independent acquisition (DIA) an advantageous alternative to data-dependent acquisition (DDA) for discovery proteomics, but traditional multiplexed quantification approaches employing mass difference labeling or isobaric tagging are incompatible with DIA. Here, we describe a strategy that permits multiplexed quantification by DIA using mass defect-based N,N-dimethyl leucine (mdDiLeu) tags and high-resolution tandem mass spectrometry (MS2) analysis. Millidalton mass differences between mdDiLeu isotopologues produce fragment ion multiplet peaks separated in mass by as little as 5.8 mDa, enabling up to 4-plex quantification in DIA MS2 spectra. Quantitative analysis of yeast samples displayed comparable accuracy and precision for MS2-based DIA and MS1-based DDA methods. Multiplexed DIA analysis of cerebrospinal fluid revealed the dynamic proteome changes in Alzheimer's disease, demonstrating its utility for discovery of potential clinical biomarkers. We show that the mdDiLeu tagging approach for multiplexed DIA is a viable methodology for investigating proteome changes, particularly for low-abundance proteins, in different biological matrices.
  5. Cancer Cell Int. 2020 ;20 280
      Background: Aberrant activity of cell cycle proteins is one of the key somatic events in non-small cell lung cancer (NSCLC) pathogenesis. In most NSCLC cases, the retinoblastoma protein tumor suppressor (RB) becomes inactivated via constitutive phosphorylation by cyclin dependent kinase (CDK) 4/6, leading to uncontrolled cell proliferation. Palbociclib, a small molecule inhibitor of CDK4/6, has shown anti-tumor activity in vitro and in vivo, with recent studies demonstrating a functional role for palbociclib in reprogramming cellular metabolism. While palbociclib has shown efficacy in preclinical models of NSCLC, the metabolic consequences of CDK4/6 inhibition in this context are largely unknown.Methods: In our study, we used a combination of stable isotope resolved metabolomics using [U-13C]-glucose and multiple in vitro metabolic assays, to interrogate the metabolic perturbations induced by palbociclib in A549 lung adenocarcinoma cells. Specifically, we assessed changes in glycolytic activity, the pentose phosphate pathway (PPP), and glutamine utilization. We performed these studies following palbociclib treatment with simultaneous silencing of RB1 to define the pRB-dependent changes in metabolism.
    Results: Our studies revealed palbociclib does not affect glycolytic activity in A549 cells but decreases glucose metabolism through the PPP. This is in part via reducing activity of glucose 6-phosphate dehydrogenase, the rate limiting enzyme in the PPP. Additionally, palbociclib enhances glutaminolysis to maintain mitochondrial respiration and sensitizes A549 cells to the glutaminase inhibitor, CB-839. Notably, the effects of palbociclib on both the PPP and glutamine utilization occur in an RB-dependent manner.
    Conclusions: Together, our data define the metabolic impact of palbociclib treatment in A549 cells and may support the targeting CDK4/6 inhibition in combination with glutaminase inhibitors in NSCLC patients with RB-proficient tumors.
    Keywords:  Glutaminolysis; Lung cancer; Metabolism; PPP; Palbociclib; RB
  6. J Cancer. 2020 ;11(16): 4641-4651
      Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive human malignancies. The metabolomic approaches are developed to discover the novel biomarkers of PDAC. Methods: 550 preoperative, postoperative PDAC and normal controls (NCs) serums were employed to characterize metabolic alterations in training and validation sets by LC-MS. Results: The results of PLS-DA analysis indicated that three groups could be distinguished clearly and the post-PDAC group is adjacent to a normal group as compared with pre-PDAC group. Further results showed that histidinyl-lysine significantly increased whereas docosahexaenoic acid and LysoPC (14:0) decreased in pre-PDAC patients as compared with NCs. And these three markers had a significant tendency to recover after tumor resection. The validation set results revealed that for CA19-9 negative patients, 92.3% (12/13) of them can be screened using these three metabolites. The combination of these markers could significantly improve the diagnostic performance for PDAC, with higher sensitivity (0.93), specificity (0.92) and AUC (0.97). Moreover, network and pathways analyses explored the latent relationship among differential metabolites. The glycerolipid metabolism and primary bile acid synthesis showed variation in network and pathway analysis. Conclusions: These three markers combined with CA199 displayed high sensitivity and specificity for detecting PDAC patients from NCs. The results indicated that these three metabolites could be regarded as potential biomarkers to distinguish PDAC from NCs.
    Keywords:  Biomarkers; Metabolomics; Multivariate analysis; Pancreatic Ductal Adenocarcinoma
  7. J Biol Chem. 2020 Jul 08. pii: jbc.RA120.013619. [Epub ahead of print]
      Recently, eicosanoid-lysophospholipids were identified as novel metabolites generated from the direct cyclooxygenase- or lipoxygenase-catalyzed oxidation of 2-arachidonoyl-lysophospholipids produced from either PLA1-mediated hydrolysis of diacyl arachidonoyl-phospholipids or through the cytochrome c-catalyzed oxidative hydrolysis of the vinyl ether linkage of arachidonoyl-plasmalogens.  Although the metabolic pathways generating eicosanoid-lysophospholipids have been increasingly appreciated, the signaling functions of eicosanoid-lysophospholipids remain largely unknown. Herein, we demonstrate that 2-12(S)-HETE-lysophospholipids as well as non-esterified 12(S)-HETE are potent lipid mediators that activate THP-1 human monocytic cells to generate tumor necrosis factor α (TNFα) and interleukin 8 (IL8).  Remarkably, low nanomolar concentrations of 12(S)-HETE-lysophospholipids, but not other oxidized signaling lipids examined, activated THP-1 cells resulting in the production of large amounts of TNFα. Moreover, TNFα release induced by 12(S)-HETE-lysophospholipids was inhibited by the TNFα converting enzyme inhibitor TAPI-0 indicating normal processing of TNFa in THP-1 cells stimulated with these agonists. Western Blot analyses revealed that 12(S)-HETE-lysophospholipids activated the phosphorylation of NFκB p65 suggesting activation of the canonical NFκB signaling pathway. Importantly, activation of THP-1 cells to release TNFα was stereoselective with 12(S)-HETE favored over 12(R)-HETE. Furthermore, the EC50 of 2-12(S)-HETE-lysophosphatidylcholine in activating THP-1 cells was 2.1 nM, while the EC50 of free 12(S)-HETE was 23 nM. Additionally, lipid extracts of activated platelets were separated by RP-HPLC demonstrating the coelution of 12(S)-HETE with fractions initiating TNFα release. Collectively, these results demonstrate the potent signaling properties of 2-12(S)-HETE-lysophospholipids and 12(S)-HETE by their ability to release TNFα and activate NFκB signaling thereby revealing a previously unknown role of 2-12(S)-HETE-lysophospholipids in mediating inflammatory responses.
    Keywords:  12(S)-HETE; NF-kappa B (NF-KB); cytokine; iPLA2gamma; inflammation; lysophospholipid; oxidized lysophospholipids; phosphorylation
  8. Theranostics. 2020 ;10(16): 7053-7069
      Lipids, the basic components of the cell membrane, execute fundamental roles in almost all the cell activities including cell-cell recognition, signalling transduction and energy supplies. Lipid metabolism is elementary for life sustentation that balances activity between synthesis and degradation. An accumulating amount of data has indicated abnormal lipid metabolism in cancer stem cells (CSCs), and that the alteration of lipid metabolism exerts a great impact on CSCs' properties such as the capability of self-renewal, differentiation, invasion, metastasis, and drug sensitivity and resistance. CSCs' formation and maintenance cannot do without the regulation of fatty acids and cholesterol. In normal cells and embryonic development, fatty acids and cholesterol metabolism are regulated by some important signalling pathways (such as Hedgehog, Notch, Wnt signalling pathways); these signalling pathways also play crucial roles in initiating and/or maintaining CSCs' properties, and such signalling is shown to be commonly modulated by the abnormal lipid metabolism in CSCs; on the other hand, the altered lipid metabolism in turn modifies the cell signalling and generates additional impacts on CSCs. Metabolic rewiring is considered as an ideal hallmark of CSCs, and metabolic alterations would be promising therapeutic targets of CSCs for aggressive tumors. In this review, we summarize the most updated findings of lipid metabolic abnormalities in CSCs and prospect the potential applications of targeting lipid metabolism for anticancer treatment.
    Keywords:  Cancer stem cells; lipid metabolism; self-renewal; signalling pathways
  9. Front Oncol. 2020 ;10 981
      Background: Colorectal cancer (CRC) is the result of complex interactions between the tumor's molecular profile and metabolites produced by its microenvironment. Despite recent studies identifying CRC molecular subtypes, a metabolite classification system is still lacking. We aimed to explore the distinct phenotypes and subtypes of CRC at the metabolite level. Methods: We conducted an untargeted metabolomics analysis of 51 paired tumor tissues and adjacent mucosa using ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry. Multivariate analysis including principal component analysis, orthogonal partial least squares discriminant analysis and heat maps, univariate analysis, and pathway analysis were used to identify potential metabolite phenotypes of CRC. Unsupervised consensus clustering was used to identify robust metabolite subtypes, and evaluated their clinical relevance. Results: A total of 173 metabolites (including nucleotides, carbohydrates, free fatty acids, and choline) were identified between CRC tumor tissue and adjacent mucosa. We found that lipid metabolism was closely related to the occurrence and progression of CRC. In particular, CRC tissues could be divided into three subtypes, and statistically significant correlations between different subtypes and clinical prognosis were observed. Conclusions: CRC tumor tissue exhibits distinct metabolite phenotypes. Metabolite differences between subtypes may provide a basis and direction for further clinical individualized treatment planning.
    Keywords:  CRC; lipid metabolism; metabolomics; prognosis; subtypes
  10. Prostaglandins Leukot Essent Fatty Acids. 2020 Jun 27. pii: S0952-3278(20)30115-0. [Epub ahead of print]160 102157
      INTRODUCTION: Obesity is associated with adipose tissue inflammation which in turn drives insulin resistance and the development of type 2 diabetes. Oxylipins are a collection of lipid metabolites, subdivided in different classes, which are involved in inflammatory cascades. They play important roles in regulating adipose tissue homeostasis and inflammation and are therefore putative biomarkers for obesity-associated adipose tissue inflammation and the subsequent risk of type 2 diabetes onset. The objective for this study is to design an assay for a specific oxylipin class and evaluate these as potential prognostic biomarker for obesity-associated adipose tissue inflammation and type 2 diabetes.METHODS: An optimized workflow was developed to extract oxylipins from plasma using solid-phase extraction followed by analysis using ultra-high performance liquid chromatography coupled to a triple quadrupole mass spectrometer in multiple reaction monitoring mode. This workflow was applied to clinical plasma samples obtained from obese-type 2 diabetes patients and from lean and obese control subjects.
    RESULTS: The assay was analytically validated and enabled reproducible analyses of oxylipins extracted from plasma with acceptable sensitivities. Analysis of clinical samples revealed discriminative values for four oxylipins between the type 2 diabetes patients and the lean and obese control subjects, viz. PGF2α, PGE2, 15-keto-PGE2 and 13,14-dihydro-15-keto-PGE2. The combination of PGF2α and 15-keto-PGE2 had the most predictive value to discriminate type 2 diabetic patients from lean and obese controls.
    CONCLUSIONS: This proof-of-principle study demonstrates the potential value of oxylipins as biomarkers to discriminate obese individuals from obese-type 2 diabetes patients.
    Keywords:  Assay developmentl; Biomarker validation; Mass spectrometry; Oxylipins; Type 2 diabetes
  11. J Biol Chem. 2020 Jul 07. pii: jbc.REV119.007624. [Epub ahead of print]
      Metabolites are not only substrates in metabolic reactions, but also signaling molecules controlling a wide range of cellular processes. Discovery of the oncometabolite 2-hydroxyglutarate (2HG) provides an important link between metabolic dysfunction and cancer, unveiling the signaling function of metabolites in regulating epigenetic and epitranscriptomic modifications, genome integrity, and signal transduction. It is now known that cancer cells sense and remodel their metabolic network to support biogenesis, caused by or resulting in the dysregulation of various metabolites. Cancer cells can sense alterations in metabolic intermediates to better coordinate multiple biological processes and enhance cell metabolism. Recent studies have demonstrated that metabolite signaling is involved in the regulation of malignant transformation, cell proliferation, epithelial-to-mesenchymal transition (EMT), differentiation blockade, and cancer stemness. Additionally, intercellular metabolite signaling modulates inflammatory response and immunosurveillance in the tumor microenvironment. Here, we review recent advances in cancer-associated metabolite signaling. An in-depth understanding of metabolite signaling will provide new opportunities for the development of therapeutic interventions that target cancer.
    Keywords:  Metabolite; Sensing; Signaling; cancer; metabolic disease; metabolic regulation; metabolomics; oncometabolite; signaling
  12. Cell. 2020 Jul 09. pii: S0092-8674(20)30676-0. [Epub ahead of print]182(1): 245-261.e17
      Genomic studies of lung adenocarcinoma (LUAD) have advanced our understanding of the disease's biology and accelerated targeted therapy. However, the proteomic characteristics of LUAD remain poorly understood. We carried out a comprehensive proteomics analysis of 103 cases of LUAD in Chinese patients. Integrative analysis of proteome, phosphoproteome, transcriptome, and whole-exome sequencing data revealed cancer-associated characteristics, such as tumor-associated protein variants, distinct proteomics features, and clinical outcomes in patients at an early stage or with EGFR and TP53 mutations. Proteome-based stratification of LUAD revealed three subtypes (S-I, S-II, and S-III) related to different clinical and molecular features. Further, we nominated potential drug targets and validated the plasma protein level of HSP 90β as a potential prognostic biomarker for LUAD in an independent cohort. Our integrative proteomics analysis enables a more comprehensive understanding of the molecular landscape of LUAD and offers an opportunity for more precise diagnosis and treatment.
    Keywords:  biomarker; clinical outcome; drug target; genomics; lung adenocarcinoma; mass spectrometry; phosphoproteomics; precision medicine; proteomics; regulatory network
  13. J Lipid Res. 2020 Jul 10. pii: jlr.RA120000984. [Epub ahead of print]
      The backbone of all sphingolipids (SLs) is a sphingoid long chain base (LCB) to which a fatty acid is N-acylated. Considerable variability exists in the chain length and degree of saturation of both these hydrophobic chains, and recent work has implicated ceramides with different LCBs and N-acyl chains in distinct biological processes; moreover, they may play different roles in disease states and possibly even act as prognostic biomarkers. We now demonstrate that the half-life, or turnover rate, of ceramides containing diverse N-acyl chains is different. By means of a pulse-labeling protocol using stable-isotope, deuterated free fatty acids, and following their incorporation into ceramide and downstream SLs, we show that very-long chain (VLC) ceramides containing C24:0- or C24:1-fatty acids turnover more rapidly than long chain (LC) ceramides containing C16:0- or C18:0-fatty acids, due to the faster metabolism of the former into VLC-sphingomyelin and VLC-hexosylceramide. In contrast, d16:1- and d18:1-ceramides show similar rates of turnover, indicating that the length of the sphingoid LCB does not influence the flux of ceramides through the biosynthetic pathway. Together, these data demonstrate that the N-acyl chain length of SLs may not only affect membrane biophysical properties but also influences the rate of metabolism of SLs so as to regulate their levels and perhaps their biological functions.
    Keywords:  Acyl Chain; Ceramides; Fatty acid; Fatty acid/Metabolism; Hexosylceramide; Lipidomics; Sphingolipids; Sphingomyelin; Stable isotopes; Turnover
  14. Metabolites. 2020 Jul 02. pii: E271. [Epub ahead of print]10(7):
      Glycomics measurements, like all other high-throughput technologies, are subject to technical variation due to fluctuations in the experimental conditions. The removal of this non-biological signal from the data is referred to as normalization. Contrary to other omics data types, a systematic evaluation of normalization options for glycomics data has not been published so far. In this paper, we assess the quality of different normalization strategies for glycomics data with an innovative approach. It has been shown previously that Gaussian Graphical Models (GGMs) inferred from glycomics data are able to identify enzymatic steps in the glycan synthesis pathways in a data-driven fashion. Based on this finding, here, we quantify the quality of a given normalization method according to how well a GGM inferred from the respective normalized data reconstructs known synthesis reactions in the glycosylation pathway. The method therefore exploits a biological measure of goodness. We analyzed 23 different normalization combinations applied to six large-scale glycomics cohorts across three experimental platforms: Liquid Chromatography - ElectroSpray Ionization - Mass Spectrometry (LC-ESI-MS), Ultra High Performance Liquid Chromatography with Fluorescence Detection (UHPLC-FLD), and Matrix Assisted Laser Desorption Ionization - Furier Transform Ion Cyclotron Resonance - Mass Spectrometry (MALDI-FTICR-MS). Based on our results, we recommend normalizing glycan data using the 'Probabilistic Quotient' method followed by log-transformation, irrespective of the measurement platform. This recommendation is further supported by an additional analysis, where we ranked normalization methods based on their statistical associations with age, a factor known to associate with glycomics measurements.
    Keywords:  data normalization; gaussian graphical models; glycomics
  15. Cell Rep. 2020 Jul 07. pii: S2211-1247(20)30829-9. [Epub ahead of print]32(1): 107848
      Immunotherapy shifted the paradigm of cancer treatment. The clinical approval of immune checkpoint blockade and adoptive cell transfer led to considerable success in several tumor types. However, for a significant number of patients, these therapies have proven ineffective. Growing evidence shows that the metabolic requirements of immune cells in the tumor microenvironment (TME) greatly influence the success of immunotherapy. It is well established that the TME influences energy consumption and metabolic reprogramming of immune cells, often inducing them to become tolerogenic and inefficient in cancer cell eradication. Increasing nutrient availability using pharmacological modulators of metabolism or antibodies targeting specific immune receptors are strategies that support energetic rewiring of immune cells and boost their anti-tumor capacity. In this review, we describe the metabolic features of the diverse immune cell types in the context of the TME and discuss how these immunomodulatory strategies could synergize with immunotherapy to circumvent its current limitations.
  16. Geroscience. 2020 Jul 06.
      Adipose tissue plays an essential role in metabolic health. Ames dwarf mice are exceptionally long-lived and display metabolically beneficial phenotypes in their adipose tissue, providing an ideal model for studying the intersection between adipose tissue and longevity. To this end, we assessed the metabolome and lipidome of adipose tissue in Ames dwarf mice. We observed distinct lipid profiles in brown versus white adipose tissue of Ames dwarf mice that are consistent with increased thermogenesis and insulin sensitivity, such as increased cardiolipin and decreased ceramide concentrations. Moreover, we identified 5-hydroxyeicosapentaenoic acid (5-HEPE), an ω-3 fatty acid metabolite, to be increased in Ames dwarf brown adipose tissue (BAT), as well as in circulation. Importantly, 5-HEPE is increased in other models of BAT activation and is negatively correlated with body weight, insulin resistance, and circulating triglyceride concentrations in humans. Together, these data represent a novel lipid signature of adipose tissue in a mouse model of extreme longevity.
    Keywords:  Aging; Ames dwarf; Beige adipose tissue; Brown adipose tissue; Lipidomics; Metabolomics; Thermogenesis
  17. Nat Commun. 2020 Jul 07. 11(1): 3400
      The Pan-Cancer Analysis of Whole Genomes (PCAWG) project generated a vast amount of whole-genome cancer sequencing resource data. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2658 cancers across 38 tumor types, we provide a user's guide to the five publicly available online data exploration and visualization tools introduced in the PCAWG marker paper. These tools are ICGC Data Portal, UCSC Xena, Chromothripsis Explorer, Expression Atlas, and PCAWG-Scout. We detail use cases and analyses for each tool, show how they incorporate outside resources from the larger genomics ecosystem, and demonstrate how the tools can be used together to understand the biology of cancers more deeply. Together, the tools enable researchers to query the complex genomic PCAWG data dynamically and integrate external information, enabling and enhancing interpretation.
  18. Nat Rev Cancer. 2020 Jul 06.
      Through the successes of checkpoint blockade and adoptive cellular therapy, immunotherapy has become an established treatment modality for cancer. Cellular metabolism has emerged as a critical determinant of the viability and function of both cancer cells and immune cells. In order to sustain prodigious anabolic needs, tumours employ a specialized metabolism that differs from untransformed somatic cells. This metabolism leads to a tumour microenvironment that is commonly acidic, hypoxic and/or depleted of critical nutrients required by immune cells. In this context, tumour metabolism itself is a checkpoint that can limit immune-mediated tumour destruction. Because our understanding of immune cell metabolism and cancer metabolism has grown significantly in the past decade, we are on the cusp of being able to unravel the interaction of cancer cell metabolism and immune metabolism in therapeutically meaningful ways. Although there are metabolic processes that are seemingly fundamental to both cancer and responding immune cells, metabolic heterogeneity and plasticity may serve to distinguish the two. As such, understanding the differential metabolic requirements of the diverse cells that comprise an immune response to cancer offers an opportunity to selectively regulate immune cell function. Such a nuanced evaluation of cancer and immune metabolism can uncover metabolic vulnerabilities and therapeutic windows upon which to intervene for enhanced immunotherapy.
  19. Int J Mol Sci. 2020 Jul 03. pii: E4753. [Epub ahead of print]21(13):
      Women with polycystic ovary syndrome (PCOS) are more likely to develop endometrial cancer (EC). The molecular mechanisms which increase the risk of EC in PCOS are unclear. Derangements in lipid metabolism are associated with EC, but there have been no studies, investigating if this might increase the risk of EC in PCOS. This was a cross-sectional study of 102 women in three groups of 34 (PCOS, EC and controls) at Nottingham University Hospital, UK. All participants had clinical assessments, followed by obtaining plasma and endometrial tissue samples. Lipidomic analyses were performed using liquid chromatography (LC) coupled with high resolution mass spectrometry (HRMS) and the obtained lipid datasets were screened using standard software and databases. Using multivariate data analysis, there were no common markers found for EC and PCOS. However, on univariate analyses, both PCOS and EC endometrial tissue samples showed a significant decrease in monoacylglycerol 24:0 and capric acid compared to controls. Further studies are required to validate these findings and investigate the potential role of monoacylglycerol 24:0 and capric acid in the link between PCOS with EC.
    Keywords:  PCOS; biomarkers; endometrial cancer; lipidomic
  20. Protein Cell. 2020 Jul 08.
      Pluripotent stem cells (PSCs) can immortally self-renew in culture with a high proliferation rate, and they possess unique metabolic characteristics that facilitate pluripotency regulation. Here, we review recent progress in understanding the mechanisms that link cellular metabolism and homeostasis to pluripotency regulation, with particular emphasis on pathways involving amino acid metabolism, lipid metabolism, the ubiquitin-proteasome system and autophagy. Metabolism of amino acids and lipids is tightly coupled to epigenetic modification, organelle remodeling and cell signaling pathways for pluripotency regulation. PSCs harness enhanced proteasome and autophagy activity to meet the material and energy requirements for cellular homeostasis. These regulatory events reflect a fine balance between the intrinsic cellular requirements and the extrinsic environment. A more complete understanding of this balance will pave new ways to manipulate PSC fate.
    Keywords:  amino acid metabolism; autophagy; lipid metabolism; pluripotent stem cell (PSC); ubiquitin-proteasome system (UPS)
  21. Clin Chim Acta. 2020 Jul 02. pii: S0009-8981(20)30313-2. [Epub ahead of print]
      The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.
    Keywords:  Lipids; biomarkers; blood; clinical profiles; liquid chromatography; tandem mass spectrometry
  22. Biochim Biophys Acta Mol Cell Biol Lipids. 2020 Jul 03. pii: S1388-1981(20)30153-0. [Epub ahead of print] 158761
      A family of glycerol-based lysolipid mediators comprises lysophosphatidic acid as a representative phospholipidic member but also a monoacylglycerol as a non-phosphorus-containing member. These critical lysolipid mediators are known to be produced from different lysophospholipids by actions of lysophospholipases C and D in mammals. Some members of the glycerophosphodiesterase (GDE) family have attracted recent attention due to their phospholipid-metabolizing activity. In this study, we found selective depletion of lysophosphatidylinositol among lysophospholipids in the culture medium of COS-7 cells transfected with a vector containing glycerophosphodiester phosphodiesterase 2 (GDPD2, GDE3). Thin-layer chromatography and liquid chromatography-tandem mass spectrometry of lipids extracted from GDE3-transfected COS-7 cells exposed to fluorescent analogs of phosphatidylinositol (PI) revealed that GDE3 acted as an ecto-type lysophospholipase C preferring endogenous lysophosphatidylinositol and PI having a long-chain acyl and a short-chain acyl group rather than endogenous PI and its fluorescent analog having two long chain acyl groups. In MC3T3-E1 cells cultured with an osteogenic or mitogenic medium, mRNA expression of GDE3 was increased by culturing in 10% fetal bovine serum for several days, concomitant with increased activity of ecto-lysophospholipase C, converting arachidonoyl-lysophosphatidylinositol, a physiological agonist of G protein-coupled receptor 55, to arachidonoylglycerol, a physiological agonist of cannabinoid receptors 1 and 2. We suggest that GDE3 acts as an ecto-lysophospholipase C, by switching signaling from lysophosphatidylinositol to that from arachidonoylglycerol in an opposite direction in mouse bone remodeling.
    Keywords:  COS-7 cell; Glycerophosphodiester phosphodiesterase; Lysophospholipase; MC3T3-E1 cell; Osteoblast; Tandem mass spectrometry
  23. Metabolites. 2020 Jun 25. pii: E262. [Epub ahead of print]10(6):
      In this era of precision medicine, there is an increasingly urgent need for highly sensitive tests for detecting tumors such as colon cancer (CC), a silent disease where the first symptoms may take 10-15 years to appear. Mass spectrometry-based lipidomics is an emerging tool for such clinical diagnosis. We used ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry operating in high energy collision spectral acquisition mode (MSE) mode (UPLC-QTOF-MSE) and gas chromatography (GC) to investigate differences between the plasmatic lipidic composition of CC patients and control (CTR) subjects. Key enzymes in lipidic metabolism were investigated using immuno-based detection assays. Our partial least squares discriminant analysis (PLS-DA) resulted in a suitable discrimination between CTR and CC plasma samples. Forty-two statistically significant discriminating lipids were putatively identified. Ether lipids showed a prominent presence and accordingly, a decrease in glyceronephosphate O-acyltransferase (GNPAT) enzyme activity was found. A receiver operating characteristic (ROC) curve built for three plasmalogens of phosphatidylserine (PS), named PS(P-36:1), PS(P-38:3) and PS(P-40:5), presented an area under the curve (AUC) of 0.998, and sensitivity and specificity of 100 and 85.7% respectively. These results show significant differences in CC patients' plasma lipid composition that may be useful in discriminating them from CTR individuals with a special role for plasmalogens.
    Keywords:  biomarkers; colon cancer; lipidomic; mass spectrometry; plasmalogens
  24. Biochim Biophys Acta Mol Basis Dis. 2020 Jul 07. pii: S0925-4439(20)30242-8. [Epub ahead of print] 165894
      Prostate cancer (PCa) is the most commonly diagnosed cancer in men worldwide. Screening and management of PCa remain controversial and, therefore, the discovery of novel molecular biomarkers is urgently needed. Alteration in cancer cell metabolism is a recognized hallmark of cancer, whereby cancer cells exhibit high glycolytic rates with subsequent lactate production, regardless of oxygen availability. To maintain the hyperglycolytic phenotype, cancer cells efficiently export lactate through the monocarboxylate transporters MCT1 and MCT4. The impact of inhibiting lactate production/extrusion on PCa cell survival and aggressiveness was investigated in vitro and ex vivo using primary tumor and metastatic PCa cell lines and the chicken embryo chorioallantoic membrane (CAM) model. In this study, we showed the metastatic PCa cell line (DU125) displayed higher expression levels of MCT1/4 isoforms and glycolysis-related markers than the localized prostate tumor-derived cell line (22RV1), indicating these proteins are differentially expressed throughout prostate malignant transformation. Moreover, disruption of lactate export by MCT1/4 silencing resulted in a decrease in PCa cell growth and motility. To support these results, we pharmacological inhibited lactate production (via inhibition of LDH) and release (via inhibition of MCTs) and a reduction in cancer cell growth in vitro and in vivo was observed. In summary, our data provide evidence that MCT1 and MCT4 are important players in prostate neoplastic progression and that inhibition of lactate production/export can be explored as a strategy for PCa treatment.
    Keywords:  Glycolytic metabolism; Lactate; Monocarboxylate transporters (MCTs), lactate dehydrogenase (LDH); Prostate cancer; Warburg effect
  25. Signal Transduct Target Ther. 2020 Jul 10. 5(1): 124
      Cancer cells must rewire cellular metabolism to satisfy the demands of unbridled growth and proliferation. As such, most human cancers differ from normal counterpart tissues by a plethora of energetic and metabolic reprogramming. Transcription factors of the MYC family are deregulated in up to 70% of all human cancers through a variety of mechanisms. Oncogenic levels of MYC regulates almost every aspect of cellular metabolism, a recently revisited hallmark of cancer development. Meanwhile, unrestrained growth in response to oncogenic MYC expression creates dependency on MYC-driven metabolic pathways, which in principle provides novel targets for development of effective cancer therapeutics. In the current review, we summarize the significant progress made toward understanding how MYC deregulation fuels metabolic rewiring in malignant transformation.
  26. J Proteome Res. 2020 Jul 09.
      Obesity is a complex disorder where the genome interacts with diet and environmental factors to ultimately influence body mass, composition and shape. Numerous studies have investigated how bulk lipid metabolism of adipose tissue changes with obesity, and in particular how the composition of triglycerides (TGs) changes with increased adipocyte expansion. However, reflecting the analytical challenge posed by examining non-TG lipids in extracts dominated by TGs, the glycerophospholipid (PL) composition of cell membranes has been seldom investigated. PLs contribute to a variety of cellular processes including maintaining organelle functionality, providing an optimised environment for membrane-associated proteins and as pools for metabolites (e.g. choline for one-carbon metabolism and for methylation of DNA). We have conducted a comprehensive lipidomic study of white adipose tissue in mice who become obese either through genetic modification (ob/ob), diet (high fat diet) or a combination of the two using both solid phase extraction and ion mobility to increase coverage of the lipidome. Composition changes in seven classes of lipid (free fatty acids, diglycerides, TGs, phosphatidylcholines, lyso-phosphatidylcholines, phosphatidylethanolamines, and phosphatidylserines) correlated with perturbations in one-carbon metabolism and transcriptional changes in adipose tissue. We demonstrate that changes in TGs that dominate the overall lipid composition of white adipose tissue are distinct from diet-induced alterations of PLs, the predominant components of the cell membranes. PLs correlate better with transcriptional and one-carbon metabolism changes within the cell, suggesting the compositional changes that occur in cell membranes during adipocyte expansion have far-reaching functional consequences. Data is available at MetaboLights under the submission number: MTBLS1775.
  27. Anal Chem. 2020 Jul 08.
      Cardiolipin (CL) analysis demands high specificity, due to the extensive diversity of CL structures, and high sensitivity, due to their low relative abundance within the lipidome. While electrospray ionization mass spectrometry (ESI-MS) is the most widely used technology in lipidomics, the potential for multiple charging presents unique challenges for CL identification and quantification. Depending on the conditions, ESI-MS of lipid extracts in negative ion mode can give rise to cardiolipins ionized as both singly and doubly deprotonated anions. This signal degeneracy diminishes the signal-to-noise ratio while in addition (for direct infusion) the dianion population falls within a m/z range already heavily congested with monoanions from more abundant glycerophospholipid subclasses. Herein, we describe a direct infusion strategy for CL profiling from total lipid extracts utilizing gas-phase proton transfer ion/ion reactions. In this approach, lipid extracts are ionized by negative ion ESI generating both singly deprotonated phospholipids and doubly deprotonated CL anions. Charge-reduction of the negative ion population by ion/ion reactions leads to an enhancement in singly deprotonated [CL - H]¯ species via proton transfer to the corresponding [CL - 2H]²¯ dianions. To concentrate the [CL - H]¯ anion signal, multiple iterations of ion accumulation and proton transfer ion/ion reaction can be performed prior to subsequent interrogation. Mass-selection and collisional activation of the enriched population of [CL - H]¯ anions facilitates the assignment of individual fatty acyl substituents and phosphatidic acid moieties. Demonstrated advantages of this new approach derive from the improved performance in complex mixture analysis affording detailed characterization of low abundant CLs directly from a total biological extract.
  28. Chembiochem. 2020 Jul 08.
      Cancer is the second leading cause of death and, 1 in 6 deaths globally is due to cancer. Cancer metabolism is a complex and one of the most actively researched area in cancer biology. Metabolic reprogramming in cancer cells entails activities which involves several enzymes and metabolites to convert nutrient into building blocks that alter energy metabolism to fuel rapid cell division. Metabolic dependencies in cancer generate signature metabolites that have key regulatory roles in tumorigenesis. In this minireview, we highlight recent advances of the popular methods ingrained in biochemistry research such as stable and flux isotope analysis, and radioisotope labeling which have valuable use in elucidating cancer metabolites. These methods together with analytical tools such as chromatography, nuclear magnetic resonance spectroscopy and mass spectrometry have helped to bring about the exploratory work in understanding the role of important as well as obscure metabolites in cancer cells. Information obtained from these analyses significantly contribute in the diagnosis and prognosis of tumors leading to potential therapeutic targets for cancer therapy.
    Keywords:  Energy metabolism; isotope flux analysis; metabolic reprogramming; radioisotope labeling; stable isotope
  29. Proteomics. 2020 Jul 08. e1900344
      Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), large-scale mass spectrometry (MS) based proteomic profiling of different kinds of human tumor samples have provided huge amount of valuable data for both basic and clinical researchers. Accurate prediction for tumor and non-tumor samples, as well as the tumor types has become a key step for biological and medical research, such as biomarker discovery, diagnosis and monitoring of diseases. The traditional MS-based classification strategy mainly depends on the identification and quantification results of MS data, which has some inherent limitations, such as the low identification rate of MS data. Here, we proposed a deep learning-based tumor classifier directly using MS raw data, which is independent of the identification and quantification results of MS data. We firstly detected and extracted the potential precursors with intensities and retention times from MS data as input. Then, we trained a deep learning-based classifier, which can accurately distinguish between the tumor and non-tumor samples. Finally, we demonstrated that the deep learning-based classifier has a good performance compared with other machine learning methods and may help researchers to find the potential biomarkers which are likely to be missed by the traditional strategy. This article is protected by copyright. All rights reserved.
    Keywords:  MS data; deep learning; proteomics; tumor classifier
  30. Anal Chem. 2020 Jul 10.
      Ganglioside is an important class of lipid species involving in intercellular signaling and various diseases, especially for neurodegenerative diseases. Systematic ganglioside profiling is challenging due to their naturally low abundance and highly diverse species. Herein, a new data independent acquisition and parallel reaction monitoring (DIA/PRM) method with superior sensitivity was developed. The untargeted DIA acquisition consecutively records all the precursor ion and fragment ions at the same time, while the targeted PRM analysis with versatile higher collisional dissociation generates full MS/MS spectra for structure elucidation and verification. As compared with traditional data dependent acquisition (DDA), the DIA/PRM method unbiasedly detected majority of abundant ganglioside species and as low as 50 pg ganglioside in the untargeted manner. Gangliosides in four kinds of biological samples including the mouse brain, mouse plasma, Hela cell and human colon cancer tissue were systematically identified, and low abundant ganglioside species were further extended based on linear chromatography retention rules of the most frequently detected ganglioside species. A total of 383 ganglioside features were defined with 329 of them derived from 32 ganglioside species. Taking advantage of the high-resolution MS analysis, rare ganglioside species were further elucidated according to their characteristic fragment ions and neutral losses. In total, 18 gangliosides with ceramide carbon number from 20 to 25 and modified gangliosides, including 18 acetylated, 8 di-acetylated, 1 phosphorylated, 36 N-glycolyneuraminic acid (NeuGc)-containing and 7 di-NeuGc-containing gangliosides, were newly identified. The developed DIA/PRM method therefore generated a rich ganglioside resource for further functional exploration and is an unique alternative of DDA analysis for global ganglioside profiling in various biological systems.
  31. Cell Metab. 2020 Jul 02. pii: S1550-4131(20)30311-9. [Epub ahead of print]
      Amino acids are fundamental building blocks supporting life. Their role in protein synthesis is well defined, but they contribute to a host of other intracellular metabolic pathways, including ATP generation, nucleotide synthesis, and redox balance, to support cellular and organismal function. Immune cells critically depend on such pathways to acquire energy and biomass and to reprogram their metabolism upon activation to support growth, proliferation, and effector functions. Amino acid metabolism plays a key role in this metabolic rewiring, and it supports various immune cell functions beyond increased protein synthesis. Here, we review the mechanisms by which amino acid metabolism promotes immune cell function, and how these processes could be targeted to improve immunity in pathological conditions.
    Keywords:  ▪▪▪
  32. Cancer Res. 2020 Jul 06. pii: canres.2269.2019. [Epub ahead of print]
      The complex yet interrelated connections between cancer metabolism, gene expression, and oncogenic driver genes have the potential to identify novel biomarkers and drug targets with prognostic and therapeutic value. Here we effectively integrated metabolomics and gene expression data from breast cancer mouse models through a novel unbiased correlation-based network analysis. This approach identified 35 metabolite and 34 gene hubs with the most network correlations. These hubs have prognostic value and are likely integral to tumor metabolism and breast cancer. The gene hub Aquaporin-7 (AQP7), a water and glycerol channel, was identified as a novel regulator of breast cancer. AQP7 was prognostic of overall survival in breast cancer patients. In mouse breast cancer models, reduced expression of Aqp7 caused reduced primary tumor burden and lung metastasis. Metabolomics and complex lipid profiling of cells and tumors with reduced Aqp7 revealed significantly altered lipid metabolism, glutathione metabolism, and urea/arginine metabolism compared to controls. These data identify Aqp7 as a critical regulator of metabolic and signaling responses to environmental cellular stresses in breast cancer, highlighting AQP7 as a potential cancer-specific therapeutic vulnerability.