bims-mascan 2021-06-20 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2021–06–20
29 papers selected by
Giovanny Rodríguez Blanco, University of Edinburgh

Peroxidation of n-3 and n-6 polyunsaturated fatty acids in the acidic tumor environment leads to ferroptosis-mediated anticancer effects.
In vitro generation of oxidized standards for lipidomics. Application to major membrane lipid components.
Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics.
mTORC1 and ferroptosis: Regulatory mechanisms and therapeutic potential.
iPLA2β-mediated lipid detoxification controls p53-driven ferroptosis independent of GPX4.
Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS.
Fatty acid synthesis in prostate cancer: vulnerability or epiphenomenon?
Advanced tandem mass spectrometry in metabolomics and lipidomics-methods and applications.
Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics.
Detection of Posttranslational Modification Autoantibodies Using Peptide Microarray.
Deepening of lipidome annotation by associating cross-metathesis reaction with mass spectrometry: application to an in vitro model of corneal toxicity.
Metabolome analysis reveals a diversity of cancer tissues in advanced epithelial ovarian cancer.
Computational Variation: An Underinvestigated Quantitative Variability Caused by Automated Data Processing in Untargeted Metabolomics.
Lipolytic enzymes and free fatty acids at the endothelial interface.
Limited survival and impaired hepatic fasting metabolism in mice with constitutive Rag GTPase signaling.
Glucose metabolic crosstalk and regulation in brain function and diseases.
An overview of lipidomics utilizing cadaver derived biological samples.
Proteomic Characterization of Cytoplasmic Lipid Droplets in Human Metastatic Breast Cancer Cells.
Overcoming chemoresistance by targeting reprogrammed metabolism: the Achilles' heel of pancreatic ductal adenocarcinoma.
Targeting Pyrimidine Metabolism in the Era of Precision Cancer Medicine.
Analytical considerations for reducing the matrix effect for the sphingolipidome quantification in whole blood.
Spatially Resolved Metabolomics Based on Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging Reveals Region-Specific Metabolic Alterations in Diabetic Encephalopathy.
Metabolic reprogramming due to hypoxia in pancreatic cancer: Implications for tumor formation, immunity, and more.
Cancer cells dysregulate PI3K/AKT/mTOR pathway activation to ensure their survival and proliferation: mimicking them is a smart strategy of gammaherpesviruses.
Correction to: CDK4/6 inhibition blocks cancer metastasis through a USP51-ZEB1-dependent deubiquitination mechanism.
Bottom-up and top-down proteomic approaches for the identification, characterization and quantification of the low molecular weight proteome with focus on short open reading frame-encoded peptides.
Development and validation of an LC-MS/MS generic assay platform for small molecule drug bioanalysis.
Amino Acid Trafficking and Skeletal Muscle Protein Synthesis: A Case of Supply and Demand.
MSTracer: A Machine Learning Software Tool for Peptide Feature Detection from Liquid Chromatography-Mass Spectrometry Data.

Cell Metab. 2021 Jun 08. pii: S1550-4131(21)00233-3. [Epub ahead of print]

Peroxidation of n-3 and n-6 polyunsaturated fatty acids in the acidic tumor environment leads to ferroptosis-mediated anticancer effects.

Emeline Dierge, Elena Debock, Céline Guilbaud, Cyril Corbet, Eric Mignolet, Louise Mignard, Estelle Bastien, Chantal Dessy, Yvan Larondelle, Olivier Feron.

  Tumor acidosis promotes disease progression through a stimulation of fatty acid (FA) metabolism in cancer cells. Instead of blocking the use of FAs by acidic cancer cells, we examined whether excess uptake of specific FAs could lead to antitumor effects. We found that n-3 but also remarkably n-6 polyunsaturated FA (PUFA) selectively induced ferroptosis in cancer cells under ambient acidosis. Upon exceeding buffering capacity of triglyceride storage into lipid droplets, n-3 and n-6 PUFA peroxidation led to cytotoxic effects in proportion to the number of double bonds and even more so in the presence of diacylglycerol acyltransferase inhibitors (DGATi). Finally, an n-3 long-chain PUFA-rich diet significantly delayed mouse tumor growth when compared with a monounsaturated FA-rich diet, an effect further accentuated by administration of DGATi or ferroptosis inducers. These data point out dietary PUFA as a selective adjuvant antitumor modality that may efficiently complement pharmacological approaches.

Keywords:  acidosis; cancer; diacylglycerol acyltransferase; docosahexaenoic acid; fatty acids; ferroptosis; lipid droplets; peroxidation; polyunsaturated fatty acids; spheroids

DOI:  https://doi.org/10.1016/j.cmet.2021.05.016
J Chromatogr A. 2021 May 19. pii: S0021-9673(21)00378-2. [Epub ahead of print]1651 462254

In vitro generation of oxidized standards for lipidomics. Application to major membrane lipid components.

Tomás Clive Barker-Tejeda, Alma Villaseñor, Carolina Gonzalez-Riano, Ángeles López-López, Ana Gradillas, Coral Barbas.

  Membrane lipids (sphingolipids, glycerophospholipids, cardiolipins, and cholesteryl esters) are critical in cellular functions. Alterations in the levels of oxidized counterparts of some of these lipids have been linked to the onset and development of many pathologies. Unfortunately, the scarce commercial availability of chemically defined oxidized lipids is a limitation for accurate quantitative analysis, characterization of oxidized composition, or testing their biological effects in lipidomic studies. To address this dearth of standards, several approaches rely on in-house prepared mixtures of oxidized species generated under in vitro conditions from different sources - non-oxidized commercial standards, liposomes, micelles, cells, yeasts, and human preparations - and using different oxidant systems - UVA radiation, air exposure, enzymatic or chemical oxidant systems, among others. Moreover, high-throughput analytical techniques such as liquid chromatography coupled to mass spectrometry (LC-MS) have provided evidence of their capabilities to study oxidized lipids both in in vitro models and complex biological samples. In this review, we describe the commercial resources currently available, the in vitro strategies carried out for obtaining oxidized lipids as standards for LC-MS analysis, and their applications in lipidomics studies, specifically for lipids found in cell and mitochondria membranes.

Keywords:  In vitro oxidant systems; LC-MS; Lipid peroxidation; Oxidative lipidomics; Oxidized lipids; Redox lipidomics; Standards

DOI:  https://doi.org/10.1016/j.chroma.2021.462254
Mass Spectrom Rev. 2021 Jun 18.

Eight key rules for successful data-dependent acquisition in mass spectrometry-based metabolomics.

Emmanuel Defossez, Julien Bourquin, Stephan von Reuss, Sergio Rasmann, Gaétan Glauser.

  In recent years, metabolomics has emerged as a pivotal approach for the holistic analysis of metabolites in biological systems. The rapid progress in analytical equipment, coupled to the rise of powerful data processing tools, now provides unprecedented opportunities to deepen our understanding of the relationships between biochemical processes and physiological or phenotypic conditions in living organisms. However, to obtain unbiased data coverage of hundreds or thousands of metabolites remains a challenging task. Among the panel of available analytical methods, targeted and untargeted mass spectrometry approaches are among the most commonly used. While targeted metabolomics usually relies on multiple-reaction monitoring acquisition, untargeted metabolomics use either data-independent acquisition (DIA) or data-dependent acquisition (DDA) methods. Unlike DIA, DDA offers the possibility to get real, selective MS/MS spectra and thus to improve metabolite assignment when performing untargeted metabolomics. Yet, DDA settings are more complex to establish than DIA settings, and as a result, DDA is more prone to errors in method development and application. Here, we present a tutorial which provides guidelines on how to optimize the technical parameters essential for proper DDA experiments in metabolomics applications. This tutorial is organized as a series of rules describing the impact of the different parameters on data acquisition and data quality. It is primarily intended to metabolomics users and mass spectrometrists that wish to acquire both theoretical background and practical tips for developing effective DDA methods.

Keywords:  DDA; Q-TOF; cycle time; exclusion list; mass window; precursor selection; tandem mass spectrometry

DOI:  https://doi.org/10.1002/mas.21715
Bioessays. 2021 Jun 14. e2100093

mTORC1 and ferroptosis: Regulatory mechanisms and therapeutic potential.

Guang Lei, Li Zhuang, Boyi Gan.

  Ferroptosis, a form of regulated cell death triggered by lipid hydroperoxide accumulation, has an important role in a variety of diseases and pathological conditions, such as cancer. Targeting ferroptosis is emerging as a promising means of therapeutic intervention in cancer treatment. Polyunsaturated fatty acids, reactive oxygen species, and labile iron constitute the major underlying triggers for ferroptosis. Other regulators of ferroptosis have also been discovered recently, among them the mechanistic target of rapamycin complex 1 (mTORC1), a central controller of cell growth and metabolism. Inhibitors of mTORC1 have been used in treating diverse diseases, including cancer. In this review, we discuss recent findings linking mTORC1 to ferroptosis, dissect mechanisms underlying the establishment of mTORC1 as a key ferroptosis modulator, and highlight the potential of co-targeting mTORC1 and ferroptosis in cancer treatment. This review will provide valuable insights for future investigations of ferroptosis and mTORC1 in fundamental biology and cancer therapy.

Keywords:  GPX4; SLC7A11; autophagy; cancer therapy; ferroptosis; lipid peroxidation; mTOR; mTORC1; oncogene

DOI:  https://doi.org/10.1002/bies.202100093
Nat Commun. 2021 06 15. 12(1): 3644

iPLA2β-mediated lipid detoxification controls p53-driven ferroptosis independent of GPX4.

Delin Chen, Bo Chu, Xin Yang, Zhaoqi Liu, Ying Jin, Ning Kon, Raul Rabadan, Xuejun Jiang, Brent R Stockwell, Wei Gu.

Here, we identify iPLA2β as a critical regulator for p53-driven ferroptosis upon reactive oxygen species (ROS)-induced stress. The calcium-independent phospholipase iPLA2β is known to cleave acyl tails from the glycerol backbone of lipids and release oxidized fatty acids from phospholipids. We found that iPLA2β-mediated detoxification of peroxidized lipids is sufficient to suppress p53-driven ferroptosis upon ROS-induced stress, even in GPX4-null cells. Moreover, iPLA2β is overexpressed in human cancers; inhibition of endogenous iPLA2β sensitizes tumor cells to p53-driven ferroptosis and promotes p53-dependent tumor suppression in xenograft mouse models. These results demonstrate that iPLA2β acts as a major ferroptosis repressor in a GPX4-independent manner. Notably, unlike GPX4, loss of iPLA2β has no obvious effect on normal development or cell viability in normal tissues but iPLA2β plays an essential role in regulating ferroptosis upon ROS-induced stress. Thus, our study suggests that iPLA2β is a promising therapeutic target for activating ferroptosis-mediated tumor suppression without serious toxicity concerns.

DOI: https://doi.org/10.1038/s41467-021-23902-6
Anal Chem. 2021 Jun 14.

Identification of 7 000-9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS.

Yangyang Bian, Matthew The, Piero Giansanti, Julia Mergner, Runsheng Zheng, Mathias Wilhelm, Alexander Boychenko, Bernhard Kuster.

A current trend in proteomics is to acquire data in a "single-shot" by LC-MS/MS because it simplifies workflows and promises better throughput and quantitative accuracy than schemes that involve extensive sample fractionation. However, single-shot approaches can suffer from limited proteome coverage when performed by data dependent acquisition (ssDDA) on nanoflow LC systems. For applications where sample quantities are not scarce, this study shows that high proteome coverage can be obtained using a microflow LC-MS/MS system operating a 1 mm i.d. × 150 mm column, at a flow-rate of 50 μL/min and coupled to an Orbitrap HF-X mass spectrometer. The results demonstrate the identification of ∼9 000 proteins from 50 μg of protein digest from Arabidopsis roots, 7 500 from mouse thymus, and 7 300 from human breast cancer cells in 3 h of analysis time in a single run. The dynamic range of protein quantification measured by the iBAQ approach spanned 5 orders of magnitude and replicate analysis showed that the median coefficient of variation was below 20%. Together, this study shows that ssDDA by μLC-MS/MS is a robust method for comprehensive and large-scale proteome analysis and which may be further extended to more rapid chromatography and data independent acquisition approaches in the future.̀.

DOI: https://doi.org/10.1021/acs.analchem.1c00738
Cancer Res. 2021 Jun 18. pii: canres.1392.2021. [Epub ahead of print]

Fatty acid synthesis in prostate cancer: vulnerability or epiphenomenon?

Laura A Sena, Samuel R Denmeade.

Tumor metabolism supports the energetic and biosynthetic needs of rapidly proliferating cancer cells and modifies intra- and intercellular signaling to enhance cancer cell invasion, metastasis, and immune evasion. Prostate cancer exhibits unique metabolism with high rates of de novo fatty acid synthesis driven by activation of the androgen receptor (AR). Increasing evidence suggests that activation of this pathway is functionally important to promote prostate cancer aggressiveness. However, the mechanisms by which fatty acid synthesis are beneficial to prostate cancer have not been well defined. In this Review, we summarize evidence indicating that fatty acid synthesis drives progression of prostate cancer. We also explore explanations for this phenomenon and discuss future directions for targeting this pathway for patient benefit.

DOI: https://doi.org/10.1158/0008-5472.CAN-21-1392
Anal Bioanal Chem. 2021 Jun 18.

Advanced tandem mass spectrometry in metabolomics and lipidomics-methods and applications.

Sven Heiles.

  Metabolomics and lipidomics are new drivers of the omics era as molecular signatures and selected analytes allow phenotypic characterization and serve as biomarkers, respectively. The growing capabilities of untargeted and targeted workflows, which primarily rely on mass spectrometric platforms, enable extensive charting or identification of bioactive metabolites and lipids. Structural annotation of these compounds is key in order to link specific molecular entities to defined biochemical functions or phenotypes. Tandem mass spectrometry (MS), first and foremost collision-induced dissociation (CID), is the method of choice to unveil structural details of metabolites and lipids. But CID fragment ions are often not sufficient to fully characterize analytes. Therefore, recent years have seen a surge in alternative tandem MS methodologies that aim to offer full structural characterization of metabolites and lipids. In this article, principles, capabilities, drawbacks, and first applications of these "advanced tandem mass spectrometry" strategies will be critically reviewed. This includes tandem MS methods that are based on electrons, photons, and ion/molecule, as well as ion/ion reactions, combining tandem MS with concepts from optical spectroscopy and making use of derivatization strategies. In the final sections of this review, the first applications of these methodologies in combination with liquid chromatography or mass spectrometry imaging are highlighted and future perspectives for research in metabolomics and lipidomics are discussed.

Keywords:  Biopolymers/lipids; HPLC; Lipidomics; Mass spectrometry imaging; Metabolomics; Tandem mass spectrometry

DOI:  https://doi.org/10.1007/s00216-021-03425-1
Mass Spectrom Rev. 2021 Jun 15.

Recent advances (2019-2021) of capillary electrophoresis-mass spectrometry for multilevel proteomics.

Daoyang Chen, Elijah N McCool, Zhichang Yang, Xiaojing Shen, Rachele A Lubeckyj, Tian Xu, Qianjie Wang, Liangliang Sun.

  Multilevel proteomics aims to delineate proteins at the peptide (bottom-up proteomics), proteoform (top-down proteomics), and protein complex (native proteomics) levels. Capillary electrophoresis-mass spectrometry (CE-MS) can achieve highly efficient separation and highly sensitive detection of complex mixtures of peptides, proteoforms, and even protein complexes because of its substantial technical progress. CE-MS has become a valuable alternative to the routinely used liquid chromatography-mass spectrometry for multilevel proteomics. This review summarizes the most recent (2019-2021) advances of CE-MS for multilevel proteomics regarding technological progress and biological applications. We also provide brief perspectives on CE-MS for multilevel proteomics at the end, highlighting some future directions and potential challenges.

Keywords:  capillary isoelectric focusing-mass spectrometry; capillary zone electrophoresis-mass spectrometry; multilevel proteomics; protein complex; proteoform

DOI:  https://doi.org/10.1002/mas.21714
Methods Mol Biol. 2021 ;2344 99-106

Detection of Posttranslational Modification Autoantibodies Using Peptide Microarray.

Meng Li, Hongye Wang, Jiayu Dai, Meng Xu, Jianhua Liu, Jing Ren, Xiaosong Qin, Xianjiang Kang, Xiaobo Yu.

  Autoantibodies are humoral antibodies against self-proteins and play vital roles in maintaining the homeostasis. Autoantibodies can also target posttranslational modifications (PTMs) of proteins and the identification of new PTM autoantibodies is important to identify biomarkers for the early diagnosis of cancer and autoimmune diseases. In this chapter, we describe a method to detect PTM autoantibodies using citrullinated peptide microarray as an example. This method can be used to screen serum autoantibodies for different human diseases.

Keywords:  Autoantibody; Biomarker; Citrullination; Peptide microarray; Posttranslational modification

DOI:  https://doi.org/10.1007/978-1-0716-1562-1_7
Anal Bioanal Chem. 2021 Jun 14.

Deepening of lipidome annotation by associating cross-metathesis reaction with mass spectrometry: application to an in vitro model of corneal toxicity.

Romain Magny, Anne Regazzetti, Karima Kessal, Christophe Baudouin, Stéphane Mélik-Parsadaniantz, Olivier Laprévote, Françoise Brignole-Baudouin, Nicolas Auzeil, Emmanuel Roulland.

  The in-depth knowledge of lipid biological functions needs a comprehensive structural annotation including a method to locate fatty acid unsaturations, which remains a thorny problem. For this purpose, we have associated Grubbs' cross-metathesis reaction and liquid chromatography hyphenated to tandem mass spectrometry to locate double bond positions in lipid species. The pretreatment of lipid-containing samples by Grubbs' catalyst and an appropriate alkene generates substituted lipids through cross-metathesis reaction under mild, chemoselective, and reproducible conditions. A systematic LC-MS/MS analysis of the reaction mixture allows locating unambiguously the double bonds in fatty acid side chains of phospholipids, glycerolipids, and sphingolipids. This method has been successfully applied at a nanomole scale to commercial standard mixtures consisting of 10 lipid subclasses as well as in lipid extracts of human corneal epithelial (HCE) cell line allowing to pinpoint double bond of more than 90 species. This method has also been useful to investigate the lipid homeostasis alteration in an in vitro model of corneal toxicity, i.e., HCE cells incubated with benzalkonium chloride. The association of cross-metathesis and tandem mass spectrometry appears suitable to locate double bond positions in lipids involved in relevant biological processes.

Keywords:  Corneal toxicity; Cross-metathesis; Double bond location; Lipidomics; Tandem mass spectrometry

DOI:  https://doi.org/10.1007/s00216-021-03438-w
Cancer Cell Int. 2021 Jun 16. 21(1): 314

Metabolome analysis reveals a diversity of cancer tissues in advanced epithelial ovarian cancer.

Kosuke Yoshida, Nobuhisa Yoshikawa, Kazuhisa Kitami, Satoshi Tamauchi, Yoshiki Ikeda, Akira Yokoi, Kimihiro Nishino, Kaoru Niimi, Hiroaki Kajiyama.

   BACKGROUND: Epithelial ovarian cancer remains one of the leading causes of cancer deaths among women worldwide, and advanced epithelial ovarian cancer frequently metastasizes to the omentum. The characteristics of metastatic cancer may differ from those of primary ovarian cancer and reflect the unique omental microenvironment. This study investigated metabolomic differences in epithelial ovarian cancers.
METHODS: Patients with advanced epithelial ovarian cancer were eligible for this study. Five patients underwent surgery and resection of paired primary ovarian and omental metastatic cancer at Nagoya University. Metabolome analysis was performed in these paired cancer and metastatic cancer tissues through a facility service (C-SCOPE) at Human Metabolome Technologies, Inc. The concentrations of 116 compounds were measured by CE-TOFMS and CE-QqQMS, and 30 metabolic parameters were calculated. For statistical analyses, Welch's t-test was used for comparisons between two independent groups.
RESULTS: Metabolite profiles were all different, which reflects diversity among these cancer tissues. Of the measured compounds, urea was the only metabolite that was significantly decreased in omental metastatic cancers compared with the primary cancers (p = 0.031). Moreover, in omental metastatic cancers, the pentose phosphate pathway was more dominant than glycolysis. Furthermore, in some cases, lactic acids in omental metastatic cancers were markedly decreased compared with primary cancers. With regard to histological subtype, the total levels of amino acids, especially the percentage of glutamine, were significantly enriched in serous carcinomas compared with nonserous carcinomas (p = 0.004 and p = 0.001). Moreover, the reduced forms of glutathione and polyamines were also more abundant in serous carcinomas than in nonserous carcinomas (p = 0.025 and 0.048).
CONCLUSIONS: The metabolite profiles differed depending on tumor location and histological subtype. Metabolome analysis may be a useful tool for identifying cancer diagnostic and prognostic markers.

Keywords:  Epithelial ovarian cancer; Metabolome; Omental metastasis

DOI:  https://doi.org/10.1186/s12935-021-02014-7
Anal Chem. 2021 Jun 16.

Computational Variation: An Underinvestigated Quantitative Variability Caused by Automated Data Processing in Untargeted Metabolomics.

Huaxu Yu, Ying Chen, Tao Huan.

Computational tools are commonly used in untargeted metabolomics to automatically extract metabolic features from liquid chromatography-mass spectrometry (LC-MS) raw data. However, due to the incapability of software to accurately determine chromatographic peak heights/areas for features with poor chromatographic peak shape, automated data processing in untargeted metabolomics faces additional quantitative variation (i.e., computational variation) besides the well-recognized analytical and biological variations. In this work, using multiple biological samples, we investigated how experimental factors, including sample concentrations, LC separation columns, and data processing programs, contribute to computational variation. For example, we found that the peak height (PH)-based quantification is more precise when MS-DIAL was used for data processing. We further systematically compared the different patterns of computational variation between PH- and peak area (PA)-based quantitative measurements. Our results suggest that the magnitude of computational variation is highly consistent at a given concentration. Hence, we proposed a quality control (QC) sample-based correction workflow to minimize computational variation by automatically selecting PH or PA-based measurement for each intensity value. This bioinformatic solution was demonstrated in a metabolomic comparison of leukemia patients before and after chemotherapy. Our novel workflow can be effectively applied on 652 out of 915 metabolic features, and over 31% (206 out of 652) of corrected features showed distinctly changed statistical significance. Overall, this work highlights computational variation, a considerable but underinvestigated quantitative variability in omics-scale quantitative analyses. In addition, the proposed bioinformatic solution can minimize computational variation, thus providing a more confident statistical comparison among biological groups in quantitative metabolomics.

DOI: https://doi.org/10.1021/acs.analchem.0c03381
Atherosclerosis. 2021 May 28. pii: S0021-9150(21)00254-9. [Epub ahead of print]329 1-8

Lipolytic enzymes and free fatty acids at the endothelial interface.

Ira J Goldberg, Ainara G Cabodevilla, Dmitri Samovski, Vincenza Cifarelli, Debapriya Basu, Nada A Abumrad.

  Lipids released from circulating lipoproteins by intravascular action of lipoprotein lipase (LpL) reach parenchymal cells in tissues with a non-fenestrated endothelium by transfer through or around endothelial cells. The actions of LpL are controlled at multiple sites, its synthesis and release by myocytes and adipocytes, its transit and association with the endothelial cell luminal surface, and finally its activation and inhibition by a number of proteins and by its product non-esterified fatty acids. Multiple pathways mediate endothelial transit of lipids into muscle and adipose tissues. These include movement of fatty acids via the endothelial cell fatty acid transporter CD36 and movement of whole or partially LpL-hydrolyzed lipoproteins via other apical endothelial cell receptors such as SR-B1and Alk1. Lipids also likely change the barrier function of the endothelium and operation of the paracellular pathway around endothelial cells. This review summarizes in vitro and in vivo support for the key role of endothelial cells in delivery of lipids and highlights incompletely understood processes that are the focus of active investigation.

Keywords:  CD36; Fatty acids; Lipoprotein lipase; Scavenger receptors; Triglyceride

DOI:  https://doi.org/10.1016/j.atherosclerosis.2021.05.018
Nat Commun. 2021 06 16. 12(1): 3660

Limited survival and impaired hepatic fasting metabolism in mice with constitutive Rag GTPase signaling.

Celia de la Calle Arregui, Ana Belén Plata-Gómez, Nerea Deleyto-Seldas, Fernando García, Ana Ortega-Molina, Julio Abril-Garrido, Elena Rodriguez, Ivan Nemazanyy, Laura Tribouillard, Alba de Martino, Eduardo Caleiras, Ramón Campos-Olivas, Francisca Mulero, Mathieu Laplante, Javier Muñoz, Mario Pende, Guadalupe Sabio, David M Sabatini, Alejo Efeyan.

The mechanistic target of rapamycin complex 1 (mTORC1) integrates cellular nutrient signaling and hormonal cues to control metabolism. We have previously shown that constitutive nutrient signaling to mTORC1 by means of genetic activation of RagA (expression of GTP-locked RagA, or RagAGTP) in mice resulted in a fatal energetic crisis at birth. Herein, we rescue neonatal lethality in RagAGTP mice and find morphometric and metabolic alterations that span glucose, lipid, ketone, bile acid and amino acid homeostasis in adults, and a median lifespan of nine months. Proteomic and metabolomic analyses of livers from RagAGTP mice reveal a failed metabolic adaptation to fasting due to a global impairment in PPARα transcriptional program. These metabolic defects are partially recapitulated by restricting activation of RagA to hepatocytes, and revert by pharmacological inhibition of mTORC1. Constitutive hepatic nutrient signaling does not cause hepatocellular damage and carcinomas, unlike genetic activation of growth factor signaling upstream of mTORC1. In summary, RagA signaling dictates dynamic responses to feeding-fasting cycles to tune metabolism so as to match the nutritional state.

DOI: https://doi.org/10.1038/s41467-021-23857-8
Prog Neurobiol. 2021 Jun 10. pii: S0301-0082(21)00103-9. [Epub ahead of print] 102089

Glucose metabolic crosstalk and regulation in brain function and diseases.

Shuai Zhang, Brittany Bolduc Lachance, Mark P Mattson, Xiaofeng Jia.

  Brain glucose metabolism, including glycolysis, the pentose phosphate pathway, and glycogen turnover, produces ATP for energetic support and provides the precursors for the synthesis of biological macromolecules. Although glucose metabolism in neurons and astrocytes has been extensively studied, the glucose metabolism of microglia and oligodendrocytes, and their interactions with neurons and astrocytes, remain critical to understand brain function. Brain regions with heterogeneous cell composition and cell-type-specific profiles of glucose metabolism suggest that metabolic networks within the brain are complex. Signal transduction proteins including those in the Wnt, GSK-3β, PI3K-AKT, and AMPK pathways are involved in regulating these networks. Additionally, glycolytic enzymes and metabolites, such as hexokinase 2, acetyl-CoA, and enolase 2, are implicated in the modulation of cellular function, microglial activation, glycation, and acetylation of biomolecules. Given these extensive networks, glucose metabolism dysfunction in the whole brain or specific cell types is strongly associated with neurologic pathology including ischemic brain injury and neurodegenerative disorders. This review characterizes the glucose metabolism networks of the brain based on molecular signaling and cellular and regional interactions, and elucidates glucose metabolism-based mechanisms of neurological diseases and therapeutic approaches that may ameliorate metabolic abnormalities in those diseases.

Keywords:  Brain; Glucose metabolism; Glycolysis; Neurological disease; Signal regulation

DOI:  https://doi.org/10.1016/j.pneurobio.2021.102089
Expert Rev Proteomics. 2021 Jun 15.

An overview of lipidomics utilizing cadaver derived biological samples.

Luheng Lyu, Neel Sonik, Sanjoy Bhattacharya.

   INTRODUCTION: We present lipidomic studies that have utilized cadaveric biological samples, including tissues and bodily fluids (excluding blood or serum). Analyses of lipids from cadaveric derived tissues play vital roles in many different fields, such as in anthropogeny to understand food habits of ancient people, in forensics for postmortem analyses, and in biomedical research to study human diseases.
AREAS COVERED: The goal of the review is to demonstrate how cadavers can be utilized for study of lipidome to get biological insight in different fields. Several important considerations need to be made when analyzing lipids from cadaver samples. For example, what important postmortem changes occur due to environmental or other intrinsic factors that introduce deviations in the observed differences versus true differences? Do these factors affect distinct classes of lipids differently? How do we arrive at a reasonable level of certainty that the observed differences are truly biological rather than artifacts of sample collection, changes during transportation, or variations in analytical procedures? These are pressing questions that need to be addressed when performing lipidomics investigations utilizing postmortem tissues, which inherently presents hurdles and unknowns beginning with harvesting methods, transportation logistics, and at analytical techniques. In our review, we have purposefully omitted blood and serum studies since they pose greater challenges in this regard. Several studies have been carried out with cadaveric tissues and fluids that support the successful use cases of these samples; however, many control studies are still necessary to provide insight into full potential of the cadaveric tissue and fluid resources. Most importantly, additional control studies will allow us to gain important insights into the opportunities lipidomics presents for biomedical studies of complex human disease and disorders. Another goal of the review is to generate awareness about limitations and pitfalls of use cadaver materials for study of lipidome.
EXPERT OPINION: We comment on the current state of lipidomics studies that utilize cadaveric tissues, provide a few pertinent examples, and discuss perspectives on both future technological directions and the applications they will enable.

Keywords:  cadaveric; lipidomics; mass spectrometry; postmortem

DOI:  https://doi.org/10.1080/14789450.2021.1941894
Front Oncol. 2021 ;11 576326

Proteomic Characterization of Cytoplasmic Lipid Droplets in Human Metastatic Breast Cancer Cells.

Alyssa S Zembroski, Chaylen Andolino, Kimberly K Buhman, Dorothy Teegarden.

  One of the characteristic features of metastatic breast cancer is increased cellular storage of neutral lipid in cytoplasmic lipid droplets (CLDs). CLD accumulation is associated with increased cancer aggressiveness, suggesting CLDs contribute to metastasis. However, how CLDs contribute to metastasis is not clear. CLDs are composed of a neutral lipid core, a phospholipid monolayer, and associated proteins. Proteins that associate with CLDs regulate both cellular and CLD metabolism; however, the proteome of CLDs in metastatic breast cancer and how these proteins may contribute to breast cancer progression is unknown. Therefore, the purpose of this study was to identify the proteome and assess the characteristics of CLDs in the MCF10CA1a human metastatic breast cancer cell line. Utilizing shotgun proteomics, we identified over 1500 proteins involved in a variety of cellular processes in the isolated CLD fraction. Interestingly, unlike other cell lines such as adipocytes or enterocytes, the most enriched protein categories were involved in cellular processes outside of lipid metabolism. For example, cell-cell adhesion was the most enriched category of proteins identified, and many of these proteins have been implicated in breast cancer metastasis. In addition, we characterized CLD size and area in MCF10CA1a cells using transmission electron microscopy. Our results provide a hypothesis-generating list of potential players in breast cancer progression and offers a new perspective on the role of CLDs in cancer.

Keywords:  breast cancer; cytoplasmic lipid droplets; metastasis; proteomics; triacylglycerol

DOI:  https://doi.org/10.3389/fonc.2021.576326
Cell Mol Life Sci. 2021 Jun 15.

Overcoming chemoresistance by targeting reprogrammed metabolism: the Achilles' heel of pancreatic ductal adenocarcinoma.

Abudureyimu Tuerhong, Jin Xu, Si Shi, Zhen Tan, Qingcai Meng, Jie Hua, Jiang Liu, Bo Zhang, Wei Wang, Xianjun Yu, Chen Liang.

  Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer-related death due to its late diagnosis that removes the opportunity for surgery and metabolic plasticity that leads to resistance to chemotherapy. Metabolic reprogramming related to glucose, lipid, and amino acid metabolism in PDAC not only enables the cancer to thrive and survive under hypovascular, nutrient-poor and hypoxic microenvironments, but also confers chemoresistance, which contributes to the poor prognosis of PDAC. In this review, we systematically elucidate the mechanism of chemotherapy resistance and the relationship of metabolic programming features with resistance to anticancer drugs in PDAC. Targeting the critical enzymes and/or transporters involved in glucose, lipid, and amino acid metabolism may be a promising approach to overcome chemoresistance in PDAC. Consequently, regulating metabolism could be used as a strategy against PDAC and could improve the prognosis of PDAC.

Keywords:  Chemotherapy; Glutamine; Glycolysis; Lipogenesis; Pancreatic cancer

DOI:  https://doi.org/10.1007/s00018-021-03866-y
Front Oncol. 2021 ;11 684961

Targeting Pyrimidine Metabolism in the Era of Precision Cancer Medicine.

Wanyan Wang, Jiayan Cui, Hui Ma, Weiqiang Lu, Jin Huang.

  Metabolic rewiring is considered as a primary feature of cancer. Malignant cells reprogram metabolism pathway in response to various intrinsic and extrinsic drawback to fuel cell survival and growth. Among the complex metabolic pathways, pyrimidine biosynthesis is conserved in all living organism and is necessary to maintain cellular fundamental function (i.e. DNA and RNA biosynthesis). A wealth of evidence has demonstrated that dysfunction of pyrimidine metabolism is closely related to cancer progression and numerous drugs targeting pyrimidine metabolism have been approved for multiple types of cancer. However, the non-negligible side effects and limited efficacy warrants a better strategy for negating pyrimidine metabolism in cancer. In recent years, increased studies have evidenced the interplay of oncogenic signaling and pyrimidine synthesis in tumorigenesis. Here, we review the recent conceptual advances on pyrimidine metabolism, especially dihydroorotate dehydrogenase (DHODH), in the framework of precision oncology medicine and prospect how this would guide the development of new drug precisely targeting the pyrimidine metabolism in cancer.

Keywords:  dihydroorotate dehydrogenase; metabolic reprogram; precision medicine; pyrimidine inhibitor; pyrimidine metabolism

DOI:  https://doi.org/10.3389/fonc.2021.684961
Bioanalysis. 2021 Jun 10.

Analytical considerations for reducing the matrix effect for the sphingolipidome quantification in whole blood.

Dezhen Wang, Peining Xu, Clementina Mesaros.

  Aim: Plasma and serum are widely used blood-derived biofluids for metabolomics and lipidomics assays, but analytes that are present in high concentrations in blood cells cannot be evaluated in those samples and isolating serum or plasma could introduce additional variability in the data. Materials & methods: In this study, we provide a comprehensive method for quantification of the whole blood (WB) sphingolipidome, combining a single-phase extraction method with LC-high-resolution mass spectrometry. Results: We were able to quantify more than 150 sphingolipids, and when compared with paired plasma, WB contained higher concentration of most sphingolipids and individual variations were lower. These findings suggest that WB could be a better alternative to plasma, and potentially guide the evaluation of the sphingolipidome for biomarker discovery.

Keywords:  ceramides; high-resolution mass spectrometry; plasma; sphingolipids; whole blood

DOI:  https://doi.org/10.4155/bio-2021-0098
J Proteome Res. 2021 Jun 17.

Spatially Resolved Metabolomics Based on Air-Flow-Assisted Desorption Electrospray Ionization-Mass Spectrometry Imaging Reveals Region-Specific Metabolic Alterations in Diabetic Encephalopathy.

Meiling Huo, Zhonghua Wang, Wenqing Fu, Lu Tian, Wanfang Li, Zhi Zhou, Yanhua Chen, Jinfeng Wei, Zeper Abliz.

  Spatially resolved metabolic profiling of brain is vital for elucidating tissue-specific molecular histology and pathology underlying diabetic encephalopathy (DE). In this study, a spatially resolved metabolomic method based on air-flow-assisted desorption electrospray ionization-mass spectrometry imaging (AFADESI-MSI) was developed for investigating the region-specific metabolic disturbances in the brain of DE model rats induced by a high-fat diet in combination with streptozotocin administration. A total of 19 discriminating metabolites associated with glycolysis and the pentose phosphate pathway (PPP); the glutamate/gamma aminobutyric acid-glutamine cycle and tricarboxylic acid cycle; nucleotide metabolism; lipid metabolism; carnitine homeostasis; and taurine, ascorbic acid, histidine, and choline metabolism were identified and located in the brains of the diabetic rats simultaneously for the first time. The results indicated that increased glycolytic and PPP activity; dysfunction of mitochondrial metabolism; dysregulation of adenosinergic, glutamatergic, dopaminergic, cholinergic, and histaminergic systems; disorder of osmotic regulation and antioxidant system; and disorder of lipid metabolism occur in a region-specific fashion in the brains of DE rats. Thus, this study provides valuable information regarding the molecular pathological signature of DE. These findings also underline the high potential of AFADESI-MSI for applications in various central nervous system diseases.

Keywords:  air-flow-assisted desorption electrospray ionization−mass spectrometry imaging; brain; diabetic encephalopathy; mass spectrometry imaging; spatially resolved metabolomics

DOI:  https://doi.org/10.1021/acs.jproteome.1c00179
Biomed Pharmacother. 2021 Jun 10. pii: S0753-3322(21)00580-1. [Epub ahead of print]141 111798

Metabolic reprogramming due to hypoxia in pancreatic cancer: Implications for tumor formation, immunity, and more.

Xiadong Hao, Yidan Ren, Maoxiao Feng, Qin Wang, Yunshan Wang.

  Hypoxia is a common phenomenon in most malignant tumors, especially in pancreatic cancer (PC). Hypoxia is the result of unlimited tumor growth and plays an active role in promoting tumor survival, progression, and invasion. As the part of the hypoxia microenvironment in PC is gradually clarified, hypoxia is becoming a key determinant and an important therapeutic target of pancreatic cancer. To adapt to the severe hypoxia environment, cells have changed their metabolic phenotypes to maintain their survival and proliferation. Enhanced glycolysis is the most prominent feature of cancer cells' metabolic reprogramming in response to hypoxia. It provides the energy source for hypoxic cancer cells (although it provides less than oxidative phosphorylation) and produces metabolites that can be absorbed and utilized by normoxic cancer cells. In addition, the uptake of glutamine and fatty acids by hypoxic cancer cells is also increased, which is also conducive to tumor progression. Their metabolites are pooled in the hexosamine biosynthesis pathway (HBP). As a nutrition sensor, HBP, in turn, can coordinate glucose and glutamine metabolism. Its end product, UDP-GlcNAc, is the substrate of protein post-translational modification (PTM) involved in various signaling pathways supporting tumor progression. Adaptive metabolic changes of cancer cells promote their survival and affect tumor immune cells in the tumor microenvironment (TME), which contributes to tumor immunosuppressive microenvironment and induces tumor immunotherapy resistance. Here, we summarize the hypoxic microenvironment, its effect on metabolic reprogramming, and its contribution to immunotherapy resistance in pancreatic cancer.

Keywords:  Hypoxia; Immunosuppressive microenvironment; Metabolic reprogramming; Pancreatic cancer (PC)

DOI:  https://doi.org/10.1016/j.biopha.2021.111798
Crit Rev Biochem Mol Biol. 2021 Jun 15. 1-10

Cancer cells dysregulate PI3K/AKT/mTOR pathway activation to ensure their survival and proliferation: mimicking them is a smart strategy of gammaherpesviruses.

Mara Cirone.

  The serine/threonine kinase mammalian target of rapamycin (mTOR) is the catalytic subunit of two complexes, mTORC1 and mTORC2, which have common and distinct subunits that mediate separate and overlapping functions. mTORC1 is activated by plenty of nutrients, and the two complexes can be activated by PI3K signaling. mTORC2 acts as an upstream regulator of AKT, and mTORC1 acts as a downstream effector. mTOR signaling integrates both intracellular and extracellular signals, acting as a key regulator of cellular metabolism, growth, and survival. A dysregulated activation of mTOR, as result of PI3K pathway or mTOR regulatory protein mutations or even due to the presence of cellular or viral oncogenes, is a common finding in cancer and represents a central mechanism in cancerogenesis. In the final part of this review, we will focus on the PI3K/AKT/mTOR activation by the human gammaherpesviruses EBV and KSHV that hijack this pathway to promote their-mediated oncogenic transformation and pathologies.

Keywords:  EBV; KSHV; PI3K/AKT; cancer; mTORC1; mTORC2; metabolism

DOI:  https://doi.org/10.1080/10409238.2021.1934811
Signal Transduct Target Ther. 2020 Jun 19. 5(1): 103

Correction to: CDK4/6 inhibition blocks cancer metastasis through a USP51-ZEB1-dependent deubiquitination mechanism.

Zhen Zhang, Jianjun Li, Yang Ou, Guang Yang, Kaiyuan Deng, Qiong Wang, Zhaoyang Wang, Wenhao Wang, Quansheng Zhang, Hang Wang, Wei Sun, Peiqing Sun, Shuang Yang.

DOI: https://doi.org/10.1038/s41392-020-00212-9
Proteomics. 2021 Jun 19. e2100008

Bottom-up and top-down proteomic approaches for the identification, characterization and quantification of the low molecular weight proteome with focus on short open reading frame-encoded peptides.

Liam Cassidy, Philipp T Kaulich, Sandra Maaß, Jürgen Bartel, Dörte Becher, Andreas Tholey.

  The recent discovery of alternative open reading frames creates a need for suitable analytical approaches to verify their translation and to characterize the corresponding gene products at the molecular level. As the analysis of small proteins within a background proteome by means of classical bottom-up proteomics is challenging, method development for the analysis of short open reading frame-encoded peptides (SEPs) have become a focal point for research. Here we highlight bottom-up and top-down proteomics approaches established for the analysis of SEPs in both pro- and eukaryotes. Major steps of analysis, including sample preparation and (small) proteome isolation, separation and mass spectrometry, data interpretation and quality control, quantification, the analysis of posttranslational modifications and exploration of functional aspects of the SEPs by means of proteomics technologies are described. These methods do not exclusively cover the analytics of SEPs but simultaneously include the low molecular weight proteome and, moreover, can also be used for the proteome-wide analysis of proteolytic processing events. This article is protected by copyright. All rights reserved.

Keywords:  LC-MS/MS < Technology, peptidomics < Technology, sample preparation < Technology, top-down proteomics < Technology, prefractionation < Technology, post-translational modification analysis < Technology ; mass spectrometry

DOI:  https://doi.org/10.1002/pmic.202100008
J Pharm Biomed Anal. 2021 Jun 02. pii: S0731-7085(21)00296-X. [Epub ahead of print]203 114185

Development and validation of an LC-MS/MS generic assay platform for small molecule drug bioanalysis.

Robert A Parise, Joseph M Covey, Melinda G Hollingshead, Apurva K Srivastava, Timothy W Synold, Jan H Beumer.

   AIM: We developed a generic high-performance liquid chromatography mass spectrometry approach for quantitation of small molecule compounds without availability of isotopically labelled standard.
METHODS: The assay utilized 50 μL of plasma and offers 8 potential internal standards (IS): acetaminophen, veliparib, busulfan, neratinib, erlotinib, abiraterone, bicalutamide, and paclitaxel. Preparation consisted of acetonitrile protein precipitation and aqueous dilution in a 96 well-plate format. Chromatographic separation was achieved with a Kinetex C18 reverse phase (2.6 μm, 2 mm x 50 mm) column and a gradient of 0.1 % formic acid in acetonitrile and water over an 8 min run time. Mass spectrometric detection was performed on an AB SCIEX4000QTRAP with electrospray, positive-mode ionization. Performance of the generic approach was evaluated with seven drugs (LMP744, olaparib, cabozantinib, triapine, ixabepilone, berzosertib, eribulin) for which validated assays were available.
RESULTS: The 8 IS covered a range of polarity, size, and ionization; eluted over the range of chromatographic retention times; were quantitatively extracted; and suffered limited matrix effects. The generic approach proved to be linear for test drugs evaluated over at least 3 orders of magnitude starting at 1-10 ng/mL, with extension of assay ranges with analyte isotopologue MRM channels. At a bias of less than 16 % and precision within 15 %, the assay performance was acceptable.
CONCLUSION: The generic approach has become a useful tool to further define the pharmacology of drugs studied in our laboratory and may be utilized as described, or as starting point to develop drug-specific assays with more extensive performance characterization.

Keywords:  Generic assay; Tandem mass spectrometry; Validation

DOI:  https://doi.org/10.1016/j.jpba.2021.114185
Front Cell Dev Biol. 2021 ;9 656604

Amino Acid Trafficking and Skeletal Muscle Protein Synthesis: A Case of Supply and Demand.

James P White.

  Skeletal muscle protein synthesis is a highly complex process, influenced by nutritional status, mechanical stimuli, repair programs, hormones, and growth factors. The molecular aspects of protein synthesis are centered around the mTORC1 complex. However, the intricacies of mTORC1 regulation, both up and downstream, have expanded overtime. Moreover, the plastic nature of skeletal muscle makes it a unique tissue, having to coordinate between temporal changes in myofiber metabolism and hypertrophy/atrophy stimuli within a tissue with considerable protein content. Skeletal muscle manages the push and pull between anabolic and catabolic pathways through key regulatory proteins to promote energy production in times of nutrient deprivation or activate anabolic pathways in times of nutrient availability and anabolic stimuli. Branched-chain amino acids (BCAAs) can be used for both energy production and signaling to induce protein synthesis. The metabolism of BCAAs occur in tandem with energetic and anabolic processes, converging at several points along their respective pathways. The fate of intramuscular BCAAs adds another layer of regulation, which has consequences to promote or inhibit muscle fiber protein anabolism. This review will outline the general mechanisms of muscle protein synthesis and describe how metabolic pathways can regulate this process. Lastly, we will discuss how BCAA availability and demand coordinate with synthesis mechanisms and identify key factors involved in intramuscular BCAA trafficking.

Keywords:  AMPK (5′-AMP activated kinase); BCKD; branch chain amino acids; branched-chain α-ketoacid dehydrogenase; mammalian target of rapamycin; protein synthesis; skeletal muscle

DOI:  https://doi.org/10.3389/fcell.2021.656604
J Proteome Res. 2021 Jun 17.

MSTracer: A Machine Learning Software Tool for Peptide Feature Detection from Liquid Chromatography-Mass Spectrometry Data.

Xiangyuan Zeng, Bin Ma.

  Liquid chromatography with tandem mass spectrometry (MS/MS) has been widely used in proteomics. Although a typical experiment includes both MS and MS/MS scans, existing bioinformatics research has focused far more on MS/MS data than on MS data. In MS data, each peptide produces a few trails of signal peaks, which are collectively called a peptide feature. Here, we introduce MSTracer, a new software tool for detecting peptide features from MS data. The software incorporates two scoring functions based on machine learning: one for detecting the peptide features and the other for assigning a quality score to each detected feature. The software was compared with several existing tools and demonstrated significantly better performance.

Keywords:  LC−MS; machine learning; peptide feature detection

DOI:  https://doi.org/10.1021/acs.jproteome.0c01029