bims-mascan 2022-01-02 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2022–01–02
twenty papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Extraction of Metabolites from Cancer Cells.
The Foundations and Development of Lipidomics.
Targeted and untargeted mass spectrometry reveals impact of high fat diet on peripheral amino acid regulation in a mouse model of Alzheimer's disease.
A clinically validated method to separate and quantify underivatized acylcarnitines and carnitine metabolic intermediates using mixed-mode chromatography with tandem mass spectrometry.
Neutrophil metabolism in the cancer context.
High Throughput UHPLC-MS-Based Lipidomics Using Vacuum Jacketed Columns.
Quantitative Accuracy and Precision in Multiplexed Single-Cell Proteomics.
Fatty Acid Metabolism and Derived-Mediators Distinctive of PPAR-α Activation in Obese Subjects Post Bariatric Surgery.
Macrophages are metabolically heterogeneous within the tumor microenvironment.
Inorganic Matrices Assisted Laser Desorption/Ionization Mass Spectrometry for Metabolic Analysis in Bio-fluids.
Novel lipidomic signature associated with metabolic risk in women with and without polycystic ovary syndrome.
Approaches for completing metabolic networks through metabolite damage and repair discovery.
Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach.
Persister cancer cells: Iron addiction and vulnerability to ferroptosis.
Impact of cancer metabolism on therapy resistance - Clinical implications.
Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets.
Isolation of Autophagy Competent Lysosomes from Cancer Cells by Differential Large-Scale Multilayered Density Gradient Centrifugations.
Measuring Glucose Consumption and Gluconeogenesis in 3D Human Tissue Cultures with Nanoliter Input Volumes.
LipidOne: user-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario.
Internal calibration as an emerging approach for endogenous analyte quantification: Application to steroids.

Methods Mol Biol. 2022 ;2445 329-335

Extraction of Metabolites from Cancer Cells.

Elena Kochetkova, Tina Becirovic, Erik Norberg.

  Cancer cells possess an elevated demand for nutrients and metabolites due to their uncontrolled proliferation and need to survive in unfavorable conditions. Autophagy is a conservative degradation pathway that counters lack of nutrients and provides organelle and protein quality control, beyond maintenance of cellular metabolism.Mass spectrometry-based metabolomics is a powerful tool to study the metabolome of a cell. Such analysis requires proper sample preparation including the extraction of metabolites. Here, we provide a protocol for the extraction of metabolites from adherent cancer cells suitable for global metabolome profiling by mass spectrometry.

Keywords:  Autophagy; CE-MS; Cancer metabolism; Chaperone-mediated autophagy; GC-MS; LC-MS; Mass spectrometry; Metabolism; Methanol extraction

DOI:  https://doi.org/10.1007/978-1-0716-2071-7_20
J Lipid Res. 2021 Dec 21. pii: S0022-2275(21)00147-4. [Epub ahead of print] 100164

The Foundations and Development of Lipidomics.

Xianlin Han, Richard W Gross.

  For over a century, the importance of lipid metabolism in biology was recognized, but difficult to mechanistically understand due to the lack of sensitive and robust technologies for identification and quantification of lipid molecular species. The enabling technological breakthroughs emerged in the 1980s with the development of soft ionization methods (Electrospray Ionization and Matrix Assisted Laser Desorption/Ionization) that could identify and quantify intact individual lipid molecular species. These soft ionization technologies laid the foundations for what was to be later named the field of lipidomics. Further innovative advances in multistage fragmentation, dramatic improvements in resolution and mass accuracy, and multiplexed sample analysis fueled the early growth of lipidomics through the early 1990s. The field exponentially grew through the use of a variety of strategic approaches, which included direct infusion, chromatographic separation, and charge-switch derivatization, which facilitated access to the low abundance species of the lipidome. In this Thematic Review, we provide a broad perspective of the foundations, enabling advances, and predicted future directions of growth of the lipidomics field.

Keywords:  Lipids; charge-switch derivatization; chromatographic separation; electrospray ionization; lipid metabolism; lipidomics; mass spectrometry; matrix-assisted laser desorption/ionization; shotgun lipidomics; soft ionization

DOI:  https://doi.org/10.1016/j.jlr.2021.100164
Alzheimers Dement. 2021 Dec;17 Suppl 2 e058428

Targeted and untargeted mass spectrometry reveals impact of high fat diet on peripheral amino acid regulation in a mouse model of Alzheimer's disease.

Amelia L Taylor, Don E Davis, Simona G Codreanu, Fiona E Harrison, Stacy D Sherrod, John A McLean.

BACKGROUND: Mass spectrometry-based metabolomics analyses were performed to examine metabolic changes under diet-induced obesity in Alzheimer's Disease (AD) and assess whether these changes are reversible with diet modification. Specifically, amino acid metabolism was investigated because amino acid levels are related to obesity/diabetes and elevated levels have been shown to induce many of the pathophysiological hallmarks of AD.
METHOD: Targeted hydrophilic interaction liquid chromatography-triple quadrupole mass spectrometry (HILIC-MS/MS) and untargeted reversed-phase liquid chromatography-high resolution tandem mass spectrometry (RPLC-HRMS/MS) assays were developed to analyze the metabolic changes that occur in AD and obesity. Frozen liver samples were obtained from a previously defined study, in which APPSwe /PS1ΔE9 (APP/PSEN1) transgenic mice (to represent familial or early-onset AD) and wild-type litter mater controls were fed either a high-fat diet (HFD, 60% kcal from lard), low-fat diet (LFD, 10% kcal from lard), or reversal diet (REV, high-fat for 7.5 months followed by low-fat for 2.5 months). Liver samples were collected after sacrifice and were prepared through homogenization and an established protein precipitation protocol.
RESULT: Multiple amino acids (including alanine, glutamic acid, leucine, isoleucine, and phenylalanine), carnitines, and members of the fatty acid oxidation pathway were significantly increased in APP/PSEN1 mice on HFD compared to LFD. More substantial effects and changes were observed in the APP/PSEN1 mice than WT mice, suggesting that they were more sensitive to a HFD. These dysregulated peripheral pathways include numerous amino acid pathways and fatty acid beta oxidation and suggest that obesity combined with AD further enhances cognitive impairment. These dysregulated peripheral pathways include pathways directly linked to the TCA cycle and mitochondrial dysfunction, which suggest that the HFD may contribute to AD pathogenesis by further contributing to this mitochondrial dysfunction. Furthermore, partial reversibility of many altered pathways was observed, which highlights that diet change can mitigate metabolic effects of AD. The same trends in individual amino acids were observed in both strategies, highlighting the biological validity of the results.
CONCLUSION: Our targeted and untargeted metabolomics results suggest that numerous peripheral pathways, specifically amino acid metabolism and fatty acid metabolism, were significantly affected in a combinatorial fashion by AD genotype and diet.

DOI: https://doi.org/10.1002/alz.058428
J Chromatogr A. 2021 Dec 16. pii: S0021-9673(21)00871-2. [Epub ahead of print]1663 462749

A clinically validated method to separate and quantify underivatized acylcarnitines and carnitine metabolic intermediates using mixed-mode chromatography with tandem mass spectrometry.

Carolina Luna, Chandler Griffin, Marcus J Miller.

  Acylcarnitines are intermediate metabolites of the mitochondria that serve as biomarkers for inherited disorders of fatty acid oxidation and amino acid metabolism. The prevailing clinical method used to quantify acylcarnitines involves flow-injection tandem mass spectrometry, an approach with a number of limitations; foremost the inability to separate and therefore distinguish key isobaric acylcarnitine species. To address these issues, we report a clinically validated liquid chromatography tandem mass spectrometry method to quantify acylcarnitines, free carnitine, and carnitine metabolic intermediates in human plasma. Importantly, this method resolves clinically relevant isobaric and isomeric acylcarnitine species in a single 22 min analysis without the use of ion pairing or derivatization reagents. This unique combination of features is not achievable by existing acylcarnitine methods and is made possible by the use of a novel mixed-mode chromatographic separation. Further clinical validation studies demonstrate excellent limits of quantification, linearity, accuracy, and inter-assay precision for analyses of 38 different calibrated analytes. An additional 28 analytes are semi-quantitatively analyzed using surrogate calibrators. The study of residual patient specimens confirms the clinical utility of this method and suggests expanded applicability to the diagnosis of peroxisomal disorders. In summary, we report a clinically validated acylcarnitine method that utilizes a novel mixed-mode chromatographic separation to provide a number of advantages in terms of specificity, accuracy, sample preparation time, and clinical utility.

Keywords:  Acylcarnitine profile analysis; Carnitine metabolism; Isomeric separation of acylcarnitines; Mixed-mode chromatography; Peroxisomal dicarboxylic acylcarnitine biomarker

DOI:  https://doi.org/10.1016/j.chroma.2021.462749
Semin Immunol. 2021 Dec 25. pii: S1044-5323(21)00114-7. [Epub ahead of print] 101583

Neutrophil metabolism in the cancer context.

Anita Bodac, Etienne Meylan.

  Neutrophils are critical innate immune cells for the host anti-bacterial defense. Throughout their lifecycle, neutrophils are exposed to different microenvironments and modulate their metabolism to survive and sustain their functions. Although tumor cell metabolism has been intensively investigated, how neutrophil metabolism is affected in cancer remains largely to be discovered. Neutrophils are described as mainly glycolytic cells. However, distinct tumor-associated neutrophil (TAN) states may co-exist in tumors and adapt their metabolism to exert different or even opposing activities ranging from tumor cell killing to tumor support. In this review, we gather evidence about the metabolic mechanisms that underly TANs' pro- or anti-tumoral functions in cancer. We first discuss how tumor-secreted factors and the heterogenous tumor microenvironment can have a strong impact on TAN metabolism. We then describe alternative metabolic pathways used by TANs to exert their functions in cancer, from basic glycolysis to more recently-recognized but less understood metabolic shifts toward mitochondrial oxidative metabolism, lipid and amino acid metabolism and even autophagy. Last, we discuss promising strategies targeting neutrophil metabolism to combat cancer.

Keywords:  Cancer metabolism; Neutrophil metabolism; Tumor-associated neutrophils

DOI:  https://doi.org/10.1016/j.smim.2021.101583
J Proteome Res. 2021 Dec 30.

High Throughput UHPLC-MS-Based Lipidomics Using Vacuum Jacketed Columns.

Robert S Plumb, Giorgis Isaac, Paul D Rainville, Jason Hill, Lee A Gethings, Kelly A Johnson, Joshua Lauterbach, Ian D Wilson.

  Reversed-phase UHPLC-MS is extensively employed for both the profiling of biological fluids and tissues to characterize lipid dysregulation in disease and toxicological studies. With conventional LC-MS systems the chromatographic performance and throughput are limited due to dispersion from the fluidic connections as well as radial and longitudinal thermal gradients in the LC column. In this study vacuum jacketed columns (VJC), positioned at the source of the mass spectrometer, were applied to the lipidomic analysis of plasma extracts. Compared to conventional UHPLC, the VJC-based methods offered greater resolution, faster analysis, and improved peak intensity. For a 5 min VJC analysis, the peak capacity increased by 66%, peak tailing reduced by up to 34%, and the number of lipids detected increased by 30% compared to conventional UHPLC. The narrower peaks, and thus increased resolution, compared to the conventional system resulted in a 2-fold increase in peak intensity as well a significant improvement in MS and MS/MS spectral quality resulting in a 22% increase in the number of lipids identified. When applied to mouse plasma samples, reproducibility of the lipid intensities in the pooled QC ranged from 1.8-12%, with no related drift in tR observed.

Keywords:  NIST 1950 plasma; gefitinib; high-throughput; lipidomics; mouse plasma

DOI:  https://doi.org/10.1021/acs.jproteome.1c00836
Anal Chem. 2021 Dec 30.

Quantitative Accuracy and Precision in Multiplexed Single-Cell Proteomics.

Claudia Ctortecka, Karel Stejskal, Gabriela Krššáková, Sasha Mendjan, Karl Mechtler.

Single-cell proteomics workflows have considerably improved in sensitivity and reproducibility to characterize as-yet unknown biological phenomena. With the emergence of multiplexed single-cell proteomics, studies increasingly present single-cell measurements in conjunction with an abundant congruent carrier to improve the precursor selection and enhance identifications. While these extreme carrier spikes are often >100× more abundant than the investigated samples, the total ion current undoubtably increases but the quantitative accuracy possibly is affected. We here focus on narrowly titrated carrier spikes (i.e., <20×) and assess their elimination for a comparable sensitivity with superior accuracy. We find that subtle changes in the carrier ratio can severely impact the measurement variability and describe alternative multiplexing strategies to evaluate data quality. Lastly, we demonstrate elevated replicate overlap while preserving acquisition throughput at an improved quantitative accuracy with DIA-TMT and discuss optimized experimental designs for multiplexed proteomics of trace samples. This comprehensive benchmarking gives an overview of currently available techniques and guides the conceptualization of the optimal single-cell proteomics experiment.

DOI: https://doi.org/10.1021/acs.analchem.1c04174
Nutrients. 2021 Dec 01. pii: 4340. [Epub ahead of print]13(12):

Fatty Acid Metabolism and Derived-Mediators Distinctive of PPAR-α Activation in Obese Subjects Post Bariatric Surgery.

Claudia Manca, Stefano Pintus, Elisabetta Murru, Giovanni Fantola, Michela Vincis, Barbara Batetta, Enrico Moroni, Gianfranca Carta, Sebastiano Banni.

  Bariatric surger (BS) is characterized by lipid metabolic changes as a response to the massive release of non-esterified fatty acids (NEFA) from adipose depots. The study aimed at evaluating changes in polyunsaturated fatty acids (PUFA) metabolism and biosynthesis of the lipid mediators N-acylethanolamines (NAE), as indices of nuclear peroxisome proliferator-activated receptor (PPAR)-α activation. The observational study was performed on 35 subjects (27 female, 8 male) with obesity, undergoing bariatric surgery. We assessed plasma FA and NAE profiles by LC-MS/MS, clinical parameters and anthropometric measures before and 1 and 6 months after bariatric surgery. One month after bariatric surgery, as body weight and clinical parameters improved significantly, we found higher plasma levels of N-oleoylethanolamine, arachidonic and a 22:6-n3/20:5-n3 ratio as evidence of PPAR-α activation. These changes corresponded to higher circulating levels of NEFA and a steep reduction of the fat mass. After 6 months 22:6-n3/20:5-n3 remained elevated and fat mass was further reduced. Our data suggest that the massive release of NEFA from adipose tissue at 1-Post, possibly by inducing PPAR-α, may enhance FA metabolism contributing to fat depot reduction and improved metabolic parameters in the early stage. However, PUFA metabolic changes favor n6 PUFA biosynthesis, requiring a nutritional strategy aimed at reducing the n6/n3 PUFA ratio.

Keywords:  N-oleoylethanolamine (OEA); bariatric surgery; non-esterified fatty acid (NEFA); obesity; peroxisome proliferator-activated receptor (PPAR)-α

DOI:  https://doi.org/10.3390/nu13124340
Cell Rep. 2021 Dec 28. pii: S2211-1247(21)01671-5. [Epub ahead of print]37(13): 110171

Macrophages are metabolically heterogeneous within the tumor microenvironment.

Xenia Geeraerts, Juan Fernández-Garcia, Felix J Hartmann, Kyra E de Goede, Liesbet Martens, Yvon Elkrim, Ayla Debraekeleer, Benoit Stijlemans, Anke Vandekeere, Gianmarco Rinaldi, Riet De Rycke, Mélanie Planque, Dorien Broekaert, Elisa Meinster, Emile Clappaert, Pauline Bardet, Aleksandar Murgaski, Conny Gysemans, Frank Aboubakar Nana, Yvan Saeys, Sean C Bendall, Damya Laoui, Jan Van den Bossche, Sarah-Maria Fendt, Jo A Van Ginderachter.

  Macrophages are often prominently present in the tumor microenvironment, where distinct macrophage populations can differentially affect tumor progression. Although metabolism influences macrophage function, studies on the metabolic characteristics of ex vivo tumor-associated macrophage (TAM) subsets are rather limited. Using transcriptomic and metabolic analyses, we now reveal that pro-inflammatory major histocompatibility complex (MHC)-IIhi TAMs display a hampered tricarboxylic acid (TCA) cycle, while reparative MHC-IIlo TAMs show higher oxidative and glycolytic metabolism. Although both TAM subsets rapidly exchange lactate in high-lactate conditions, only MHC-IIlo TAMs use lactate as an additional carbon source. Accordingly, lactate supports the oxidative metabolism in MHC-IIlo TAMs, while it decreases the metabolic activity of MHC-IIhi TAMs. Lactate subtly affects the transcriptome of MHC-IIlo TAMs, increases L-arginine metabolism, and enhances the T cell suppressive capacity of these TAMs. Overall, our data uncover the metabolic intricacies of distinct TAM subsets and identify lactate as a carbon source and metabolic and functional regulator of TAMs.

Keywords:  TCA cycle break; immunometabolism; immunosuppression; lactate; macrophage metabolism; metabolomics; non-small-cell lung carcinoma; single-cell metabolic profiling; tumor microenvironment; tumor-associated macrophages

DOI:  https://doi.org/10.1016/j.celrep.2021.110171
Chem Asian J. 2021 Dec 28.

Inorganic Matrices Assisted Laser Desorption/Ionization Mass Spectrometry for Metabolic Analysis in Bio-fluids.

Yajie Ding, Congcong Pei, Weikang Shu, Jingjing Wan.

  Metabolic analysis in bio-fluids interprets the end products in the bio-process, emerging as an irreplaceable disease diagnosis and monitoring platform. Laser desorption/ionization mass spectrometry (LDI MS) based metabolic analysis exhibits great potential for clinical applications in terms of high throughput, rapid signal readout, and minimal sample preparation. There are two essential elements to construct the LDI MS-based metabolic analysis: 1) well-designed nanomaterials as matrices; 2) machine learning algorithms for data analysis. This review highlights the development of various inorganic matrices to comprehend the advantages of LDI MS in metabolite detection and the recent diagnostic applications based on target metabolite detection and untargeted metabolic fingerprints in biological fluids.

Keywords:  biological fluids; laser desorption ionization; mass spectrometry; metabolic diagnosis; metabolomics

DOI:  https://doi.org/10.1002/asia.202101310
J Clin Endocrinol Metab. 2021 Dec 31. pii: dgab931. [Epub ahead of print]

Novel lipidomic signature associated with metabolic risk in women with and without polycystic ovary syndrome.

Aya Mousa, Kevin Huynh, Stacey J Ellery, Boyd J Strauss, Anju E Joham, Barbora de Courten, Peter J Meikle, Helena J Teede.

   BACKGROUND: Dyslipidaemia is a feature of polycystic ovary syndrome (PCOS) and may augment metabolic dysfunction in this population.
OBJECTIVE: Using comprehensive lipidomic profiling and gold-standard metabolic measures, we examined whether distinct lipid biomarkers were associated with metabolic risk in women with and without PCOS.
METHODS: Using pre-existing data and bio-banked samples from 76 women (n=42 with PCOS), we profiled >700 lipid species by mass spectrometry. Lipids were compared between women with and without PCOS and correlated with direct measures of adiposity (dual X-ray absorptiometry and computed tomography) and insulin sensitivity (hyperinsulinaemic-euglycaemic clamp), as well as fasting insulin, HbA1c, and hormonal parameters (luteinizing and follicle stimulating hormones; total and free testosterone; sex hormone-binding globulin [SHBG]; and free androgen index [FAI]). Multivariable linear regression was used with correction for multiple testing.
RESULTS: Despite finding no differences by PCOS status, lysophosphatidylinositol (LPI) species esterified with an 18:0 fatty acid were the strongest lipid species associated with all the metabolic risk factors measured in women with and without PCOS. Across the cohort, higher concentrations of LPI(18:0) and lower concentrations of lipids containing docosahexaenoic acid (DHA, 22:6) n-3 polyunsaturated fatty acids (PUFA) were associated with higher adiposity, insulin resistance, fasting insulin, HbA1c and FAI, and lower SHBG.
CONCLUSIONS: Our data indicate that a distinct lipidomic signature comprising high LPI(18:0) and low DHA-containing lipids are associated with key metabolic risk factors that cluster in PCOS, independent of PCOS status. Prospective studies are needed to corroborate these findings in larger cohorts of women with varying PCOS phenotypes.

Keywords:  Polycystic ovary syndrome; biomarkers; cardiometabolic risk; insulin resistance; lipidomics; obesity

DOI:  https://doi.org/10.1210/clinem/dgab931
Curr Opin Syst Biol. 2021 Dec;28 None

Approaches for completing metabolic networks through metabolite damage and repair discovery.

Corey M Griffith, Adhish S Walvekar, Carole L Linster.

  Metabolites are prone to damage, either via enzymatic side reactions, which collectively form the underground metabolism, or via spontaneous chemical reactions. The resulting non-canonical metabolites that can be toxic, are mended by dedicated "metabolite repair enzymes." Deficiencies in the latter can cause severe disease in humans, whereas inclusion of repair enzymes in metabolically engineered systems can improve the production yield of value-added chemicals. The metabolite damage and repair loops are typically not yet included in metabolic reconstructions and it is likely that many remain to be discovered. Here, we review strategies and associated challenges for unveiling non-canonical metabolites and metabolite repair enzymes, including systematic approaches based on high-resolution mass spectrometry, metabolome-wide side-activity prediction, as well as high-throughput substrate and phenotypic screens.

Keywords:  Metabolite repair enzymes; Non-canonical metabolites; Underground metabolism; Untargeted metabolomics

DOI:  https://doi.org/10.1016/j.coisb.2021.100379
Methods Mol Biol. 2022 ;2445 183-203

Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach.

Kiran Bala Sharma, Suruchi Aggarwal, Amit Kumar Yadav, Sudhanshu Vrati, Manjula Kalia.

  Maintenance of cellular homeostasis through regulated degradation of proteins and organelles is a defining feature of autophagy. This process itself is tightly regulated in a series of well-defined biochemical reactions governed largely by the highly conserved ATG protein family. Given its crucial role in regulating protein levels under both basal and stress conditions such as starvation and infection, genetic or pharmacological perturbation of autophagy results in massive changes in the cellular proteome and impacts nearly every biological process. Therefore, studying autophagy perturbations at a global scale assumes prime importance. In recent years, quantitative mass spectrometry (MS)-based proteomics has emerged as a powerful approach to explore biological processes through global proteome quantification analysis. Tandem mass tag (TMT)-based MS proteomics is one such robust quantitative technique that can examine relative protein abundances in multiple samples (parallel multiplexing). Investigating autophagy through TMT-based MS approach can give great insights into autophagy-regulated biological processes, protein-protein interaction networks, spatiotemporal protein dynamics, and identification of new autophagy substrates. This chapter provides a detailed protocol for studying the impact of a dysfunctional autophagy pathway on the cellular proteome and pathways in a healthy vs. disease (virus infection) condition using a 16-plex TMT-based quantitative proteomics approach. We also provide a pipeline on data processing and analysis using available web-based tools.

Keywords:  ATG5; Autophagy; Mass spectrometry; Quantitative proteomics; TMT

DOI:  https://doi.org/10.1007/978-1-0716-2071-7_12
Mol Cell. 2021 Dec 20. pii: S1097-2765(21)01038-8. [Epub ahead of print]

Persister cancer cells: Iron addiction and vulnerability to ferroptosis.

Raphaël Rodriguez, Stuart L Schreiber, Marcus Conrad.

Ferroptosis is a unique type of non-apoptotic cell death resulting from the unrestrained occurrence of peroxidized phospholipids, which are subject to iron-mediated production of lethal oxygen radicals. This cell death modality has been detected across many organisms, including in mammals, where it can be used as a defense mechanism against pathogens or even harnessed by T cells to sensitize tumor cells toward effective killing. Conversely, ferroptosis is considered one of the main cell death mechanisms promoting degenerative diseases. Emerging evidence suggests that ferroptosis represents a vulnerability in certain cancers. Here, we critically review recent advances linking ferroptosis vulnerabilities of dedifferentiating and persister cancer cells to the dependency of these cells on iron, a potential Achilles heel for small-molecule intervention. We provide a perspective on the mechanisms reliant on iron that contribute to the persister cancer cell state and how this dependency may be exploited for therapeutic benefits.

DOI: https://doi.org/10.1016/j.molcel.2021.12.001
Drug Resist Updat. 2021 Dec 16. pii: S1368-7646(21)00057-1. [Epub ahead of print] 100797

Impact of cancer metabolism on therapy resistance - Clinical implications.

Ana Cristina Gonçalves, Elena Richiardone, Joana Jorge, Bárbara Polónia, Cristina P R Xavier, Iris Chiara Salaroglio, Chiara Riganti, M Helena Vasconcelos, Cyril Corbet, Ana Bela Sarmento-Ribeiro.

  Despite an increasing arsenal of anticancer therapies, many patients continue to have poor outcomes due to the therapeutic failures and tumor relapses. Indeed, the clinical efficacy of anticancer therapies is markedly limited by intrinsic and/or acquired resistance mechanisms that can occur in any tumor type and with any treatment. Thus, there is an urgent clinical need to implement fundamental changes in the tumor treatment paradigm by the development of new experimental strategies that can help to predict the occurrence of clinical drug resistance and to identify alternative therapeutic options. Apart from mutation-driven resistance mechanisms, tumor microenvironment (TME) conditions generate an intratumoral phenotypic heterogeneity that supports disease progression and dismal outcomes. Tumor cell metabolism is a prototypical example of dynamic, heterogeneous, and adaptive phenotypic trait, resulting from the combination of intrinsic [(epi)genetic changes, tissue of origin and differentiation dependency] and extrinsic (oxygen and nutrient availability, metabolic interactions within the TME) factors, enabling cancer cells to survive, metastasize and develop resistance to anticancer therapies. In this review, we summarize the current knowledge regarding metabolism-based mechanisms conferring adaptive resistance to chemo-, radio-and immunotherapies as well as targeted therapies. Furthermore, we report the role of TME-mediated intratumoral metabolic heterogeneity in therapy resistance and how adaptations in amino acid, glucose, and lipid metabolism support the growth of therapy-resistant cancers and/or cellular subpopulations. We also report the intricate interplay between tumor signaling and metabolic pathways in cancer cells and discuss how manipulating key metabolic enzymes and/or providing dietary changes may help to eradicate relapse-sustaining cancer cells. Finally, in the current era of personalized medicine, we describe the strategies that may be applied to implement metabolic profiling for tumor imaging, biomarker identification, selection of tailored treatments and monitoring therapy response during the clinical management of cancer patients.

Keywords:  Cancer metabolism; Glycolysis; Intratumor heterogeneity; Metabolic plasticity; Oxidative phosphorylation; Therapy resistance; Tumor microenvironment

DOI:  https://doi.org/10.1016/j.drup.2021.100797
Metab Eng. 2021 Dec 22. pii: S1096-7176(21)00193-2. [Epub ahead of print]

Isotopically nonstationary 13C metabolic flux analysis in resting and activated human platelets.

Cara L Sake, Alexander J Metcalf, Michelle Meagher, Jorge Di Paola, Keith B Neeves, Nanette R Boyle.

  Platelet metabolism is linked to platelet hyper- and hypoactivity in numerous human diseases. Developing a detailed understanding of the link between metabolic shifts and platelet activation state is integral to improving human health. Here, we show the first application of isotopically nonstationary 13C metabolic flux analysis to quantitatively measure carbon fluxes in both resting and thrombin activated platelets. Metabolic flux analysis results show that resting platelets primarily metabolize glucose to lactate via glycolysis, while acetate is oxidized to fuel the tricarboxylic acid cycle. Upon activation with thrombin, a potent platelet agonist, platelets increase their uptake of glucose 3-fold. This results in an absolute increase in flux throughout central metabolism, but when compared to resting platelets they redistribute carbon dramatically. Activated platelets decrease relative flux to the oxidative pentose phosphate pathway and TCA cycle from glucose and increase relative flux to lactate. These results provide the first report of reaction-level carbon fluxes in platelets and allow us to distinguish metabolic fluxes with much higher resolution than previous studies.

Keywords:  Blood platelets; Metabolic flux analysis; Metabolomics; Thrombin

DOI:  https://doi.org/10.1016/j.ymben.2021.12.007
Methods Mol Biol. 2022 ;2445 27-38

Isolation of Autophagy Competent Lysosomes from Cancer Cells by Differential Large-Scale Multilayered Density Gradient Centrifugations.

Merve Kacal, Helin Vakifahmetoglu-Norberg.

  Accurate isolation of functional and intact lysosomes enables the quantification and analyses of abundances, dynamic changes and enrichment levels of lysosomal content, allowing specific lysosomal investigations induced by autophagy. In this protocol chapter, we describe detailed practical instructions and advices for an efficacious lysosomal enrichment and isolation procedure by differential multilayered density gradient centrifugations using human cancer cell lines. By this method, intact and autophagy competent lysosomes can be isolated from cancer cells based on their distinct density and obtained fractions can further be analyzed for functional lysosomal assays, as well as for protein or metabolic loads to identify select spatiotemporal changes by comparative quantitative measurement. This method has been used to enrich lysosomes from a variety of cancer cells with activated chaperone-mediated autophagy, but can be optimized for other cell lines and tissues for multiple autophagy-induced conditions.

Keywords:  Autophagy; Cancer; Chaperone-mediated autophagy; LAMP-2A; Lysosomes

DOI:  https://doi.org/10.1007/978-1-0716-2071-7_2
Methods Mol Biol. 2022 ;2445 337-349

Measuring Glucose Consumption and Gluconeogenesis in 3D Human Tissue Cultures with Nanoliter Input Volumes.

Aurino M Kemas, Volker M Lauschke.

  Organotypic and microphysiological culture of primary human tissues and cancers has emerged as a powerful set of technologies that allow to faithfully mimic cellular metabolism and functions ex vivo. The predominant 3D culture methods include spheroids and microfluidic chips. These cultures use low cell numbers and culture volumes, which, however, poses important limitations for the available amounts of sample for downstream analyses. Here, we describe a detailed method for the measurement of glucose consumption dynamics in organotypic culture using a bienzymatic colorimetric assay that accurately quantifies glucose levels using nanoliter input volumes. As an example we utilize spheroids consisting of primary human hepatocytes. The assay has been carefully optimized and benchmarked and is compatible with both longitudinal and high-throughput screening in both static and perfused conditions. The method is straightforward and only requires a microplate reader capable of running absorbance kinetic measurements.

Keywords:  3D culture; Cellular spheroid; Colorimetric assay; Glucose consumption; Glucose sensor; Microfluidic chip

DOI:  https://doi.org/10.1007/978-1-0716-2071-7_21
Bioinformatics. 2021 Dec 31. pii: btab867. [Epub ahead of print]

LipidOne: user-friendly lipidomic data analysis tool for a deeper interpretation in a systems biology scenario.

Roberto Maria Pellegrino, Matteo Giulietti, Husam B R Alabed, Sandra Buratta, Lorena Urbanelli, Francesco Piva, Carla Emiliani.

SUMMARY: LC/MS-based analysis techniques combined with specialised lipid tool allow for the qualitative and quantitative determination of thousands of lipid molecules. Some recent bioinformatics tools have been developed to study changes in the lipid profile in case-control experiments and correlate these changes to different enzyme activity or gene expression. However, the existing tools have the limitation to treat only the assembled lipid molecules. In reality, each individual molecule can be considered as an assembly of smaller parts, often called building blocks. These are the result of a myriad of biochemical synthesis and transformation processes that, from a systems biology perspective, should not be ignored. Here, we present LipidOne, a new lipidomic tool which highlights all qualitative and quantitative changes in lipid building blocks both among all detected lipid classes and among experimental groups. Thanks to LipidOne, even differences in lipid building blocks can now be linked to the activity of specific classes of enzymes, transcripts and genes.
AVAILABILITY AND IMPLEMENTATION: LipidOne software is freely available at www.dcbb.unipg.it/LipidOne and https://github.com/matteogiulietti/LipidOne.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

DOI: https://doi.org/10.1093/bioinformatics/btab867
Talanta. 2021 Dec 15. pii: S0039-9140(21)01071-7. [Epub ahead of print]240 123149

Internal calibration as an emerging approach for endogenous analyte quantification: Application to steroids.

Gioele Visconti, Eulalia Olesti, Víctor González-Ruiz, Gaëtan Glauser, David Tonoli, Pierre Lescuyer, Nicolas Vuilleumier, Serge Rudaz.

  The use of mass spectrometry methods with triple quadrupole instruments is well established for quantification. However, the preparation of calibration curves can be time-consuming and prone to analytical errors. In this study, an innovative internal calibration (IC) approach using a one-standard calibration with a stable isotope-labeled (SIL) standard version of the endogenous compound was developed. To ensure optimal quantitative performance, the following parameters were evaluated: the stability of the analyte-to-SIL response factor (RF), the chemical and isotopic purities of the SIL, and the instrumental reproducibility. Using six clinically important endogenous steroids and their respective SIL standards, we demonstrated that RFs obtained on different LC-MS platforms were consistent. The quantitative performance of the proposed approach was determined using quality control samples prepared in depleted serum, and showed both satisfactory precision (1.3%-12.4%) and trueness (77.5%-107.0%, with only 3 values outside ±30%). The developed method was then applied to human serum samples, and the results were similar to those obtained with the conventional quantification approach based on external calibration: the Passing-Bablok regression showed a proportional bias of 6.8% and a mean difference of -5.9% between the two methodologies. Finally, we showed that the naturally occurring isotopes of the SIL can be used to provide additional calibration points and increase the accuracy for analytes with low concentrations.

Keywords:  Internal calibration; Multiple isotopologue reaction monitoring; Quantification; Response factor; Steroids

DOI:  https://doi.org/10.1016/j.talanta.2021.123149