bims-mascan 2023-11-19 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2023‒11‒19
25 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh

Enhancing Proteome Coverage by Using Strong Anion-Exchange in Tandem with Basic-pH Reversed-Phase Chromatography for Sample Multiplexing-Based Proteomics.
Targeted Mass Spectrometry Reveals Interferon-Dependent Eicosanoid and Fatty Acid Alterations in Chronic Myeloid Leukaemia.
Improved 13C metabolic flux analysis in Escherichia coli metabolism: application of a high resolution MS (GC-EI-QTOF) for comprehensive assessment MS/MS fragments.
G-Aligner: a graph-based feature alignment method for untargeted LC-MS-based metabolomics.
Identification of Acetylation Sites of Fatty Acid Synthase (FASN) by Mass Spectrometry and FASN Activity Assay.
SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution.
Flexible Quality Control for Protein Turnover Rates Using d2ome.
Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics.
Ferroptosis induction via targeting metabolic alterations in triple-negative breast cancer.
Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research.
Inhibition of the proline metabolism rate-limiting enzyme P5CS allows proliferation of glutamine-restricted cancer cells.
Characterisation of Aberrant Metabolic Pathways in Hepatoblastoma Using Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS).
OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.
Stable Isotope Labeling-Based Nontargeted Strategy for Characterization of the In Vitro Metabolic Profile of a Novel Doping BPC-157 in Doping Control by UHPLC-HRMS.
Sensitization of cancer cells to ferroptosis coincident with cell cycle arrest.
Ferroptosis Inducers as Promising Radiosensitizer Agents in Cancer Radiotherapy.
Fatty acids abrogate the growth-suppressive effects induced by inhibition of cholesterol flux in pancreatic cancer cells.
Computational Expansion of High-Resolution-MSn Spectral Libraries.
One-carbon unit supplementation fuels tumor-infiltrating T cells and augments checkpoint blockade.
Rewiring of cortical glucose metabolism fuels human brain cancer growth.
Revised Model for the Type A Glycan Biosynthetic Pathway in Clostridioides difficile Strain 630Δerm Based on Quantitative Proteomics of cd0241-cd0244 Mutant Strains.
Cholesterol Metabolism in Pancreatic Cancer.
Targeting phosphoinositide signaling in cancer: relevant techniques to study lipids and novel avenues for therapeutic intervention.
Fatty acid desaturation and lipoxygenase pathways support trained immunity.
DriverDBv4: a multi-omics integration database for cancer driver gene research.

J Proteome Res. 2023 Nov 14.

Enhancing Proteome Coverage by Using Strong Anion-Exchange in Tandem with Basic-pH Reversed-Phase Chromatography for Sample Multiplexing-Based Proteomics.

Tian Zhang, Xinyue Liu, Valentina Rossio, Shane L Dawson, Steven P Gygi, Joao A Paulo.

  Sample multiplexing-based proteomic strategies rely on fractionation to improve proteome coverage. Tandem mass tag (TMT) experiments, for example, can currently accommodate up to 18 samples with proteins spanning several orders of magnitude, thus necessitating fractionation to achieve reasonable proteome coverage. Here, we present a simple yet effective peptide fractionation strategy that partitions a pooled TMT sample with a two-step elution using a strong anion-exchange (SAX) spin column prior to gradient-based basic pH reversed-phase (BPRP) fractionation. We highlight our strategy with a TMTpro18-plex experiment using nine diverse human cell lines in biological duplicate. We collected three data sets, one using only BPRP fractionation and two others of each SAX-partition followed by BPRP. The three data sets quantified a similar number of proteins and peptides, and the data highlight noticeable differences in the distribution of peptide charge and isoelectric point between the SAX partitions. The combined SAX partition data set contributed 10% more proteins and 20% more unique peptides that were not quantified by BPRP fractionation alone. In addition to this improved fractionation strategy, we provide an online resource of relative abundance profiles for over 11,000 proteins across the nine human cell lines, as well as two additional experiments using ovarian and pancreatic cancer cell lines.

Keywords:  FAIMS; RTS; SAX; SPS-MS3; TMTpro; eclipse

DOI:  https://doi.org/10.1021/acs.jproteome.3c00492
Int J Mol Sci. 2023 Oct 24. pii: 15513. [Epub ahead of print]24(21):

Targeted Mass Spectrometry Reveals Interferon-Dependent Eicosanoid and Fatty Acid Alterations in Chronic Myeloid Leukaemia.

Hannah C Scott, Simeon D Draganov, Zhanru Yu, Benedikt M Kessler, Adán Pinto-Fernández.

  Bioactive lipids are involved in cellular signalling events with links to human disease. Many of these are involved in inflammation under normal and pathological conditions. Despite being attractive molecules from a pharmacological point of view, the detection and quantification of lipids has been a major challenge. Here, we have optimised a liquid chromatography-dynamic multiple reaction monitoring-targeted mass spectrometry (LC-dMRM-MS) approach to profile eicosanoids and fatty acids in biological samples. In particular, by applying this analytic workflow to study a cellular model of chronic myeloid leukaemia (CML), we found that the levels of intra- and extracellular 2-Arachidonoylglycerol (2-AG), intracellular Arachidonic Acid (AA), extracellular Prostaglandin F2α (PGF2α), extracellular 5-Hydroxyeicosatetraenoic acid (5-HETE), extracellular Palmitic acid (PA, C16:0) and extracellular Stearic acid (SA, C18:0), were altered in response to immunomodulation by type I interferon (IFN-I), a currently approved treatment for CML. Our observations indicate changes in eicosanoid and fatty acid metabolism, with potential relevance in the context of cancer inflammation and CML.

Keywords:  bioactive lipids; cancer inflammation; cancer metabolism; chronic myeloid leukaemia; eicosanoids; fatty acids; innate immunity; lipidomics; mass spectrometry; type I interferon response

DOI:  https://doi.org/10.3390/ijms242115513
J Ind Microbiol Biotechnol. 2023 Nov 13. pii: kuad039. [Epub ahead of print]

Improved 13C metabolic flux analysis in Escherichia coli metabolism: application of a high resolution MS (GC-EI-QTOF) for comprehensive assessment MS/MS fragments.

Chris Richter, Eva Grafahrend-Belau, Jörg Ziegler, Manish L Raorane, Björn H Junker.

  Gas chromatography-tandem mass spectrometry with electron ionization (GC-EI-MS/MS) provides rich information on stable-isotope labeling for 13C-metabolic flux analysis (13C-MFA). To pave the way for the routine application of tandem MS data for metabolic flux quantification, we aimed to compile a comprehensive library of GC-EI-MS/MS fragments of tert-butyldimethylsilyl (TBDMS) derivatized proteinogenic amino acids. First, we established an analytical workflow which combines high resolution gas chromatography-quadrupole time-of-flight mass spectrometry (GC-EI-QTOFMS) and fully 13C-labeled biomass to identify and structurally elucidate tandem MS amino acid fragments. Application of the high-mass accuracy MS procedure resulted into the identification of 129 validated precursor-product ion pairs of 13 amino acids with 30 fragments being accepted for 13C-MFA. The practical benefit of the novel tandem MS data was demonstrated by a proof-of-concept study which confirmed the importance of the compiled library for high resolution 13C-MFA.

Keywords:   13C-metabolic flux analysis; GC-MS/MS; isotopomer; metabolism; stable isotope tracer

DOI:  https://doi.org/10.1093/jimb/kuad039
BMC Bioinformatics. 2023 Nov 14. 24(1): 431

G-Aligner: a graph-based feature alignment method for untargeted LC-MS-based metabolomics.

Ruimin Wang, Miaoshan Lu, Shaowei An, Jinyin Wang, Changbin Yu.

  BACKGROUND: Liquid chromatography-mass spectrometry is widely used in untargeted metabolomics for composition profiling. In multi-run analysis scenarios, features of each run are aligned into consensus features by feature alignment algorithms to observe the intensity variations across runs. However, most of the existing feature alignment methods focus more on accurate retention time correction, while underestimating the importance of feature matching. None of the existing methods can comprehensively consider feature correspondences among all runs and achieve optimal matching.RESULTS: To comprehensively analyze feature correspondences among runs, we propose G-Aligner, a graph-based feature alignment method for untargeted LC-MS data. In the feature matching stage, G-Aligner treats features and potential correspondences as nodes and edges in a multipartite graph, considers the multi-run feature matching problem an unbalanced multidimensional assignment problem, and provides three combinatorial optimization algorithms to find optimal matching solutions. In comparison with the feature alignment methods in OpenMS, MZmine2 and XCMS on three public metabolomics benchmark datasets, G-Aligner achieved the best feature alignment performance on all the three datasets with up to 9.8% and 26.6% increase in accurately aligned features and analytes, and helped all comparison software obtain more accurate results on their self-extracted features by integrating G-Aligner to their analysis workflow. G-Aligner is open-source and freely available at https://github.com/CSi-Studio/G-Aligner under a permissive license. Benchmark datasets, manual annotation results, evaluation methods and results are available at https://doi.org/10.5281/zenodo.8313034 CONCLUSIONS: In this study, we proposed G-Aligner to improve feature matching accuracy for untargeted metabolomics LC-MS data. G-Aligner comprehensively considered potential feature correspondences between all runs, converting the feature matching problem as a multidimensional assignment problem (MAP). In evaluations on three public metabolomics benchmark datasets, G-Aligner achieved the highest alignment accuracy on manual annotated and popular software extracted features, proving the effectiveness and robustness of the algorithm.

Keywords:  Combinatorial optimization; Feature alignment; LC–MS; Multidimensional assignment problem

DOI:  https://doi.org/10.1186/s12859-023-05525-4
Bio Protoc. 2023 Nov 05. 13(21): e4873

Identification of Acetylation Sites of Fatty Acid Synthase (FASN) by Mass Spectrometry and FASN Activity Assay.

Ting Miao, Hua Bai.

  Lysine acetylation is a conserved post-translational modification and a key regulatory mechanism for various cellular processes, including metabolic control, epigenetic regulation, and cellular signaling transduction. Recent advances in mass spectrometry (MS) enable the extensive identification of acetylated lysine residues of histone and non-histone proteins. However, protein enrichment before MS analysis may be necessary to improve the detection of low-abundant proteins or proteins that exhibit low acetylation levels. Fatty acid synthase (FASN), an essential enzyme catalyzing the de novo synthesis of fatty acids, has been found to be acetylated in various species, from fruit flies to humans. Here, we describe a step-by-step process of antibody-based protein enrichment and sample preparation for acetylation identification of endogenous FASN protein by MS-based proteomics analysis. Meanwhile, we provide a protocol for nicotinamide adenine dinucleotide phosphate (NADPH) absorbance assay for FASN activity measurement, which is one of the primary functional readouts of de novo lipogenesis. Key features • A comprehensive protocol for protein immunoprecipitation and sample preparation for acetylation site identification by mass spectrometry. • Step-by-step procedures for measurement of FASN activity of fruit fly larvae using an absorbance assay.

Keywords:  Acetyl-CoA; Auto-acetylation; De novo lipogenesis; FASN activity; Mass spectrometry; Post-translational modification

DOI:  https://doi.org/10.21769/BioProtoc.4873
Nucleic Acids Res. 2023 Nov 11. pii: gkad1018. [Epub ahead of print]

SPDB: a comprehensive resource and knowledgebase for proteomic data at the single-cell resolution.

Fang Wang, Chunpu Liu, Jiawei Li, Fan Yang, Jiangning Song, Tianyi Zang, Jianhua Yao, Guohua Wang.

The single-cell proteomics enables the direct quantification of protein abundance at the single-cell resolution, providing valuable insights into cellular phenotypes beyond what can be inferred from transcriptome analysis alone. However, insufficient large-scale integrated databases hinder researchers from accessing and exploring single-cell proteomics, impeding the advancement of this field. To fill this deficiency, we present a comprehensive database, namely Single-cell Proteomic DataBase (SPDB, https://scproteomicsdb.com/), for general single-cell proteomic data, including antibody-based or mass spectrometry-based single-cell proteomics. Equipped with standardized data process and a user-friendly web interface, SPDB provides unified data formats for convenient interaction with downstream analysis, and offers not only dataset-level but also protein-level data search and exploration capabilities. To enable detailed exhibition of single-cell proteomic data, SPDB also provides a module for visualizing data from the perspectives of cell metadata or protein features. The current version of SPDB encompasses 133 antibody-based single-cell proteomic datasets involving more than 300 million cells and over 800 marker/surface proteins, and 10 mass spectrometry-based single-cell proteomic datasets involving more than 4000 cells and over 7000 proteins. Overall, SPDB is envisioned to be explored as a useful resource that will facilitate the wider research communities by providing detailed insights into proteomics from the single-cell perspective.

DOI: https://doi.org/10.1093/nar/gkad1018
Int J Mol Sci. 2023 Oct 25. pii: 15553. [Epub ahead of print]24(21):

Flexible Quality Control for Protein Turnover Rates Using d2ome.

Henock M Deberneh, Rovshan G Sadygov.

  Bioinformatics tools are used to estimate in vivo protein turnover rates from the LC-MS data of heavy water labeled samples in high throughput. The quantification includes peak detection and integration in the LC-MS domain of complex input data of the mammalian proteome, which requires the integration of results from different experiments. The existing software tools for the estimation of turnover rate use predefined, built-in, stringent filtering criteria to select well-fitted peptides and determine turnover rates for proteins. The flexible control of filtering and quality measures will help to reduce the effects of fluctuations and interferences to the signals from target peptides while retaining an adequate number of peptides. This work describes an approach for flexible error control and filtering measures implemented in the computational tool d2ome for automating protein turnover rates. The error control measures (based on spectral properties and signal features) reduced the standard deviation and tightened the confidence intervals of the estimated turnover rates.

Keywords:  heavy water metabolic labeling; isotope profiles; label incorporation; protein turnover; retention time alignment

DOI:  https://doi.org/10.3390/ijms242115553
J Chromatogr A. 2023 Oct 31. pii: S0021-9673(23)00704-5. [Epub ahead of print]1712 464479

Unravelling the brain metabolome: A review of liquid chromatography - mass spectrometry strategies for extracellular brain metabolomics.

Liam Nestor, Dimitri De Bundel, Yvan Vander Heyden, Ilse Smolders, Ann Van Eeckhaut.

  The analysis of the brain extracellular metabolome is of interest for numerous subdomains within neuroscience. Not only does it provide information about normal physiological functions, it is even more of interest for biomarker discovery and target discovery in disease. The extracellular analysis of the brain is particularly interesting as it provides information about the release of mediators in the brain extracellular fluid to look at cellular signaling and metabolic pathways through the release, diffusion and re-uptake of neurochemicals. In vivo samples are obtained through microdialysis, cerebral open-flow microperfusion or solid-phase microextraction. The analytes of potential interest are typically low in concentration and can have a wide range of physicochemical properties. Liquid chromatography coupled to mass spectrometry has proven its usefulness in brain metabolomics. It allows sensitive and specific analysis of low sample volumes, obtained through different approaches. Several strategies for the analysis of the extracellular fluid have been proposed. The most widely used approaches apply sample derivatization, specific stationary phases and/or hydrophilic interaction liquid chromatography. Miniaturization of these methods allows an even higher sensitivity. The development of chiral metabolomics is indispensable, as it allows to compare the enantiomeric ratio of compounds and provides even more challenges. Some limitations continue to exist for the previously developed methods and the development of new, more sensitive methods remains needed. This review provides an overview of the methods developed for sampling and liquid chromatography-mass spectrometry analysis of the extracellular metabolome.

Keywords:  Brain; Extracellular fluid; Liquid chromatography-mass spectrometry; Metabolomics; Sample collection

DOI:  https://doi.org/10.1016/j.chroma.2023.464479
Biomed Pharmacother. 2023 Nov 09. pii: S0753-3322(23)01664-5. [Epub ahead of print]169 115866

Ferroptosis induction via targeting metabolic alterations in triple-negative breast cancer.

Yaru Wang, Yue Sun, Feiran Wang, Hongyi Wang, Jing Hu.

  Triple-negative breast cancer (TNBC), the most aggressive form of breast cancer, presents severe threats to women's health. Therefore, it is critical to find novel treatment approaches. Ferroptosis, a newly identified form of programmed cell death, is marked by the buildup of lipid reactive oxygen species (ROS) and high iron concentrations. According to previous studies, ferroptosis sensitivity can be controlled by a number of metabolic events in cells, such as amino acid metabolism, iron metabolism, and lipid metabolism. Given that TNBC tumors are rich in iron and lipids, inducing ferroptosis in these tumors is a potential approach for TNBC treatment. Notably, the metabolic adaptability of cancer cells allows them to coordinate an attack on one or more metabolic pathways to initiate ferroptosis, offering a novel perspective to improve the high drug resistance and clinical therapy of TNBC. However, a clear picture of ferroptosis in TNBC still needs to be completely revealed. In this review, we provide an overview of recent advancements regarding the connection between ferroptosis and amino acid, iron, and lipid metabolism in TNBC. We also discuss the probable significance of ferroptosis as an innovative target for chemotherapy, radiotherapy, immunotherapy, nanotherapy and natural product therapy in TNBC, highlighting its therapeutic potential and application prospects.

Keywords:  Ferroptosis; Metabolic reprogramming; Therapy; Triple-negative breast cancer (TNBC)

DOI:  https://doi.org/10.1016/j.biopha.2023.115866
Molecules. 2023 Nov 04. pii: 7430. [Epub ahead of print]28(21):

Recent Progress in Mass Spectrometry-Based Metabolomics in Major Depressive Disorder Research.

Mingxia Liu, Wen Ma, Yi He, Zuoli Sun, Jian Yang.

  Major depressive disorder (MDD) is a serious mental illness with a heavy social burden, but its underlying molecular mechanisms remain unclear. Mass spectrometry (MS)-based metabolomics is providing new insights into the heterogeneous pathophysiology, diagnosis, treatment, and prognosis of MDD by revealing multi-parametric biomarker signatures at the metabolite level. In this comprehensive review, recent developments of MS-based metabolomics in MDD research are summarized from the perspective of analytical platforms (liquid chromatography-MS, gas chromatography-MS, supercritical fluid chromatography-MS, etc.), strategies (untargeted, targeted, and pseudotargeted metabolomics), key metabolite changes (monoamine neurotransmitters, amino acids, lipids, etc.), and antidepressant treatments (both western and traditional Chinese medicines). Depression sub-phenotypes, comorbid depression, and multi-omics approaches are also highlighted to stimulate further advances in MS-based metabolomics in the field of MDD research.

Keywords:  biomarkers; major depressive disorder; mass spectrometry; metabolomics

DOI:  https://doi.org/10.3390/molecules28217430
Nat Metab. 2023 Nov 13.

Inhibition of the proline metabolism rate-limiting enzyme P5CS allows proliferation of glutamine-restricted cancer cells.

Samantha J Linder, Tiziano Bernasocchi, Bárbara Martínez-Pastor, Kelly D Sullivan, Matthew D Galbraith, Caroline A Lewis, Christina M Ferrer, Ruben Boon, Giorgia G Silveira, Hyo Min Cho, Charles Vidoudez, Stuti Shroff, Joao P Oliveira-Costa, Kenneth N Ross, Rami Massri, Yusuke Matoba, Eugene Kim, Bo R Rueda, Shannon L Stott, Eyal Gottlieb, Joaquin M Espinosa, Raul Mostoslavsky.

Glutamine is a critical metabolite for rapidly proliferating cells as it is used for the synthesis of key metabolites necessary for cell growth and proliferation. Glutamine metabolism has been proposed as a therapeutic target in cancer and several chemical inhibitors are in development or in clinical trials. How cells subsist when glutamine is limiting is poorly understood. Here, using an unbiased screen, we identify ALDH18A1, which encodes P5CS, the rate-limiting enzyme in the proline biosynthetic pathway, as a gene that cells can downregulate in response to glutamine starvation. Notably, P5CS downregulation promotes de novo glutamine synthesis, highlighting a previously unrecognized metabolic plasticity of cancer cells. The glutamate conserved from reducing proline synthesis allows cells to produce the key metabolites necessary for cell survival and proliferation under glutamine-restricted conditions. Our findings reveal an adaptive pathway that cancer cells acquire under nutrient stress, identifying proline biosynthesis as a previously unrecognized major consumer of glutamate, a pathway that could be exploited for developing effective metabolism-driven anticancer therapies.

DOI: https://doi.org/10.1038/s42255-023-00919-3
Cancers (Basel). 2023 Oct 28. pii: 5182. [Epub ahead of print]15(21):

Characterisation of Aberrant Metabolic Pathways in Hepatoblastoma Using Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS).

Alison Whitby, Pardeep Pabla, Bhoomi Shastri, Laudina Amugi, Álvaro Del Río-Álvarez, Dong-Hyun Kim, Laura Royo, Carolina Armengol, Madhumita Dandapani.

  Hepatoblastoma (HB) is a rare childhood tumour with an evolving molecular landscape. We present the first comprehensive metabolomic analysis using untargeted and targeted liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) of paired tumour and non-tumour surgical samples in HB patients (n = 8 pairs). This study demonstrates that the metabolomic landscape of HB is distinct from that of non-tumour (NT) liver tissue, with 35 differentially abundant metabolites mapping onto pathways such as fatty acid transport, glycolysis, the tricarboxylic acid (TCA) cycle, branched-chain amino acid degradation and glutathione synthesis. Targeted metabolomics demonstrated reduced short-chain acylcarnitines and a relative accumulation of branched-chain amino acids. Medium- and long-chain acylcarnitines in HB were similar to those in NT. The metabolomic changes reported are consistent with previously reported transcriptomic data from tumour and non-tumour samples (49 out of 54 targets) as well as metabolomic data obtained using other techniques. Gene set enrichment analysis (GSEA) from RNAseq data (n = 32 paired HB and NT samples) demonstrated a downregulation of the carnitine metabolome and immunohistochemistry showed a reduction in CPT1a (n = 15 pairs), which transports fatty acids into the mitochondria, suggesting a lack of utilisation of long-chain fatty acids in HB. Thus, our findings suggest a reduced metabolic flux in HB which is corroborated at the gene expression and protein levels. Further work could yield novel insights and new therapeutic targets.

Keywords:  acylcarnitine; carnitine palmitoyl transferase (CPT1); fatty acid oxidation; hepatoblastoma; liquid chromatography and tandem mass spectrometry; metabolomics

DOI:  https://doi.org/10.3390/cancers15215182
Chin J Cancer Res. 2023 Oct 30. 35(5): 550-562

OpenNAU: An open-source platform for normalizing, analyzing, and visualizing cancer untargeted metabolomics data.

Qingrong Sun, Qingqing Xu, Majie Wang, Yongcheng Wang, Dandan Zhang, Maode Lai.

  Objective: As an important part of metabolomics analysis, untargeted metabolomics has become a powerful tool in the study of tumor mechanisms and the discovery of metabolic markers with high-throughput spectrometric data which also poses great challenges to data analysis, from the extraction of raw data to the identification of differential metabolites. To date, a large number of analytical tools and processes have been developed and constructed to serve untargeted metabolomics research. The different selection of analytical tools and parameter settings lead to varied results of untargeted metabolomics data. Our goal is to establish an easily operated platform and obtain a repeatable analysis result.Methods: We used the R language basic environment to construct the preprocessing system of the original data and the LAMP (Linux+Apache+MySQL+PHP) architecture to build a cloud mass spectrum data analysis system.
Results: An open-source analysis software for untargeted metabolomics data (openNAU) was constructed. It includes the extraction of raw mass data and quality control for the identification of differential metabolic ion peaks. A reference metabolomics database based on public databases was also constructed.
Conclusions: A complete analysis system platform for untargeted metabolomics was established. This platform provides a complete template interface for the addition and updating of the analysis process, so we can finish complex analyses of untargeted metabolomics with simple human-computer interactions. The source code can be downloaded from https://github.com/zjuRong/openNAU.

Keywords:  LAMP architecture; Untargeted metabolomics; normalization; reference metabolomics; shiny

DOI:  https://doi.org/10.21147/j.issn.1000-9604.2023.05.11
Molecules. 2023 Oct 30. pii: 7345. [Epub ahead of print]28(21):

Stable Isotope Labeling-Based Nontargeted Strategy for Characterization of the In Vitro Metabolic Profile of a Novel Doping BPC-157 in Doping Control by UHPLC-HRMS.

Tian Tian, Jing Jing, Yuanyuan Li, Yang Wang, Xiaojun Deng, Yuanhong Shan.

  Traditional strategies for the metabolic profiling of doping are limited by the unpredictable metabolic pathways and the numerous proportions of background and chemical noise that lead to inadequate metabolism knowledge, thereby affecting the selection of optimal detection targets. Thus, a stable isotope labeling-based nontargeted strategy combined with ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS) was first proposed for the effective and rapid metabolism analysis of small-molecule doping agents and demonstrated via its application to a novel doping BPC-157. Using 13C/15N-labeled BPC-157, a complete workflow including automatic 13C0,15N0-13C6,15N2m/z pair picking based on the characteristic behaviors of isotope pairs was constructed, and one metabolite produced by a novel metabolic pathway plus eight metabolites produced by the conventional amide-bond breaking metabolic pathway were successfully discovered from two incubation models. Furthermore, a specific method for the detection of BPC-157 and the five main metabolites in human urine was developed and validated with satisfactory detection limits (0.01~0.11 ng/mL) and excellent quantitative ability (linearity: 0.02~50 ng/mL with R2 > 0.999; relative error (RE)% < 10% and relative standard deviation (RSD)% < 5%; recovery > 90%). The novel metabolic pathway and the in vitro metabolic profile could provide new insights into the biotransformation of BPC-157 and improved targets for doping control.

Keywords:  BPC-157; UHPLC-HRMS; doping control; metabolic profile; stable isotope labeling

DOI:  https://doi.org/10.3390/molecules28217345
Cell Chem Biol. 2023 Nov 09. pii: S2451-9456(23)00372-0. [Epub ahead of print]

Sensitization of cancer cells to ferroptosis coincident with cell cycle arrest.

Jason Rodencal, Nathan Kim, Andrew He, Veronica L Li, Mike Lange, Jianping He, Amy Tarangelo, Zachary T Schafer, James A Olzmann, Jonathan Z Long, Julien Sage, Scott J Dixon.

  Ferroptosis is a non-apoptotic form of cell death that can be triggered by inhibiting the system xc- cystine/glutamate antiporter or the phospholipid hydroperoxidase glutathione peroxidase 4 (GPX4). We have investigated how cell cycle arrest caused by stabilization of p53 or inhibition of cyclin-dependent kinase 4/6 (CDK4/6) impacts ferroptosis sensitivity. Here, we show that cell cycle arrest can enhance sensitivity to ferroptosis induced by covalent GPX4 inhibitors (GPX4i) but not system xc- inhibitors. Greater sensitivity to GPX4i is associated with increased levels of oxidizable polyunsaturated fatty acid-containing phospholipids (PUFA-PLs). Higher PUFA-PL abundance upon cell cycle arrest involves reduced expression of membrane-bound O-acyltransferase domain-containing 1 (MBOAT1) and epithelial membrane protein 2 (EMP2). A candidate orally bioavailable GPX4 inhibitor increases lipid peroxidation and shrinks tumor volumes when combined with a CDK4/6 inhibitor. Thus, cell cycle arrest may make certain cancer cells more susceptible to ferroptosis in vivo.

Keywords:  CDK4/6; EMP2; MBOAT1; MUFA; PUFA; ferroptosis; iron; lipid peroxidation; p53; palbociclib

DOI:  https://doi.org/10.1016/j.chembiol.2023.10.011
Curr Radiopharm. 2023 Nov 16.

Ferroptosis Inducers as Promising Radiosensitizer Agents in Cancer Radiotherapy.

Fatemeh-Jalali Zefrei, Mohammd Shormij, Leila Dastranj, Maryam Alvandi, Zahra Shaghaghi, Soghra Farzipour, Nasim Zarei-Polgardani.

  Radiotherapy (RT) failure has historically been mostly attributed to radioresistance. Ferroptosis is a type of controlled cell death that depends on iron and is caused by polyunsaturated fatty acid peroxidative damage. Utilizing a ferroptosis inducer may be a successful tactic for preventing tumor growth and radiotherapy-induced cell death. A regulated form of cell death known as ferroptosis is caused by the peroxidation of phospholipids containing polyunsaturated fatty acids in an iron-dependent manner (PUFA-PLs). The ferroptosis pathway has a number of important regulators. By regulating the formation of PUFA-PLs, the important lipid metabolism enzyme ACSL4 promotes ferroptosis, whereas SLC7A11 and (glutathione peroxidase 4) GPX4 prevent ferroptosis. In addition to introducing the ferroptosis inducer chemicals that have recently been demonstrated to have a radiosensitizer effect, this review highlights the function and methods by which ferroptosis contributes to RT-induced cell death and tumor suppression in vitro and in vivo.

Keywords:  Ferroptosis; cancer; radio-oncology; radioresistance; radiosensitizer; radiotherapy

DOI:  https://doi.org/10.2174/0118744710262369231110065230
Cancer Cell Int. 2023 Nov 17. 23(1): 276

Fatty acids abrogate the growth-suppressive effects induced by inhibition of cholesterol flux in pancreatic cancer cells.

Yuchuan Li, Manoj Amrutkar, Anette Vefferstad Finstadsveen, Knut Tomas Dalen, Caroline S Verbeke, Ivar P Gladhaug.

  BACKGROUND: Despite therapeutic advances, the prognosis of pancreatic ductal adenocarcinoma (PDAC) remains extremely poor. Metabolic reprogramming is increasingly recognized as a key contributor to tumor progression and therapy resistance in PDAC. One of the main metabolic changes essential for tumor growth is altered cholesterol flux. Targeting cholesterol flux appears an attractive therapeutic approach, however, the complex regulation of cholesterol balance in PDAC cells remains poorly understood.METHODS: The lipid content in human pancreatic duct epithelial (HPDE) cells and human PDAC cell lines (BxPC-3, MIA PaCa-2, and PANC-1) was determined. Cells exposed to eight different inhibitors targeting different regulators of lipid flux, in the presence or absence of oleic acid (OA) stimulation were assessed for changes in viability, proliferation, migration, and invasion. Intracellular content and distribution of cholesterol was assessed. Lastly, proteome profiling of PANC-1 exposed to the sterol O-acyltransferase 1 (SOAT1) inhibitor avasimibe, in presence or absence of OA, was performed.
RESULTS: PDAC cells contain more free cholesterol but less cholesteryl esters and lipid droplets than HPDE cells. Exposure to different lipid flux inhibitors increased cell death and suppressed proliferation, with different efficiency in the tested PDAC cell lines. Avasimibe had the strongest ability to suppress proliferation across the three PDAC cell lines. All inhibitors showing cell suppressive effect disturbed intracellular cholesterol flux and increased cholesterol aggregation. OA improved overall cholesterol balance, reduced free cholesterol aggregation, and reversed cell death induced by the inhibitors. Treatment with avasimibe changed the cellular proteome substantially, mainly for proteins related to biosynthesis and metabolism of lipids and fatty acids, apoptosis, and cell adhesion. Most of these changes were restored by OA.
CONCLUSIONS: The study reveals that disturbing the cholesterol flux by inhibiting the actions of its key regulators can yield growth suppressive effects on PDAC cells. The presence of fatty acids restores intracellular cholesterol balance and abrogates the alternations induced by cholesterol flux inhibitors. Taken together, targeting cholesterol flux might be an attractive strategy to develop new therapeutics against PDAC. However, the impact of fatty acids in the tumor microenvironment must be taken into consideration.

Keywords:  Cholesterol; Fatty acids; Lipid flux; Pancreatic cancer

DOI:  https://doi.org/10.1186/s12935-023-03138-8
Anal Chem. 2023 Nov 14.

Computational Expansion of High-Resolution-MSn Spectral Libraries.

Brandon Y Lieng, Andrew T Quaile, Xavier Domingo-Almenara, Hannes L Röst, J Rafael Montenegro-Burke.

Commonly, in MS-based untargeted metabolomics, some metabolites cannot be confidently identified due to ambiguities in resolving isobars and structurally similar species. To address this, analytical techniques beyond traditional MS2 analysis, such as MSn fragmentation, can be applied to probe metabolites for additional structural information. In MSn fragmentation, recursive cycles of activation are applied to fragment ions originating from the same precursor ion detected on an MS1 spectrum. This resonant-type collision-activated dissociation (CAD) can yield information that cannot be ascertained from MS2 spectra alone, which helps improve the performance of metabolite identification workflows. However, most approaches for metabolite identification require mass-to-charge (m/z) values measured with high resolution, as this enables the determination of accurate mass values. Unfortunately, high-resolution-MSn spectra are relatively rare in spectral libraries. Here, we describe a computational approach to generate a database of high-resolution-MSn spectra by converting existing low-resolution-MSn spectra using complementary high-resolution-MS2 spectra generated by beam-type CAD. Using this method, we have generated a database, derived from the NIST20 MS/MS database, of MSn spectral trees representing 9637 compounds and 19386 precursor ions where at least 90% of signal intensity was converted from low-to-high resolution.

DOI: https://doi.org/10.1021/acs.analchem.3c03343
bioRxiv. 2023 Nov 03. pii: 2023.11.01.565193. [Epub ahead of print]

One-carbon unit supplementation fuels tumor-infiltrating T cells and augments checkpoint blockade.

Xincheng Xu, Zihong Chen, Caroline R Bartman, Xi Xing, Kellen Olszewski, Joshua D Rabinowitz.

Nucleotides perform important metabolic functions, carrying energy and feeding nucleic acid synthesis. Here, we use isotope tracing-mass spectrometry to quantitate the contributions to purine nucleotides of salvage versus de novo synthesis. We further explore the impact of augmenting a key precursor for purine synthesis, one-carbon (1C) units. We show that tumors and tumor-infiltrating T cells (relative to splenic T cells) synthesize purines de novo . Purine synthesis requires two 1C units, which come from serine catabolism and circulating formate. Shortage of 1C units is a potential bottleneck for anti-tumor immunity. Elevating circulating formate drives its usage by tumor-infiltrating T cells. Orally administered methanol functions as a formate pro-drug, with deuteration enabling control of formate-production kinetics. In MC38 tumors, safe doses of methanol raise formate levels and augment anti-PD-1 checkpoint blockade, tripling durable regressions. Thus, 1C deficiency can gate antitumor immunity and this metabolic checkpoint can be overcome with pharmacological 1C supplementation.Statement of significance: Checkpoint blockade has revolutionized cancer therapy. Durable tumor control, however, is achieved in only a minority of patients. We show that the efficacy of anti-PD-1 blockade can be enhanced by metabolic supplementation with one-carbon donors. Such donors support nucleotide synthesis in tumor-infiltrating T cells and merit future clinical evaluation.

DOI: https://doi.org/10.1101/2023.11.01.565193
medRxiv. 2023 Oct 25. pii: 2023.10.24.23297489. [Epub ahead of print]

Rewiring of cortical glucose metabolism fuels human brain cancer growth.

Andrew J Scott, Anjali Mittal, Baharan Meghdadi, Sravya Palavalasa, Abhinav Achreja, Alexandra O'Brien, Ayesha U Kothari, Weihua Zhou, Jie Xu, Angelica Lin, Kari Wilder-Romans, Donna M Edwards, Zhe Wu, Jiane Feng, Anthony C Andren, Li Zhang, Vijay Tarnal, Kimberly A Redic, Nathan Qi, Joshua Fischer, Ethan Yang, Michael S Regan, Sylwia A Stopka, Gerard Baquer, Theodore S Lawrence, Sriram Venneti, Nathalie Y R Agar, Costas A Lyssiotis, Wajd N Al-Holou, Deepak Nagrath, Daniel R Wahl.

The brain avidly consumes glucose to fuel neurophysiology. Cancers of the brain, such as glioblastoma (GBM), lose aspects of normal biology and gain the ability to proliferate and invade healthy tissue. How brain cancers rewire glucose utilization to fuel these processes is poorly understood. Here we perform infusions of 13 C-labeled glucose into patients and mice with brain cancer to define the metabolic fates of glucose-derived carbon in tumor and cortex. By combining these measurements with quantitative metabolic flux analysis, we find that human cortex funnels glucose-derived carbons towards physiologic processes including TCA cycle oxidation and neurotransmitter synthesis. In contrast, brain cancers downregulate these physiologic processes, scavenge alternative carbon sources from the environment, and instead use glucose-derived carbons to produce molecules needed for proliferation and invasion. Targeting this metabolic rewiring in mice through dietary modulation selectively alters GBM metabolism and slows tumor growth.Significance: This study is the first to directly measure biosynthetic flux in both glioma and cortical tissue in human brain cancer patients. Brain tumors rewire glucose carbon utilization away from oxidation and neurotransmitter production towards biosynthesis to fuel growth. Blocking these metabolic adaptations with dietary interventions slows brain cancer growth with minimal effects on cortical metabolism.

DOI: https://doi.org/10.1101/2023.10.24.23297489
ACS Infect Dis. 2023 Nov 15.

Revised Model for the Type A Glycan Biosynthetic Pathway in Clostridioides difficile Strain 630Δerm Based on Quantitative Proteomics of cd0241-cd0244 Mutant Strains.

Bart Claushuis, Arnoud H de Ru, Sarah A Rotman, Peter A van Veelen, Lisa F Dawson, Brendan W Wren, Jeroen Corver, Wiep Klaas Smits, Paul J Hensbergen.

  The bacterial flagellum is involved in a variety of processes including motility, adherence, and immunomodulation. In the Clostridioides difficile strain 630Δerm, the main filamentous component, FliC, is post-translationally modified with an O-linked Type A glycan structure. This modification is essential for flagellar function, since motility is seriously impaired in gene mutants with improper biosynthesis of the Type A glycan. The cd0240-cd0244 gene cluster encodes the Type A biosynthetic proteins, but the role of each gene, and the corresponding enzymatic activity, have not been fully elucidated. Using quantitative mass spectrometry-based proteomics analyses, we determined the relative abundance of the observed glycan variations of the Type A structure in cd0241, cd0242, cd0243, and cd0244 mutant strains. Our data not only confirm the importance of CD0241, CD0242, and CD0243 but, in contrast to previous data, also show that CD0244 is essential for the biosynthesis of the Type A modification. Combined with additional bioinformatic analyses, we propose a revised model for Type A glycan biosynthesis.

Keywords:  Glycosylation; biosynthesis; enzyme; flagella; mass spectrometry; proteomics

DOI:  https://doi.org/10.1021/acsinfecdis.3c00485
Cancers (Basel). 2023 Oct 27. pii: 5177. [Epub ahead of print]15(21):

Cholesterol Metabolism in Pancreatic Cancer.

Artur Rebelo, Jörg Kleeff, Yoshiaki Sunami.

  Pancreatic cancer's substantial impact on cancer-related mortality, responsible for 8% of cancer deaths and ranking fourth in the US, persists despite advancements, with a five-year relative survival rate of only 11%. Forecasts predict a 70% surge in new cases and a 72% increase in global pancreatic cancer-related deaths by 2040. This review explores the intrinsic metabolic reprogramming of pancreatic cancer, focusing on the mevalonate pathway, including cholesterol biosynthesis, transportation, targeting strategies, and clinical studies. The mevalonate pathway, central to cellular metabolism, significantly shapes pancreatic cancer progression. Acetyl coenzyme A (Acetyl-CoA) serves a dual role in fatty acid and cholesterol biosynthesis, fueling acinar-to-ductal metaplasia (ADM) and pancreatic intraepithelial neoplasia (PanIN) development. Enzymes, including acetoacetyl-CoA thiolase, 3-hydroxy-3methylglutaryl-CoA (HMG-CoA) synthase, and HMG-CoA reductase, are key enzymes in pancreatic cancer. Inhibiting HMG-CoA reductase, e.g., by using statins, shows promise in delaying PanIN progression and impeding pancreatic cancer. Dysregulation of cholesterol modification, uptake, and transport significantly impacts tumor progression, with Sterol O-acyltransferase 1 (SOAT1) driving cholesterol ester (CE) accumulation and disrupted low-density lipoprotein receptor (LDLR) expression contributing to cancer recurrence. Apolipoprotein E (ApoE) expression in tumor stroma influences immune suppression. Clinical trials targeting cholesterol metabolism, including statins and SOAT1 inhibitors, exhibit potential anti-tumor effects, and combination therapies enhance efficacy. This review provides insights into cholesterol metabolism's convergence with pancreatic cancer, shedding light on therapeutic avenues and ongoing clinical investigations.

Keywords:  cholesterol metabolism; clinical trial; lipid metabolism; lipoprotein; mevalonate pathway; pancreatic cancer

DOI:  https://doi.org/10.3390/cancers15215177
Front Cell Dev Biol. 2023 ;11 1297355

Targeting phosphoinositide signaling in cancer: relevant techniques to study lipids and novel avenues for therapeutic intervention.

Alicia Llorente, Ryan M Loughran, Brooke M Emerling.

  Phosphoinositides serve as essential players in numerous biological activities and are critical for overall cellular function. Due to their complex chemical structures, localization, and low abundance, current challenges in the phosphoinositide field include the accurate measurement and identification of specific variants, particularly those with acyl chains. Researchers are intensively developing innovative techniques and approaches to address these challenges and advance our understanding of the impact of phosphoinositide signaling on cellular biology. This article provides an overview of recent advances in the study of phosphoinositides, including mass spectrometry, lipid biosensors, and real-time activity assays using fluorometric sensors. These methodologies have proven instrumental for a comprehensive exploration of the cellular distribution and dynamics of phosphoinositides and have shed light on the growing significance of these lipids in human health and various pathological processes, including cancer. To illustrate the importance of phosphoinositide signaling in disease, this perspective also highlights the role of a family of lipid kinases named phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks), which have recently emerged as exciting therapeutic targets for cancer treatment. The ongoing exploration of phosphoinositide signaling not only deepens our understanding of cellular biology but also holds promise for novel interventions in cancer therapy.

Keywords:  PI5P4K; cancer; lipid; lipidomics; mass spectometry; metabolism; phosphoinositide; signaling

DOI:  https://doi.org/10.3389/fcell.2023.1297355
Nat Commun. 2023 Nov 15. 14(1): 7385

Fatty acid desaturation and lipoxygenase pathways support trained immunity.

Anaísa V Ferreira, Juan Carlos Alarcon-Barrera, Jorge Domínguez-Andrés, Özlem Bulut, Gizem Kilic, Priya A Debisarun, Rutger J Röring, Hatice N Özhan, Eva Terschlüsen, Athanasios Ziogas, Sarantos Kostidis, Yassene Mohammed, Vasiliki Matzaraki, George Renieris, Evangelos J Giamarellos-Bourboulis, Mihai G Netea, Martin Giera.

Infections and vaccines can induce enhanced long-term responses in innate immune cells, establishing an innate immunological memory termed trained immunity. Here, we show that monocytes with a trained immunity phenotype, due to exposure to the Bacillus Calmette-Guérin (BCG) vaccine, are characterized by an increased biosynthesis of different lipid mediators (LM) derived from long-chain polyunsaturated fatty acids (PUFA). Pharmacological and genetic approaches show that long-chain PUFA synthesis and lipoxygenase-derived LM are essential for the BCG-induced trained immunity responses of human monocytes. Furthermore, products of 12-lipoxygenase activity increase in monocytes of healthy individuals after BCG vaccination. Grasping the underscoring lipid metabolic pathways contributes to our understanding of trained immunity and may help to identify therapeutic tools and targets for the modulation of innate immune responses.

DOI: https://doi.org/10.1038/s41467-023-43315-x
Nucleic Acids Res. 2023 Nov 13. pii: gkad1060. [Epub ahead of print]

DriverDBv4: a multi-omics integration database for cancer driver gene research.

Chia-Hsin Liu, Yo-Liang Lai, Pei-Chun Shen, Hsiu-Cheng Liu, Meng-Hsin Tsai, Yu-De Wang, Wen-Jen Lin, Fang-Hsin Chen, Chia-Yang Li, Shu-Chi Wang, Mien-Chie Hung, Wei-Chung Cheng.

Advancements in high-throughput technology offer researchers an extensive range of multi-omics data that provide deep insights into the complex landscape of cancer biology. However, traditional statistical models and databases are inadequate to interpret these high-dimensional data within a multi-omics framework. To address this limitation, we introduce DriverDBv4, an updated iteration of the DriverDB cancer driver gene database (http:////driverdb.bioinfomics.org//). This updated version offers several significant enhancements: (i) an increase in the number of cohorts from 33 to 70, encompassing approximately 24 000 samples; (ii) inclusion of proteomics data, augmenting the existing types of omics data and thus expanding the analytical scope; (iii) implementation of multiple multi-omics algorithms for identification of cancer drivers; (iv) new visualization features designed to succinctly summarize high-context data and redesigned existing sections to accommodate the increased volume of datasets and (v) two new functions in Customized Analysis, specifically designed for multi-omics driver identification and subgroup expression analysis. DriverDBv4 facilitates comprehensive interpretation of multi-omics data across diverse cancer types, thereby enriching the understanding of cancer heterogeneity and aiding in the development of personalized clinical approaches. The database is designed to foster a more nuanced understanding of the multi-faceted nature of cancer.

DOI: https://doi.org/10.1093/nar/gkad1060