bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–04–16
27 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Recent advances of data-independent acquisition mass spectrometry-based proteomics.
  2. Lipid Metabolic Reprogramming in Embryonal Neoplasms with MYCN Amplification.
  3. Targeting cancer metabolic vulnerabilities for advanced therapeutic efficacy.
  4. "Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome.
  5. Development of Chemical Isotope Labeling Liquid Chromatography Orbitrap Mass Spectrometry for Comprehensive Analysis of Dipeptides.
  6. Encoding LC-MS-Based Untargeted Metabolomics Data into Images toward AI-Based Clinical Diagnosis.
  7. Optimal LC-MS metabolomic profiling reveals emergent changes to monocyte metabolism in response to lipopolysaccharide.
  8. Peak Pair Pruner: a post-processing software to MS-DIAL for peak pair validation and ratio quantification of isotopic labeling LC-MS(/MS) data.
  9. Mannose metabolism inhibition sensitizes acute myeloid leukaemia cells to therapy by driving ferroptotic cell death.
  10. A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry.
  11. Stable isotope labeling-mass spectrometry as a new approach to determine remyelination.
  12. Delineating regions of interest for mass spectrometry imaging by multimodally corroborated spatial segmentation.
  13. Atherosclerosis and lipid metabolism.
  14. Biosynthesis and Significance of Fatty Acids, Glycerophospholipids, and Triacylglycerol in the Processes of Glioblastoma Tumorigenesis.
  15. The role of extracellular vesicles in cancer.
  16. Amino acids in hematologic malignancies: Current status and future perspective.
  17. Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma.
  18. Lipid Profiling Reveals Lipidomic Signatures of Weight Loss Interventions.
  19. Fatty acid metabolism: A new therapeutic target for cervical cancer.
  20. Rapid Profiling of Protein Complex Reorganization in Perturbed Systems.
  21. BUDDY: molecular formula discovery via bottom-up MS/MS interrogation.
  22. Lipid droplets are intracellular mechanical stressors that impair hepatocyte function.
  23. Circulating succinate-modifying metabolites accurately classify and reflect the status of fumarate hydratase-deficient renal cell carcinoma.
  24. Secreted microRNAs in bone metastasis.
  25. Ceramides biomarkers determination in quantitative dried blood spots by UHPLC-MS/MS.
  26. VeRification: an R Shiny application for laboratory method verification and validation.
  27. Asparagine starvation suppresses histone demethylation through iron depletion.
  1. Proteomics. 2023 Apr;23(7-8): e2200011
    Recent advances of data-independent acquisition mass spectrometry-based proteomics.
    Tiannan Guo, Ruedi Aebersold.
      
    DOI:  https://doi.org/10.1002/pmic.202200011
  2. Cancers (Basel). 2023 Apr 04. pii: 2144. [Epub ahead of print]15(7):
    Lipid Metabolic Reprogramming in Embryonal Neoplasms with MYCN Amplification.
    Jyotirmayee Talapatra, Mamatha M Reddy.
      Tumor cells reprogram their metabolism, including glucose, glutamine, nucleotide, lipid, and amino acids to meet their enhanced energy demands, redox balance, and requirement of biosynthetic substrates for uncontrolled cell proliferation. Altered lipid metabolism in cancer provides lipids for rapid membrane biogenesis, generates the energy required for unrestricted cell proliferation, and some of the lipids act as signaling pathway mediators. In this review, we focus on the role of lipid metabolism in embryonal neoplasms with MYCN dysregulation. We specifically review lipid metabolic reactions in neuroblastoma, retinoblastoma, medulloblastoma, Wilms tumor, and rhabdomyosarcoma and the possibility of targeting lipid metabolism. Additionally, the regulation of lipid metabolism by the MYCN oncogene is discussed.
    Keywords:  MYCN; cancer; embryonal tumors; lipid metabolism; therapeutic targeting
    DOI:  https://doi.org/10.3390/cancers15072144
  3. Biomed Pharmacother. 2023 Apr 07. pii: S0753-3322(23)00446-8. [Epub ahead of print]162 114658
    Targeting cancer metabolic vulnerabilities for advanced therapeutic efficacy.
    Tobias Achu Muluh, Xing-Sheng Shu, Ying Ying.
      Cancer metabolism is how cancer cells utilize nutrients and energy to support their growth and proliferation. Unlike normal cells, cancer cells have a unique metabolic profile that allows them to generate energy and the building blocks they need for rapid growth and division. This metabolic profile is marked by an increased reliance on glucose and glutamine as energy sources and changes in how cancer cells use and make key metabolic intermediates like ATP, NADH, and NADPH. This script analyzes a comprehensive overview of the latest advances in tumor metabolism, identifying the key unresolved issues, elaborates on how tumor cells differ from normal cells in their metabolism of nutrients, and explains how tumor cells conflate growth signals and nutrients to proliferate. The metabolic interaction of tumorigenesis and lipid metabolism within the tumor microenvironment and the role of ROS as an anti-tumor agent by mediating various signaling pathways for clinical cancer therapeutic targeting are outlined. Cancer metabolism is highly dynamic and heterogeneous; thus, advanced technologies to better investigate metabolism at the unicellular level without altering tumor tissue are necessary for better research and clinical transformation. The study of cancer metabolism is an area of active research, as scientists seek to understand the underlying metabolic changes that drive cancer growth and to identify potential therapeutic targets.
    Keywords:  Cancer metabolism; Lipid metabolism; Metabolic reprogramming and Pathways; Reactive oxygen species; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.biopha.2023.114658
  4. J Vis Exp. 2023 Mar 24.
    "Cell Surface Capture" Workflow for Label-Free Quantification of the Cell Surface Proteome.
    Akul Naik, Sanjeeva Srivastava, Arun P Wiita.
      Over the past decade, mass spectrometry-based proteomics has enabled an in-depth characterization of biological systems across a broad array of applications. The cell surface proteome ("surfaceome") in human disease is of significant interest, as plasma membrane proteins are the primary target of most clinically approved therapeutics, as well as a key feature by which to diagnostically distinguish diseased cells from healthy tissues. However, focused characterization of membrane and surface proteins of the cell has remained challenging, primarily due to the complexity of cellular lysates, which mask proteins of interest by other high-abundance proteins. To overcome this technical barrier and accurately define the cell surface proteome of various cell types using mass spectrometry proteomics, it is necessary to enrich the cell lysate for cell surface proteins prior to analysis on the mass spectrometer. This paper presents a detailed workflow for labeling cell surface proteins from cancer cells, enriching these proteins out of the cell lysate, and subsequent sample preparation for mass spectrometry analysis.
    DOI:  https://doi.org/10.3791/64952
  5. Anal Chem. 2023 Apr 11.
    Development of Chemical Isotope Labeling Liquid Chromatography Orbitrap Mass Spectrometry for Comprehensive Analysis of Dipeptides.
    Zhan Cheng, Liang Li.
      Dipeptides have recently attracted considerable attention due to their newly found biological functions and potential biomarkers of diseases. Global analysis of dipeptides (400 common dipeptides in total number) in samples of complex matrices would enable functional studies of dipeptides and biomarker discovery. In this work, we report a method for high-coverage detection and accurate relative quantification of dipeptides. This method is based on differential chemical isotope labeling (CIL) of dipeptides with dansylation and liquid chromatography Orbitrap tandem mass spectrometry (LC-Orbitrap-MS). An optimized LC gradient ensured the separation of dansyl-dipeptides, including positional isomers (e.g., leucine- and isoleucine-containing dipeptides). MS/MS collision energy in Orbitrap MS was optimized to provide characteristic fragment ion information to sequence dansyl-dipeptides. Using the optimized conditions, a CIL standard library consisting of retention time, MS, and MS/MS information of a whole set of 400 dansyl-dipeptides was constructed to facilitate rapid dipeptide identification. For qualitative analysis of dipeptides in real samples, IsoMS data processing software's parameters were tuned to improve the coverage of dipeptide annotation. Data-dependent acquisition was also carried out to improve the reliability of dipeptide identification. As examples of applications, we successfully identified a total of 321 dipeptides in rice wines and 105 dipeptides in human serum samples. For quantitative analysis, we demonstrated that the intensity ratios of the peak pairs from 96% of the dansyl-dipeptides detectable in a 1:1 mixture of 12C- and 13C-labeled rice wine samples were within ±20% of an expected value of 1.0. More than 90% of dipeptides were detected with a relative standard deviation of less than 10%, showing good performance of relative quantification.
    DOI:  https://doi.org/10.1021/acs.analchem.2c05796
  6. Anal Chem. 2023 Apr 12.
    Encoding LC-MS-Based Untargeted Metabolomics Data into Images toward AI-Based Clinical Diagnosis.
    Hongmiao Wang, Yandong Yin, Zheng-Jiang Zhu.
      Liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics provides comprehensive and quantitative profiling of metabolites in clinical investigations. The use of whole metabolome profiles is a promising strategy for disease diagnosis but technically challenging. Here, we developed an approach, namely MetImage, to encode LC-MS-based untargeted metabolomics data into multi-channel digital images. Then, the images that represent the comprehensive metabolome profiles can be employed for developing deep learning-based AI models toward clinical diagnosis. In this work, we demonstrated the application of MetImage for clinical screening of esophageal squamous cell carcinoma (ESCC) in a clinical cohort with 1104 participants. A convolutional neuronal network-based AI model was trained to distinguish ESCC screening positive and negative subjects using their serum metabolomics data. Superior performances such as sensitivity (85%), specificity (92%), and area under curve (0.95) were validated in an independent testing cohort (N = 442). Importantly, we demonstrated that our AI-based ESCC screening model is not a "black box". The encoded images reserved the characteristics of mass spectra from the raw LC-MS data; therefore, metabolite identifications in key image features were readily achieved. Altogether, MetImage is a unique approach that encodes raw LC-MS-based untargeted metabolomics data into images and facilitates the utilization of whole metabolome profiles for AI-based clinical applications with improved interpretability.
    DOI:  https://doi.org/10.1021/acs.analchem.2c05079
  7. Front Immunol. 2023 ;14 1116760
    Optimal LC-MS metabolomic profiling reveals emergent changes to monocyte metabolism in response to lipopolysaccharide.
    Emma Leacy, Isabella Batten, Laetitia Sanelli, Matthew McElheron, Gareth Brady, Mark A Little, Hania Khouri.
       Introduction: Immunometabolism examines the links between immune cell function and metabolism. Dysregulation of immune cell metabolism is now an established feature of innate immune cell activation. Advances in liquid chromatography mass spectrometry (LC-MS) technologies have allowed discovery of unique insights into cellular metabolomics. Here we have studied and compared different sample preparation techniques and data normalisation methods described in the literature when applied to metabolomic profiling of human monocytes.
    Methods: Primary monocytes stimulated with lipopolysaccharide (LPS) for four hours was used as a study model. Monocytes (n=24) were freshly isolated from whole blood and stimulated for four hours with lipopolysaccharide (LPS). A methanol-based extraction protocol was developed and metabolomic profiling carried out using a Hydrophilic Interaction Liquid Chromatography (HILIC) LC-MS method. Data analysis pipelines used both targeted and untargeted approaches, and over 40 different data normalisation techniques to account for technical and biological variation were examined. Cytokine levels in supernatants were measured by ELISA.
    Results: This method provided broad coverage of the monocyte metabolome. The most efficient and consistent normalisation method was measurement of residual protein in the metabolite fraction, which was further validated and optimised using a commercial kit. Alterations to the monocyte metabolome in response to LPS can be detected as early as four hours post stimulation. Broad and profound changes in monocyte metabolism were seen, in line with increased cytokine production. Elevated levels of amino acids and Krebs cycle metabolites were noted and decreases in aspartate and β-alanine are also reported for the first time. In the untargeted analysis, 154 metabolite entities were significantly altered compared to unstimulated cells. Pathway analysis revealed the most prominent changes occurred to (phospho-) inositol metabolism, glycolysis, and the pentose phosphate pathway.
    Discussion: These data report the emergent changes to monocyte metabolism in response to LPS, in line with reports from later time points. A number of these metabolites are reported to alter inflammatory gene expression, which may facilitate the increases in cytokine production. Further validation is needed to confirm the link between metabolic activation and upregulation of inflammatory responses.
    Keywords:  LC-MS; LPS; data normalization; metabolomics; monocyte
    DOI:  https://doi.org/10.3389/fimmu.2023.1116760
  8. Bioinform Adv. 2023 ;3(1): vbad044
    Peak Pair Pruner: a post-processing software to MS-DIAL for peak pair validation and ratio quantification of isotopic labeling LC-MS(/MS) data.
    Ryan A Smith, Qibin Zhang.
       Motivation: Isotopic labeling is an essential relative quantification strategy in mass spectrometry-based metabolomics, ideal for studying large cohorts by minimizing common sources of variations in quantitation. MS-DIAL is a free and popular general metabolomics platform that has isotopic labeling data processing capabilities but lacks features provided by other software specialized for isotopic labeling data analysis, such as isotopic pair validation and tabular light-to-heavy peak ratio reporting.
    Results: We developed Peak Pair Pruner (PPP), a standalone Python program for post-processing of MS-DIAL alignment matrixes. PPP provides these missing features and innovation including isotopic overlap subtraction based on a light-tagged pool sample as quality control. The MS-DIAL+PPP workflow for isotopic labeling-based metabolomics data processing was validated using light and heavy dansylated amino acid standard mixture and metabolite extract from human plasma.
    Availability and implementation: Peak Pair Pruner is freely available on Github: https://github.com/QibinZhangLab/Peak_Pair_Pruner. Raw MS data and .ibf files analyzed are on Metabolomics Workbench with Study ID ST002427.
    Contact: q_zhang2@uncg.edu.
    Supplementary information: Supplementary data are available at Bioinformatics Advances online.
    DOI:  https://doi.org/10.1093/bioadv/vbad044
  9. Nat Commun. 2023 Apr 14. 14(1): 2132
    Mannose metabolism inhibition sensitizes acute myeloid leukaemia cells to therapy by driving ferroptotic cell death.
    Keith Woodley, Laura S Dillingh, George Giotopoulos, Pedro Madrigal, Kevin M Rattigan, Céline Philippe, Vilma Dembitz, Aoife M S Magee, Ryan Asby, Louie N van de Lagemaat, Christopher Mapperley, Sophie C James, Jochen H M Prehn, Konstantinos Tzelepis, Kevin Rouault-Pierre, George S Vassiliou, Kamil R Kranc, G Vignir Helgason, Brian J P Huntly, Paolo Gallipoli.
      Resistance to standard and novel therapies remains the main obstacle to cure in acute myeloid leukaemia (AML) and is often driven by metabolic adaptations which are therapeutically actionable. Here we identify inhibition of mannose-6-phosphate isomerase (MPI), the first enzyme in the mannose metabolism pathway, as a sensitizer to both cytarabine and FLT3 inhibitors across multiple AML models. Mechanistically, we identify a connection between mannose metabolism and fatty acid metabolism, that is mediated via preferential activation of the ATF6 arm of the unfolded protein response (UPR). This in turn leads to cellular accumulation of polyunsaturated fatty acids, lipid peroxidation and ferroptotic cell death in AML cells. Our findings provide further support to the role of rewired metabolism in AML therapy resistance, unveil a connection between two apparently independent metabolic pathways and support further efforts to achieve eradication of therapy-resistant AML cells by sensitizing them to ferroptotic cell death.
    DOI:  https://doi.org/10.1038/s41467-023-37652-0
  10. Int J Mol Sci. 2023 Mar 24. pii: 6129. [Epub ahead of print]24(7):
    A Standardized Protocol for Assuring the Validity of Proteomics Results from Liquid Chromatography-High-Resolution Mass Spectrometry.
    Andrzej Gawor, Ewa Bulska.
      Significant advances in the technological development of mass spectrometry in the field of proteomics and the generation of extremely large amounts of data require a very critical approach to assure the validity of results. Commonly used procedures involved liquid chromatography followed by high-resolution mass spectrometry measurements. Proteomics analysis is used in many fields including the investigation of the metabolism of biologically active substances in organisms. Thus, there is a need to care about the validity of the obtained results. In this work, we proposed a standardized protocol for proteomic analysis using liquid chromatography-high-resolution mass spectrometry, which covers all of these analytical steps to ensure the validity of the results. For this purpose, we explored the requirements of the ISO/IEC 17025:2017 standard as a reference document for quality control in biochemistry research-based mass spectrometry.
    Keywords:  ISO 15189:2022; ISO/IEC 17025:2017; mass spectrometry; proteomics; quality control; valid result
    DOI:  https://doi.org/10.3390/ijms24076129
  11. Neural Regen Res. 2023 Oct;18(10): 2184-2185
    Stable isotope labeling-mass spectrometry as a new approach to determine remyelination.
    Anddre Osmar Valdivia, Faith Christine Harvey, Sanjoy K Bhattacharya.
      
    DOI:  https://doi.org/10.4103/1673-5374.369104
  12. Gigascience. 2022 12 28. pii: giad021. [Epub ahead of print]12
    Delineating regions of interest for mass spectrometry imaging by multimodally corroborated spatial segmentation.
    Ang Guo, Zhiyu Chen, Fang Li, Qian Luo.
      Mass spectrometry imaging (MSI), which localizes molecules in a tag-free, spatially resolved manner, is a powerful tool for the understanding of underlying biochemical mechanisms of biological phenomena. When analyzing MSI data, it is essential to delineate regions of interest (ROIs) that correspond to tissue areas of different anatomical or pathological labels. Spatial segmentation, obtained by clustering MSI pixels according to their mass spectral similarities, is a popular approach to automate ROI definition. However, how to select the number of clusters (#Clusters), which determines the granularity of segmentation, remains to be resolved, and an inappropriate #Clusters may lead to ROIs not biologically real. Here we report a multimodal fusion strategy to enable an objective and trustworthy selection of #Clusters by utilizing additional information from corresponding histology images. A deep learning-based algorithm is proposed to extract "histomorphological feature spectra" across an entire hematoxylin and eosin image. Clustering is then similarly performed to produce histology segmentation. Since ROIs originating from instrumental noise or artifacts would not be reproduced cross-modally, the consistency between histology and MSI segmentation becomes an effective measure of the biological validity of the results. So, #Clusters that maximize the consistency is deemed as most probable. We validated our strategy on mouse kidney and renal tumor specimens by producing multimodally corroborated ROIs that agreed excellently with ground truths. Downstream analysis based on the said ROIs revealed lipid molecules highly specific to tissue anatomy or pathology. Our work will greatly facilitate MSI-mediated spatial lipidomics, metabolomics, and proteomics research by providing intelligent software to automatically and reliably generate ROIs.
    Keywords:  mass spectrometry imaging; multimodal data fusion; spatial segmentation
    DOI:  https://doi.org/10.1093/gigascience/giad021
  13. Clin Chem Lab Med. 2023 May 25. 61(s1): s359-s399
    Atherosclerosis and lipid metabolism.
      
    DOI:  https://doi.org/10.1515/cclm-2023-7038
  14. Cancers (Basel). 2023 Apr 06. pii: 2183. [Epub ahead of print]15(7):
    Biosynthesis and Significance of Fatty Acids, Glycerophospholipids, and Triacylglycerol in the Processes of Glioblastoma Tumorigenesis.
    Jan Korbecki, Mateusz Bosiacki, Izabela Gutowska, Dariusz Chlubek, Irena Baranowska-Bosiacka.
      One area of glioblastoma research is the metabolism of tumor cells and detecting differences between tumor and healthy brain tissue metabolism. Here, we review differences in fatty acid metabolism, with a particular focus on the biosynthesis of saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA) by fatty acid synthase (FASN), elongases, and desaturases. We also describe the significance of individual fatty acids in glioblastoma tumorigenesis, as well as the importance of glycerophospholipid and triacylglycerol synthesis in this process. Specifically, we show the significance and function of various isoforms of glycerol-3-phosphate acyltransferases (GPAT), 1-acylglycerol-3-phosphate O-acyltransferases (AGPAT), lipins, as well as enzymes involved in the synthesis of phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), and cardiolipin (CL). This review also highlights the involvement of diacylglycerol O-acyltransferase (DGAT) in triacylglycerol biosynthesis. Due to significant gaps in knowledge, the GEPIA database was utilized to demonstrate the significance of individual enzymes in glioblastoma tumorigenesis. Finally, we also describe the significance of lipid droplets in glioblastoma and the impact of fatty acid synthesis, particularly docosahexaenoic acid (DHA), on cell membrane fluidity and signal transduction from the epidermal growth factor receptor (EGFR).
    Keywords:  brain tumor; docosahexaenoic acid; fatty acid; glioblastoma; glycerophospholipids; lipid droplets; polyunsaturated fatty acid; triacylglycerol
    DOI:  https://doi.org/10.3390/cancers15072183
  15. Cell. 2023 Apr 13. pii: S0092-8674(23)00263-5. [Epub ahead of print]186(8): 1610-1626
    The role of extracellular vesicles in cancer.
    Raghu Kalluri, Kathleen M McAndrews.
      Intercellular communication is a key feature of cancer progression and metastasis. Extracellular vesicles (EVs) are generated by all cells, including cancer cells, and recent studies have identified EVs as key mediators of cell-cell communication via packaging and transfer of bioactive constituents to impact the biology and function of cancer cells and cells of the tumor microenvironment. Here, we review recent advances in understanding the functional contribution of EVs to cancer progression and metastasis, as cancer biomarkers, and the development of cancer therapeutics.
    DOI:  https://doi.org/10.1016/j.cell.2023.03.010
  16. Front Nutr. 2023 ;10 1113228
    Amino acids in hematologic malignancies: Current status and future perspective.
    Mengyao Wang, Ailin Zhao, Meng Li, Ting Niu.
      In recent years, growing emphasis has been placed on amino acids and their role in hematologic malignancies. Cancer cell metabolism is altered during tumorigenesis and development to meet expanding energetic and biosynthetic demands. Amino acids not only act as energy-supplying substances, but also play a vital role via regulating key signaling pathways, modulating epigenetic factors and remodeling tumor microenvironment. Targeting amino acids may be an effective therapeutic approach to address the current therapeutic challenges. Here, we provide an updated overview of mechanisms by which amino acids facilitate tumor development and therapy resistance. We also summarize novel therapies targeting amino acids, focusing on recent advances in basic research and their potential clinical implications.
    Keywords:  amino acid; glutaminolysis; glutathione; hematologic malignancy; metabolism; therapy
    DOI:  https://doi.org/10.3389/fnut.2023.1113228
  17. Int J Mol Sci. 2023 Mar 27. pii: 6290. [Epub ahead of print]24(7):
    Comparison of SPEED, S-Trap, and In-Solution-Based Sample Preparation Methods for Mass Spectrometry in Kidney Tissue and Plasma.
    Evelyn M Templeton, Anna P Pilbrow, Torsten Kleffmann, John W Pickering, Miriam T Rademaker, Nicola J A Scott, Leigh J Ellmers, Christopher J Charles, Zoltan H Endre, A Mark Richards, Vicky A Cameron, Moritz Lassé.
      Mass spectrometry is a powerful technique for investigating renal pathologies and identifying biomarkers, and efficient protein extraction from kidney tissue is essential for bottom-up proteomic analyses. Detergent-based strategies aid cell lysis and protein solubilization but are poorly compatible with downstream protein digestion and liquid chromatography-coupled mass spectrometry, requiring additional purification and buffer-exchange steps. This study compares two well-established detergent-based methods for protein extraction (in-solution sodium deoxycholate (SDC); suspension trapping (S-Trap)) with the recently developed sample preparation by easy extraction and digestion (SPEED) method, which uses strong acid for denaturation. We compared the quantitative performance of each method using label-free mass spectrometry in both sheep kidney cortical tissue and plasma. In kidney tissue, SPEED quantified the most unique proteins (SPEED 1250; S-Trap 1202; SDC 1197). In plasma, S-Trap produced the most unique protein quantifications (S-Trap 150; SDC 148; SPEED 137). Protein quantifications were reproducible across biological replicates in both tissue (R2 = 0.85-0.90) and plasma (SPEED R2 = 0.84; SDC R2 = 0.76, S-Trap R2 = 0.65). Our data suggest SPEED as the optimal method for proteomic preparation in kidney tissue and S-Trap or SPEED as the optimal method for plasma, depending on whether a higher number of protein quantifications or greater reproducibility is desired.
    Keywords:  SPEED; SWATH-MS; kidney; mass spectrometry; plasma; proteomics; quantitative proteomics; renal; sample preparation techniques; suspension trap
    DOI:  https://doi.org/10.3390/ijms24076290
  18. Nutrients. 2023 Apr 06. pii: 1784. [Epub ahead of print]15(7):
    Lipid Profiling Reveals Lipidomic Signatures of Weight Loss Interventions.
    Kaiqing Lin, Wei Cheng, Qiwei Shen, Hui Wang, Ruwen Wang, Shanshan Guo, Xianmin Wu, Wei Wu, Peijie Chen, Yongfei Wang, Hongying Ye, Qiongyue Zhang, Ru Wang.
      Obesity is an epidemic all around the world. Weight loss interventions that are effective differ from each other with regard to various lipidomic responses. Here, we aimed to find lipidomic biomarkers that are related to beneficial changes in weight loss. We adopted an untargeted liquid chromatography with tandem mass spectrometry (LC-MS/MS) method to measure 953 lipid species for Exercise (exercise intervention cohort, N = 25), 1388 lipid species for LSG (laparoscopic sleeve gastrectomy cohort, N = 36), and 886 lipid species for Cushing (surgical removal of the ACTH-secreting pituitary adenomas cohort, N = 25). Overall, the total diacylglycerol (DG), triacylglycerol (TG), phosphatidylethanolamine (PE), phosphatidylinositol (PI), phosphatidylserine (PS), and sphingomyelin (SM) levels were associated with changes in BMI, glycated hemoglobin (HbA1c), triglyceride, and total cholesterol according to weight loss interventions. We found that 73 lipid species changed among the three weight loss interventions. We screened 13 lipid species with better predictive accuracy in diagnosing weight loss situations in either Exercise, LSG, or Cushing cohorts (AUROC > 0.7). More importantly, we identified three phosphatidylcholine (PC) lipid species, PC (14:0_18:3), PC (31:1), and PC (32:2) that were significantly associated with weight change in three studies. Our results highlight potential lipidomic biomarkers that, in the future, could be used in personalized approaches involving weight loss interventions.
    Keywords:  cushing; exercise; laparoscopic sleeve gastrectomy; lipidomics
    DOI:  https://doi.org/10.3390/nu15071784
  19. Front Oncol. 2023 ;13 1111778
    Fatty acid metabolism: A new therapeutic target for cervical cancer.
    Pengbin Ping, Juan Li, Hongbin Lei, Xiaoying Xu.
      Cervical cancer (CC) is one of the most common malignancies in women. Cancer cells can use metabolic reprogramming to produce macromolecules and ATP needed to sustain cell growth, division and survival. Recent evidence suggests that fatty acid metabolism and its related lipid metabolic pathways are closely related to the malignant progression of CC. In particular, it involves the synthesis, uptake, activation, oxidation, and transport of fatty acids. Similarly, more and more attention has been paid to the effects of intracellular lipolysis, transcriptional regulatory factors, other lipid metabolic pathways and diet on CC. This study reviews the latest evidence of the link between fatty acid metabolism and CC; it not only reveals its core mechanism but also discusses promising targeted drugs for fatty acid metabolism. This study on the complex relationship between carcinogenic signals and fatty acid metabolism suggests that fatty acid metabolism will become a new therapeutic target in CC.
    Keywords:  cervical cancer; fatty acid metabolism; fatty acids; metabolic reprogramming; therapeutic target
    DOI:  https://doi.org/10.3389/fonc.2023.1111778
  20. J Proteome Res. 2023 Apr 14.
    Rapid Profiling of Protein Complex Reorganization in Perturbed Systems.
    Isabell Bludau, Charlotte Nicod, Claudia Martelli, Peng Xue, Moritz Heusel, Andrea Fossati, Federico Uliana, Fabian Frommelt, Ruedi Aebersold, Ben C Collins.
      Protein complexes constitute the primary functional modules of cellular activity. To respond to perturbations, complexes undergo changes in their abundance, subunit composition, or state of modification. Understanding the function of biological systems requires global strategies to capture this contextual state information. Methods based on cofractionation paired with mass spectrometry have demonstrated the capability for deep biological insight, but the scope of studies using this approach has been limited by the large measurement time per biological sample and challenges with data analysis. There has been little uptake of this strategy into the broader life science community despite its rich biological information content. We present a rapid integrated experimental and computational workflow to assess the reorganization of protein complexes across multiple cellular states. The workflow combines short gradient chromatography and DIA/SWATH mass spectrometry with a data analysis toolset to quantify changes in a complex organization. We applied the workflow to study the global protein complex rearrangements of THP-1 cells undergoing monocyte to macrophage differentiation and subsequent stimulation of macrophage cells with lipopolysaccharide. We observed substantial proteome reorganization on differentiation and less pronounced changes in macrophage stimulation. We establish our integrated differential pipeline for rapid and state-specific profiling of protein complex organization.
    Keywords:  DIA/SWATH; protein complex; protein−protein interactions; quantitative interaction proteomics
    DOI:  https://doi.org/10.1021/acs.jproteome.3c00125
  21. Nat Methods. 2023 Apr 13.
    BUDDY: molecular formula discovery via bottom-up MS/MS interrogation.
    Shipei Xing, Sam Shen, Banghua Xu, Xiaoxiao Li, Tao Huan.
      A substantial fraction of metabolic features remains undetermined in mass spectrometry (MS)-based metabolomics, and molecular formula annotation is the starting point for unraveling their chemical identities. Here we present bottom-up tandem MS (MS/MS) interrogation, a method for de novo formula annotation. Our approach prioritizes MS/MS-explainable formula candidates, implements machine-learned ranking and offers false discovery rate estimation. Compared with the mathematically exhaustive formula enumeration, our approach shrinks the formula candidate space by 42.8% on average. Method benchmarking on annotation accuracy was systematically carried out on reference MS/MS libraries and real metabolomics datasets. Applied on 155,321 recurrent unidentified spectra, our approach confidently annotated >5,000 novel molecular formulae absent from chemical databases. Beyond the level of individual metabolic features, we combined bottom-up MS/MS interrogation with global optimization to refine formula annotations while revealing peak interrelationships. This approach allowed the systematic annotation of 37 fatty acid amide molecules in human fecal data. All bioinformatics pipelines are available in a standalone software, BUDDY ( https://github.com/HuanLab/BUDDY ).
    DOI:  https://doi.org/10.1038/s41592-023-01850-x
  22. Proc Natl Acad Sci U S A. 2023 Apr 18. 120(16): e2216811120
    Lipid droplets are intracellular mechanical stressors that impair hepatocyte function.
    Abigail E Loneker, Farid Alisafaei, Aayush Kant, David Li, Paul A Janmey, Vivek B Shenoy, Rebecca G Wells.
      Matrix stiffening and external mechanical stress have been linked to disease and cancer development in multiple tissues, including the liver, where cirrhosis (which increases stiffness markedly) is the major risk factor for hepatocellular carcinoma. Patients with nonalcoholic fatty liver disease and lipid droplet-filled hepatocytes, however, can develop cancer in noncirrhotic, relatively soft tissue. Here, by treating primary human hepatocytes with the monounsaturated fatty acid oleate, we show that lipid droplets are intracellular mechanical stressors with similar effects to tissue stiffening, including nuclear deformation, chromatin condensation, and impaired hepatocyte function. Mathematical modeling of lipid droplets as inclusions that have only mechanical interactions with other cellular components generated results consistent with our experiments. These data show that lipid droplets are intracellular sources of mechanical stress and suggest that nuclear membrane tension integrates cell responses to combined internal and external stresses.
    Keywords:  HNF4α; chromatin condensation; cytoskeleton; mechanobiology; nuclear deformation
    DOI:  https://doi.org/10.1073/pnas.2216811120
  23. J Clin Invest. 2023 Apr 13. pii: e165028. [Epub ahead of print]
    Circulating succinate-modifying metabolites accurately classify and reflect the status of fumarate hydratase-deficient renal cell carcinoma.
    Liang Zheng, Zi-Ran Zhu, Tal Sneh, Weituo Zhang, Zao-Yu Wang, Guang-Yu Wu, Wei He, Hong-Gang Qi, Hang Wang, Xiao-Yu Wu, Jonatan Fernández-García, Ifat Abramovich, Yun-Ze Xu, Jin Zhang, Eyal Gottlieb.
      Germline or somatic loss-of-function mutations of fumarate hydratase (FH) predispose patients to an aggressive form of renal cell carcinoma (RCC). Since other than tumor resection, there is no effective therapy for metastatic FH-deficient RCC, an accurate method for early diagnosis is needed. Although MRI or CT scans are offered, they cannot differentiate FH-deficient tumors from other RCCs. Therefore, finding noninvasive plasma biomarkers suitable for rapid diagnosis, screening and surveillance would improve clinical outcomes. Taking advantage of the robust metabolic rewiring that occurs in FH-deficient cells, we performed plasma metabolomics analysis and identified two tumor-derived metabolites, succinyl-adenosine and succinic-cysteine, as outstanding plasma biomarkers for early diagnosis (receiver operating characteristic area under curve (ROCAUC) = 0.98). These two molecules reliably reflected the FH mutation status and tumor mass. We further identified the enzymatic cooperativity by which these biomarkers are produced within the tumor microenvironment. Longitudinal monitoring of patients demonstrated that these circulating biomarkers can be used for reporting on treatment efficacy and identifying recurrent or metastatic tumors.
    Keywords:  Cancer; Genetic diseases; Metabolism; Molecular diagnosis; Oncology
    DOI:  https://doi.org/10.1172/JCI165028
  24. J Bone Miner Metab. 2023 Apr 08.
    Secreted microRNAs in bone metastasis.
    Hanna Taipaleenmäki.
      Bone metastasis is a common complication in several solid cancers, including breast, prostate, and lung. In the bone microenvironment, metastatic cancer cells disturb bone homeostasis leading to osteolytic or osteosclerotic lesions. Osteolytic lesions are characterized by an increased osteoclast-mediated bone resorption while osteosclerotic lesions are caused by enhanced activity of osteoblasts and formation of poor-quality bone. A common feature in bone metastasis is the complex interplay between the cancer cells and the cells of the bone microenvironment, which can occur already before the cancer cells enter the distant site. Cancer cells at the primary site can secrete soluble factors and extracellular vesicles to bone to create a "pre-metastatic niche" i.e., prime the microenvironment permissive for cancer cell homing, survival, and growth. Once in the bone, cancer cells secrete factors to activate the osteoclasts or osteoblasts and the so called "vicious cycle of bone metastases". These pathological cell-cell interactions are largely dependent on secreted proteins. However, increasing evidence demonstrates that secreted RNA molecules, in particular small non-coding microRNAs are critical mediators of the crosstalk between bone and cancer cells. This review article discusses the role of secreted miRNAs in bone metastasis development and progression, and their potential as non-invasive biomarkers.
    Keywords:  Biomarker; Bone metastasis; Bone microenvironment; Extracellular vesicle; microRNA
    DOI:  https://doi.org/10.1007/s00774-023-01424-z
  25. Anal Chim Acta. 2023 May 15. pii: S0003-2670(23)00352-5. [Epub ahead of print]1255 341131
    Ceramides biomarkers determination in quantitative dried blood spots by UHPLC-MS/MS.
    Thomas Meikopoulos, Olga Begou, Georgios Theodoridis, Helen Gika.
      A method was developed for the analysis of four ceramide species; namely C16:0, C18:0, C24:0 and C24:1 in quantitative Dried Blood Samples (qDBS) by LC-MS/MS and validated with the aim to give prominence to an interesting application of at-home blood microsampling for health monitoring. Ceramides, being key-role metabolites implicated in regulation of diverse cellular processes have been considered as emerging biomarkers for different disease states, such as cardiovascular diseases, type 2 diabetes and others. Here, Capitainer device was utilized to provide accurate and consistent volumes of samples, ideal for accurate determinations. The method requires a 10 μL sample offering duplicate analysis by device, is quick and enables the sample collection by distance as it was proved that ceramides under study were stable at various conditions, including RT. Intra and inter-day accuracy of the determination were estimated between 87.6% - 113% and 90.6% -113%, respectively, while intra- and inter-day precision were calculated from 0.2% to 9.9% %RSD and 0.1% - 8.0% %RSD, respectively. The data acquired by ten healthy individuals indicated that circulating ceramides are at higher levels in whole blood taken from the fingertip in comparison to the reported values in plasma or serum.
    Keywords:  Blood microsampling; Dried blood spot; LC-MS/MS; qDBS
    DOI:  https://doi.org/10.1016/j.aca.2023.341131
  26. Clin Chem Lab Med. 2023 Apr 13.
    VeRification: an R Shiny application for laboratory method verification and validation.
    Edmund H Wilkes.
       OBJECTIVES: According to international standards, clinical laboratories are required to verify the performance of assays prior to their implementation in routine practice. This typically involves the assessment of the assay's imprecision and trueness vs. appropriate targets. The analysis of these data is typically performed using frequentist statistical methods and often requires the use of closed source, proprietary software. The motivation for this paper was therefore to develop an open-source, freely available software capable of performing Bayesian analysis of verification data.
    METHODS: The veRification application presented here was developed with the freely available R statistical computing environment, using the Shiny application framework. The codebase is fully open-source and is available as an R package on GitHub.
    RESULTS: The developed application allows the user to analyze imprecision, trueness against external quality assurance, trueness against reference material, method comparison, and diagnostic performance data within a fully Bayesian framework (with frequentist methods also being available for some analyses).
    CONCLUSIONS: Bayesian methods can have a steep learning curve and thus the work presented here aims to make Bayesian analyses of clinical laboratory data more accessible. Moreover, the development of the application and seeks to encourage the dissemination of open-source software within the community and provides a framework through which Shiny applications can be developed, shared, and iterated upon.
    Keywords:  Bayesian; statistics; verification
    DOI:  https://doi.org/10.1515/cclm-2023-0158
  27. iScience. 2023 Apr 21. 26(4): 106425
    Asparagine starvation suppresses histone demethylation through iron depletion.
    Jie Jiang, Sankalp Srivastava, Sheng Liu, Gretchen Seim, Rodney Claude, Minghua Zhong, Sha Cao, Utpal Davé, Reuben Kapur, Amber L Mosley, Chi Zhang, Jun Wan, Jing Fan, Ji Zhang.
      Intracellular α-ketoglutarate is an indispensable substrate for the Jumonji family of histone demethylases (JHDMs) mediating most of the histone demethylation reactions. Since α-ketoglutarate is an intermediate of the tricarboxylic acid cycle and a product of transamination, its availability is governed by the metabolism of several amino acids. Here, we show that asparagine starvation suppresses global histone demethylation. This process is neither due to the change of expression of histone-modifying enzymes nor due to the change of intracellular levels of α-ketoglutarate. Rather, asparagine starvation reduces the intracellular pool of labile iron, a key co-factor for the JHDMs to function. Mechanistically, asparagine starvation suppresses the expression of the transferrin receptor to limit iron uptake. Furthermore, iron supplementation to the culture medium restores histone demethylation and alters gene expression to accelerate cell death upon asparagine depletion. These results suggest that suppressing iron-dependent histone demethylation is part of the cellular adaptive response to asparagine starvation.
    Keywords:  Biological sciences; Epigenetics; Molecular biology; Molecular mechanism of gene regulation; Physiology
    DOI:  https://doi.org/10.1016/j.isci.2023.106425
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