bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022–12–25
28 papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz



  1. Nat Methods. 2022 Dec 21.
      Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.
    DOI:  https://doi.org/10.1038/s41592-022-01710-0
  2. Nat Metab. 2022 Dec;4(12): 1792-1811
      The mechanistic target of rapamycin complex 1 (mTORC1) senses and relays environmental signals from growth factors and nutrients to metabolic networks and adaptive cellular systems to control the synthesis and breakdown of macromolecules; however, beyond inducing de novo lipid synthesis, the role of mTORC1 in controlling cellular lipid content remains poorly understood. Here we show that inhibition of mTORC1 via small molecule inhibitors or nutrient deprivation leads to the accumulation of intracellular triglycerides in both cultured cells and a mouse tumor model. The elevated triglyceride pool following mTORC1 inhibition stems from the lysosome-dependent, but autophagy-independent, hydrolysis of phospholipid fatty acids. The liberated fatty acids are available for either triglyceride synthesis or β-oxidation. Distinct from the established role of mTORC1 activation in promoting de novo lipid synthesis, our data indicate that mTORC1 inhibition triggers membrane phospholipid trafficking to the lysosome for catabolism and an adaptive shift in the use of constituent fatty acids for storage or energy production.
    DOI:  https://doi.org/10.1038/s42255-022-00706-6
  3. Anal Chem. 2022 Dec 20. 94(50): 17370-17378
      The success of precision medicine relies upon collecting data from many individuals at the population level. Although advancing technologies have made such large-scale studies increasingly feasible in some disciplines such as genomics, the standard workflows currently implemented in untargeted metabolomics were developed for small sample numbers and are limited by the processing of liquid chromatography/mass spectrometry data. Here we present an untargeted metabolomics workflow that is designed to support large-scale projects with thousands of biospecimens. Our strategy is to first evaluate a reference sample created by pooling aliquots of biospecimens from the cohort. The reference sample captures the chemical complexity of the biological matrix in a small number of analytical runs, which can subsequently be processed with conventional software such as XCMS. Although this generates thousands of so-called features, most do not correspond to unique compounds from the samples and can be filtered with established informatics tools. The features remaining represent a comprehensive set of biologically relevant reference chemicals that can then be extracted from the entire cohort's raw data on the basis of m/z values and retention times by using Skyline. To demonstrate applicability to large cohorts, we evaluated >2000 human plasma samples with our workflow. We focused our analysis on 360 identified compounds, but we also profiled >3000 unknowns from the plasma samples. As part of our workflow, we tested 14 different computational approaches for batch correction and found that a random forest-based approach outperformed the others. The corrected data revealed distinct profiles that were associated with the geographic location of participants.
    DOI:  https://doi.org/10.1021/acs.analchem.2c01270
  4. Eur J Pharmacol. 2022 Dec 16. pii: S0014-2999(22)00584-2. [Epub ahead of print] 175323
      Glutamine, as the most abundant amino acid in the body, participates in the biological synthesis of nucleotides and other non-essential amino acids in the process of cell metabolism. Recent studies showed that glutamine metabolic reprogramming is an important signal during cancer development and progression. This metabolic signature in cancer cells can promote the development of cancer by activating multiple signaling pathways and oncogenes. It can also be involved in tumor immune regulation and promote the development of drug resistance to tumors. In this review, we mainly summarize the role of glutamine metabolic reprogramming in tumors, including the regulation of multiple signaling pathways. We further discussed the promising tumor treatment strategy by targeting glutamine metabolism alone or in combination with chemotherapeutics.
    Keywords:  Glutamine; Multidrug resistance; Tumor immunotherapy; Tumor metabolism
    DOI:  https://doi.org/10.1016/j.ejphar.2022.175323
  5. J Korean Neurosurg Soc. 2022 Dec 20.
       Objective: The types and functions of lipids involved in glioblastoma (GB) are not well known. Lipidomics is a new field that examines cellular lipids on a large scale and novel aplication of lipidomics in the biomedical sciences have emerged. This study aimed to investigate the potential of blood lipids for use as biomarkers for the diagnosis of GB via untargated lipidomic approach. Gaining a deeper understanding of lipid metabolism in patients with GB can contribute to the early diagnosis with GB patiens and also development of novel and better therapeutic options.
    Methods: This study was performed using blood samples collected from 14 patients (eight females and six males) and 14 controls (eight females and six males). Lipids were extracted from blood samples and quantified using phosphorus assay. Lipid profiles of between patients with GB and controls were compared via an untargeted lipidomics approach using 6530 Accurate-Mass Q-TOF LC/MS mass spectrometer.
    Results: According to the results obtained using the untargeted lipidomics approach, differentially regulated lipid species, including fatty acid (FA), glycerolipid (GL), glycerophospholipid (PG), saccharolipid (SL), sphingolipid (SP), and sterol lipid (ST) were identified between in patients with GB and controls.
    Conclusion: Differentially regulated lipids were identified in patients with GB, and these lipid species were predicted as potential biomarkers for diagnosis of GB.
    Keywords:  Biomarkers; Cancer; Electrospray Ionization mass spectrometry; Glioblastoma; Lipidomics
    DOI:  https://doi.org/10.3340/jkns.2022.0091
  6. Metabolites. 2022 Dec 03. pii: 1214. [Epub ahead of print]12(12):
      Metabolism is a series of life-sustaining chemical reactions in organisms, providing energy required for cellular processes and building blocks for cellular constituents of proteins, lipids, carbohydrates and nucleic acids. Cancer cells frequently reprogram their metabolic behaviors to adapt their rapid proliferation and altered tumor microenvironments. Not only aerobic glycolysis (also termed the Warburg effect) but also altered mitochondrial metabolism, amino acid metabolism and lipid metabolism play important roles for cancer growth and aggressiveness. Thus, the mechanistic elucidation of these metabolic changes is invaluable for understanding the pathogenesis of cancers and developing novel metabolism-targeted therapies. In this review article, we first provide an overview of essential metabolic mechanisms, and then summarize the recent findings of metabolic reprogramming and the recent reports of metabolism-targeted therapies for thyroid cancer.
    Keywords:  TCA cycle; electron transport chain; glutaminolysis; glycolysis; lipid metabolism; metabolomics; the Warburg effect; thyroid cancer
    DOI:  https://doi.org/10.3390/metabo12121214
  7. Metabolites. 2022 Nov 24. pii: 1168. [Epub ahead of print]12(12):
      As a comprehensive analysis of all metabolites in a biological system, metabolomics is being widely applied in various clinical/health areas for disease prediction, diagnosis, and prognosis. However, challenges remain in dealing with the metabolomic complexity, massive data, metabolite identification, intra- and inter-individual variation, and reproducibility, which largely limit its widespread implementation. This study provided a comprehensive workflow for clinical metabolomics, including sample collection and preparation, mass spectrometry (MS) data acquisition, and data processing and analysis. Sample collection from multiple clinical sites was strictly carried out with standardized operation procedures (SOP). During data acquisition, three types of quality control (QC) samples were set for respective MS platforms (GC-MS, LC-MS polar, and LC-MS lipid) to assess the MS performance, facilitate metabolite identification, and eliminate contamination. Compounds annotation and identification were implemented with commercial software and in-house-developed PAppLineTM and UlibMS library. The batch effects were removed using a deep learning model method (NormAE). Potential biomarkers identification was performed with tree-based modeling algorithms including random forest, AdaBoost, and XGBoost. The modeling performance was evaluated using the F1 score based on a 10-times repeated trial for each. Finally, a sub-cohort case study validated the reliability of the entire workflow.
    Keywords:  GC-MS; LC-MS; clinical cohort; data modeling; data normalization; metabolomics; quality control
    DOI:  https://doi.org/10.3390/metabo12121168
  8. Int J Cancer. 2022 Dec 19.
      The mechanisms linking tumor microenvironment acidosis to disease progression are not understood. Here, we used mammary, pancreatic, and colon cancer cells to show that adaptation to growth at an extracellular pH (pHe ) mimicking acidic tumor niches is associated with upregulated net acid extrusion capacity and elevated intracellular pH at physiological pHe , but not at the acidic pHe . Using metabolic profiling, shotgun lipidomics, imaging, and biochemical analyses, we show that the acid adaptation-induced phenotype is characterized by a shift toward oxidative metabolism, increased lipid droplet-, triacylglycerol-, peroxisome content, and mitochondrial hyperfusion. Peroxisome proliferator-activated receptor-α (PPARA, PPARα) expression and activity are upregulated, at least in part by increased fatty acid uptake. PPARα upregulates genes driving increased mitochondrial and peroxisomal mass and β-oxidation capacity, including mitochondrial lipid import proteins CPT1A, CPT2, and SLC25A20, electron transport chain components, peroxisomal proteins PEX11A and ACOX1, and thioredoxin-interacting protein (TXNIP), a negative regulator of glycolysis. This endows acid-adapted cancer cells with increased capacity for utilizing fatty acids for metabolic needs, while limiting glycolysis. As a consequence, the acid-adapted cells exhibit increased sensitivity to PPARα inhibition. We conclude that PPARα is a key upstream regulator of metabolic changes favoring cancer cell survival in acidic tumor niches. This article is protected by copyright. All rights reserved.
    Keywords:  PPARα; acidic microenvironment; cancer metabolism; fatty acid metabolism; β-oxidation
    DOI:  https://doi.org/10.1002/ijc.34404
  9. J Proteome Res. 2022 Dec 21.
      In the rapidly moving proteomics field, a diverse patchwork of data analysis pipelines and algorithms for data normalization and differential expression analysis is used by the community. We generated a mass spectrometry downstream analysis pipeline (MS-DAP) that integrates both popular and recently developed algorithms for normalization and statistical analyses. Additional algorithms can be easily added in the future as plugins. MS-DAP is open-source and facilitates transparent and reproducible proteome science by generating extensive data visualizations and quality reporting, provided as standardized PDF reports. Second, we performed a systematic evaluation of methods for normalization and statistical analysis on a large variety of data sets, including additional data generated in this study, which revealed key differences. Commonly used approaches for differential testing based on moderated t-statistics were consistently outperformed by more recent statistical models, all integrated in MS-DAP. Third, we introduced a novel normalization algorithm that rescues deficiencies observed in commonly used normalization methods. Finally, we used the MS-DAP platform to reanalyze a recently published large-scale proteomics data set of CSF from AD patients. This revealed increased sensitivity, resulting in additional significant target proteins which improved overlap with results reported in related studies and includes a large set of new potential AD biomarkers in addition to previously reported.
    Keywords:  Alzheimer’s disease; benchmarking; bioinformatics; proteomics; software
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00513
  10. Mol Genet Metab. 2022 Nov 30. pii: S1096-7192(22)00442-5. [Epub ahead of print]138(1): 106966
      Acetyl-coenzyme A (Ac-CoA) is a core metabolite with essential roles throughout cell physiology. These functions can be classified into energetics, biosynthesis, regulation and acetylation of large and small molecules. Ac-CoA is essential for oxidative metabolism of glucose, fatty acids, most amino acids, ethanol, and of free acetate generated by endogenous metabolism or by gut bacteria. Ac-CoA cannot cross lipid bilayers, but acetyl groups from Ac-CoA can shuttle across membranes as part of carrier molecules like citrate or acetylcarnitine, or as free acetate or ketone bodies. Ac-CoA is the basic unit of lipid biosynthesis, providing essentially all of the carbon for the synthesis of fatty acids and of isoprenoid-derived compounds including cholesterol, coenzyme Q and dolichols. High levels of Ac-CoA in hepatocytes stimulate lipid biosynthesis, ketone body production and the diversion of pyruvate metabolism towards gluconeogenesis and away from oxidation; low levels exert opposite effects. Acetylation changes the properties of molecules. Acetylation is necessary for the synthesis of acetylcholine, acetylglutamate, acetylaspartate and N-acetyl amino sugars, and to metabolize/eliminate some xenobiotics. Acetylation is a major post-translational modification of proteins. Different types of protein acetylation occur. The most-studied form occurs at the epsilon nitrogen of lysine residues. In histones, lysine acetylation can alter gene transcription. Acetylation of other proteins has diverse, often incompletely-documented effects. Inborn errors related to Ac-CoA feature a broad spectrum of metabolic, neurological and other features. To date, a small number of studies of animals with inborn errors of CoA thioesters has included direct measurement of acyl-CoAs. These studies have shown that low levels of tissue Ac-CoA correlate with the development of clinical signs, hinting that shortage of Ac-CoA may be a recurrent theme in these conditions. Low levels of Ac-CoA could potentially disrupt any of its roles.
    Keywords:  Acetyl-CoA; Acetylation; Acylation; Energy metabolism; Inborn errors
    DOI:  https://doi.org/10.1016/j.ymgme.2022.106966
  11. Metabolites. 2022 Nov 30. pii: 1198. [Epub ahead of print]12(12):
      Eicosanoids are lipid mediators generated from arachidonic acid with pro- and anti-inflammatory properties. Despite these lipid mediators being known for decades, quantitative determination in biological samples is still challenging due to low abundance, instability, the existence of regio- and stereoisomers, and a wide polarity range that hampers chromatographic separation. In this study, we developed a supercritical fluid chromatography mass spectrometry (SFC-MS) platform for the quantification of relevant eicosanoids. Application of a chiral amylose-based column and modifier combination of 2-propanol/acetonitrile offered separation and sufficient resolution of 11 eicosanoids (5-, 12-, 15-HETE, PGB1, LTB4, t-LTB4, 20-OH-LTB4, PGE2, PGD2, PGF2α, TxB2) with baseline separation of isobaric analytes within 12 min. The method was validated in terms of range (78-2500 ng/mL), linearity, accuracy, precision, and recovery according to EMA guidelines. Finally, we confirmed the method's applicability by quantifying eicosanoid levels in human primary blood cells. In conclusion, we present a validated SFC-MS method for the determination of relevant eicosanoids in biological samples with a wide range of polarity while maintaining baseline separation of isobars, which allows coupling to a single quadrupole mass detector.
    Keywords:  lipid mediators; monocytes; neutrophils; oxylipins; platelets; supercritical fluid chromatography; validation
    DOI:  https://doi.org/10.3390/metabo12121198
  12. Environ Res. 2022 Dec 20. pii: S0013-9351(22)02464-1. [Epub ahead of print] 115137
      Plastic biodegradation by insects has made significant progress, opening up new avenues for the treatment of plastic waste. Wax moth larvae, for example, have attracted the attention of the scientific community because they are known to chew, ingest, and biodegrade natural polymer bee waxes. Despite this, we know very little about how these insects perform on manufactured plastics or how manufactured plastics affect insect metabolism. As a result, we studied the metabolism of greater wax moths (Galleria mellonela) fed on molasses-supplemented polylactic acid plastic (PLA) blocks. An analysis of the central carbon metabolism (CCM) metabolites was performed using liquid chromatography triple quadrupole mass spectrometry (LC-QQQ-MS), while an analysis of untargeted metabolites and lipidomics was conducted using liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF-MS). In total, 169 targeted CCM metabolites, 222 untargeted polar metabolites, and 196 untargeted polar lipids were identified within the insect samples. In contrast, compared to control larvae, PLA-fed larvae displayed significantly different levels of 97 CCM metabolites, 75 polar metabolites, and 57 lipids. Purine and pyrimidine metabolisms were affected by PLA feeding, as well as amino acid metabolism, carbohydrates, cofactors, vitamins, and related metabolisms. Additionally, PLA exposure disrupted insect energy metabolism and oxidative stress, among other metabolic disturbances. The larvae fed PLA have lower levels of several lipids, suggesting a reduction in lipid reserves, and ceramide levels are likely to have changed due to apoptosis and inflammation. The study indicates that G. mellonela larvae could ingest PLA, but this process causes some metabolic stress for the host. Future studies of the molecular pathways of this biodegradation process might help to provide strategies for stress reduction that would speed up insect digestion of plastic.
    Keywords:  Insects; Lipidomics; Metabolomics; Omics; Plastic biodegradation; Polylactic acid
    DOI:  https://doi.org/10.1016/j.envres.2022.115137
  13. Toxicol In Vitro. 2022 Dec 20. pii: S0887-2333(22)00238-7. [Epub ahead of print] 105540
      Mass spectrometry based 'omics pairs well with organ-on-a-chip-based investigations, which often have limited cellular material for sampling. However, a common issue with these chip-based platforms is well-to-well or chip-to-chip variability in the proteome and metabolome due to factors such as plate edge effects, cellular asynchronization, effluent flow, and limited cell count. This causes high variability in the quantitative multi-omics analysis of samples, potentially masking true biological changes within the system. Solutions to this have been approached via data processing tools and post-acquisition normalization strategies such as constant median, constant sum, and overall signal normalization. Unfortunately, these methods do not adequately correct for the large variations, resulting in a need for increased biological replicates. The methods in this work utilize a dansylation based assay with a subset of labeled metabolites that allow for pre-acquisition normalization to better correlate the biological perturbations that truly occur in chip-based platforms. BCA protein assays were performed in tandem with a proteomics pipeline to achieve pre-acquisition normalization. The CN Bio PhysioMimix was seeded with primary hepatocytes and challenged with VX after six days of culture, and the metabolome and proteome were analyzed using the described normalization methods. A decreased coefficient of variation percentage is achieved, significant changes are observed through the proteome and metabolome, and better classification of biological replicates acquired because of these strategies.
    Keywords:  CNBio; Dansylation; Mass spectrometry; Metabolomics; Organ-on-a-chip; Proteomics
    DOI:  https://doi.org/10.1016/j.tiv.2022.105540
  14. Cancers (Basel). 2022 Dec 19. pii: 6267. [Epub ahead of print]14(24):
      Breast cancer (BC) is a heterogeneous disease that can be triggered by genetic alterations in mammary epithelial cells, leading to diverse disease outcomes in individual patients. The metabolic heterogeneity of BC enhances its ability to adapt to changes in the tumor microenvironment and metabolic stress, but unfavorably affects the patient's therapy response, prognosis and clinical effect. Extrinsic factors from the tumor microenvironment and the intrinsic parameters of cancer cells influence their mitochondrial functions, which consequently alter their lipid metabolism and their ability to proliferate, migrate and survive in a harsh environment. The balanced interplay between mitochondria and fatty acid synthesis or fatty acid oxidation has been attributed to a combination of environmental factors and to the genetic makeup, oncogenic signaling and activities of different transcription factors. Hence, understanding the mechanisms underlying lipid metabolic heterogeneity and alterations in BC is gaining interest as a major target for drug resistance. Here we review the major recent reports on lipid metabolism heterogeneity and bring to light knowledge on the functional contribution of diverse lipid metabolic pathways to breast tumorigenesis and therapy resistance.
    Keywords:  breast cancer; cancer progression; drug resistance; heterogeneity; hypoxia; lipid metabolism; oxidative stress; tumor microenvironment
    DOI:  https://doi.org/10.3390/cancers14246267
  15. Anal Chem. 2022 Dec 20.
      Large cohorts of samples from multiple batches are usually required for global metabolomic studies to characterize the metabolic state of human disease. As such, it is critical to eliminate systematic variation and truly reveal the biologically associated alterations. In this study, we proposed a reference material-based approach (Ref-M) for data correction by liquid chromatography-mass spectrometry and represented by an analysis of multibatch human serum samples. The reference material was generated by mixing serum from healthy donors and distributed to each extraction batch of subject samples. Pooled quality control samples and isotopic internal standards were then applied in each acquisition batch for data quality control. Finally, each metabolite in subject samples was normalized by its counterpart in the reference serum. We demonstrated that Ref-M significantly enhanced the numbers of efficient features and effectively eliminated the batch variation of 522 serum samples of healthy individuals, benign pulmonary nodules, and lung cancer patients. Twenty differential metabolites were identified to distinguish lung cancer from healthy controls in the training set. The discriminant model was validated in an independent data set with an area under the receiver operating characteristics (ROC) curve (AUC) of 0.853. Another 40 serum samples further tested with Ref-M were achieved an AUC of 0.843 by the established model. Our results showed that the reference material-based approach presents the potential to improve the data comparability and precision for biomarker discovery in large-scale metabolomic studies.
    DOI:  https://doi.org/10.1021/acs.analchem.2c04188
  16. Methods Mol Biol. 2023 ;2610 149-165
      Viruses like influenza A virus (IAV) hijack host cells in order to replicate. To actively and abundantly synthesize viral proteins, they reprogram the cellular transcriptional and translational landscape. Here, we present a proteomic approach that allows us to quantify the differences in host and viral protein synthesis comparatively for different strains of IAV. The method is based on combining quantitative proteomics using stable isotope labelling by amino acids in cell culture (SILAC) and bioorthogonal labeling with methionine analogs. This methodology accurately quantifies synthesis of host and viral proteins with high temporal resolution and faithfully detects global changes in cellular translation capacity. It thus provides unique insights into the dynamics of protein synthesis as the infection progresses.
    Keywords:  BONCAT; Influenza A virus; Orthogonal labeling; Quantitative proteomics; Shutoff; Species barrier; Translation
    DOI:  https://doi.org/10.1007/978-1-0716-2895-9_13
  17. Biomolecules. 2022 Dec 19. pii: 1902. [Epub ahead of print]12(12):
      Cancer metabolic reprogramming is essential for maintaining cancer cell survival and rapid replication. A common target of this metabolic reprogramming is one-carbon metabolism which is notable for its function in DNA synthesis, protein and DNA methylation, and antioxidant production. Polyamines are a key output of one-carbon metabolism with widespread effects on gene expression and signaling. As a result of these functions, one-carbon and polyamine metabolism have recently drawn a lot of interest for their part in cancer malignancy. Therapeutic inhibitors that target one-carbon and polyamine metabolism have thus been trialed as anticancer medications. The significance and future possibilities of one-carbon and polyamine metabolism as a target in cancer therapy are discussed in this review.
    Keywords:  autophagy; cancer; metabolic therapy; methionine; one-carbon metabolism; polyamines; reactive oxygen species
    DOI:  https://doi.org/10.3390/biom12121902
  18. Antioxidants (Basel). 2022 Dec 02. pii: 2401. [Epub ahead of print]11(12):
      2-Oxo-imidazole-containing dipeptides (2-oxo-IDPs), novel imidazole-containing dipeptide (IDP) derivatives, exhibit a much higher antioxidant capacity than that of IDPs. However, quantitative methods have only been developed for IDPs, and methods for the quantitative analysis of 2-oxo-IDPs are needed. In this study, we developed methods for the quantitative analysis of 2-oxo-IDPs by high-performance liquid chromatography with online electrospray ionization-tandem mass spectrometry (HPLC-ESI-MS/MS) coupled with a stable isotope dilution method. First, we prepared stable isotope-labeled IDP and 2-oxo-IDP standards for MS analyses. Next, using these standards, we established highly sensitive, selective, and absolute quantitative analysis methods for five IDPs and five 2-oxo-IDPs by HPLC-ESI-MS/MS, achieving a limit of detection in the fmol range. Finally, we applied the method to various types of meat, such as beef, pork, chicken, and whale meat, demonstrating the detection of both IDPs and 2-oxo-IDPs. Furthermore, we provide the first evidence for the endogenous production of 2-oxo-balenine in meats. The methods developed in this study enable the detection of trace levels of 2-oxo-IDPs in biological samples and could be helpful for understanding the biological relevance of 2-oxo-IDPs.
    Keywords:  2-oxo-imidazole-containing dipeptides; anserine; balenine; carnosine; homoanserine; homocarnosine; imidazole-containing dipeptides; mass spectrometry; meat; stable isotope dilution method
    DOI:  https://doi.org/10.3390/antiox11122401
  19. J Clin Invest. 2022 Dec 22. pii: e161472. [Epub ahead of print]
      Insulin and IGF-1 receptors (IR/IGF1R) are highly homologous and share similar signaling systems, but each has a unique physiological role, with IR primarily regulating metabolic homeostasis and IGF1R regulating mitogenic control and growth. Here, we showed that replacement of a single amino acid at position 973, just distal to the NPEY motif in the intracellular juxtamembrane region, from leucine, which is highly-conserved in IRs, to phenylalanine, the highly-conserved homologous residue in IGF1Rs, resulted in decreased IRS-1-PI3K-Akt-mTORC1 signaling and increased of Shc-Gab1-MAPK-cell cycle signaling. As a result, cells expressing L973F-IR exhibited decreased insulin-induced glucose uptake, increased cell growth and impaired receptor internalization. Mice with knockin of the L973F-IR showed similar alterations in signaling in vivo, and this leaded to decreased insulin sensitivity, a modest increase in growth and decreased weight gain when challenged with high-fat diet. Thus, leucine973 in the juxtamembrane region of the IR acts as a crucial residue differentiating IR signaling from IGF1R signaling.
    Keywords:  Endocrinology; Insulin signaling; Metabolism
    DOI:  https://doi.org/10.1172/JCI161472
  20. J Proteome Res. 2022 Dec 19.
      Background: Idiopathic intracranial hypertension (IIH) is characterized by increased intracranial pressure occurring predominantly in women with obesity. The pathogenesis is not understood. We have applied untargeted metabolomic analysis using ultrahigh-performance liquid chromatography-mass spectrometry to characterize the cerebrospinal fluid (CSF) and serum in IIH compared to control subjects. Methods and findings: Samples were collected from IIH patients (n = 66) with active disease at baseline and again at 12 months following therapeutic weight loss. Control samples were collected from gender- and weight-matched healthy controls (n = 20). We identified annotated metabolites in CSF, formylpyruvate and maleylpyruvate/fumarylpyruvate, which were present at lower concentrations in IIH compared to control subjects and returned to values observed in controls following weight loss. These metabolites showed the opposite trend in serum at baseline. Multiple amino acid metabolic pathways and lipid classes were perturbed in serum and CSF in IIH alone. Serum lipid metabolite pathways were significantly increased in IIH. Conclusions: We observed a number of differential metabolic pathways related to amino acid, lipid, and acylpyruvate metabolism, in IIH compared to controls. These pathways were associated with clinical measures and normalized with disease remission. Perturbation of these metabolic pathways provides initial understanding of disease dysregulation in IIH.
    Keywords:  arginine metabolism; idiopathic intracranial hypertension; intracranial pressure; lipid metabolism; metabolomics
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00449
  21. Eur J Cancer. 2022 Nov 26. pii: S0959-8049(22)01770-1. [Epub ahead of print]180 30-51
      Cell metabolism is characterised by the highly coordinated conversion of nutrients into energy and biomass. In solid cancers, hypoxia, nutrient deficiencies, and tumour vasculature are incompatible with accelerated anabolic growth and require a rewiring of cancer cell metabolism. Driver gene mutations direct malignant cells away from oxidation to maximise energy production and biosynthesis while tumour-secreted factors degrade peripheral tissues to fuel disease progression and initiate metastasis. As it is vital to understand cancer cell metabolism and survival mechanisms, this review discusses the metabolic switch and current drug targets and clinical trials. In the future, metabolic markers may be included when phenotyping individual tumours to improve the therapeutic opportunities for personalised therapy.
    Keywords:  Biosynthesis; Energy production; Hypoxia; Metabolic reprogramming; Nutrient exploitation; Wasting syndrome
    DOI:  https://doi.org/10.1016/j.ejca.2022.11.025
  22. Data Brief. 2023 Feb;46 108802
      Circulating polyunsaturated fatty acids (PUFAs) and lipid mediators were extracted from human red blood cells and quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The method encompassed 13 different PUFAs and lipid mediators, however, due to instrument capability only five were confidently quantified (EPA, ALA, AA, DHA, and LA). The extraction focused on free polyunsaturated fatty acids since they have a strong correlation with health in humans. The study design was a secondary analysis of the OPPERA-2 study of chronic overlapping pain conditions in adults. The data included are: a) raw LC-MS/MS data (.raw); b) processed data (.xlsx) including chromatographic peak area for each compound and a concentration (ng/mL) based on external calibration with internal standardization using pure analytical grade standards and heavy-isotope labeled internal standards; c) study participant demographics and phenotypes (.xlsx). This dataset consisting of circulating PUFA quantities measured in 605 humans has been made publicly available for analysis and interpretation.
    Keywords:  Mass spectrometry; Pain; Polyunsaturated fatty acids; Quantitative analysis
    DOI:  https://doi.org/10.1016/j.dib.2022.108802
  23. Metabolites. 2022 Dec 16. pii: 1275. [Epub ahead of print]12(12):
      Recent developments in molecular networking have expanded our ability to characterize the metabolome of diverse samples that contain a significant proportion of ion features with no mass spectral match to known compounds. Manual and tool-assisted natural annotation propagation is readily used to classify molecular networks; however, currently no annotation propagation tools leverage consensus confidence strategies enabled by hierarchical chemical ontologies or enable the use of new in silico tools without significant modification. Herein we present ConCISE (Consensus Classifications of In Silico Elucidations) which is the first tool to fuse molecular networking, spectral library matching and in silico class predictions to establish accurate putative classifications for entire subnetworks. By limiting annotation propagation to only structural classes which are identical for the majority of ion features within a subnetwork, ConCISE maintains a true positive rate greater than 95% across all levels of the ChemOnt hierarchical ontology used by the ClassyFire annotation software (superclass, class, subclass). The ConCISE framework expanded the proportion of reliable and consistent ion feature annotation up to 76%, allowing for improved assessment of the chemo-diversity of dissolved organic matter pools from three complex marine metabolomics datasets comprising dominant reef primary producers, five species of the diatom genus Pseudo-nitzchia, and stromatolite sediment samples.
    Keywords:  CANOPUS; annotation propagation; dissolved organic matter; metabolomics
    DOI:  https://doi.org/10.3390/metabo12121275
  24. Cells. 2022 Dec 12. pii: 4015. [Epub ahead of print]11(24):
      The fatal clinical course of human glioblastoma (GBM) despite aggressive adjuvant therapies is due to high rates of recurrent tumor growth driven by tumor cells with stem-cell characteristics (glioma stem cells, GSCs). The aldehyde dehydrogenase 1 (ALDH1) family of enzymes has been shown to be a biomarker for GSCs, and ALDH1 seems to be involved in the biological processes causing therapy resistance. Ferroptosis is a recently discovered cell death mechanism, that depends on iron overload and lipid peroxidation, and it could, therefore, be a potential therapeutic target in various cancer types. Since both ALDH1 and ferroptosis interact with lipid peroxidation (LPO), we aimed to investigate a possible connection between ALDH1 and ferroptosis. Here, we show that RSL3-induced LPO and ferroptotic cell death revealed RSL3-sensitive and -resistant malignant glioma cell lines. Most interestingly, RSL3 sensitivity correlates with ALDH1a3 expression; only high ALDH1a3-expressing cells seem to be sensitive to ferroptosis induction. In accordance, inhibition of ALDH1a3 enzymatic activity by chemical inhibition or genetic knockout protects tumor cells from RSL3-induced ferroptotic cell death. Both RSL-3-dependent binding of ALDH1a3 to LC3B and autophagic downregulation of ferritin could be completely blocked by ALDH inhibition. Therefore, ALDH1a3 seems to be involved in ferroptosis through the essential release of iron by ferritinophagy. Our results also indicate that ferroptosis induction might be a particularly interesting clinical approach for targeting the highly aggressive cell population of GSC.
    Keywords:  autophagy; cancer stem cells; ferroptosis; glioblastoma; therapy
    DOI:  https://doi.org/10.3390/cells11244015
  25. Nat Commun. 2022 Dec 17. 13(1): 7802
      Neoadjuvant chemoradiotherapy (nCRT) has become the standard treatment for patients with locally advanced rectal cancer (LARC). Therapeutic efficacy of nCRT is significantly affected by treatment-induced diarrhea and hematologic toxicities. Metabolic alternations in cancer therapy are key determinants to therapeutic toxicities and responses, but exploration in large-scale clinical studies remains limited. Here, we analyze 743 serum samples from 165 LARC patients recruited in a phase III clinical study using untargeted metabolomics and identify responsive metabolic traits over the course of nCRT. Pre-therapeutic serum metabolites successfully predict the chances of diarrhea and hematologic toxicities during nCRT. Particularly, levels of acyl carnitines are linked to sex disparity in nCRT-induced diarrhea. Finally, we show that differences in phenylalanine metabolism and essential amino acid metabolism may underlie distinct therapeutic responses of nCRT. This study illustrates the metabolic dynamics over the course of nCRT and provides potential to guide personalized nCRT treatment using responsive metabolic traits.
    DOI:  https://doi.org/10.1038/s41467-022-35511-y
  26. Anal Chem. 2022 Dec 22.
      Carbohydrates play important roles in biological processes, but their identification remains a significant analytical problem. While mass spectrometry has increasingly enabled the elucidation of carbohydrates, current approaches are limited in their abilities to differentiate isomeric carbohydrates when these are not separated prior to tandem-mass spectrometry analysis. This analytical challenge takes on increased relevance because of the pervasive presence of isomeric carbohydrates in biological systems. Here, we demonstrate that TIMS2-MS2 workflows enabled by tandem-trapped ion mobility spectrometry-mass spectrometry (tTIMS/MS) provide a general approach to differentiate isomeric, nonseparated carbohydrates. Our analysis shows that (1) cross sections measured by TIMS are sufficiently precise and robust for ion identification; (2) fragment ion cross sections from TIMS2 analysis can be analytically exploited to identify carbohydrate precursors even if the precursor ions are not separated by TIMS; (3) low-abundant fragment ions can be exploited to identify carbohydrate precursors even if the precursor ions are not separated by IMS. (4) MS2 analysis of fragment ions produced by TIMS2 can be used to validate and/or further characterize carbohydrate structures. Taken together, our analysis underlines the opportunities that tandem-ion mobility spectrometry/MS methods offer for the characterization of mixtures of isomeric carbohydrates.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02844
  27. Methods Mol Biol. 2023 ;2610 1-16
      Sphingolipids are a critical family of membrane lipids with diverse functions in eukaryotic cells, and a growing body of literature supports that these lipids play essential roles during the lifecycles of viruses. While small molecule inhibitors of sphingolipid synthesis and metabolism are widely used, the advent of CRISPR-based genomic editing techniques allows for nuanced exploration into the manners in which sphingolipids influence various stages of viral infections. Here we describe some of these critical considerations needed in designing studies utilizing genomic editing techniques for manipulating the sphingolipid metabolic pathway, as well as the current body of literature regarding how viruses depend on the products of this pathway. Here, we highlight the ways in which sphingolipids affect viruses as these pathogens interact with and influence their host cell and describe some of the many open questions remaining in the field.
    Keywords:  Ceramide; Genetic editing; Host–pathogen interactions; Lipid metabolism; Sphingolipids; Sphingomyelin; Sphingosine; Sphingosine-1-phosphate; Viral infection; Virus
    DOI:  https://doi.org/10.1007/978-1-0716-2895-9_1
  28. Chem Sci. 2022 Dec 07. 13(47): 14114-14123
      The importance of chiral amino acids (AAs) in living organisms has been widely recognized since the discovery of endogenous d-AAs as potential biomarkers in several metabolic disorders. Chiral analysis by ion mobility spectrometry-mass spectrometry (IMS-MS) has the advantages of high speed and sensitivity but is still in its infancy. Here, an N α-(2,4-dinitro-5-fluorophenyl)-l-alaninamide (FDAA) derivatization is combined with trapped ion mobility spectrometry-mass spectrometry (TIMS-MS) for chiral AA analysis. For the first time, we demonstrate the simultaneous separation of 19 pairs of chiral proteinogenic AAs in a single fixed condition TIMS-MS run. The utility of this approach is presented for mouse brain extracts by direct-infusion TIMS-MS. The robust separation ability in complex biological samples was proven in matrix-assisted laser desorption/ionization (MALDI) TIMS mass spectrometry imaging (MSI) as well by directly depositing 19 pairs of chiral AAs on a tissue slide following on-tissue derivatization. In addition, endogenous chiral amino acids were also detected and distinguished. The developed methods show compelling application prospects in biomarker discovery and biological research.
    DOI:  https://doi.org/10.1039/d2sc03604e