bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022–09–04
23 papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh



  1. Anal Chem. 2022 Sep 01.
      A key element of successful lipidomics analysis is a sufficient extraction of lipid molecules typically by two-phase systems such as chloroform-based Bligh and Dyer (B&D). However, numerous metabolomics and lipidomics studies today apply easy to use one-phase extractions. In this work, quantitative flow injection analysis high-resolution mass spectrometry was applied to benchmark the lipid recovery of popular one-phase extraction methods for human plasma samples. The following organic solvents were investigated: methanol (MeOH), ethanol (EtOH), 2-propanol (IPA), 1-butanol (BuOH), acetonitrile (ACN) and the solvent mixtures BuOH/MeOH (3:1) and MeOH/ACN (1:1). The recovery of polar lysophospholipids was sufficient for all tested solvents. However, nonpolar lipid classes such as triglycerides (TG) and cholesteryl esters (CE) revealed extraction efficiencies less than 5% due to precipitation in polar solvents EtOH, MeOH, MeOH/ACN, and ACN. Sample pellets also contained a substantial amount of phospholipids, for example, more than 75% of total phosphatidylcholine and sphingomyelin for ACN. The loss of lipids by precipitation was directly related to the polarity of solvents and lipid classes. Although, lipid recovery increased with the volume of organic solvent, recovery in polar MeOH remains incomplete also for less polar lipid classes such as ceramides. Addition of stable isotope-labeled internal standards prior to lipid extraction could compensate for insufficient lipid recovery for polar lipid classes including lysolipids and phospholipids but not for nonpolar CE and TG. In summary, application of one-phase extractions should be limited to polar lipid classes unless sufficient recovery/solubility of nonpolar lipids has been demonstrated. The presented data reveal that appropriate lipid extraction efficiency is fundamental to achieve accurate lipid quantification.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02117
  2. Proteomics. 2022 Aug 29. e2200046
      Protein post-translational modifications (PTMs) increase the functional diversity of the cellular proteome. Accurate and high throughput identification and quantification of protein PTMs is a key task in proteomics research. Recent advancements in data-independent acquisition (DIA) mass spectrometry (MS) technology have achieved deep coverage and accurate quantification of proteins and PTMs. This review provides an overview of DIA data processing methods that cover three aspects of PTMs analysis, i.e., detection of PTMs, site localization, and characterization of complex modification moieties, such as glycosylation. In addition, a survey of deep learning methods that boost DIA-based PTMs analysis is presented, including in silico spectral library generation, as well as feature scoring and error rate control. The limitations and future directions of DIA methods for PTMs analysis are also discussed. Novel data analysis methods will take advantage of advanced MS instrumentation techniques to empower DIA MS for in-depth and accurate PTMs measurements. This article is protected by copyright. All rights reserved.
    Keywords:  LC-MS/MS; data-independent acquisition; glycosylation; post-translational modifications; site localization; spectral library
    DOI:  https://doi.org/10.1002/pmic.202200046
  3. OMICS. 2022 Aug 26.
      Clinical proteomics is a rapidly emerging frontier in laboratory medicine. High-throughput proteomic investigations of biopsy tissues provide mechanistic insights into complex human diseases. For large-scale proteomics, formalin-fixed and paraffin-embedded (FFPE) tissue samples offer a viable alternative to fresh-frozen (FF) tissues that have restricted availability. In this context, meningioma is one of the most common primary brain tumors where innovation in diagnostics and therapeutic targets can benefit from clinical proteomics. We present here an integrated workflow for quantitative proteomics and biomarker validation of meningioma FFPE tissues. Applying label-free quantitative (LFQ) proteomics, we reproducibly (Pearson's correlation: 0.84-0.91) obtained an in-depth proteome coverage (nearly 4000 proteins per sample) from 120 min gradient of single unfractionated mass spectrometry run. Furthermore, building upon LFQ data and literature curated set of meningioma-associated proteins, we validated VIM, AHNAK, and CLU from FFPE tissues using selected reaction monitoring (SRM) assay and compared its performance with FF tissues. This study illustrates how knowledge from label-free proteomics can be integrated for selecting peptides for targeted validation and suggests that FFPE tissues are comparable to FF tissues for SRM assays. This quantitative clinical proteomics workflow is scalable for large-scale clinical diagnostics studies in the future, for example, utilizing the global repository of FFPE tissues in meningioma and possibly in other cancers.
    Keywords:  biomarker validation; cancer research; clinical proteomics; meningioma; omics workflow; targeted proteomics
    DOI:  https://doi.org/10.1089/omi.2022.0082
  4. Cell Oncol (Dordr). 2022 Aug 29.
       BACKGROUND: Prostate cancer is the leading cause of cancer in men, and its incidence increases with age. Among other risk factors, pre-existing metabolic diseases have been recently linked with prostate cancer, and our current knowledge recognizes prostate cancer as a condition with important metabolic anomalies as well. In malignancies, metabolic disorders are commonly associated with aberrations in mTOR, which is the master regulator of protein synthesis and energetic homeostasis. Although there are reports demonstrating the high dependency of prostate cancer cells for lipid derivatives and even for carbohydrates, the understanding regarding amino acids, and the relationship with the mTOR pathway ultimately resulting in metabolic aberrations, is still scarce.
    CONCLUSIONS AND PERSPECTIVES: In this review, we briefly provide evidence supporting prostate cancer as a metabolic disease, and discuss what is known about mTOR signaling and prostate cancer. Next, we emphasized on the amino acids glutamine, leucine, serine, glycine, sarcosine, proline and arginine, commonly related to prostate cancer, to explore the alterations in their regulatory pathways and to link them with the associated metabolic reprogramming events seen in prostate cancer. Finally, we display potential therapeutic strategies for targeting mTOR and the referred amino acids, as experimental approaches to selectively attack prostate cancer cells.
    Keywords:  Amino acids; Cancer metabolism; Prostate cancer; mTOR
    DOI:  https://doi.org/10.1007/s13402-022-00706-4
  5. Front Mol Biosci. 2022 ;9 859787
      Cellular glutamine synthesis is thought to be an important resistance factor in protecting cells from nutrient deprivation and may also contribute to drug resistance. The application of ‟targeted stable isotope resolved metabolomics" allowed to directly measure the activity of glutamine synthetase in the cell. With the help of this method, the fate of glutamine derived nitrogen within the biochemical network of the cells was traced. The application of stable isotope labelled substrates and analyses of isotope enrichment in metabolic intermediates allows the determination of metabolic activity and flux in biological systems. In our study we used stable isotope labelled substrates of glutamine synthetase to demonstrate its role in the starvation response of cancer cells. We applied 13C labelled glutamate and 15N labelled ammonium and determined the enrichment of both isotopes in glutamine and nucleotide species. Our results show that the metabolic compensatory pathways to overcome glutamine depletion depend on the ability to synthesise glutamine via glutamine synthetase. We demonstrate that the application of dual-isotope tracing can be used to address specific reactions within the biochemical network directly. Our study highlights the potential of concurrent isotope tracing methods in medical research.
    Keywords:  GLUL; cancer metabolism; glutamine addiction; glutamine synthetase; nucleotide biosynthesis; targeted stable isotope resolved metabolomics
    DOI:  https://doi.org/10.3389/fmolb.2022.859787
  6. Mol Omics. 2022 Sep 01.
      Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.
    DOI:  https://doi.org/10.1039/d2mo00122e
  7. Anal Chim Acta. 2022 Sep 08. pii: S0003-2670(22)00786-3. [Epub ahead of print]1225 340215
      Fatty acids (FAs) possess highly diverse structures and can be divided into saturated and unsaturated classes. For unsaturated FAs, both the numbers and positions of carbon-carbon double bond (C=C) determine their biological functions. Abnormal levels of FA isomers have been reported to be involved in various disease development, such as cancer. Despite numerous advances in lipidomics, simultaneous quantifying and pinpointing C=C bond positions in a high-throughput manner remains a challenge. Here we conducted epoxidation of C=C bonds of unsaturated FAs followed by the conjugation with isobaric SUGAR tags. With the assistance of LC-MS, FA isomers with the same masses were separated on the C18 column and individually subjected to MS/MS fragmentation. Upon higher-energy collisional dissociation, not only reporter ions for multiplexed quantification but also diagnostic ions for C=C localization were generated at the same time, allowing quantitative analyses of different unsaturated FA isomers in samples. The performance of this approach including epoxidation, labeling efficiencies, quantitation accuracy, and capability to pinpoint C=C bond position were evaluated. To evaluate our method, free FA extracts from healthy human serum were used to demonstrate the feasibility of this method for complex sample analysis. Finally, this method was also applied to investigate the changes of unsaturated FA isomers between heathy human and Alzheimer's disease (AD) patient serum.
    Keywords:  Carbon-carbon double bonds; Fatty acids; Human serum; LC-MS/MS; Multiplexed quantification; SUGAR tags
    DOI:  https://doi.org/10.1016/j.aca.2022.340215
  8. Exp Hematol Oncol. 2022 Sep 01. 11(1): 49
      Cancer cells are well-known for their capacity to adapt their metabolism to their increasing energy demands which is necessary for tumor progression. This is no different for Multiple Myeloma (MM), a hematological cancer which develops in the bone marrow (BM), whereby the malignant plasma cells accumulate and impair normal BM functions. It has become clear that the hypoxic BM environment contributes to metabolic rewiring of the MM cells, including changes in metabolite levels, increased/decreased activity of metabolic enzymes and metabolic shifts. These adaptations will lead to a pro-tumoral environment stimulating MM growth and drug resistance In this review, we discuss the identified metabolic changes in MM and the BM microenvironment and summarize how these identified changes have been targeted (by inhibitors, genetic approaches or deprivation studies) in order to block MM progression and survival.
    Keywords:  Bone marrow microenvironment; Glucose metabolism; Glutamine metabolism; Glycolysis; Hypoxia; Lactate metabolism; Lipid metabolism; Metabolism; Multiple myeloma; Oxidative phosphorylation
    DOI:  https://doi.org/10.1186/s40164-022-00303-z
  9. Sci Adv. 2022 Sep 02. 8(35): eabn9550
      In mice and humans with cancer, intravenous 13C-glucose infusion results in 13C labeling of tumor tricarboxylic acid (TCA) cycle intermediates, indicating that pyruvate oxidation in the TCA cycle occurs in tumors. The TCA cycle is usually coupled to the electron transport chain (ETC) because NADH generated by the cycle is reoxidized to NAD+ by the ETC. However, 13C labeling does not directly report ETC activity, and other pathways can oxidize NADH, so the ETC's role in these labeling patterns is unverified. We examined the impact of the ETC complex I inhibitor IACS-010759 on tumor 13C labeling. IACS-010759 suppresses TCA cycle labeling from glucose or lactate and increases labeling from glutamine. Cancer cells expressing yeast NADH dehydrogenase-1, which recycles NADH to NAD+ independently of complex I, display normalized labeling when complex I is inhibited, indicating that cancer cell ETC activity regulates TCA cycle metabolism and 13C labeling from multiple nutrients.
    DOI:  https://doi.org/10.1126/sciadv.abn9550
  10. J Biol Chem. 2022 Aug 25. pii: S0021-9258(22)00861-4. [Epub ahead of print] 102418
      Macrophages (MФ) are an essential immune cell for defense and repair that travel to different tissues and adapt based on local stimuli. A critical factor that may govern their polarization is the cross-talk between metabolism and epigenetics. However, simultaneous measurements of metabolites, epigenetics, and proteins (phenotype) has been a major technical challenge. To address this, we have developed a novel triomics approach using mass spectrometry to comprehensively analyze metabolites, proteins, and histone modifications, in a single sample. To demonstrate this technique, we investigated the metabolic-epigenetic-phenotype axis following polarization of human blood-derived monocytes into either 'pro-inflammatory M1'- or 'anti-inflammatory M2-' MФs. We report here a complex relationship between arginine, tryptophan, glucose, and the citric acid cycle (TCA) metabolism, protein and histone post-translational modifications, and human macrophage polarization that was previously not described. Surprisingly, M1-MФs had globally reduced histone acetylation levels but high levels of acetylated amino acids. This suggests acetyl-CoA was diverted, in part, towards acetylated amino acids. Consistent with this, stable isotope tracing of glucose revealed reduced usage of acetyl-CoA for histone acetylation in M1-MФs. Furthermore, isotope tracing also revealed MФs uncoupled glycolysis from the TCA cycle, as evidenced by poor isotope enrichment of succinate. M2-MФs had high levels of kynurenine and serotonin which are reported to have immune-suppressive effects. Kynurenine is upstream of de novo NAD+ metabolism which is a necessary cofactor for Sirtuin-type histone deacetylases. Taken together, we demonstrate a complex interplay between metabolism and epigenetics that may ultimately influence cell phenotype.
    DOI:  https://doi.org/10.1016/j.jbc.2022.102418
  11. Talanta. 2022 Aug 05. pii: S0039-9140(22)00526-4. [Epub ahead of print]252 123730
      In this paper, we report about the application of a sensitive fluorescent derivatization reagent Coumarin151-N-Hydroxysuccinimidyl Carbamate (Cou151DSC) for amino compounds using high-performance liquid chromatography (HPLC) compatible with ultraviolet (UV), fluorescence detector (FLD) and electrospray ionization - tandem mass spectrometry (ESI-MS/MS)-positive mode. We optimized derivatization procedure and validated an analytical method to determine 24 amino acids in Kvass drink using Norvaline as an internal standard. Compared to 6-Aminoquinolyl-N-Hydroxysuccinimidyl Carbamate (6-AQC), the derivatization with Cou151 DSC is faster and milder, for 5 min at 40°C instead of 15 min at 55°C. The limit of quantitation (LOQ, pmol on column) for 21 amino acids in this work is lower 1.1-30.0 times than values obtained with 6-AQC. The derivatives have excitation wavelength at 355 nm and emission wavelength at 486 nm. Their MS/MS fragmentation behaviors were examined together with 23 other amino compounds. We found three possibilities to lose a neutral group which can be Coumarin 151 isocyanate Cou151NCO (255 Da), amine Coumarin 151 (229 Da) or urea Cou151CONH2 (272 Da). The accuracy of the proposed method was within 83-107% with good relative standard deviations (RSDs) of equal or less than 6%. The recoveries were from 82 to 120% in four spiked concentrations, repeatability was between 0 and 14%. The intra- and inter-day precision are less than 13% and 18%, respectively.
    Keywords:  Amino acids; Cou151DSC; Coumarin151-N-Hydroxysuccinimidyl Carbamate; Derivatization; ESI; LC-MS; MS/MS; Neutral loss
    DOI:  https://doi.org/10.1016/j.talanta.2022.123730
  12. J Proteome Res. 2022 Aug 30.
      Capillary- and micro-flow liquid chromatography-tandem mass spectrometry (capLC-MS/MS and μLC-MS/MS) is becoming a valuable alternative to nano-flow LC-MS/MS due to its high robustness and throughput. The systematic comparison of capLC-MS/MS and μLC-MS/MS systems for global proteome profiling has not been reported yet. Here, the capLC-MS/MS (150 μm i.d. column, 1 μL/min) and μLC-MS/MS (1 mm i.d. column, 50 μL/min) systems were both established based on UltiMate 3000 RSLCnano coupled to an Orbitrap Exploris 240 by integrating with different flowmeters. We evaluated both systems in terms of sensitivity, analysis throughput, separation efficiency, and robustness. capLC-MS/MS was about 10 times more sensitive than μLC-MS/MS at different gradient lengths. Compared with capLC-MS/MS, μLC-MS/MS was able to achieve higher analysis throughput and separation efficiency. During the 7 days' long-term performance test, both systems showed good reproducibility of chromatographic full width (RSD < 3%), retention time (RSD < 0.4%), and protein identification (RSD < 3%). These results demonstrate that capLC-MS/MS is more suitable for high-throughput analysis of clinical samples with a limited starting material. When enough samples are available, μLC-MS/MS is preferred. Together, capLC and μLC coupled to Orbitrap Exploris 240 with moderate sensitivity should well meet the needs of large-cohort clinical proteomic analysis.
    Keywords:  capLC−MS/MS; clinical proteomics; large-cohort; μLC−MS/MS
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00405
  13. Front Immunol. 2022 ;13 961708
      Rheumatoid arthritis (RA) is an autoimmune disease accompanied by metabolic alterations. The metabolic profiles of patients with RA can be determined using targeted and non-targeted metabolomics technology. Metabolic changes in glucose, lipid, and amino acid levels are involved in glycolysis, the tricarboxylic acid cycle, the pentose phosphate pathway, the arachidonic acid metabolic pathway, and amino acid metabolism. These alterations in metabolic pathways and metabolites can fulfill bio-energetic requirements, promote cell proliferation, drive inflammatory mediator secretion, mediate leukocyte infiltration, induce joint destruction and muscle atrophy, and regulate cell proliferation, which may reflect the etiologies of RA. Differential metabolites can be used as biomarkers for the diagnosis, prognosis, and risk prediction, improving the specificity and accuracy of diagnostics and prognosis prediction. Additionally, metabolic changes associated with therapeutic responses can improve the understanding of drug mechanism. Metabolic homeostasis and regulation are new therapeutic strategies for RA. In this review, we provide a comprehensive overview of advances in metabolomics for RA.
    Keywords:  biomarkers; medicine; metabolomics; pathogenesis; rheumatoid arthritis
    DOI:  https://doi.org/10.3389/fimmu.2022.961708
  14. Front Endocrinol (Lausanne). 2022 ;13 988295
      It is notorious that cancer cells alter their metabolism to adjust to harsh environments of hypoxia and nutritional starvation. Metabolic reprogramming most often occurs in the tumor microenvironment (TME). TME is defined as the cellular environment in which the tumor resides. This includes surrounding blood vessels, fibroblasts, immune cells, signaling molecules and the extracellular matrix (ECM). It is increasingly recognized that cancer cells, fibroblasts and immune cells within TME can regulate tumor progression through metabolic reprogramming. As the most significant proportion of cells among all the stromal cells that constitute TME, cancer-associated fibroblasts (CAFs) are closely associated with tumorigenesis and progression. Multitudinous studies have shown that CAFs participate in and promote tumor metabolic reprogramming and exert regulatory effects via the dysregulation of metabolic pathways. Previous studies have demonstrated that curbing the substance exchange between CAFs and tumor cells can dramatically restrain tumor growth. Emerging studies suggest that CAFs within the TME have emerged as important determinants of metabolic reprogramming. Metabolic reprogramming also occurs in the metabolic pattern of immune cells. In the meanwhile, immune cell phenotype and functions are metabolically regulated. Notably, immune cell functions influenced by metabolic programs may ultimately lead to alterations in tumor immunity. Despite the fact that multiple previous researches have been devoted to studying the interplays between different cells in the tumor microenvironment, the complicated relationship between CAFs and immune cells and implications of metabolic reprogramming remains unknown and requires further investigation. In this review, we discuss our current comprehension of metabolic reprogramming of CAFs and immune cells (mainly glucose, amino acid, and lipid metabolism) and crosstalk between them that induces immune responses, and we also highlight their contributions to tumorigenesis and progression. Furthermore, we underscore potential therapeutic opportunities arising from metabolism dysregulation and metabolic crosstalk, focusing on strategies targeting CAFs and immune cell metabolic crosstalk in cancer immunotherapy.
    Keywords:  Tumor microenvironment; cancer-associated fibroblasts; immune cells; immunotherapy; metabolic reprogramming
    DOI:  https://doi.org/10.3389/fendo.2022.988295
  15. Metabolomics. 2022 Aug 29. 18(9): 71
       INTRODUCTION: Solitary pulmonary nodules (SPNs) are commonly found in imaging technologies, but are plagued by high false-positive rates.
    OBJECTIVE: We aimed to identify metabolic alterations in SPN etiology and diagnosis using less invasive plasma metabolomics and lipidomics.
    METHODS: In total, 1160 plasma samples were obtained from healthy volunteers (n = 280), benign SPNs (n = 157) and malignant SPNs (stage I, n = 723) patients enrolled from 5 independent centers. Gas chromatography-triple quadrupole mass spectrometry (GC‒MS) and liquid chromatography-Q Exactive Hybrid Quadrupole-Orbitrap mass spectrometry (LC‒MS) were used to analyze the samples for untargeted metabolomics and lipidomics.
    RESULTS AND CONCLUSION: GC‒MS-based metabolomics revealed 1336 metabolic features, while LC‒MS-based lipidomics revealed 6088 and 2542 lipid features in the positive and negative ion modes, respectively. The metabolic and lipidic characteristics of healthy vs. benign or malignant SPNs exhibited substantial pattern differences. Of note, benign and malignant SPNs had no significant variations in circulating metabolic and lipidic markers and were validated in four other centers. This study demonstrates evidence of early metabolic alterations that can possibly distinguish SPNs from healthy controls, but not between benign and malignant SPNs.
    Keywords:  Less invasive diagnosis; Lipidomics; Metabolomics; Solitary pulmonary nodules
    DOI:  https://doi.org/10.1007/s11306-022-01929-0
  16. J Proteome Res. 2022 Aug 31.
      The direct correlation between proteoforms and biological phenotype necessitates the exploration of mass spectrometry (MS)-based methods more suitable for proteoform detection and characterization. Here, we couple nano-hydrophobic interaction chromatography (nano-HIC) to ultraviolet photodissociation MS (UVPD-MS) for separation and characterization of intact proteins and proteoforms. High linearity, sensitivity, and sequence coverage are obtained with this method for a variety of proteins. Investigation of collisional cross sections of intact proteins during nano-HIC indicates semifolded conformations in low charge states, enabling a different dimension of separation in comparison to traditional, fully denaturing reversed-phase separations. This method is demonstrated for a mixture of intact proteins from Escherichia coli ribosomes; high sequence coverage is obtained for a variety of modified and unmodified proteoforms.
    Keywords:  collisional cross section (CCS); hydrophobic interaction chromatography (HIC); liquid chromatography (LC); mass spectrometry (MS); native mass spectrometry (nMS); orbitrap mass spectrometer; protein; proteoform; top-down mass spectrometry (TDMS); ultraviolet photodissociation (UVPD)
    DOI:  https://doi.org/10.1021/acs.jproteome.2c00450
  17. Anal Chem. 2022 Aug 31.
      Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU. The dual-trap single-column configuration (DTSC) presented here maximizes IU in rapid analysis (15 min per sample) of blood and cell lysates by parallelizing trap column cleaning and sample loading and desalting with the analysis of the previous sample. We achieved 90% IU in low microflow (9.5 μL/min) analysis of blood while reproducibly quantifying 300-400 proteins and over 6000 precursor ions. The same IU was achieved for cell lysates and over 4000 proteins (3000 at CV below 20%) and 40,000 precursor ions were quantified at a rate of 15 min/sample. Thus, DTSC enables high-throughput epidemiological blood-based biomarker cohort studies and cell-based perturbation screening.
    DOI:  https://doi.org/10.1021/acs.analchem.2c02609
  18. Genome Biol. 2022 Sep 01. 23(1): 184
      Out of the thousands of metabolites in a given specimen, most metabolomics experiments measure only hundreds, with poor overlap across experimental platforms. Here, we describe Metabolite Imputation via Rank-Transformation and Harmonization (MIRTH), a method to impute unmeasured metabolite abundances by jointly modeling metabolite covariation across datasets which have heterogeneous coverage of metabolite features. MIRTH successfully recovers masked metabolite abundances both within single datasets and across multiple, independently-profiled datasets. MIRTH demonstrates that latent information about otherwise unmeasured metabolites is embedded within existing metabolomics data, and can be used to generate novel hypotheses and simplify existing metabolomic workflows.
    Keywords:  Imputation; Matrix factorization; Metabolomics; Missing data; Unmeasured metabolites
    DOI:  https://doi.org/10.1186/s13059-022-02738-3
  19. J Hematol Oncol. 2022 Aug 29. 15(1): 120
      Metabolic reprogramming of cancer cells within the tumor microenvironment typically occurs in response to increased nutritional, translation and proliferative demands. Altered lipid metabolism is a marker of tumor progression that is frequently observed in aggressive tumors with poor prognosis. Underlying these abnormal metabolic behaviors are posttranslational modifications (PTMs) of lipid metabolism-related enzymes and other factors that can impact their activity and/or subcellular localization. This review focuses on the roles of these PTMs and specifically on how they permit the re-wiring of cancer lipid metabolism, particularly within the context of the tumor microenvironment.
    Keywords:  Cancer; Lipid metabolism reprogramming; Posttranslational modification; Tumor microenvironment
    DOI:  https://doi.org/10.1186/s13045-022-01340-1
  20. J Chem Inf Model. 2022 Aug 31.
      Competitive Fragmentation Modeling for Metabolite Identification (CFM-ID) is a machine learning tool to predict in silico tandem mass spectra (MS/MS) for known or suspected metabolites for which chemical reference standards are not available. As a machine learning tool, it relies on both an underlying statistical model and an explicit training set that encompasses experimental mass spectra for specific compounds. Such mass spectra depend on specific parameters such as collision energies, instrument types, and adducts which are accumulated in libraries. Yet, ultimately prediction tools that are meant to cover wide expanses of entities must be validated on cases that were not included in the initial training and testing sets. Hence, we here benchmarked the performance of CFM-ID 4.0 to correctly predict MS/MS spectra for spectra that were not included in the CFM-ID training set and for different mass spectrometry conditions. We used 609,456 experimental tandem spectra from the NIST20 mass spectral library that were newly added to the previous NIST17 library version. We found that CFM-ID's highest energy prediction output would maximize the capacity for library generation. Matching the experimental collision energy with CFM-ID's prediction energy produced the best results, even for HCD-Orbitrap instruments. For benzenoids, better MS/MS predictions were achieved than for heterocyclic compounds. However, when exploring CFM-ID's performance on 8,305 compounds at 40 eV HCD-Orbitrap collision energy, >90% of the 20/80 split test compounds showed <700 MS/MS similarity score. Instead of a stand-alone tool, CFM-ID 4.0 might be useful to boost candidate structures in the greater context of identification workflows.
    DOI:  https://doi.org/10.1021/acs.jcim.2c00936
  21. Sci Adv. 2022 Sep 02. 8(35): eabq5206
      Nucleic acid and histone modifications critically depend on the tricarboxylic acid (TCA) cycle for substrates and cofactors. Although a few TCA cycle enzymes have been reported in the nucleus, the corresponding pathways are considered to operate in mitochondria. Here, we show that a part of the TCA cycle is operational also in the nucleus. Using 13C-tracer analysis, we identified activity of glutamine-to-fumarate, citrate-to-succinate, and glutamine-to-aspartate routes in the nuclei of HeLa cells. Proximity labeling mass spectrometry revealed a spatial vicinity of the involved enzymes with core nuclear proteins. We further show nuclear localization of aconitase 2 and 2-oxoglutarate dehydrogenase in mouse embryonic stem cells. Nuclear localization of the latter enzyme, which produces succinyl-CoA, changed from pluripotency to a differentiated state with accompanying changes in the nuclear protein succinylation. Together, our results demonstrate operation of an extended metabolic pathway in the nucleus, warranting a revision of the canonical view on metabolic compartmentalization.
    DOI:  https://doi.org/10.1126/sciadv.abq5206
  22. Clin Chem. 2022 Sep 03. pii: hvac135. [Epub ahead of print]
       BACKGROUND: Parathyroid hormone (PTH) measurement is important for patients with disorders of calcium metabolism, including those needing bone-turnover monitoring due to chronic kidney disease-mineral bone disorder. There are currently 2 generations of PTH immunoassays on the market, both having cross-reactivity issues and lacking standardization. Therefore, we developed an LC-MS/MS higher-order method for PTH analysis.
    METHODS: The method was calibrated against the international standard for 1-84 PTH (WHO 95/646). Antibody-free sample preparation with the addition of an isotope-labeled internal standard was performed by solid-phase extraction. Extracts were analyzed by LC-MS/MS. EDTA-K2 plasma was used throughout the development and validation. Bias and uncertainty sources were tested according to ISO 15193. Clinical Laboratory Standards Institute guidelines and reference measurement procedures were consulted for the design of the validation. Patient samples and external quality controls were compared between LC-MS/MS and 2 third-generation immunoassays.
    RESULTS: The method was validated for 1-84 PTH from 5.7 to 872.6 pg/mL. The interassay imprecision was between 1.2% and 3.9%, and the accuracy ranged from 96.2% to 103.2%. The measurement uncertainty was <5.6%. The comparison between LC-MS/MS and the immunoassays showed a proportional bias but moderate to substantial correlation between methods.
    CONCLUSIONS: This LC-MS/MS method, which is independent of antibodies, is suitable for a wide range of PTH concentrations. The obtained analytical performance specifications demonstrate that development of a reference measurement procedure will be possible once a higher order reference standard is available.
    Keywords:  LC-MS/MS; intact parathormone; liquid chromatography; mass spectrometry; reference measurement procedure
    DOI:  https://doi.org/10.1093/clinchem/hvac135