bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒06‒12
sixteen papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh


  1. Proteomics. 2022 Jun 10. e2100256
      Mass spectrometry (MS) has emerged at the forefront of quantitative proteomic techniques. Liquid chromatography-mass spectrometry (LC-MS) can be used to determine relative abundances of proteins and peptides in complex biological samples. Several methods have been developed and adapted for accurate quantification based on chemical isotopic labeling. Among various chemical isotopic labeling techniques, isobaric tagging approaches rely on the analysis of peptides from MS2-based quantification rather than MS1-based quantification. In this review, we will provide an overview of several isobaric tags along with some recent developments including complementary ion tags, improvements in sensitive quantitation of analytes with lower abundance, strategies to increase multiplexing capabilities, and targeted analysis strategies. We will also discuss limitations of isobaric tags and approaches to alleviate these restrictions through bioinformatic tools and data acquisition methods. This review will highlight several applications of isobaric tags, including biomarker discovery and validation, thermal proteome profiling, cross-linking for structural investigations, single-cell analysis, top-down proteomics, along with applications to different molecules including neuropeptides, glycans, metabolites, and lipids, while providing considerations and evaluations to each application. This article is protected by copyright. All rights reserved.
    Keywords:  Isobaric Tags; Isotopic Labeling; Mass Spectrometry; Protein Quantitation; Quantitative Proteomics; Systems Biology
    DOI:  https://doi.org/10.1002/pmic.202100256
  2. Mol Cancer Res. 2022 Jun 08. pii: molcanres.1069.2021. [Epub ahead of print]
      Cancer cells feature increased macromolecular biosynthesis to support the formation of new organelles and membranes for cell division. In particular, lipids are key macromolecules that comprise cellular membrane components, substrates for energy generation and mediators of inter- and intracellular signalling. The emergence of more sensitive and accurate technology for profiling the "lipidome" of cancer cells has led to unprecedented leaps in understanding the complexity of cancer metabolism, but also highlighted promising therapeutic vulnerabilities. Notably, fatty acids, as lipid building blocks, are critical players in all stages of cancer development and progression and the importance of fatty acid desaturation and its impact on cancer cell biology has been well established. Recent years have seen the reports of new mechanistic insights into the role of monounsaturated fatty acids (MUFAs) in cancer, as regulators of cell death and lipid-related cellular signalling. This commentary aims to highlight these diverse roles of MUFAs in cancer cells which may yield new directions for therapeutic interventions involving these important fatty acids.
    DOI:  https://doi.org/10.1158/1541-7786.MCR-21-1069
  3. Anal Chim Acta. 2022 Jul 04. pii: S0003-2670(22)00550-5. [Epub ahead of print]1215 339979
      Metabolomics-based precision medicine is facing several obstacles including cross-platform data comparison issue and the lack of metabolome benchmark values of healthy population, one of main reasons is the shortage of comprehensive metabolome quantitation methods. Here, we developed an alternate reversed-phase liquid chromatography-mass spectrometry (RPLC-MS) method to quantitatively determine metabolites and lipids. Assisted by a wide set of reference standards and real samples, up to 397 multiple reaction monitoring (MRM) transitions (239 for positive and 158 for negative ion modes) and 1080 MRM transitions (607 for positive and 473 for negative ion modes) were defined respectively in the metabolomic and lipidomic analyses with more than 1000 metabolites and lipids being quantified. Among them, 144 analytes including amines, amino acids, benzenoids, peptides, nucleobases and related, bile acids, carboxylic acids, fatty acids, hormones, indoles and others were absolutely quantified, while carnitines, lyso-phosphatidylcholines, lyso-phosphatidylethanolamines, free fatty acids, sphingomyelins, phosphatidylcholines (PCs), alkyl and alkenyl substituted PCs, phosphatidylethanolamines (PEs), alkyl and alkenyl substituted PEs and triacylglycerols were semiquantified. The developed method was validated to have good analytical characteristics. Analytical results of standard reference material 1950 human plasma had a good agreement with literature data. As a proof of application, this method was used to study serum metabolic pattern changes of patients with hyperuricemia and nonalcoholic fatty liver. This alternate RPLC-MS method for quantitative metabolites and lipids analysis can further be used to provide technology and large-scale data support for precision medicine and life sciences.
    Keywords:  Alternate analysis; Lipidomics; Metabolomics; Quantitation
    DOI:  https://doi.org/10.1016/j.aca.2022.339979
  4. J Hematol Oncol. 2022 Jun 03. 15(1): 72
      Ferroptosis, a novel non-apoptotic form of cell death, can induce tumor cell death and treatment resistance. Lipid metabolism is closely related to ferroptosis; however, the effect of mammary adipocytes on breast cancer ferroptosis remains to be elucidated. Here, we established the co-culture system of adipocyte-breast cancer cells and revealed the protection of triple-negative breast cancer from ferroptosis by adipocytes. Then, we performed the lipidomics analysis comparing lipid metabolites of co-cultured and normal-cultured cells. Mechanistically, oleic acid secreted from adipocytes inhibited lipid peroxidation and ferroptosis of triple-negative breast cancer cells in the presence of ACSL3. Taken together, mammary adipocytes can protect breast cancer cells from ferroptosis through oleic acid in the presence of ACSL3. These findings could provide new ideas and targets for tumor treatment.
    Keywords:  Adipocytes; Breast cancer; Cell death; Ferroptosis; Lipid metabolism
    DOI:  https://doi.org/10.1186/s13045-022-01297-1
  5. Cancer Res. 2022 Jun 08. pii: canres.1301.2021-5-4 10:59:25.103. [Epub ahead of print]
      Prostate cancer is the second most common cause of cancer mortality in men worldwide. Applying a novel genetically engineered mouse model (GEMM) of aggressive prostate cancer driven by deficiency of the tumour suppressors PTEN and SPRY2 (Sprouty 2), we identified enhanced creatine metabolism as a central component of progressive disease. Creatine treatment was associated with enhanced cellular basal respiration in vitro and increased tumour cell proliferation in vivo. Stable isotope tracing revealed that intracellular levels of creatine in prostate cancer cells are predominantly dictated by exogenous availability rather than by de novo synthesis from arginine. Genetic silencing of creatine transporter SLC6A8 depleted intracellular creatine levels and reduced the colony-forming capacity of human prostate cancer cells. Accordingly, in vitro treatment of prostate cancer cells with cyclocreatine, a creatine analog, dramatically reduced intracellular levels of creatine and its derivatives phosphocreatine and creatinine and suppressed proliferation. Supplementation with cyclocreatine impaired cancer progression in the PTEN and SPRY-deficient prostate cancer GEMMs and in a xenograft liver metastasis model. Collectively, these results identify a metabolic vulnerability in prostate cancer and demonstrate a rational therapeutic strategy to exploit this vulnerability to impede tumour progression.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-21-1301
  6. Nat Commun. 2022 Jun 06. 13(1): 3124
      We integrated lipidomics and genomics to unravel the genetic architecture of lipid metabolism and identify genetic variants associated with lipid species putatively in the mechanistic pathway for coronary artery disease (CAD). We quantified 596 lipid species in serum from 4,492 individuals from the Busselton Health Study. The discovery GWAS identified 3,361 independent lipid-loci associations, involving 667 genomic regions (479 previously unreported), with validation in two independent cohorts. A meta-analysis revealed an additional 70 independent genomic regions associated with lipid species. We identified 134 lipid endophenotypes for CAD associated with 186 genomic loci. Associations between independent lipid-loci with coronary atherosclerosis were assessed in ∼456,000 individuals from the UK Biobank. Of the 53 lipid-loci that showed evidence of association (P < 1 × 10-3), 43 loci were associated with at least one lipid endophenotype. These findings illustrate the value of integrative biology to investigate the aetiology of atherosclerosis and CAD, with implications for other complex diseases.
    DOI:  https://doi.org/10.1038/s41467-022-30875-7
  7. Front Mol Biosci. 2022 ;9 880559
      Lipid tracing studies are a key method to gain a better understanding of the complex metabolic network lipids are involved in. In recent years, alkyne lipid tracers and mass spectrometry have been developed as powerful tools for such studies. This study aims to review the present standing of the underlying technique, highlight major findings the strategy allowed for, summarize its advantages, and discuss some limitations. In addition, an outlook on future developments is given.
    Keywords:  analog; click; fatty acid; lipidomics; metabolism; probe; tracer; β-oxidation
    DOI:  https://doi.org/10.3389/fmolb.2022.880559
  8. Cancer Sci. 2022 Jun 07.
      Renal cell carcinoma (RCC) features altered lipid metabolism and accumulated polyunsaturated fatty acid (PUFAs). Elongation of very-long-chain fatty acid (ELOVL) family enzymes catalyze fatty acid elongation, and ELOVL5 is indispensable for PUFAs elongation, but its role in RCC progression remains unclear. Here, we show that higher levels of ELOVL5 correlate with poor RCC clinical prognosis. Liquid chromatography/electrospray ionization-tandem mass spectrometry analysis showed decreases in ELOVL5 end products (arachidonic acid and eicosapentaenoic acid) under CRISPR/Cas9-mediated knockout of ELOVL5 while supplementation with these fatty acids partially reversed the cellular proliferation and invasion effects of ELOVL5 knockout. Regarding cellular proliferation and invasion, CRISPR/Cas9-mediated knockout of ELOVL5 suppressed the formation of lipid droplets and induced apoptosis via endoplasmic reticulum stress while suppressing renal cancer cell proliferation and in vivo tumor growth. Furthermore, CRISPR/Cas9-mediated knockout of ELOVL5 inhibited AKT Ser473 phosphorylation and suppressed renal cancer cell invasion through chemokine (C-C motif) ligand-2 downregulation by AKT-mTOR-STAT3 signaling. Collectively, these results suggest that ELOVL5-mediated fatty acid elongation promotes not only cellular proliferation but also invasion in RCC.
    Keywords:  cellular invasion; cellular proliferation; elongation of very-long-chain fatty acid 5; polyunsaturated fatty acid; renal cell carcinoma
    DOI:  https://doi.org/10.1111/cas.15454
  9. Molecules. 2022 May 25. pii: 3390. [Epub ahead of print]27(11):
      The use of a proper sample processing methodology for maximum proteome coverage and high-quality quantitative data is an important choice to make before initiating a liquid chromatography-mass spectrometry (LC-MS)-based proteomics study. Popular sample processing workflows for proteomics involve in-solution proteome digestion and single-pot, solid-phase-enhanced sample preparation (SP3). We tested them on both HeLa cells and human plasma samples, using lysis buffers containing SDS, or guanidinium hydrochloride. We also studied the effect of using commercially available depletion mini spin columns before SP3, to increase proteome coverage in human plasma samples. Our results show that the SP3 protocol, using either buffer, achieves the highest number of quantified proteins in both the HeLa cells and plasma samples. Moreover, the use of depletion mini spin columns before SP3 results in a two-fold increase of quantified plasma proteins. With additional fractionation, we quantified nearly 1400 proteins, and examined lower-abundance proteins involved in neurodegenerative pathways and mitochondrial metabolism. Therefore, we recommend the use of the SP3 methodology for biological sample processing, including those after depletion of high-abundance plasma proteins.
    Keywords:  cells; depletion; guanidinium hydrochloride; in-solution digestion; liquid chromatography–mass spectrometry; plasma; proteomics; single-pot; sodium dodecyl sulfate; solid-phase-enhanced sample preparation
    DOI:  https://doi.org/10.3390/molecules27113390
  10. Cancers (Basel). 2022 May 27. pii: 2655. [Epub ahead of print]14(11):
      Metabolic alterations in neoplastic cells have recently gained increasing attention as a main topic of research, playing a crucial regulatory role in the development and progression of tumors. The interplay between epigenetic modifications and metabolic pathways in glioblastoma cells has emerged as a key pathogenic area with great potential for targeted therapy. Epigenetic mechanisms have been demonstrated to affect main metabolic pathways, such as glycolysis, pentose phosphate pathway, gluconeogenesis, oxidative phosphorylation, TCA cycle, lipid, and glutamine metabolism by modifying key regulatory genes. Although epigenetic modifications can primarily promote the activity of metabolic pathways, they may also exert an inhibitory role. In this way, they participate in a complex network of interactions that regulate the metabolic behavior of malignant cells, increasing their heterogeneity and plasticity. Herein, we discuss the main epigenetic mechanisms that regulate the metabolic pathways in glioblastoma cells and highlight their targeting potential against tumor progression.
    Keywords:  DNA; Krebs cycle; TCA cycle; acetylation; glioblastoma; glioma; gluconeogenesis; glutamine; glycolysis; histones; methylation; microRNAs; oxidative phosphorylation; pentose phosphate pathway
    DOI:  https://doi.org/10.3390/cancers14112655
  11. Cancer Med. 2022 Jun 06.
      BACKGROUND: The AMP-activated protein kinase (AMPK) is a central regulator of energy homeostasis, with deregulation leading to cancer and other diseases. However, how this pathway is dysregulated in cancer has not been well clarified.METHODS: Using a tandem affinity purification/mass-spec technique and biochemical analyses, we identified tumor protein D52 (TPD52) as an AMPKα-interacting molecule. To explore the biological effects of TPD52 in cancers, we conducted biochemical and metabolic assays in vitro and in vivo with cancer cells and TPD52 transgenic mice. Finally, we assessed the clinical significance of TPD52 expression in breast cancer patients using bioinformatics techniques.
    RESULTS: TPD52, initially identified to be overexpressed in many human cancers, was found to form a stable complex with AMPK in cancer cells. TPD52 directly interacts with AMPKα and inhibits AMPKα kinase activity in vitro and in vivo. In TPD52 transgenic mice, overexpression of TPD52 leads to AMPK inhibition and multiple metabolic defects. Clinically, high TPD52 expression predicts poor survival of breast cancer patients.
    CONCLUSION: The findings revealed that TPD52 is a novel regulator of energy stress-induced AMPK activation and cell metabolism. These results shed new light on AMPK regulation and understanding of the etiology of cancers with TPD52 overexpression.
    Keywords:  AMP-activated protein kinase (AMPK); cell metabolism; tumor protein D52 (TPD52)
    DOI:  https://doi.org/10.1002/cam4.4911
  12. Anal Chem. 2022 Jun 07.
      Liquid chromatography-high-resolution mass spectrometry (LC-HRMS) is the most popular platform for untargeted metabolomics studies, but compound annotation is a challenge. In this work, we developed a new LC-HRMS data-targeted extraction method called MetEx for metabolite annotation. MetEx contains the retention time (tR), MS1, and MS2 information of 30 620 metabolites from freely available spectral databases, including MoNA and KEGG. The tR values of 95.4% of the compounds in our database were calculated by the GNN-RT model. The MS2 spectra of 39.4% compounds were also predicted using CFM-ID. MetEx was initially examined on a mixture of 634 standards, considering chemical coverage and accurate metabolite assignment, and later applied to human plasma (NIST SRM 1950), human urine, HepG2 cells, mouse liver tissue, and mouse feces. MetEx correctly assigned 252 out of 253 standards detected in our instruments. The platform also provided 8.0-44.2% more compounds in the biological samples compared to XCMS, MS-DIAL, and MZmine 2. MetEx is implemented and visualized in R and freely available at http://www.metaboex.cn/MetEx.
    DOI:  https://doi.org/10.1021/acs.analchem.1c04783
  13. Mol Genet Metab. 2022 May 25. pii: S1096-7192(22)00321-3. [Epub ahead of print]
      The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing genetic variant(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in genes associated with metabolic processes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 81% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with Combined Annotation Dependent Depletion (CADD) scores (a measure for gene variant deleteriousness) and ranked the metabolic genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the genes containing the disease-causing variant when compared with the two approaches individually. For 15/27 IEM patients the correct affected gene was ranked within the top 0.25% of the set of potentially affected genes. Together, our findings suggest that metabolomics data improves the identification of affected genes in patients suffering from IEM.
    Keywords:  CADD scores; Data integration; ES; Inborn errors of metabolism; Metabolic pathways; Untargeted metabolomics
    DOI:  https://doi.org/10.1016/j.ymgme.2022.05.002
  14. Nat Commun. 2022 Jun 07. 13(1): 3108
      Integrating data-dependent acquisition (DDA) and data-independent acquisition (DIA) approaches can enable highly sensitive mass spectrometry, especially for imunnopeptidomics applications. Here we report a streamlined platform for both DDA and DIA data analysis. The platform integrates deep learning-based solutions of spectral library search, database search, and de novo sequencing under a unified framework, which not only boosts the sensitivity but also accurately controls the specificity of peptide identification. Our platform identifies 5-30% more peptide precursors than other state-of-the-art systems on multiple benchmark datasets. When evaluated on immunopeptidomics datasets, we identify 1.7-4.1 and 1.4-2.2 times more peptides from DDA and DIA data, respectively, than previously reported results. We also discover six T-cell epitopes from SARS-CoV-2 immunopeptidome that might represent potential targets for COVID-19 vaccine development. The platform supports data formats from all major instruments and is implemented with the distributed high-performance computing technology, allowing analysis of tera-scale datasets of thousands of samples for clinical applications.
    DOI:  https://doi.org/10.1038/s41467-022-30867-7
  15. Mol Omics. 2022 Jun 07.
      Mass spectrometry-based proteomics experiments can be subject to a large variability, which forms an obstacle to obtaining deep and accurate protein identification. Here, to obtain an optimal sample preparation workflow for in-depth proteome identification in human tissues, we systematically compared typical procedures in the four key steps during sample preparation, including two lysis buffers (5% SDS and 7M urea/2M thiourea), acetone precipitation, two proteolytic enzyme methods (in-solution digestion and FASP), and two pre-fractionation methods (SDS-PAGE and hi-pH RPLC). Compared with other methods, the procedure, including urea/thiourea as the lysis buffer, in-solution digestion, followed by hi-pH RPLC, yields an increase in proteome coverage (+15%), matched peptides (+42.4%), and significantly high protein concentrations. We also used combinations of these sample preparation methods to demonstrate a high identification rate in the range of low molecular weight (LMW), and the performance of sample preparation workflows varied between different groups of proteins. Importantly, 3 proteins defined as missing proteins (MPs) following the Human Proteome Project (HPP) guidelines were found in our data set. Overall, our findings provide an optimal sample preparation workflow for highly efficient and unbiased global proteomic analysis in human tissues.
    DOI:  https://doi.org/10.1039/d2mo00076h
  16. Int J Mol Sci. 2022 Jun 02. pii: 6235. [Epub ahead of print]23(11):
      Lipids are not only constituents of cellular membranes, but they are also key signaling mediators, thus acting as "bioactive lipids". Among the prominent roles exerted by bioactive lipids are immune regulation, inflammation, and maintenance of homeostasis. Accumulated evidence indicates the existence of a bidirectional relationship between the immune and nervous systems, and lipids can interact particularly with the aggregation and propagation of many pathogenic proteins that are well-renowned hallmarks of several neurodegenerative disorders, including Alzheimer's (AD) and Parkinson's (PD) diseases. In this review, we summarize the current knowledge about the presence and quantification of the main classes of endogenous bioactive lipids, namely glycerophospholipids/sphingolipids, classical eicosanoids, pro-resolving lipid mediators, and endocannabinoids, in AD and PD patients, as well as their most-used animal models, by means of lipidomic analyses, advocating for these lipid mediators as powerful biomarkers of pathology, diagnosis, and progression, as well as predictors of response or activity to different current therapies for these neurodegenerative diseases.
    Keywords:  Alzheimer’s; Parkinson’s; classical eicosanoids; endocannabinoids; glycerophospholipids; specialized pro-resolving mediators; sphingolipids
    DOI:  https://doi.org/10.3390/ijms23116235