bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒10‒23
nineteen papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. J Proteome Res. 2022 Oct 20.
      Lipids play a key role in many biological processes, and their accurate measurement is critical to unraveling the biology of diseases and human health. A high throughput HILIC-based (LC-MS) method for the semiquantitative screening of over 2000 lipids, based on over 4000 MRM transitions, was devised to produce an accessible and robust lipidomic screen for phospholipids in human plasma/serum. This methodology integrates many of the advantages of global lipid analysis with those of targeted approaches. Having used the method as an initial "wide class" screen, it can then be easily adapted for a more targeted analysis and quantification of key, dysregulated lipids. Robustness was assessed using 1550 continuous injections of plasma extracts onto a single column and via the evaluation of columns from 5 different batches of stationary phase. Initial screens in positive (239 lipids, 431 MRM transitions) and negative electrospray ionization (ESI) mode (232 lipids, 446 MRM transitions) were assessed for reproducibility, sensitivity, and dynamic range using analysis times of 8 min. The total number of lipids monitored using these screening methods was 433 with an overlap of 38 lipids in both modes. A polarity switching method for accurate quantification, using the same LC conditions, was assessed for intra- and interday reproducibility, accuracy, dynamic range, stability, carryover, dilution integrity, and matrix interferences and found to be acceptable. This polarity switching method was then applied to lipids important in the stratification of human prostate cancer samples.
    Keywords:  high throughput; lipidomics; plasma; prostate cancer; quantification; serum
  2. Cell Metab. 2022 Oct 14. pii: S1550-4131(22)00447-8. [Epub ahead of print]
      Lipids have essential biological functions in the body (e.g., providing energy storage, acting as a signaling molecule, and being a structural component of membranes); however, an excess of lipids can promote tumorigenesis, colonization, and metastatic capacity of tumor cells. To metastasize, a tumor cell goes through different stages that require lipid-related metabolic and structural adaptations. These adaptations include altering the lipid membrane composition for invading other niches and overcoming cell death mechanisms and promoting lipid catabolism and anabolism for energy and oxidative stress protective purposes. Cancer cells also harness lipid metabolism to modulate the activity of stromal and immune cells to their advantage and to resist therapy and promote relapse. All this is especially worrying given the high fat intake in Western diets. Thus, metabolic interventions aiming to reduce lipid availability to cancer cells or to exacerbate their metabolic vulnerabilities provide promising therapeutic opportunities to prevent cancer progression and treat metastasis.
    Keywords:  lipid metabolism; metastasis; metastatic-initiating cells; tumor storm
  3. Proteomics. 2022 Oct;22(19-20): e2200260
      Tandem mass tag (TMT) technology enables mass spectrometry-based multiplexed sample profiling of protein abundance. The degree of isobaric labeling with TMT has increased from 2 to 6, 11, 16 [1] and recently 18 [2] channels, enabling the development of higher throughput assays. In TMT experiments, measurement of reporter tag intensities is confounded by ratio compression. Although both pre- and post-acquisition methods have been developed to decrease interference, ratio compression remains a problem in complex samples. The work of Sun et al. presented a TMT29-plex workflow that combines the TMT11-plex and TMTpro18-plex labeling strategies and uses their inherent features to address the ratio compression problem, increasing the TMT throughput and quantitative accuracy for potential applications [3].
    Keywords:  29-plex; TMT; interference; ratio compression; ratio restoration
  4. J Chromatogr A. 2022 Oct 08. pii: S0021-9673(22)00747-6. [Epub ahead of print]1684 463556
      In this study, a targeted approach with wide metabolite coverage was developed for cellular metabolomic analysis using a UHPLC-QTrap-MS system operated in the scheduled multiple reaction monitoring (sMRM) mode. MRM ion pairs were acquired from HeLa cell samples through untargeted analysis using UHPLC-QTOF-MS with SWATH acquisition complemented by missing metabolites from pathway databases. Four different cell extraction protocols were studied and compared based on an experiment series involving the calculation of individual metabolite recoveries (pre/post extraction spiking U-13C isotope-labeled standards), with a Methanol/Water extraction mixture (1:1; v/v) showing the best results. Two HILIC-MS methods employing a Waters Premier BEH Amide column were developed, utilizing two different chromatographic conditions (20 mM ammonium formate as buffer additive adjusted to a pH = 3.5 with formic acid in ESI+ mode and 20 mM ammonium acetate adjusted to a pH = 7.5 with acetic acid in ESI- mode. One hundred sixty-one (161) metabolites were successfully detected in ESI+ mode, whereas 92 were detected in negative ionization mode, totaling to a number of 253 compounds in three different biological matrices covered by the analytical system employed. Both established HILIC methods were calibrated and validated based on 105 authentic chemical standards and U-13C-labeled Pichia pastoris (Komagataella phaffii) yeast extract as internal standards for cellular matrix (HeLa cells). Within-day and between-day precision was determined on three different QC concentration levels and was below 15% for the entirety of the analytes. Inter- and intra-day accuracies showed values in the range between 85 and 115% (assessed as % recovery) in the entire range. Matrix effects, extraction recoveries and process efficiencies were evaluated following the Matuszewski protocol with U-13C-labeled Pichia pastoris metabolite extract as internal standards. Eventually, the method was utilized to quantify metabolites in HeLa cell extracts.
    Keywords:  13C-cell extract; Hydrophilic interaction liquid chromatography; Stable isotope-labelled internal standards; Targeted metabolomics; UHPLC
  5. Biomed Chromatogr. 2022 Oct 21. e5531
      Targeted mass spectrometry is extensively used for the quantitative measurement of various molecules present in complex matrices. It is certainly one of the most important analytical duties in a mass spectrometry laboratory. Systematic development of selected-reaction monitoring (SRM), multiple-reaction monitoring (MRM) and parallel-reaction monitoring (PRM) methods for targeted mass spectrometry-based analysis were performed without considering future opportunities. The advancement of hardware and software technologies have resulted in more resolution, more accuracy, more speed and more depth. For sure, SRM, MRM or PRM acquisitions can quantify molecules very accurately at trace levels. However, it does not provide datasets allowing future data mining. Obviously, we cannot truly quantify something that we don't know is there. However, using non-targeted data acquisition for target analysis (nDATA), we can generate a MS1 and MS2 digital libraries of each sample providing future proof datasets. This is instrumental for data mining following new questions potentially arising in time permitting new and deeper processing and interpretation. This perspective article provides thoughts on why we believe it is time to question the status quo in targeted mass spectrometry.
    Keywords:  Bioanalysis; Data-dependent acquisition; Data-independent acquisition; Mass spectrometry; Metabolomics; Proteomics
  6. Anal Chem. 2022 Oct 20.
      Blood is one of the most important clinical samples for protein biomarker discovery, as it provides rich physiological and pathological information and is easy to obtain with low invasiveness. However, the discovery of protein biomarkers in the blood by mass spectrometry (MS)-based proteomic strategies has been shown to be highly challenging due to the particularly large concentration range of proteins and the strong interference by the high-abundant proteins in the blood. Therefore, developing sensitive methods for low-abundant biomarker protein identification is a key issue that has received great attention. Here, we report the synthesis and characterization of surface-functionalized magnetic molybdenum disulfide (MoS2) for the large-scale adsorption of low-abundant plasma proteins and deep profiling by MS. MoS2 nanomaterials resulted in the coverage of more than 3400 proteins (including a single-peptide hit) in a single LC-MS analysis without peptide prefractionation using pooled plasma samples, which were five times more than those obtained by the direct analysis of the plasma proteome. A detection limit in the low ng L-1 range was obtained, which is rare compared with previous reports.
  7. Semin Cancer Biol. 2022 Oct 13. pii: S1044-579X(22)00205-X. [Epub ahead of print]
      Metabolic reprogramming is an important cancer hallmark that plays a key role in cancer malignancies and therapy resistance. Cancer cells reprogram the metabolic pathways to generate not only energy and building blocks but also produce numerous key signaling metabolites to impact signaling and epigenetic/transcriptional regulation for cancer cell proliferation and survival. A deeper understanding of the mechanisms by which metabolic reprogramming is regulated in cancer may provide potential new strategies for cancer targeting. Recent studies suggest that deregulated transcription factors have been observed in various human cancers and significantly impact metabolism and signaling in cancer. In this review, we highlight the key transcription factors that are involved in metabolic control, dissect the crosstalk between signaling and transcription factors in metabolic reprogramming, and offer therapeutic strategies targeting deregulated transcription factors for cancer treatment.
    Keywords:  Cancer treatment; Cell metabolism; Metabolic Reprogramming; Transcription Factors; signaling metabolites
  8. Front Oncol. 2022 ;12 1014748
      Dysregulated metabolism in cancers is, by now, well established. Although metabolic adaptations provide cancers with the ability to synthesize the precursors required for rapid biosynthesis, some metabolites have direct functional, or bioactive, effects in human cells. Here we summarize recently identified metabolites that have bioactive roles either as post-translational modifications (PTMs) on proteins or in, yet unknown ways. We propose that these metabolites could play a bioactive role in promoting or inhibiting cancer cell phenotypes in a manner that is mostly unexplored. To study these potentially important bioactive roles, we discuss several novel metabolomic and proteomic approaches aimed at defining novel PTMs and metabolite-protein interactions. Understanding metabolite PTMs and protein interactors of bioactive metabolites may provide entirely new therapeutic targets for cancer.
    Keywords:  bioactive metabolite; cancer metabolism; cancer therapeutics; metabolite-protein interaction profiling; post-translational modification
  9. Transl Oncol. 2022 Oct 18. pii: S1936-5233(22)00215-7. [Epub ahead of print]27 101556
      The field of single-cell omics is rapidly progressing. Although DNA and RNA sequencing-based methods have dominated the field to date, global proteome profiling has also entered the main stage. Single-cell proteomics was facilitated by advancements in different aspects of mass spectrometry (MS)-based proteomics, such as instrument design, sample preparation, chromatography and ion mobility. Single-cell proteomics by mass spectrometry (scp-MS) has moved beyond being a mere technical development, and is now able to deliver actual biological application and has been successfully applied to characterize different cell states. Here, we review some key developments of scp-MS, provide a background to the field, discuss the various available methods and foresee possible future directions.
  10. Cancer Biol Med. 2022 Oct 24. pii: j.issn.2095-3941.2022.0381. [Epub ahead of print]
      The tumor microenvironment is an ecosystem composed of multiple types of cells, such as tumor cells, immune cells, and cancer-associated fibroblasts. Cancer cells grow faster than non-cancerous cells and consume larger amounts of nutrients. The rapid growth characteristic of cancer cells fundamentally alters nutrient availability in the tumor microenvironment and results in reprogramming of immune cell metabolic pathways. Accumulating evidence suggests that cellular metabolism of nutrients, such as lipids and amino acids, beyond being essential to meet the bioenergetic and biosynthetic demands of immune cells, also regulates a broad spectrum of cellular signal transduction, and influences immune cell survival, differentiation, and anti-tumor effector function. The cancer immunometabolism research field is rapidly evolving, and exciting new discoveries are reported in high-profile journals nearly weekly. Therefore, all new findings in this field cannot be summarized within this short review. Instead, this review is intended to provide a brief introduction to this rapidly developing research field, with a focus on the metabolism of two classes of important nutrients-lipids and amino acids-in immune cells. We highlight recent research on the roles of lipids and amino acids in regulating the metabolic fitness and immunological functions of T cells, macrophages, and natural killer cells in the tumor microenvironment. Furthermore, we discuss the possibility of "editing" metabolic pathways in immune cells to act synergistically with currently available immunotherapies in enhancing anti-tumor immune responses.
    Keywords:  Lipids; NK cells; T cells; amino acids; anti-tumor immunity; cancer; immunometabolism; metabolism
  11. Handb Exp Pharmacol. 2022 Oct 22.
      While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.
    Keywords:  Applications; Experimental methods; NMR spectroscopy; Targeted metabolomics; Untargeted metabolomics
  12. Nat Metab. 2022 Oct;4(10): 1232-1244
      Metabolism has historically been studied at the levels of whole cells, whole tissues and whole organisms. As a result, our understanding of how compartmentalization-the spatial and temporal separation of pathways and components-shapes organismal metabolism remains limited. At its essence, metabolic compartmentalization fulfils three important functions or 'pillars': establishing unique chemical environments, providing protection from reactive metabolites and enabling the regulation of metabolic pathways. However, how these pillars are established, regulated and maintained at both the cellular and systemic levels remains unclear. Here we discuss how the three pillars are established, maintained and regulated within the cell and discuss the consequences of dysregulation of metabolic compartmentalization in human disease. Organelles are increasingly emerging as 'command-and-control centres' and the increased understanding of metabolic compartmentalization is revealing new aspects of metabolic homeostasis, with this knowledge being translated into therapies for the treatment of cancer and certain neurodegenerative diseases.
  13. Adv Sci (Weinh). 2022 Oct 17. e2203339
      Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.
    Keywords:  artificial intelligence; computational methods; data mining; data-driven experiments; mass spectrometry imaging
  14. J Lipid Res. 2022 Oct 17. pii: S0022-2275(22)00135-3. [Epub ahead of print] 100302
      Oxylipins are important biological regulators that have received extensive research attention. Due to the extremely low concentrations, large concentration variations, and high structural similarity of many oxylipins, the quantitative analysis of oxylipins in biological samples is always a great challenge. Here, we developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method with high sensitivity, wide linearity, and acceptable resolution for quantitative profiling of oxylipins in multiple biological samples. A total of 104 oxylipins, some with a high risk of detection crosstalk, were well separated on a 150 mm column over 20 min. The method showed high sensitivity with lower limits of quantitation for 87 oxylipins, reaching 0.05-0.5 pg. Unexpectedly, we found that the linear range for 16, 18, and 17 oxylipins reached 10,000, 20,000, and 40,000 folds, respectively. Due to the high sensitivity, while reducing sample consumption to below half the volume of previous methods, 74, 78, and 59 low-abundance oxylipins, among which some were difficult to detect like lipoxins and resolvins, were well quantified in the tested mouse plasma, mouse liver, and human plasma samples, respectively. Additionally, we determined that analytes with multifarious concentrations of over a thousand-fold difference could be well quantified simultaneously due to the wide linearity. In conclusion, most likely due to the instrumental advancement, this method effectively improves the quantitative sensitivity and linear range over existing methods, which will facilitate and advance the study of the physiological and pathophysiological functions of oxylipins.
    Keywords:  Biological regulators; Linear range; Lipoxins; Liquid chromatography-tandem mass spectrometry; Lower limits of quantitation; Plasma samples; Quantitative profiling; Quantitative sensitivity; Reduced sample consumption; Resolvins
  15. Nat Commun. 2022 Oct 20. 13(1): 6239
      The systemic metabolic shifts that occur during aging and the local metabolic alterations of a tumor, its stroma and their communication cooperate to establish a unique tumor microenvironment (TME) fostering cancer progression. Here, we show that methylmalonic acid (MMA), an aging-increased oncometabolite also produced by aggressive cancer cells, activates fibroblasts in the TME, which reciprocally secrete IL-6 loaded extracellular vesicles (EVs) that drive cancer progression, drug resistance and metastasis. The cancer-associated fibroblast (CAF)-released EV cargo is modified as a result of reactive oxygen species (ROS) generation and activation of the canonical and noncanonical TGFβ signaling pathways. EV-associated IL-6 functions as a stroma-tumor messenger, activating the JAK/STAT3 and TGFβ signaling pathways in tumor cells and promoting pro-aggressive behaviors. Our findings define the role of MMA in CAF activation to drive metastatic reprogramming, unveiling potential therapeutic avenues to target MMA at the nexus of aging, the tumor microenvironment and metastasis.
  16. Front Endocrinol (Lausanne). 2022 ;13 971313
      The mechanism by which pancreatic beta cells are destroyed in type 1 diabetes (T1D) remains to be fully understood. Recent observations indicate that the disease may arise because of different pathobiological mechanisms (endotypes). The discovery of one or several protein biomarkers measurable in readily available liquid biopsies (e.g. blood plasma) during the pre-diabetic period may enable personalized disease interventions. Recent studies have shown that extracellular vesicles (EVs) are a source of tissue proteins in liquid biopsies. Using plasma samples collected from pre-diabetic non-obese diabetic (NOD) mice (an experimental model of T1D) we addressed if combined analysis of whole plasma samples and plasma-derived EV fractions increases the number of unique proteins identified by mass spectrometry (MS) compared to the analysis of whole plasma samples alone. LC-MS/MS analysis of plasma samples depleted of abundant proteins and subjected to peptide fractionation identified more than 2300 proteins, while the analysis of EV-enriched plasma samples identified more than 600 proteins. Of the proteins detected in EV-enriched samples, more than a third were not identified in whole plasma samples and many were classified as either tissue-enriched or of tissue-specific origin. In conclusion, parallel profiling of EV-enriched plasma fractions and whole plasma samples increases the overall proteome depth and facilitates the discovery of tissue-enriched proteins in plasma. If applied to plasma samples collected longitudinally from the NOD mouse or from models with other pathobiological mechanisms, the integrated proteome profiling scheme described herein may be useful for the discovery of new and potentially endotype specific biomarkers in T1D.
    Keywords:  biomarkers; exosome; extracellular vesicles; mass spectrometry; mouse; non-diabetic (NOD) mouse; plasma; type 1 diabetes
  17. J Proteome Res. 2022 Oct 20.
      Cerebral infarction (CI) remains a major cause of high mortality and long-term disability worldwide. The exploration of biomarkers and pathogenesis is crucial for the early diagnosis of CI. Although the understanding of metabolic perturbations underlying CI has increased in recent years, the relationship between altered metabolites and disease pathogenesis has only been partially elucidated and requires further investigation. In this study, we performed an integrated metabolomics and lipidomics analysis on 59 healthy subjects and 47 CI patients. Ultimately, 49 metabolite and 68 lipid biomarkers were identified and enriched in 24 disturbed pathways. The metabolic network revealed a significant interaction between altered lipids and other metabolites. Using receiver operating characteristic curve (ROC) analysis, a panel of three polar metabolites and seven lipids was optimized in the training set, which included taurine, oleoylcarnitine, creatinine, PE(22:6/P-18:0), Cer 34:2, GlcCer(d18:0/18:0), DG 44:0, LysoPC(16:0), 22:6-OH/LysoPC, and TAG58:7-FA22:4. Subsequently, a support vector machine (SVM) model was constructed and validated, which showed excellent predictive ability in the validation set. Thereby, the integrated metabolomics and lipidomics approach could contribute to a comprehensive understanding of the metabolic dyshomeostasis associated with the pathogenesis of underlying CI. The present research may promote a deeper understanding and early diagnosis of CI in the clinic. All raw data were deposited in PRIDE (PXD036199).
    Keywords:  LC-MS; biomarkers; cerebral infarction; lipidomics; metabolomics
  18. J Clin Invest. 2022 Oct 18. pii: e161408. [Epub ahead of print]
      Glutamine synthetase (GS) catalyzes de novo synthesis of glutamine that facilitates cancer cell growth. In the liver, GS functions next to the urea cycle to remove ammonia waste. As dysregulated urea cycle is implicated in cancer development, the impact of GS' ammonia clearance function has not been explored in cancer. Here we show that, oncogenic activation of beta-catenin led to decreased urea cycle and elevated ammonia waste burden. While beta-catenin induced the expression of GS, which is thought to be cancer-promoting, surprisingly, genetic ablation of hepatic GS accelerated the onset of liver tumors in several mouse models that involved β-catenin activation. Mechanistically, GS ablation exacerbated hyperammonemia and facilitated the production of glutamate-derived non-essential amino acids (NEAAs), which subsequently stimulated mTORC1. Pharmacological and genetic inhibition of mTORC1 and glutamic transaminases suppressed tumorigenesis facilitated by GS ablation. While HCC patients, especially those with CTNNB1 mutations, have an overall defective urea cycle and increased expression of GS, there exists a subset of patients with low GS expression that is associated with mTORC1 hyperactivation. Therefore, GS-mediated ammonia clearance serves as a tumor-suppressing mechanism in livers that harbor β-catenin activation mutations and a compromised urea cycle.
    Keywords:  Hepatology; Liver cancer; Metabolism
  19. Mol Cell. 2022 Oct 20. pii: S1097-2765(22)00958-3. [Epub ahead of print]82(20): 3760-3762
      The dietary factor vitamin K has been found to protect against ferroptosis, a form of cell death driven by lipid peroxidation. This reveals new dietary links to cancers and degenerative conditions and a key factor involved in warfarin poisoning.