bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒07‒10
twenty papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Int J Mol Sci. 2022 Jun 29. pii: 7210. [Epub ahead of print]23(13):
      Cancer metabolism has been of interest for decades; however, the recent development of sophisticated techniques such as metabolomics or lipidomics have significantly increased our understanding of processes taking place in tumour cells [...].
  2. Cancer Cell Int. 2022 Jul 05. 22(1): 224
      Bioactive lipid molecules have been proposed to play important roles linking obesity/metabolic syndrome and cancers. Studies reveal that aberrant lipid metabolic signaling can reprogram cancer cells and non-cancer cells in the tumor microenvironment, contributing to cancer initiation, progression, metastasis, recurrence, and poor therapeutic response. Existing evidence indicates that controlling lipid metabolism can be a potential strategy for cancer prevention and therapy. By reviewing the current literature on the lipid metabolism in various cancers, we summarized major lipid molecules including fatty acids and cholesterol as well as lipid droplets and discussed their critical roles in cancer cells and non-cancer in terms of either promoting- or anti-tumorigenesis. This review provides an overview of the lipid molecules in cellular entities and their tumor microenvironment, adding to the existing knowledge with lipid metabolic reprogramming in immune cells and cancer associated cells. Comprehensive understanding of the regulatory role of lipid metabolism in cellular entities and their tumor microenvironment will provide a new direction for further studies, in a shift away from conventional cancer research. Exploring the lipid-related signaling targets that drive or block cancer development may lead to development of novel anti-cancer strategies distinct from traditional approaches for cancer prevention and treatment.
    Keywords:  Cholesterol; Fatty acid; Lipid; Lipid metabolism; Tumor microenvironment
  3. J Agric Food Chem. 2022 Jul 05.
      Metabolome analysis of high-salt fermented food can be an analytical challenge, as the salts can interfere with the sample processing and analysis. In this work, we describe a four-channel chemical isotope labeling (CIL) LC-MS approach for a comprehensive metabolome analysis of high-salt fermented food. The workflow includes metabolite extraction, chemical labeling of metabolites using dansyl chloride, dansylhydrazine, or p-dimethylaminophenacyl bromide reagents to enhance separation and ionization, LC-UV measurement of the total concentration of dansyl-labeled metabolites in each sample for sample normalization, mixing of 13C- and 12C-reagent-labeled samples, high-resolution LC-MS analysis, and data processing. Metabolome analysis of fermented foods, including fermented red pepper (FRP) sauce, soy sauce, and sufu (a fermented soybean food), showed unprecedented high metabolic coverage. Metabolome comparison of FRP, soy sauce, and sufu, as well as soy sauce and sufu, indicated great diversity of metabolite types and abundances in these foods. In addition, we analyzed two groups of samples of the same type, FRP with 10% (w/w) and 15% (w/w) salt contents, and detected large variations in multiple categories of metabolites belonging to a number of different metabolic pathways. We envisage that this CIL LC-MS approach can be generally used for metabolomic studies of high-salt fermented food. CIL LC-MS allows high-coverage identification and quantification that could not be done using other methods.
    Keywords:  LC−MS; chemical isotope labeling; fermented food; high-salt; metabolomics
  4. BMC Bioinformatics. 2022 Jul 08. 23(1): 267
      BACKGROUND: Modern mass spectrometry has revolutionized the detection and analysis of metabolites but likewise, let the data skyrocket with repositories for metabolomics data filling up with thousands of datasets. While there are many software tools for the analysis of individual experiments with a few to dozens of chromatograms, we see a demand for a contemporary software solution capable of processing and analyzing hundreds or even thousands of experiments in an integrative manner with standardized workflows.RESULTS: Here, we introduce MetHoS as an automated web-based software platform for the processing, storage and analysis of great amounts of mass spectrometry-based metabolomics data sets originating from different metabolomics studies. MetHoS is based on Big Data frameworks to enable parallel processing, distributed storage and distributed analysis of even larger data sets across clusters of computers in a highly scalable manner. It has been designed to allow the processing and analysis of any amount of experiments and samples in an integrative manner. In order to demonstrate the capabilities of MetHoS, thousands of experiments were downloaded from the MetaboLights database and used to perform a large-scale processing, storage and statistical analysis in a proof-of-concept study.
    CONCLUSIONS: MetHoS is suitable for large-scale processing, storage and analysis of metabolomics data aiming at untargeted metabolomic analyses. It is freely available at: . Users interested in analyzing their own data are encouraged to apply for an account.
    Keywords:  Distributed analysis; Distributed storage; Large-scale metabolomics; Mass spectrometry data; Parallel processing
  5. Cancer Metab. 2022 Jul 07. 10(1): 11
      BACKGROUND: 13C tracer analysis is increasingly used to monitor cellular metabolism in vivo and in intact cells, but data interpretation is still the key element to unveil the complexity of metabolic activities. The distinct 13C labeling patterns (e.g., M + 1 species in vivo but not in vitro) of metabolites from [U-13C]-glucose or [U-13C]-glutamine tracing in vivo and in vitro have been previously reported by multiple groups. However, the reason for the difference in the M + 1 species between in vivo and in vitro experiments remains poorly understood.METHODS: We have performed [U-13C]-glucose and [U-13C]-glutamine tracing in sarcoma-bearing mice (in vivo) and in cancer cell lines (in vitro). 13C enrichment of metabolites in cultured cells and tissues was determined by LC coupled with high-resolution mass spectrometry (LC-HRMS). All p-values are obtained from the Student's t-test two-tailed using GraphPad Prism 8 unless otherwise noted.
    RESULTS: We observed distinct enrichment patterns of tricarboxylic acid cycle intermediates in vivo and in vitro. As expected, citrate M + 2 or M + 4 was the dominant mass isotopologue in vitro. However, citrate M + 1 was unexpectedly the dominant isotopologue in mice receiving [U-13C]-glucose or [U-13C]-glutamine infusion, but not in cultured cells. Our results are consistent with a model where the difference in M + 1 species is due to the different sources of CO2 in vivo and in vitro, which was largely overlooked in the past. In addition, a time course study shows the generation of high abundance citrate M + 1 in plasma of mice as early as few minutes after [U-13C]-glucose infusion.
    CONCLUSIONS: Altogether, our results show that recycling of endogenous CO2 is substantial in vivo. The production and recycling of 13CO2 from the decarboxylation of [U-13C]-glucose or [U-13C]-glutamine is negligible in vitro partially due to dilution by the exogenous HCO3-/CO2 source, but in vivo incorporation of endogenous 13CO2 into M + 1 metabolites is substantial and should be considered. These findings provide a new paradigm to understand carbon atom transformations in vivo and should be taken into account when developing mathematical models to better reflect carbon flux.
    Keywords:  13C tracing; Anaplerotic metabolism; CO2 recycling; High-resolution mass spectrometry
  6. Int J Mol Sci. 2022 Jul 04. pii: 7419. [Epub ahead of print]23(13):
      Cancer cells switch their metabolism toward glucose metabolism to sustain their uncontrolled proliferation. Consequently, glycolytic intermediates are diverted into the pentose phosphate pathway (PPP) to produce macromolecules necessary for cell growth. The transcription regulator RIP140 controls glucose metabolism in tumor cells, but its role in cancer-associated reprogramming of cell metabolism remains poorly understood. Here, we show that, in human breast cancer cells and mouse embryonic fibroblasts, RIP140 inhibits the expression of the gene-encoding G6PD, the first enzyme of the PPP. RIP140 deficiency increases G6PD activity as well as the level of NADPH, a reducing cofactor essential for macromolecule synthesis. Moreover, G6PD knock-down inhibits the gain of proliferation observed when RIP140 expression is reduced. Importantly, RIP140-deficient cells are more sensitive to G6PD inhibition in cell proliferation assays and tumor growth experiments. Altogether, this study describes a novel role for RIP140 in regulating G6PD levels, which links its effect on breast cancer cell proliferation to metabolic rewiring.
    Keywords:  G6PD; RIP140; breast cancer; pentose phosphate pathway; transcription
  7. Prog Lipid Res. 2022 Jun 30. pii: S0163-7827(22)00032-7. [Epub ahead of print] 101177
      Large 'omics studies are of particular interest to population and clinical research as they allow elucidation of biological pathways that are often out of reach of other methodologies. Typically, these information rich datasets are produced from multiple coordinated profiling studies that may include lipidomics, metabolomics, proteomics or other strategies to generate high dimensional data. In lipidomics, the generation of such data presents a series of unique technological and logistical challenges; to maximize the power (number of samples) and coverage (number of analytes) of the dataset while minimizing the sources of unwanted variation. Technological advances in analytical platforms, as well as computational approaches, have led to improvement of data quality - especially with regard to instrumental variation. In the small scale, it is possible to control systematic bias from beginning to end. However, as the size and complexity of datasets grow, it is inevitable that unwanted variation arises from multiple sources, some potentially unknown and out of the investigators control. Increases in cohort sizes and complexity has led to new challenges in sample collection, handling, storage, and preparation stages. If not considered and dealt with appropriately, this unwanted variation may undermine the quality of the data and reliability of any subsequent analysis. Here we review the various experimental phases where unwanted variation may be introduced and review general strategies and approaches to handle this variation, specifically addressing issues relevant to lipidomics studies.
    Keywords:  Data analysis; High-throughput; Lipidomics; Normalization; Preprocessing; Unwanted variation
  8. Front Oncol. 2022 ;12 881252
      Oxygen is critical to energy metabolism, and tumors are often characterized by a hypoxic microenvironment. Owing to the high metabolic energy demand of malignant tumor cells, their survival is promoted by metabolic reprogramming in the hypoxic microenvironment, which can confer tumor cell resistance to pyroptosis. Pyroptosis resistance can inhibit anti-tumor immunity and promote the development of malignant tumors. Hypoxia inducible factor-1α (HIF-1α) is a key regulator of metabolic reprogramming in tumor cells, and estrogen-related receptor α (ERRα) plays a key role in regulating cellular energy metabolism. Therefore, the close interaction between HIF-1α and ERRα influences the metabolic and functional changes in cancer cells. In this review, we summarize the reprogramming of tumor metabolism involving HIF-1α/ERRα. We review our understanding of the role of HIF-1α/ERRα in promoting tumor growth adaptation and pyroptosis resistance, emphasize its key role in energy homeostasis, and explore the regulation of HIF-1α/ERRα in preventing and/or treating endometrial carcinoma patients. This review provides a new perspective for the study of the molecular mechanisms of metabolic changes in tumor progression.
    Keywords:  ERRα; HIF-1α; endometrial cancer; glucose metabolism; lipid metabolism
  9. Mol Genet Metab Rep. 2022 Jun;31 100868
      We have developed a fast and accurate method that uses a small volume of sample to determine over 25 of the typically reported amino acids in human plasma. Samples were prepped with a single step using a spin filter to remove proteins, avoiding the decreased sensitivity from dilution in acid precipitation. Using a reverse phase (RP) High Performance Liquid Chromatography (HPLC) system with O-phthaldehyde (OPA) as the pre-column derivatization reagent, and UV detection at 338 nm, we did a direct comparison with the most common ion exchange/ninhydrin method used in clinical labs on the same plasma samples with 95% concurrence, analysis of amino acid standard solutions returned 99% concurrence. With a sample preparation time of 30 min, utilizing less than 25 μl of sample and with a chromatography run of 30 min, this method can substantially increase access to analysis in both clinical and research laboratories using instruments that are more widely available.Synopsis: We describe a rapid and easily deployed method for sensitive amino measurement in biological samples.
    Keywords:  Amino acid; Clinical biochemistry; HPLC; IEM; Inborn error of metabolism
  10. Nat Biotechnol. 2022 Jul 07.
      Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.
  11. Bioinformatics. 2022 Jul 04. pii: btac441. [Epub ahead of print]
      SUMMARY: We present MobilityTransformR, an R/Bioconductor package for the effective mobility scaling of capillary zone electrophoresis-mass spectrometry (CE-MS) data. It uses functionality from different R packages that are frequently used for data processing and analysis in MS-based metabolomics workflows, allowing the subsequent use of reproducible transformed CE-MS data in existing workflows.AVAILABILITY AND IMPLEMENTATION: MobilityTransformR is implemented in R (Version > = 4.2) and can be downloaded directly from the Bioconductor database ( or GitHub (
    SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
  12. J Proteome Res. 2022 Jul 06.
      Mass spectrometry-based proteomics is constantly challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are almost impossible to avoid. For data-dependent acquisition (DDA) proteomics, an exclusion list can be used to reduce the influence of protein contaminants. However, protein contamination has not been evaluated and is rarely addressed in data-independent acquisition (DIA). How protein contaminants influence proteomic data is also unclear. In this study, we established new protein contaminant FASTA and spectral libraries that are applicable to all proteomic workflows and evaluated the impact of protein contaminants on both DDA and DIA proteomics. We demonstrated that including our contaminant libraries can reduce false discoveries and increase protein identifications, without influencing the quantification accuracy in various proteomic software platforms. With the pressing need to standardize proteomic workflow in the research community, we highly recommend including our contaminant FASTA and spectral libraries in all bottom-up proteomic data analysis. Our contaminant libraries and a step-by-step tutorial to incorporate these libraries in various DDA and DIA data analysis platforms can be valuable resources for proteomic researchers, freely accessible at
    Keywords:  DDA; DIA; DIA-NN; FASTA; Spectronaut; contamination; keratin; protein contaminant; spectral library; trypsin
  13. Front Oncol. 2022 ;12 916661
      Gastric cancer has been one of the most common cancers worldwide with extensive metastasis and high mortality. Chemotherapy has been found as a main treatment for metastatic gastric cancer, whereas drug resistance limits the effectiveness of chemotherapy and leads to treatment failure. Chemotherapy resistance in gastric cancer has a complex and multifactorial mechanism, among which lipid metabolism plays a vital role. Increased synthesis of new lipids or uptake of exogenous lipids can facilitate the rapid growth of cancer cells and tumor formation. Lipids form the structural basis of biofilms while serving as signal molecules and energy sources. It is noteworthy that lipid metabolism is capable of inducing drug resistance in gastric cancer cells by reshaping the tumor micro-environment. In this study, new mechanisms of lipid metabolism in gastric cancer and the metabolic pathways correlated with chemotherapy resistance are reviewed. In particular, we discuss the effects of lipid metabolism on autophagy, biomarkers treatment and drug resistance in gastric cancer from the perspective of lipid metabolism. In brief, new insights can be gained into the development of promising therapies through an in-depth investigation of the mechanism of lipid metabolism reprogramming and resensitization to chemotherapy in gastric cancer cells, and scientific treatment can be provided by applying lipid-key enzyme inhibitors as cancer chemical sensitizers in clinical settings.
    Keywords:  biomarkers; chemoresistance; gastric cancer; lipid metabolism; treatment
  14. FEBS Lett. 2022 Jul 07.
      Glycosphingolipids fulfil diverse functions in cells. Abnormalities in their metabolism are associated with specific pathologies and, consequently, the pharmacological modulation of glycosphingolipids is considered a therapeutic avenue. The accurate measurement of in situ metabolism of glycosphingolipids and the modulatory impact of drugs is warranted. Employing synthesized sphingosine and sphinganine containing 13 C atoms, we developed a method to monitor the de novo synthesis of glucosylceramide, the precursor of complex glycosphingolipids, by the enzyme glucosylceramide synthase (GCS). We show that feeding cells with isotope-labelled precursor combined with LC-MS/MS analysis allows accurate determination of the IC50 values of therapeutically considered inhibitors (iminosugars and ceramide mimics) of GCS in cultured cells. Acquired data were comparable to those obtained with an earlier method using artificial fluorescently labelled ceramide to feed cells.
    Keywords:  13C-labelled lipids; glucosylceramide synthase; glycosphingolipid metabolism; mass spectrometry
  15. Anticancer Res. 2022 Jul;42(7): 3313-3324
      BACKGROUND/AIM: Resistance to chemotherapy is a major obstacle for patients with unresectable colorectal cancer (CRC); however, the factors that induce chemoresistance have not been elucidated. Lipid composition influences neoplastic behaviour. Therefore, this study examined whether lipid composition affects sensitivity to chemotherapeutic agents in CRC.MATERIALS AND METHODS: We performed a lipidomic analysis of a CRC xenograft-derived spheroid model to identify potential relationships between the lipid profile and chemoresistance to 5-fluorouracil (5-FU). Genetic and pharmacological modulation of lipid synthesis were also used in the HCT-116 and DLD-1 CRC cell lines to further characterize resistance to 5-FU.
    RESULTS: Our lipidomic profiling revealed that phospholipids with saturated fatty acids (SFAs) were more abundant in 5-FU-resistant spheroids. The importance of phospholipids containing SFA in chemoresistance was confirmed by showing that in HCT-116 and DLD-1 cells, genetic or pharmacological inactivation of stearoyl-CoA desaturase-1, a key enzyme that converts SFAs to monounsaturated fatty acids, increased the proportion of SFAs in membranous phospholipids and reduced cell membrane fluidity, and this ultimately resulted in resistance to 5-FU.
    CONCLUSION: These data suggest that the saturated to monounsaturated fatty acid ratio in cellular membranous phospholipids affects sensitivity to chemotherapeutic agents.
    Keywords:  Saturated fatty acid; chemoresistance; liquid chromatography mass spectrometry; membrane fluidity; stearoyl-CoA desaturase
  16. Nat Commun. 2022 Jul 08. 13(1): 3944
      The dia-PASEF technology uses ion mobility separation to reduce signal interferences and increase sensitivity in proteomic experiments. Here we present a two-dimensional peak-picking algorithm and generation of optimized spectral libraries, as well as take advantage of neural network-based processing of dia-PASEF data. Our computational platform boosts proteomic depth by up to 83% compared to previous work, and is specifically beneficial for fast proteomic experiments and those with low sample amounts. It quantifies over 5300 proteins in single injections recorded at 200 samples per day throughput using Evosep One chromatography system on a timsTOF Pro mass spectrometer and almost 9000 proteins in single injections recorded with a 93-min nanoflow gradient on timsTOF Pro 2, from 200 ng of HeLa peptides. A user-friendly implementation is provided through the incorporation of the algorithms in the DIA-NN software and by the FragPipe workflow for spectral library generation.
  17. Metabolomics. 2022 Jul 04. 18(7): 48
      INTRODUCTION: Rheumatoid arthritis (RA) and osteoarthritis (OA) are clinicopathologically different.OBJECTIVES: We aimed to assess the feasibility of metabolomics in differentiating the metabolite profiles of synovial fluid between RA and OA using gas chromatography/time-of-flight mass spectrometry.
    METHODS: We first compared the global metabolomic changes in the synovial fluid of 19 patients with RA and OA. Partial least squares-discriminant, hierarchical clustering, and univariate analyses were performed to distinguish metabolites of RA and OA. These findings were then validated using synovial fluid samples from another set of 15 patients with RA and OA.
    RESULTS: We identified 121 metabolites in the synovial fluid of the first 19 samples. The score plot of PLS-DA showed a clear separation between RA and OA. Twenty-eight crucial metabolites, including hypoxanthine, xanthine, adenosine, citrulline, histidine, and tryptophan, were identified to be capable of distinguishing RA metabolism from that of OA; these were found to be associated with purine and amino acid metabolism.
    CONCLUSION: Our results demonstrated that metabolite profiling of synovial fluid could clearly discriminate between RA and OA, suggesting that metabolomics may be a feasible tool to assist in the diagnosis and advance the comprehension of pathological processes for diseases.
    Keywords:  Gas chromatography–mass spectrometry; Metabolite profiling; Osteoarthritis; Rheumatoid arthritis; Synovial fluid
  18. J Am Soc Mass Spectrom. 2022 Jul 06. 33(7): 1276-1281
      The identification and confirmation of steroid sulfate metabolites in biological samples are essential to various fields, including anti-doping analysis and clinical sciences. Ultra-high-performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) is the leading method for the detection of intact steroid conjugates in biofluids, but because of the inherent complexity of biological samples and the low concentration of many targets of interest, metabolite identification based solely on mass spectrometry remains a major challenge. The confirmation of new metabolites typically depends on a comparison with synthetically derived reference materials that encompass a range of possible conjugation sites and stereochemistries. Herein, energy-resolved collision-induced dissociation (CID) is used as part of UHPLC-HRMS/MS analysis to distinguish between regio- and stereo-isomeric steroid sulfate compounds. This wholly MS-based approach was employed to guide the synthesis of reference materials to unambiguously confirm the identity of an equine steroid sulfate biomarker of testosterone propionate administration.
  19. Discov Oncol. 2022 Jul 07. 13(1): 58
      Acetyl-CoA synthetase 2 (ACSS2), an important member of the acetyl-CoA synthetase (ACSS) family, can catalyze the conversion of acetate to acetyl coenzyme A (acetyl-CoA). Currently, acetyl-CoA is considered an important intermediate metabolite in the metabolism of energy substrates. In addition, nutrients converge through acetyl-CoA into a common metabolic pathway, the tricarboxylic acid cycle and oxidative phosphorylation. Not only does ACSS2 play a crucial role in material energy metabolism, it is also involved in the regulation of various acetylation processes, such as regulation of histone and transcription factor acetylation. ACSS2-mediated regulation of acetylation is related to substance metabolism and tumorigenesis. In mammalian cells, ACSS2 utilizes intracellular acetate to synthesize acetyl-CoA, a step in the process of DNA and histone acetylation. In addition, studies in tumors have shown that cancer cells adapt to the growth conditions in the tumor microenvironment (TME) by activating or increasing the expression level of ACSS2 under metabolic stress. Therefore, this review mainly outlines the role of ACSS2 in substance metabolism and tumors and provides insights useful for investigating ACSS2 as a therapeutic target.
    Keywords:  ACSS2; Acetyl-CoA; Acetylation modification; Metabolism
  20. Cell Rep Methods. 2022 Jun 20. 2(6): 100237
      Single-cell proteomics has the potential to decipher tumor heterogeneity, and a method like single-cell proteomics by mass spectrometry (SCoPE-MS) allows profiling several tens of single cells for >1,000 proteins per cell. This method, however, cannot link the proteome of individual cells with phenotypes of interest. Here, we developed a microscopy-based functional single-cell proteomic-profiling technology, called FUNpro, to address this. FUNpro enables screening, identification, and isolation of single cells of interest in a real-time fashion, even if the phenotypes are dynamic or the cells of interest are rare. We applied FUNpro to proteomically profile a newly identified small subpopulation of U2OS osteosarcoma cells displaying an abnormal, prolonged DNA damage response (DDR) after ionizing radiation (IR). With this, we identified the PDS5A protein contributing to the abnormal DDR dynamics and helping the cells survive after IR.
    Keywords:  53BP1; DDR foci dynamics; DNA damage response; PDS5A; functional single-cell selection; phenotype-to-proteome linking; phototagging; single-cell proteomics; tumor heterogeneity; ultrawide field-of-view optical microscope