bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒04‒24
twenty papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Methods Mol Biol. 2022 ;2486 3-17
      Proteomics plays a pivotal role in systems medicine, in which pharmacoproteomics and toxicoproteomics have been developed to address questions related to efficacy and toxicity of drugs. Mass spectrometry is the core technology for quantitative proteomics, providing the capabilities of identification and quantitation of thousands of proteins. The technology has been applied to biomarker discovery and understanding the mechanisms of drug action. Both stable isotope labeling of proteins or peptides and label-free approaches have been incorporated with multidimensional LC separation and tandem mass spectrometry (LC-MS/MS) to increase the coverage and depth of proteome analysis. A protocol of such an approach exemplified by dimethyl labeling in combination with 2D-LC-MS/MS is described. With further development of novel proteomic tools and increase in sample throughput, the full spectrum of mass spectrometry-based proteomic research will greatly advance systems medicine.
    Keywords:  Biomarker; Liquid chromatography; Mass spectrometry; Protein quantitation; Proteomics; Stable isotope labeling; Tandem MS
  2. Metabolites. 2022 Apr 07. pii: 333. [Epub ahead of print]12(4):
      The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.
    Keywords:  autoimmune disease; cardiovascular disease; eicosanoids; inflammation; lipid mediators; lipidomics; mass spectrometry; neurodegeneration; respiratory disease; special pro-resolving lipid mediators
  3. Metabolites. 2022 Apr 14. pii: 351. [Epub ahead of print]12(4):
      Though biallelic variants in SLC13A5 are known to cause severe encephalopathy, the mechanism of this disease is poorly understood. SLC13A5 protein deficiency reduces citrate transport into the cell. Downstream abnormalities in fatty acid synthesis and energy generation have been described, though biochemical signs of these perturbations are inconsistent across SLC13A5 deficiency patients. To investigate SLC13A5-related disorders, we performed untargeted metabolic analyses on the liver, brain, and serum from a Slc13a5-deficient mouse model. Metabolomic data were analyzed using the connect-the-dots (CTD) methodology and were compared to plasma and CSF metabolomics from SLC13A5-deficient patients. Mice homozygous for the Slc13a5tm1b/tm1b null allele had perturbations in fatty acids, bile acids, and energy metabolites in all tissues examined. Further analyses demonstrated that for several of these molecules, the ratio of their relative tissue concentrations differed widely in the knockout mouse, suggesting that deficiency of Slc13a5 impacts the biosynthesis and flux of metabolites between tissues. Similar findings were observed in patient biofluids, indicating altered transport and/or flux of molecules involved in energy, fatty acid, nucleotide, and bile acid metabolism. Deficiency of SLC13A5 likely causes a broader state of metabolic dysregulation than previously recognized, particularly regarding lipid synthesis, storage, and metabolism, supporting SLC13A5 deficiency as a lipid disorder.
    Keywords:  SLC13A5; SLC13A5 deficiency; bile acid metabolism; citrate transport; lipid synthesis; lipid utilization; liver-brain axis; untargeted metabolomics
  4. Metabolites. 2022 Apr 15. pii: 354. [Epub ahead of print]12(4):
      In targeted metabolomic analysis using liquid chromatography-multiple reaction monitoring-mass spectrometry (LC-MRM-MS), hundreds of MRMs are performed in a single run, yielding a large dataset containing thousands of chromatographic peaks. Automation tools for processing large MRM datasets have been reported, but a visual review of chromatograms is still critical, as real samples with biological matrices often cause complex chromatographic patterns owing to non-specific, insufficiently separated, isomeric, and isotopic components. Herein, we report the development of new software, TRACES, a lightweight chromatogram browser for MRM-based targeted LC-MS analysis. TRACES provides rapid access to all MRM chromatograms in a dataset, allowing users to start ad hoc data browsing without preparations such as loading compound libraries. As a special function of the software, we implemented a chromatogram-level deisotoping function that facilitates the identification of regions potentially affected by isotopic signals. Using MRM libraries containing precursor and product formulae, the algorithm reveals all possible isotopic interferences in the dataset and generates deisotoped chromatograms. To validate the deisotoping function in real applications, we analyzed mouse tissue phospholipids in which isotopic interference by molecules with different fatty-acyl unsaturation levels is known. TRACES successfully removed isotopic signals within the MRM chromatograms, helping users avoid inappropriate regions for integration.
    Keywords:  LC-MRM-MS; deisotoping; phospholipids; software; targeted lipidomics; targeted metabolomics
  5. Metabolites. 2022 Mar 30. pii: 305. [Epub ahead of print]12(4):
      This review presents an overview of the statistical methods on differential abundance (DA) analysis for mass spectrometry (MS)-based metabolomic data. MS has been widely used for metabolomic abundance profiling in biological samples. The high-throughput data produced by MS often contain a large fraction of zero values caused by the absence of certain metabolites and the technical detection limits of MS. Various statistical methods have been developed to characterize the zero-inflated metabolomic data and perform DA analysis, ranging from simple tests to more complex models including parametric, semi-parametric, and non-parametric approaches. In this article, we discuss and compare DA analysis methods regarding their assumptions and statistical modeling techniques.
    Keywords:  differential abundance; mass spectrometry; metabolomics; zero-inflated data
  6. Sports Med. 2022 Apr 23.
      In 1924, Otto Warburg asked "How does the metabolism of a growing tissue differ from that of a non-growing tissue?" Currently, we know that proliferating healthy and cancer cells reprogramme their metabolism. This typically includes increased glucose uptake, glycolytic flux and lactate synthesis. A key function of this reprogramming is to channel glycolytic intermediates and other metabolites into anabolic reactions such as nucleotide-RNA/DNA synthesis, amino acid-protein synthesis and the synthesis of, for example, acetyl and methyl groups for epigenetic modification. In this review, we discuss evidence that a hypertrophying muscle similarly takes up more glucose and reprogrammes its metabolism to channel energy metabolites into anabolic pathways. We specifically discuss the functions of the cancer-associated enzymes phosphoglycerate dehydrogenase and pyruvate kinase muscle 2 in skeletal muscle. In addition, we ask whether increased glucose uptake by a hypertrophying muscle explains why muscularity is often negatively associated with type 2 diabetes mellitus and obesity.
  7. JHEP Rep. 2022 May;4(5): 100477
      Background & Aims: Non-alcoholic fatty liver disease (NAFLD) is a progressive liver disease with potentially severe complications including cirrhosis and hepatocellular carcinoma. Previously, we have identified circulating lipid signatures associating with liver fat content and non-alcoholic steatohepatitis (NASH). Here, we develop a metabolomic map across the NAFLD spectrum, defining interconnected metabolic signatures of steatosis (non-alcoholic fatty liver, NASH, and fibrosis).Methods: We performed mass spectrometry analysis of molecular lipids and polar metabolites in serum samples from the European NAFLD Registry patients (n = 627), representing the full spectrum of NAFLD. Using various univariate, multivariate, and machine learning statistical approaches, we interrogated metabolites across 3 clinical perspectives: steatosis, NASH, and fibrosis.
    Results: Following generation of the NAFLD metabolic network, we identify 15 metabolites unique to steatosis, 18 to NASH, and 15 to fibrosis, with 27 common to all. We identified that progression from F2 to F3 fibrosis coincides with a key pathophysiological transition point in disease natural history, with n = 73 metabolites altered.
    Conclusions: Analysis of circulating metabolites provides important insights into the metabolic changes during NAFLD progression, revealing metabolic signatures across the NAFLD spectrum and features that are specific to NAFL, NASH, and fibrosis. The F2-F3 transition marks a critical metabolic transition point in NAFLD pathogenesis, with the data pointing to the pathophysiological importance of metabolic stress and specifically oxidative stress.
    Clinical Trials registration: The study is registered at (NCT04442334).
    Lay summary: Non-alcoholic fatty liver disease is characterised by the build-up of fat in the liver, which progresses to liver dysfunction, scarring, and irreversible liver failure, and is markedly increasing in its prevalence worldwide. Here, we measured lipids and other small molecules (metabolites) in the blood with the aim of providing a comprehensive molecular overview of fat build-up, liver fibrosis, and diagnosed severity. We identify a key metabolic 'watershed' in the progression of liver damage, separating severe disease from mild, and show that specific lipid and metabolite profiles can help distinguish and/or define these cases.
    Keywords:  2-HB, 2-hydroxybutanoic acid; 3-HB, 3-hydroxybutanoic acid; ALT, alanine aminotransferase; AST, aspartate aminotransferase; CE, cholesterol ester; Cer, ceramide; FFA, free fatty acid; FLIP, Fatty Liver Inhibition of Progression; Fibrosis; GC, gas chromatography; HCC, hepatocellular carcinoma; HSD, honest significant difference; LC, lipid cluster; LDL, low-density lipoprotein; LM, lipid and metabolite; LMC, lipid, metabolite, and clinical variable; LPC, lysophosphatidylcholine; Lipidomics; Mass spectrometry; Metabolomics; NAFL, non-alcoholic fatty liver; NAFLD, non-alcoholic fatty liver disease; NAS, NASH activity score; NASH, non-alcoholic steatohepatitis; NIDDK NASH-CRN, National Institute of Digestive Diseases and Kidney NASH Clinical Research Network; NRR, non-rejection rate; Non-alcoholic steatohepatitis; PC(O), ether PC; PC, phosphatidylcholine; PCA, principal component analysis; PE, phosphatidylethanolamine; QTOFMS, quadrupole-time-of-flight mass spectrometry; ROC, receiving operator characteristic; SAF, steatosis, activity, and fibrosis; SM, sphingomyelin; T2DM, type 2 diabetes mellitus; TG, triacylglycerol; UHPLC, ultrahigh-performance liquid chromatography
  8. Mol Reprod Dev. 2022 Apr 22.
      Conceptus elongation and early placentation involve growth and remodeling that requires proliferation and migration of cells. This demands conceptuses expend energy before establishment of a placenta connection and when they are dependent upon components of histotroph secreted or transported into the uterine lumen from the uterus. Glucose and fructose, as well as many amino acids (including arginine, aspartate, glutamine, glutamate, glycine, methionine, and serine), increase in the uterine lumen during the peri-implantation period. Glucose and fructose enter cells via their transporters, SLC2A, SLC2A3, and SLC2A8, and amino acids enter the cells via specific transporters that are expressed by the conceptus trophectoderm. However, porcine conceptuses develop rapidly through extensive cellular proliferation and migration as they elongate and attach to the uterine wall resulting in increased metabolic demands. Therefore, coordination of multiple metabolic biosynthetic pathways is an essential aspect of conceptus development. Oxidative metabolism primarily occurs through the tricarboxylic acid (TCA) cycle and the electron transport chain, but proliferating and migrating cells, like the trophectoderm of pigs, enhance aerobic glycolysis. The glycolytic intermediates from glucose can then be shunted into the pentose phosphate pathway and one-carbon metabolism for the de novo synthesis of nucleotides. A result of aerobic glycolysis is limited availability of pyruvate for maintaining the TCA cycle, and trophectoderm cells likely replenish TCA cycle metabolites primarily through glutaminolysis to convert glutamine into TCA cycle intermediates. The synthesis of ATP, nucleotides, amino acids, and fatty acids through these biosynthetic pathways is essential to support elongation, migration, hormone synthesis, implantation, and early placental development of conceptuses.
    Keywords:  conceptus; fructose; glucose; metabolism; pig; uterus
  9. Metabolites. 2022 Apr 15. pii: 357. [Epub ahead of print]12(4):
      Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.
    Keywords:  metabolic pathways summary; metabolomics; metabolomics analysis tools; multi-omics integration algorithms
  10. Molecules. 2022 Apr 09. pii: 2427. [Epub ahead of print]27(8):
      Blood levels of the vitamin D3 (D3) metabolites 25-hydroxyvitamin D3 (25(OH)D3), 24R,25-dihydroxyvitamin D3, and 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3) are recognized indicators for the diagnosis of bone metabolism-related diseases, D3 deficiency-related diseases, and hypercalcemia, and are generally measured by liquid-chromatography tandem mass spectrometry (LC-MS/MS) using an isotope dilution method. However, other D3 metabolites, such as 20-hydroxyvitamin D3 and lactone D3, also show interesting biological activities and stable isotope-labeled derivatives are required for LC-MS/MS analysis of their concentrations in serum. Here, we describe a versatile synthesis of deuterium-labeled D3 metabolites using A-ring synthons containing three deuterium atoms. Deuterium-labeled 25(OH)D3 (2), 25(OH)D3-23,26-lactone (6), and 1,25(OH)2D3-23,26-lactone (7) were synthesized, and successfully applied as internal standards for the measurement of these compounds in pooled human serum. This is the first quantification of 1,25(OH)2D3-23,26-lactone (7) in human serum.
    Keywords:  deuterium labeling; liquid-chromatography tandem mass spectrometry; measurement of vitamin D metabolites in blood; vitamin D
  11. Molecules. 2022 Apr 08. pii: 2411. [Epub ahead of print]27(8):
      Mass Spectrometry (MS) allows the analysis of proteins and peptides through a variety of methods, such as Electrospray Ionization-Mass Spectrometry (ESI-MS) or Matrix-Assisted Laser Desorption Ionization-Mass Spectrometry (MALDI-MS). These methods allow identification of the mass of a protein or a peptide as intact molecules or the identification of a protein through peptide-mass fingerprinting generated upon enzymatic digestion. Tandem mass spectrometry (MS/MS) allows the fragmentation of proteins and peptides to determine the amino acid sequence of proteins (top-down and middle-down proteomics) and peptides (bottom-up proteomics). Furthermore, tandem mass spectrometry also allows the identification of post-translational modifications (PTMs) of proteins and peptides. Here, we discuss the application of MS/MS in biomedical research, indicating specific examples for the identification of proteins or peptides and their PTMs as relevant biomarkers for diagnostic and therapy.
    Keywords:  biomarkers; biomedical research; proteomics; tandem mass spectrometry (MS/MS)
  12. Bioinformatics. 2022 Apr 20. pii: btac280. [Epub ahead of print]
      MOTIVATION: Tandem mass tag (TMT)-based tandem mass spectrometry (MS/MS) has become the method of choice for the quantification of post-translational modifications in complex mixtures. Many cancer proteogenomic studies have highlighted the importance of large-scale phosphopeptide quantification coupled with TMT labeling. Herein, we propose a predicted Spectral DataBase (pSDB) search strategy called Deephos that can improve both sensitivity and specificity in identifying MS/MS spectra of TMT-labeled phosphopeptides.RESULTS: With deep learning-based fragment ion prediction, we compiled a pSDB of TMT-labeled phosphopeptides generated from ∼8,000 human phosphoproteins annotated in UniProt. Deep learning could successfully recognize the fragmentation patterns altered by both TMT labeling and phosphorylation. In addition, we discuss the decoy spectra for false discovery rate (FDR) estimation in the pSDB search. We show that FDR could be inaccurately estimated by the existing decoy spectra generation methods and propose an innovative method to generate decoy spectra for more accurate FDR estimation. The utilities of Deephos were demonstrated in multi-stage analyses (coupled with database searches) of glioblastoma, acute myeloid leukemia, and breast cancer phosphoproteomes.
    AVAILABILITY: Deephos pSDB and the search software are available at
  13. Metabolites. 2022 Mar 29. pii: 302. [Epub ahead of print]12(4):
      The dual-sugar intestinal permeability test is a commonly used test to assess changes in gut barrier function. However, it does not identify functional changes and the exact mechanism of damage caused by the increased intestinal permeability. This study aims to explore the application of untargeted metabolomics and lipidomics to identify markers of increased intestinal permeability. Fifty fasting male participants (18-50 years) attended a single visit to conduct the following procedures: assessment of anthropometric measures, assessment of gastrointestinal symptoms, intestinal permeability test, and assessment of blood samples 90 min post-administration of the intestinal permeability test. Rhamnose and lactulose were analysed using gas chromatography-mass spectrometry (GC-MS). Untargeted polar metabolites and lipidomics were assessed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF MS). There was an elevated lactulose/rhamnose ratio in 27 subjects, indicating increased permeability compared to the remaining 23 control subjects. There were no significant differences between groups in characteristics such as age, body mass index (BMI), weight, height, and waist conference. Fourteen metabolites from the targeted metabolomics data were identified as statistically significant in the plasma samples from intestinal permeability subjects. The untargeted metabolomics and lipidomics analyses yielded fifteen and fifty-one statistically significant features, respectively. Individuals with slightly elevated intestinal permeability had altered energy, nucleotide, and amino acid metabolism, in addition to increased glutamine levels. Whether these biomarkers may be used to predict the early onset of leaky gut warrants further investigation.
    Keywords:  intestinal permeability; lactulose-to-rhamnose ratio; lipidomics; metabolomics
  14. Annu Rev Genomics Hum Genet. 2022 Apr 19.
      Proteins are the molecular effectors of the information encoded in the genome. Proteomics aims at understanding the molecular functions of proteins in their biological context. In contrast to transcriptomics and genomics, the study of proteomes provides deeper insight into the dynamic regulatory layers encoded at the protein level, such as posttranslational modifications, subcellular localization, cell signaling, and protein-protein interactions. Currently, mass spectrometry (MS)-based proteomics is the technology of choice for studying proteomes at a system-wide scale, contributing to clinical biomarker discovery and fundamental molecular biology. MS technologies are continuously being developed to fulfill the requirements of speed, resolution, and quantitative accuracy, enabling the acquisition of comprehensive proteomes. In this review, we present how MS technology and acquisition methods have evolved to meet the requirements of cutting-edge proteomics research, which is describing the human proteome and its dynamic posttranslational modifications with unprecedented depth. Finally, we provide a perspective on studying proteomes at single-cell resolution. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see for revised estimates.
  15. J Chromatogr A. 2022 Mar 31. pii: S0021-9673(22)00211-4. [Epub ahead of print]1672 463013
      Metabolic phenotyping studies using mouse liver extracts as a model, performed on a novel zwitterionic HILIC UHPLC column, which is based on ethylene-bridged hybrid organic/inorganic particles bonded with sulfobetaine groups and packed into column hardware modified with hybrid surface technology are reported. Initially the chromatographic performance was evaluated under different mobile phase conditions using selected metabolite standards. Following optimization of the chromatographic conditions for 88 hydrophilic metabolites both targeted and untargeted profiling analyses were performed on tissue extracts using LC-MS/MS and LC-TOF/MS, respectively. Chromatographic efficiency parameters such as peak resolution, peak shapes, selectivity and precision in retention and peak areas as well as characteristics that are critical for metabolic profiling analysis such as metabolite coverage and retention time distribution were assessed. The hybrid zwitterionic column exhibited efficient chromatographic separations providing analysis of ca 80 hydrophilic metabolites from different chemical classes and polarities. Utilizing a one-dimensional separation both targeted and untargeted profiling provided comprehensive metabolic signatures that enabled the acquisition of the metabolic phenotypes of the tissue extracts.
    Keywords:  Hydrophilic interaction chromatography; Metabolic phenotyping; Metabolomics; Multitargeted assay; Polar metabolites; Zwitterionic phases
  16. J Agric Food Chem. 2022 Apr 19.
      A metabolomic ratio rule-based classification method was developed and programmed for automated metabolite profiling and differentiation of four major cinnamon species using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). The computational program identifies key cinnamon metabolites, including proanthocyanidins, cinnamaldehyde, and coumarin, from test samples through LC-MS data processing and assigns cinnamon species by critical metabolite ratios using a stepwise classification strategy. Further, 100% classification accuracy was achieved on the training sample set through critical ratio optimization, and over 95% accuracy was achieved on the validation sample set. The proposed cinnamon classification method exhibited superior accuracy compared to the metabolomic-based PLS-DA modeling method and offered great value for the authentication of cinnamon samples and evaluation of their potential health benefits.
    Keywords:  Cinnamon; authentication; classification; mass spectrometry; proanthocyanidins
  17. Front Immunol. 2022 ;13 861559
      Cancer cells, as well as surrounding stromal and inflammatory cells, form an inflammatory tumor microenvironment (TME) to promote all stages of carcinogenesis. As an emerging post-translational modification (PTM) of serine and threonine residues of proteins, O-linked-N-Acetylglucosaminylation (O-GlcNAcylation) regulates diverse cancer-relevant processes, such as signal transduction, transcription, cell division, metabolism and cytoskeletal regulation. Recent studies suggest that O-GlcNAcylation regulates the development, maturation and functions of immune cells. However, the role of protein O-GlcNAcylation in cancer-associated inflammation has been less explored. This review summarizes the current understanding of the influence of protein O-GlcNAcylation on cancer-associated inflammation and the mechanisms whereby O-GlcNAc-mediated inflammation regulates tumor progression. This will provide a theoretical basis for further development of anti-cancer therapies.
    Keywords:  HBP pathway; O-GlcNAcylation; TME (tumor microenvironment); cancer inflammation; post-translational modification (PTM)
  18. World J Stem Cells. 2022 Feb 26. 14(2): 146-162
      Cancer stem cells (CSCs) comprise a subpopulation of cancer cells with stem cell properties, which exhibit the characteristics of high tumorigenicity, self-renewal, and tumor initiation and are associated with the occurrence, metastasis, therapy resistance, and relapse of cancer. Compared with differentiated cells, CSCs have unique metabolic characteristics, and metabolic reprogramming contributes to the self-renewal and maintenance of stem cells. It has been reported that CSCs are highly dependent on lipid metabolism to maintain stemness and satisfy the requirements of biosynthesis and energy metabolism. In this review, we demonstrate that lipid anabolism alterations promote the survival of CSCs, including de novo lipogenesis, lipid desaturation, and cholesterol synthesis. In addition, we also emphasize the molecular mechanism underlying the relationship between lipid synthesis and stem cell survival, the signal trans-duction pathways involved, and the application prospect of lipid synthesis reprogramming in CSC therapy. It is demonstrated that the dependence on lipid synthesis makes targeting of lipid synthesis metabolism a promising therapeutic strategy for eliminating CSCs. Targeting key molecules in lipid synthesis will play an important role in anti-CSC therapy.
    Keywords:  Anti-cancer therapy; Cancer stem cells; Lipid anabolism; Lipid synthesis; Stem cell survival
  19. Biomolecules. 2022 Apr 14. pii: 580. [Epub ahead of print]12(4):
      In recent years, an increasingly more in depth understanding of tumor metabolism in tumorigenesis, tumor growth, metastasis, and prognosis has been achieved. The broad heterogeneity in tumor tissue is the critical factor affecting the outcome of tumor treatment. Metabolic heterogeneity is not only found in tumor cells but also in their surrounding immune and stromal cells; for example, many suppressor cells, such as tumor-associated macrophages (TAMs), myeloid-derived suppressor cells (MDSCs), and tumor-associated T-lymphocytes. Abnormalities in metabolism often lead to short survival or resistance to antitumor therapy, e.g., chemotherapy, radiotherapy, targeted therapy, and immunotherapy. Using the metabolic characteristics of the tumor microenvironment to identify and treat cancer has become a great research hotspot. This review systematically addresses the impacts of metabolism on tumor cells and effector cells and represents recent research advances of metabolic effects on other cells in the tumor microenvironment. Finally, we introduce some applications of metabolic features in clinical oncology.
    Keywords:  fatty acid metabolism; glutaminolysis; glycolysis; immunotherapy; metabolism; tumor microenvironment
  20. Analyst. 2022 Apr 20.
      Background: Abnormal lipid metabolism affects the regulation of tumor progression, though use of serum lipids and sphingolipids for disease progression identification is uncertain. Methods: Serum samples from 51 healthy volunteers and 76 patients were collected and analyzed by liquid chromatography tandem mass spectrometry. Results: Levels of serum total cholesterol and high-density lipoprotein were significantly lower in colorectal cancer patients. Multivariate analysis demonstrated distinct sphingolipid profiles between healthy individuals and patients. Of 106 sphingolipids, 15 metabolites that showed statistical significance were selected, and receiver operating characteristic analysis of these metabolites yielded an area under the curve of 0.868 to 0.9 by machine learning algorithms for distinguishing colorectal cancer from a healthy status. Conclusions: Healthy individuals, polyps patients and colorectal cancer patients have different serum sphingolipid signatures. Serum sphingolipids might be used as biomarkers for early detection or prediction of colorectal cancer.