bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2020‒10‒04
twenty papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh

  1. Protein Cell. 2020 Oct 01.
      The cystine/glutamate antiporter SLC7A11 (also commonly known as xCT) functions to import cystine for glutathione biosynthesis and antioxidant defense and is overexpressed in multiple human cancers. Recent studies revealed that SLC7A11 overexpression promotes tumor growth partly through suppressing ferroptosis, a form of regulated cell death induced by excessive lipid peroxidation. However, cancer cells with high expression of SLC7A11 (SLC7A11high) also have to endure the significant cost associated with SLC7A11-mediated metabolic reprogramming, leading to glucose- and glutamine-dependency in SLC7A11high cancer cells, which presents potential metabolic vulnerabilities for therapeutic targeting in SLC7A11high cancer. In this review, we summarize diverse regulatory mechanisms of SLC7A11 in cancer, discuss ferroptosis-dependent and -independent functions of SLC7A11 in promoting tumor development, explore the mechanistic basis of SLC7A11-induced nutrient dependency in cancer cells, and conceptualize therapeutic strategies to target SLC7A11 in cancer treatment. This review will provide the foundation for further understanding SLC7A11 in ferroptosis, nutrient dependency, and tumor biology and for developing novel effective cancer therapies.
    Keywords:  SLC7A11; cancer therapy; cysteine; cystine; ferroptosis; nutrient dependency; xCT
  2. MethodsX. 2020 ;7 101055
      Evidence of the involvement of epigenetics in pathologies such as cancer, diabetes, and neurodegeneration has increased global interest in epigenetic modifications. For nearly thirty years, it has been known that cancer cells exhibit abnormal DNA methylation patterns. In contrast, the large-scale analysis of histone post-translational modifications (hPTMs) has lagged behind because classically, histone modification analysis has relied on site specific antibody-based techniques. Mass spectrometry (MS) is a technique that holds the promise to picture the histone code comprehensively in a single experiment. Therefore, we developed an MS-based method that is capable of tracking all possible hPTMs in an untargeted approach. In this way, trends in single and combinatorial hPTMs can be reported and enable prediction of the epigenetic toxicity of compounds. Moreover, this method is based on the use of human cells to provide preliminary data, thereby omitting the need to sacrifice laboratory animals. Improving the workflow and the user-friendliness in order to become a high throughput, easily applicable, toxicological screening assay is an ongoing effort. Still, this novel toxicoepigenetic assay and the data it generates holds great potential for, among others, pharmaceutical industry, food science, clinical diagnostics and, environmental toxicity screening. •There is a growing interest in epigenetic modifications, and more specifically in histone post-translational modifications (hPTMs).•We describe an MS-based workflow that is capable of tracking all possible hPTMs in an untargeted approach that makes use of human cells.•Improving the workflow and the user-friendliness in order to become a high throughput, easily applicable, toxicological screening assay is an ongoing effort.
    Keywords:  AUC, area under the curve; DDA, data-dependent acquisition; DIA, data-independent acquisition; DTT, dithiothreitol; Drug safety; FA, formic acid; FDR, false discovery rate; GABA, gamma-aminobutyric acid; GRX, gingisrex; HAT, histone acetyltransferase; HDACi, histone deacetylase inhibitor; HLB, hypotonic lysis buffer; HPLC, high-performance liquid chromatography; Histone post-translational modifications; K, Lysine; LC-MS/MS; M, Methionine; MS, Mass spectrometry; MS/MS, tandem mass spectrometry; N, asparagine; PBS, phosphate buffered saline; Pharmacoepigenetics; Proteomics; Q, glutamine; R, arginine; RA, relative abundance; RP, reversed phase; RT, room temperature; S, serine; SWATH, sequential window acquisition of all theoretical fragment ion spectra; T, threonine; TEAB, triethylammonium bicarbonate; Toxicoepigenetics; VPA, valproic acid; Y, tyrosine; hESC, human embryonic stem cell; hPTM, histone post-translational modification
  3. Mass Spectrom Rev. 2020 Sep 30.
      Lipid research is attracting more and more attention as various key roles and novel biological functions of lipids have been demonstrated and discovered in the organism. Mass spectrometry (MS)-based lipidomics approaches are the most powerful and effective tools for analysis of cellular lipidomes with very high sensitivity and specificity. However, the artifacts generated from in-source fragmentation are always present in all kinds of ion sources, even soft ionization techniques (i.e., electrospray ionization and matrix-assisted laser desorption/ionization [MALDI]). These artifacts can cause many problems for lipidomics, especially when the fragment ions correspond to/are isomeric species of other endogenous lipid species in complex biological samples. These commonly observed artifacts could lead to misannotation, false identification, and consequently, incorrect attribution of phenotypes, and will have negative impact on any MS-based lipidomics research including but not limited to biomarker discovery, drug development, etc. Liquid chromatography-MS, shotgun lipidomics, and MALDI-MS imaging are three representative lipidomics approaches in which ion source-generated artifacts are all manifested and are comprehensively summarized in this article. The strategies on how to avoid/reduce the artifacts of in-source fragmentation on lipidomics analysis are also discussed in detail. We believe that with the recognition and avoidance of ion source-generated artifacts, MS-based lipidomics approaches will provide better accuracy on comprehensive analysis of biological samples and will make greater contribution to the research on metabolism and translational/precision medicine (collectively termed functional lipidomics). © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
    Keywords:  MALDI-MSI; artifacts; functional lipidomics; in-source fragmentation; lipidomics; mass spectrometry
  4. Cancer Metastasis Rev. 2020 Oct 02.
      Environment surrounding tumours are now recognized to play an important role in tumour development and progression. Among the cells found in the tumour environment, adipocytes from adipose tissue establish a vicious cycle with cancer cells to promote cancer survival, proliferation, metastasis and treatment resistance. This cycle is particularly of interest in the context of obesity, which has been found as a cancer risk factor. Cancers cells can reprogram adipocyte physiology leading to an "activated" phenotype characterized by delipidation and secretion of inflammatory adipokines. The adipocyte secretions then influence tumour growth and metastasis which has been mainly attributed to interleukin 6 (IL-6) or leptin but also to the release of fatty acids which are able to change cancer cell metabolism and signalling pathways. The aim of this review is to report recent advances in the understanding of the molecular mechanisms linking adipose tissue with cancer progression in order to propose new therapeutic strategies based on pharmacological or nutritional intervention.
    Keywords:  Adipocyte; Adipokines; Cancer; Exosome; Fatty acid; Metabolism
  5. Cancer Metab. 2020 ;8 22
      Abstract: Background: Rewiring of metabolism induced by oncogenic K-Ras in cancer cells involves both glucose and glutamine utilization sustaining enhanced, unrestricted growth. The development of effective anti-cancer treatments targeting metabolism may be facilitated by the identification and rational combinatorial targeting of metabolic pathways.
    Methods: We performed mass spectrometric metabolomics analysis in vitro and in vivo experiments to evaluate the efficacy of drugs and identify metabolic connectivity.
    Results: We show that K-Ras-mutant lung and colon cancer cells exhibit a distinct metabolic rewiring, the latter being more dependent on respiration. Combined treatment with the glutaminase inhibitor CB-839 and the PI3K/aldolase inhibitor NVP-BKM120 more consistently reduces cell growth of tumor xenografts. Maximal growth inhibition correlates with the disruption of redox homeostasis, involving loss of reduced glutathione regeneration, redox cofactors, and a decreased connectivity among metabolites primarily involved in nucleic acid metabolism.
    Conclusions: Our findings open the way to develop metabolic connectivity profiling as a tool for a selective strategy of combined drug repositioning in precision oncology.
    Keywords:  Combinatorial drug treatment; Glutamine; Glycolysis; Metabolic cancer therapy; Metabolic connectivity; Metabolic rewiring; Metabolic signature; Precision oncology
  6. Mol Cell Proteomics. 2020 Sep 29. pii: mcp.RA120.002012. [Epub ahead of print]
      Endometrial carcinoma (EC) is the most common gynecologic malignancy in the United States, with limited effective targeted therapies. Endometrial tumors exhibit frequent alterations in protein kinases, yet only a small fraction of the kinome has been therapeutically explored. To identify kinase therapeutic avenues for EC, we profiled the kinome of endometrial tumors and normal endometrial tissues using Multiplexed Inhibitor Beads and Mass Spectrometry (MIB-MS). Our proteomics analysis identified a network of kinases overexpressed in tumors, including Serine/Arginine-Rich Splicing Factor Kinase 1 (SRPK1). Immunohistochemical (IHC) analysis of endometrial tumors confirmed MIB-MS findings and showed SRPK1 protein levels were highly expressed in endometrioid and uterine serous cancer (USC) histological subtypes. Moreover, querying large-scale genomics studies of EC tumors revealed high expression of SRPK1 correlated with poor survival. Loss-of-function studies targeting SRPK1 in an established USC cell line demonstrated SRPK1 was integral for RNA splicing, as well as cell cycle progression and survival under nutrient deficient conditions. Profiling of USC cells identified a compensatory response to SRPK1 inhibition that involved EGFR and the upregulation of IGF1R and downstream AKT signaling. Co-targeting SRPK1 and EGFR or IGF1R synergistically enhanced growth inhibition in serous and endometrioid cell lines, representing a promising combination therapy for EC.
    Keywords:  Affinity proteomics; Cancer biomarker(s); Combination Therapies; Endometrial Carcinoma; Kinases*; Kinome; Pathway Analysis; Splicing; Therapeutic targets*; Tissue Proteomics
  7. Eur Respir Rev. 2020 Sep 30. pii: 200134. [Epub ahead of print]29(157):
      Lung cancer is the leading cause of death from cancer worldwide. Recent studies demonstrated that the tumour microenvironment (TME) is pivotal for tumour progression, providing multiple targeting opportunities for therapeutic strategies. As one of the most abundant stromal cell types in the TME, tumour-associated macrophages (TAMs) exhibit high plasticity. Malignant cells alter their metabolic profiles to adapt to the limited availability of oxygen and nutrients in the TME, resulting in functional alteration of TAMs. The metabolic features of TAMs are strongly associated with their functional plasticity, which further impacts metabolic profiling in the TME and contributes to tumourigenesis and progression. Here, we review the functional determination of the TME by TAM metabolic alterations, including glycolysis as well as fatty acid and amino acid metabolism, which in turn are influenced by environmental changes. Additionally, we discuss metabolic reprogramming of TAMs to a tumouricidal phenotype as a potential antitumoural therapeutic strategy.
  8. Anal Bioanal Chem. 2020 Sep 29.
      To better understand cell-to-cell heterogeneity, advanced analytical tools are in a growing demand for elucidating chemical compositions of each cell within a population. However, the progress of single-cell chemical analysis has been restrained by the limitations of small cell volumes and minute cellular concentrations. Here, we present a rapid and sensitive method for investigating the lipid profiles of isolated single cells using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS). In this work, HeLa cells were dispersed onto a glass slide, and the cellular contents were ionized by IR-MALDESI and measured using a Q-Exactive HF-X mass spectrometer. Importantly, this approach does not require extraction and/or enrichment of analytes prior to MS analysis. Using this approach, 45 distinct lipid species, predominantly phospholipids, were detected and putatively annotated from the single HeLa cells. The proof-of-concept study demonstrates the feasibility and efficacy of IR-MALDESI-MS for rapid lipidomic profiling of single cells, which provides an important basis for future work on differentiation between normal and diseased cells at various developmental states, which can offer new insights into cellular metabolic pathways and pathological processes. Although not yet accomplished, we believe this approach can be readily used as an assessment tool to compare the number of identified species during source evolution and method optimization (intra-laboratory), and also disclose the complementary nature of different direct analytical approaches for the coverage of different types of endogenous analytes (inter-laboratory).Graphical abstract.
    Keywords:  IR-MALDESI; Lipidome; Mass spectrometry; Orbitrap; Single-cell analysis
  9. Mol Cancer. 2020 10 01. 19(1): 146
      Metabolic reprogramming, including enhanced biosynthesis of macromolecules, altered energy metabolism, and maintenance of redox homeostasis, is considered a hallmark of cancer, sustaining cancer cell growth. Multiple signaling pathways, transcription factors and metabolic enzymes participate in the modulation of cancer metabolism and thus, metabolic reprogramming is a highly complex process. Recent studies have observed that ubiquitination and deubiquitination are involved in the regulation of metabolic reprogramming in cancer cells. As one of the most important type of post-translational modifications, ubiquitination is a multistep enzymatic process, involved in diverse cellular biological activities. Dysregulation of ubiquitination and deubiquitination contributes to various disease, including cancer. Here, we discuss the role of ubiquitination and deubiquitination in the regulation of cancer metabolism, which is aimed at highlighting the importance of this post-translational modification in metabolic reprogramming and supporting the development of new therapeutic approaches for cancer treatment.
    Keywords:  Cancer; Deubiquitination; Metabolic reprogramming; Ubiquitination
  10. Mol Cell. 2020 Sep 22. pii: S1097-2765(20)30614-6. [Epub ahead of print]
      Metabolism reprogramming is critical for both cancer progression and effective immune responses in the tumor microenvironment. Amino acid metabolism in different cells and their cross-talk shape tumor immunity and therapy efficacy in patients with cancer. In this review, we focus on multiple amino acids and their transporters, solute carrier (SLC) members. We discuss their involvement in regulation of immune responses in the tumor microenvironment and assess their associations with cancer immunotherapy, chemotherapy, and radiation therapy, and we review their potential as targets for cancer therapy. We stress the necessity to understand individual amino acids and their transporters in different cell subsets, the molecular intersection between amino acid metabolism, and effective T cell immunity and its relevance in cancer therapies.
    Keywords:  CD8(+) T cell; amino acid; cancer; checkpoint blockade; immunotherapy; metabolism; solute carriers
  11. Lab Invest. 2020 Sep 29.
      Metabolic flux analysis (MFA) aims at revealing the metabolic reaction rates in a complex biochemical network. To do so, MFA uses the input of stable isotope labeling patterns of the intracellular metabolites. Elementary metabolic unit (EMU) is the computational framework to simulate the metabolite labeling patterns in a network, which was originally designed for simulating mass isotopomer distributions (MIDs) at the MS1 level. Recently, the EMU framework is expanded to simulate tandem mass spectrometry data. Tandem mass spectrometry has emerged as a new experimental approach to provide information on the positional isotope labeling of metabolites and therefore greatly improves the precision of MFA. In this review, we will discuss the new EMU framework that can accommodate the tandem mass isotopomer distributions (TMIDs) data. We will also analyze the improvement on the MFA precision by using TMID. Our analysis shows that combining the MIDs of the parent and daughter ions and the TMID for the MFA is more powerful than using TMID alone.
  12. Adv Sci (Weinh). 2020 Sep;7(18): 2001388
      Tumors reprogram their metabolic pathways to meet the bioenergetic and biosynthetic demands of cancer cells. These reprogrammed activities are now recognized as the hallmarks of cancer, which not only provide cancer cells with unrestricted proliferative and metastatic potentials, but also strengthen their resistance against stress conditions and therapeutic challenges. Although recent progress in nanomedicine has largely promoted the developments of various therapeutic modalities, such as photodynamic therapy, photothermal therapy, nanocatalytic therapy, tumor-starving/suffocating therapy, etc., the therapeutic efficacies of nanomedicines are still not high enough to achieve satisfactory tumor-suppressing effects. Therefore, researchers are obliged to look back to the essence of cancer cell biology, such as metabolism, for tailoring a proper therapeutic regimen. In this work, the characteristic metabolic pathways of cancer cells, such as aerobic respiration, glycolysis, autophagy, glutaminolysis, etc. are reviewed, to summarize the very recent advances in the smart design of nanomedicines that can regulate tumor metabolism for enhancing conventional therapeutic modalities. The underlying chemistry of these nanomedicines by which tumor metabolism is harnessed, is also discussed in a comprehensive manner. It is expected that by harnessing tumor metabolism cancer nanotherapeutics will be substantially improved in the future.
    Keywords:  cancer; material chemistry; metabolism regulation; nanomedicine; synergistic therapy
  13. Lipids Health Dis. 2020 Sep 30. 19(1): 214
      The process of autophagy is integral to cellular function. In this process, proteins, organelles, and metabolites are engulfed in a lipid vesicle and trafficked to a lysosome for degradation. Its central role in protein and organelle homeostasis has piqued interest for autophagy dysfunction as a driver of pathology for a number of diseases including cancer, muscular disorders, neurological disorders, and non-alcoholic fatty liver disease. For much of its history, the study of autophagy has centered around proteins, however, due to advances in mass spectrometry and refined methodologies, the role of lipids in this essential cellular process has become more apparent. This review discusses the diverse endogenous lipid compounds shown to mediate autophagy. Downstream lipid signaling pathways are also reviewed in the context of autophagy regulation. Specific focus is placed upon the Mammalian Target of Rapamycin (mTOR) and Peroxisome Proliferator-Activated Receptor (PPAR) signaling pathways as integration hubs for lipid regulation of autophagy.
    Keywords:  Autophagy; Fatty acids; Lipids; Mammalian target of rapamycin; Peroxisome proliferator-activated receptor; Phospholipids; Sphingolipids
  14. Amino Acids. 2020 Sep 29.
      Creatine is an amino acid derivative synthesized from arginine, glycine and methionine. It serves as the substrate for the creatine kinase system, which is vital for maintaining ATP levels in tissues with high and fluctuating energy demand. There exists evidence that the creatine kinase system operates in both the endometrial and myometrial layers of the uterus. While use and regulation of this system in the uterus are not well understood, it is likely to be important given uterine tissues undergo phases of increased energy demand during certain stages of the female reproductive cycle, pregnancy, and parturition. This review discusses known adaptations of creatine metabolism in the uterus during the reproductive cycle (both estrous and menstrual), pregnancy and parturition, highlighting possible links to fertility and the existing knowledge gaps. Specifically, we discuss the adaptations and regulation of uterine creatine metabolite levels, cell creatine transport, de novo creatine synthesis, and creatine kinase expression in the various layers and cell types of the uterus. Finally, we discuss the effects of dietary creatine on uterine metabolism. In summary, there is growing evidence that creatine metabolism is up-regulated in uterine tissues during phases where energy demand is increased. While it remains unclear how important these adaptations are in the maintenance of healthy uterine function, furthering our understanding of uterine creatine metabolism may uncover strategies to combat poor embryo implantation and failure to conceive, as well as enhancing uterine contractile performance during labor.
    Keywords:  Creatine; Female reproductive cycle; Phosphocreatine; Pregnancy; Uterus
  15. Mol Cell Proteomics. 2020 Sep 30. pii: mcp.TIR120.002061. [Epub ahead of print]
      Over the past decade, modern methods of mass spectrometry (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. While MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem mass spectrometry (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC-MS measurements. Peptide masses are then extracted from MS1 data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient - less than two minutes per sample - and has been successfully tested by a test set of 39 LC-MS1 peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.
    Keywords:  Bacteria; Bioinformatics software; Diagnostic; Identification of Microorganisms; LC-MS1; Mass Spectrometry; Microbiology
  16. J Biomed Res. 2020 Aug 06. 1-11
      There is growing evidence that cellular metabolism can directly participate in epigenetic dynamics and consequently modulate gene expression. However, the role of metabolites in activating the key gene regulatory network for specialization of germ cell lineage remains largely unknown. Here, we identified some cellular metabolites with significant changes by untargeted metabolomics between mouse epiblast-like cells (EpiLCs) and primordial germ cell-like cells (PGCLCs). More importantly, we found that inhibition of glutaminolysis by bis-2- (5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide (BPTES) impeded PGCLC specialization, but the impediment could be rescued by addition of α-ketoglutarate (αKG), the intermediate metabolite of oxidative phosphorylation and glutaminolysis. Moreover, adding αKG alone to the PGCLC medium accelerated the PGCLC specialization through promoting H3K27me3 demethylation. Thus, our study reveals the importance of metabolite αKG in the germ cell fate determination and highlights the essential role of cellular metabolism in shaping the cell identities through epigenetic events.
    Keywords:  cellular metabolism; epigenome; primordial germ cells; α-ketoglutarate
  17. Biomolecules. 2020 Sep 26. pii: E1370. [Epub ahead of print]10(10):
      Glutamine is a non-essential amino acid that plays a key role in the metabolism of proliferating cells including neoplastic cells. In the central nervous system (CNS), glutamine metabolism is particularly relevant, because the glutamine-glutamate cycle is a way of controlling the production of glutamate-derived neurotransmitters by tightly regulating the bioavailability of the amino acids in a neuron-astrocyte metabolic symbiosis-dependent manner. Glutamine-related metabolic adjustments have been reported in several CNS malignancies including malignant gliomas that are considered 'glutamine addicted'. In these tumors, glutamine becomes an essential amino acid preferentially used in energy and biomass production including glutathione (GSH) generation, which is crucial in oxidative stress control. Therefore, in this review, we will highlight the metabolic remodeling that gliomas undergo, focusing on glutamine metabolism. We will address some therapeutic regimens including novel research attempts to target glutamine metabolism and a brief update of diagnosis strategies that take advantage of this altered profile. A better understanding of malignant glioma cell metabolism will help in the identification of new molecular targets and the design of new therapies.
    Keywords:  CNS; cancer metabolism; glutamine-glutamate cycle; malignant gliomas; metabolic adaptation; new metabolic-driven targets
  18. Metabolomics. 2020 Sep 30. 16(10): 104
      INTRODUCTION: Metabolite annotation is a critical and challenging step in mass spectrometry-based metabolomic profiling. In a typical untargeted MS/MS-based metabolomic study, experimental MS/MS spectra are matched against those in spectral libraries for metabolite annotation. Yet, existing spectral libraries comprise merely a marginal percentage of known compounds.OBJECTIVE: The objective is to develop a method that helps rank putative metabolite IDs for analytes whose reference MS/MS spectra are not present in spectral libraries.
    METHODS: We introduce MetFID, which uses an artificial neural network (ANN) trained for predicting molecular fingerprints based on experimental MS/MS data. To narrow the search space, MetFID retrieves candidates from metabolite databases using molecular formula or m/z value of the precursor ions of the analytes. The candidate whose fingerprint is most analogous to the predicted fingerprint is used for metabolite annotation. A comprehensive evaluation was performed by training MetFID using MS/MS spectra from the MoNA repository and NIST library and by testing with structure-disjoint MS/MS spectra from the NIST library, the CASMI 2016 dataset, and in-house MS/MS data from a cancer biomarker discovery study.
    RESULTS: We observed that training separate models for distinct ranges of collision energies enhanced model performance compared to a single model that covers a wide range of collision energies. Using MetaboQuest to retrieve candidates, MetFID prioritized the correct putative ID in the first place rank for about 50% of the testing cases. Through the independent testing dataset, we demonstrated that MetFID has the potential to improve the accuracy of ranking putative metabolite IDs by more than 5% compared to other tools such as ChemDistiller, CSI:FingerID, and MetFrag.
    CONCLUSION: MetFID offers a promising opportunity to enhance the accuracy of metabolite annotation by using ANN for molecular fingerprint prediction.
    Keywords:  Artificial neural network; Metabolite identification; Metabolomics; Molecular fingerprint
  19. Cancer Res. 2020 Sep 30. pii: canres.2199.2020. [Epub ahead of print]
      Lipid rafts are tightly packed, cholesterol- and sphingolipid-enriched microdomains within the plasma membrane that play important roles in many pathophysiological processes. Rafts have been strongly implicated as master regulators of signal transduction in cancer, where raft compartmentalization can promote transmembrane receptor oligomerization, shield proteins from enzymatic degradation, and act as scaffolds to enhance intracellular signaling cascades. Cancer cells have been found to exploit these mechanisms to initiate oncogenic signaling and promote tumor progression. This review highlights the roles of lipid rafts within the metastatic cascade, specifically within tumor angiogenesis, cell adhesion, migration, EMT, and transendothelial migration. Additionally, the interplay between lipid rafts and different modes of cancer cell death, including necrosis, apoptosis, and anoikis will be described. The clinical role of lipid raft-specific proteins caveolin and flotillin in assessing patient prognosis and evaluating metastatic potential of various cancers will be presented. Collectively, elucidation of the complex roles of lipid rafts and raft components within the metastatic cascade may be instrumental for therapeutic discovery to curb pro-metastatic processes.
  20. Anal Chem. 2020 Oct 01.
      Sphingolipids constitute a heterogeneous lipid category that is involved in many key cellular functions. For high-throughput analyses of sphingolipids, tandem mass spectrometry (MS/MS) is the method of choice, offering sufficient sensitivity, structural information, and quantitative precision for detecting hundreds to thousands of species simultaneously. While glycerolipids and phospholipids are predominantly non-hydroxylated, sphingolipids are typically dihydroxylated. However, species containing one or three hydroxylation sites can be detected frequently. This variability in the number of hydroxylation sites on the sphingolipid long-chain base and the fatty acyl moiety produces many more isobaric species and fragments than for other lipid categories. Due to this complexity, the automated annotation of sphingolipid species is challenging, and incorrect annotations are common. In this study, we present an extension of the Lipid Data Analyzer (LDA) "decision rule set" concept that considers the structural characteristics that are specific for this lipid category. To address the challenges inherent to automated annotation of sphingolipid structures from MS/MS data, we first developed decision rule sets using spectra from authentic standards and then tested the applicability on biological samples including murine brain and human plasma. A benchmark test based on the murine brain samples revealed a highly improved annotation quality as measured by sensitivity and reliability. The results of this benchmark test combined with the easy extensibility of the software to other (sphingo)lipid classes and the capability to detect and correctly annotate novel sphingolipid species make LDA broadly applicable to automated sphingolipid analysis, especially in high-throughput settings.