bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023‒10‒08
twenty-one papers selected by
Giovanny Rodriguez Blanco, University of Edinburgh



  1. Proteomics. 2023 Oct 03. e2300211
      The integration of robust single-pot, solid-phase-enhanced sample preparation with powerful liquid chromatography-tandem mass spectrometry (LC-MS/MS) is routinely used to define the extracellular vesicle (EV) proteome landscape and underlying biology. However, EV proteome studies are often limited by sample availability, requiring upscaling cell cultures or larger volumes of biofluids to generate sufficient materials. Here, we have refined data independent acquisition (DIA)-based MS analysis of EV proteome by optimizing both protein enzymatic digestion and chromatography gradient length (ranging from 15 to 44 min). Our short 15 min gradient length can reproducibly quantify 1168 (from as little as 500 pg of EV peptides) to 3882 proteins groups (from 50 ng peptides), including robust quantification of 22 core EV marker proteins. Compared to data-dependent acquisition, DIA achieved significantly greater EV proteome coverage and quantification of low abundant protein species. Moreover, we have achieved optimal magnetic bead-based sample preparation tailored to low quantities of EVs (0.5 to 1 µg protein) to obtain sufficient peptides for MS quantification of 1908-2340 protein groups. We demonstrate the power and robustness of our pipeline in obtaining sufficient EV proteomes granularity of different cell sources to ascertain known EV biology. This underscores the capacity of our optimised workflow to capture precise and comprehensive proteome of EVs, especially from ultra-low sample quantities (sub-nanogram), an important challenge in the field where obtaining in-depth proteome information is essential.
    Keywords:  data-independent acquisition; extracellular vesicles; high sensitivity; mass spectrometry; proteomics; subcellular; ultra-low proteomics
    DOI:  https://doi.org/10.1002/pmic.202300211
  2. Philos Trans R Soc Lond B Biol Sci. 2023 Nov 20. 378(1890): 20220237
      Citrullination is an important post-translational modification (PTM) of arginine, known to play a role in autoimmune disorders, innate immunity response and maintenance of stem cell potency. However, citrullination remains poorly characterized and not as comprehensively understood compared to other PTMs, such as phosphorylation and ubiquitylation. High-resolution mass spectrometry (MS)-based proteomics offers a valuable approach for studying citrullination in an unbiased manner, allowing confident identification of citrullination modification sites and distinction from deamidation events on asparagine and glutamine. MS efforts have already provided valuable insights into peptidyl arginine deaminase targeting along with site-specific information of citrullination in for example synovial fluids derived from rheumatoid arthritis patients. Still, there is unrealized potential for the wider citrullination field by applying MS-based mass spectrometry approaches for proteome-wide investigations. Here we will outline contemporary methods and current challenges for studying citrullination by MS, and discuss how the development of neoteric citrullination-specific proteomics approaches still may improve our understanding of citrullination networks. This article is part of the Theo Murphy meeting issue 'The virtues and vices of protein citrullination'.
    Keywords:  citrullination; mass spectrometry; post-translational modifications; proteomics
    DOI:  https://doi.org/10.1098/rstb.2022.0237
  3. Crit Rev Anal Chem. 2023 Oct 02. 1-32
      Lipids, as one of the most important organic compounds in organisms, are important components of cells and participate in energy storage and signal transduction of living organisms. As a rapidly rising field, lipidomics research involves the identification and quantification of multiple classes of lipid molecules, as well as the structure, function, dynamics, and interactions of lipids in living organisms. Due to its inherent high selectivity and high sensitivity, mass spectrometry (MS) is the "gold standard" analysis technique for small molecules in biological samples. The combination chemical derivatization with MS detection is a unique strategy that could improve MS ionization efficiency, facilitate structure identification and quantitative analysis. Herein, this review discusses derivatization-based MS strategies for lipidomic analysis over the past decade and focuses on all the reported lipid categories, including fatty acids and modified fatty acids, glycerolipids, glycerophospholipids, sterols and saccharolipids. The functional groups of lipids mainly involved in chemical derivatization include the C=C group, carboxyl group, hydroxyl group, amino group, carbonyl group. Furthermore, representative applications of these derivatization-based lipid profiling methods were summarized. Finally, challenges and countermeasures of lipid derivatization are mentioned and highlighted to guide future studies of derivatization-based MS strategy in lipidomics.
    Keywords:  Lipidomics; derivatization; mass spectrometry; structure analysis
    DOI:  https://doi.org/10.1080/10408347.2023.2261130
  4. Nat Methods. 2023 Oct;20(10): 1530-1536
      Single-cell proteomics by mass spectrometry is emerging as a powerful and unbiased method for the characterization of biological heterogeneity. So far, it has been limited to cultured cells, whereas an expansion of the method to complex tissues would greatly enhance biological insights. Here we describe single-cell Deep Visual Proteomics (scDVP), a technology that integrates high-content imaging, laser microdissection and multiplexed mass spectrometry. scDVP resolves the context-dependent, spatial proteome of murine hepatocytes at a current depth of 1,700 proteins from a cell slice. Half of the proteome was differentially regulated in a spatial manner, with protein levels changing dramatically in proximity to the central vein. We applied machine learning to proteome classes and images, which subsequently inferred the spatial proteome from imaging data alone. scDVP is applicable to healthy and diseased tissues and complements other spatial proteomics and spatial omics technologies.
    DOI:  https://doi.org/10.1038/s41592-023-02007-6
  5. Front Immunol. 2023 ;14 1250762
      Adenine nucleotides (AN) are ubiquitous metabolites that regulate cellular energy metabolism and modulate cell communication and inflammation. To understand how disturbances in AN balance arise and affect cellular function, robust quantification techniques for these metabolites are crucial. However, due to their hydrophilicity, simultaneous quantification of AN across various biological samples has been challenging. Here we present a hydrophilic interaction high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) based method for the quantification of 26 adenosine nucleotides and precursors as well as metabolic products of nicotinamide adenine dinucleotide (NAD) in plasma, liver, and adipose tissue samples as well as cell culture supernatants and cells. Method validation was performed with regard to linearity, accuracy, precision, matrix effects, and carryover. Finally, analysis of cell culture supernatants derived from intestinal organoids and RAW 264.7 cells illustrates that the here described method is a reliable and easy-to-use tool to quantify AN and opens up new avenues to understand the role of AN generation and breakdown for cellular functions.
    Keywords:  HILIC; LC-MS/MS; adenine nucleotides; metabolomics; purinergic signaling; quantification
    DOI:  https://doi.org/10.3389/fimmu.2023.1250762
  6. Talanta. 2023 Sep 22. pii: S0039-9140(23)00982-7. [Epub ahead of print]267 125231
      Fatty acids (FAs) play a vital physiological role in lipid metabolism, which is reported as potential diagnostic biomarker for various diseases. Thus, it is urgent to develop a credible method that can profile FA metabolism with a holistic view. Here, a targeted strategy to screen FAs was developed by parallel labeling with d0/d6-dansylhydrazine (d0/d6-DnsHz) and using ultra-high performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-MS/MS) in data-dependent MS/MS (ddMS2) mode. The simple and mild derivatization procedure within 3 h allowed for a significant improvement in sensitivity. Additionally, the characteristic product ions introduced by the derivatization reagent assist to identify the unknown FA species. A quantitation method was established by multiple reaction monitoring (MRM) and the d6-DnsHz tagged standards for each analyte were used as internal standards to overcome the matrix effects. By applying the method to determine FA levels in plasma collected from the esophageal squamous cell carcinoma (ESCC) patients and healthy controls, 65 FA metabolites were characterized and six FAs were found to be altered by the invasion of tumors. The parallel derivatization strategy provides insights into the identification of unknown FAs and paves a new way for targeted metabolomics. Also, this novel method is a powerful tool for characterization and quantification of FAs in biological samples, which shows a great potential application in clinical diagnosis and investigation of disease mechanisms.
    Keywords:  Biomarker; Esophageal squamous cell carcinoma; Fatty acid; LC–MS/MS; Parallel derivatization
    DOI:  https://doi.org/10.1016/j.talanta.2023.125231
  7. Redox Biol. 2023 Sep 27. pii: S2213-2317(23)00309-9. [Epub ahead of print]67 102908
      Protein cysteinyl thiols are susceptible to reduction-oxidation reactions that can influence protein function. Accurate quantification of cysteine oxidation is therefore crucial for decoding protein redox regulation. Here, we present CysQuant, a novel approach for simultaneous quantification of cysteine oxidation degrees and protein abundancies. CysQuant involves light/heavy iodoacetamide isotopologues for differential labeling of reduced and reversibly oxidized cysteines analyzed by data-dependent acquisition (DDA) or data-independent acquisition mass spectrometry (DIA-MS). Using plexDIA with in silico predicted spectral libraries, we quantified an average of 18% cysteine oxidation in Arabidopsis thaliana by DIA-MS, including a subset of highly oxidized cysteines forming disulfide bridges in AlphaFold2 predicted structures. Applying CysQuant to Arabidopsis seedlings exposed to excessive light, we successfully quantified the well-established increased reduction of Calvin-Benson cycle enzymes and discovered yet uncharacterized redox-sensitive disulfides in chloroplastic enzymes. Overall, CysQuant is a highly versatile tool for assessing the cysteine modification status that can be widely applied across various mass spectrometry platforms and organisms.
    DOI:  https://doi.org/10.1016/j.redox.2023.102908
  8. Cell Metab. 2023 Sep 27. pii: S1550-4131(23)00337-6. [Epub ahead of print]
      Cold-induced thermogenesis (CIT) is widely studied as a potential avenue to treat obesity, but a thorough understanding of the metabolic changes driving CIT is lacking. Here, we present a comprehensive and quantitative analysis of the metabolic response to acute cold exposure, leveraging metabolomic profiling and minimally perturbative isotope tracing studies in unanesthetized mice. During cold exposure, brown adipose tissue (BAT) primarily fueled the tricarboxylic acid (TCA) cycle with fat in fasted mice and glucose in fed mice, underscoring BAT's metabolic flexibility. BAT minimally used branched-chain amino acids or ketones, which were instead avidly consumed by muscle during cold exposure. Surprisingly, isotopic labeling analyses revealed that BAT uses glucose largely for TCA anaplerosis via pyruvate carboxylation. Finally, we find that cold-induced hepatic gluconeogenesis is critical for CIT during fasting, demonstrating a key functional role for glucose metabolism. Together, these findings provide a detailed map of the metabolic rewiring driving acute CIT.
    Keywords:  FBP1; brown adipose tissue; cold exposure; flux; gluconeogenesis; glucose; metabolomics; pyruvate carboxylase; thermogenesis
    DOI:  https://doi.org/10.1016/j.cmet.2023.09.002
  9. J Chromatogr B Analyt Technol Biomed Life Sci. 2023 Oct 01. pii: S1570-0232(23)00303-3. [Epub ahead of print]1229 123893
      Accurate quantification of amino acids (AA) is essential for several applications, including clinical research, food analysis, and pharmaceutical studies. In this study, we developed an analytical method based on liquid chromatography with electrospray ionization coupled to tandem mass spectrometry detection (LC-ESI-MS/MS). This method was devised to accurately quantify a spectrum of amino acids, notably taurine, creatinine, glutathione (GSH), and sulfur-containing amino acids (SAAs) such as methionine, cysteine, and homocysteine, using only 10 μL of human plasma. A stable isotope derivative of each AA is used as an internal standard (IS) for accurate quantification. For retention and separation on a C18 column, heptafluorobutyric acid (HFBA) was employed as an ion pair agent. Multiple reaction monitoring (MRM) in positive mode with the precursor-to-product ion transitions at m/z is used for quantification. The method showed excellent linearity for all AA with a high correlation coefficient (r > 0.9927). The linear fit indicates that the detector response is linear over the tested range of standard concentrations. The accuracy and precision of the method were within the acceptable range of 92-110% and < 15%, respectively. The limit of detection (LOD) and limit of quantification (LOQ) were in the range of 0.001-1.80 µM and 0.004-6.0 µM, respectively. No significant ion suppression or carry over was observed. In conclusion, the assay was validated and found to have adequate accuracy, precision, linearity, sensitivity and selectivity. The assay has been successfully applied to the analysis of human plasma.
    Keywords:  Amino acids; Liquid chromatography-mass spectrometry; Underivatized
    DOI:  https://doi.org/10.1016/j.jchromb.2023.123893
  10. Anal Chem. 2023 Oct 04.
      Lipid analysis gained significant importance due to the enormous range of lipid functions, e.g., energy storage, signaling, or structural components. Whole lipidomes can be quantitatively studied in-depth thanks to recent analytical advancements. However, the systematic comparison of thousands of distinct lipidomes remains challenging. We introduce LipidSpace, a standalone tool for analyzing lipidomes by assessing their structural and quantitative differences. A graph-based comparison of lipid structures is the basis for calculating structural space models and subsequently computing lipidome similarities. When adding study variables such as body weight or health condition, LipidSpace can determine lipid subsets across all lipidomes that describe these study variables well by utilizing machine-learning approaches. The user-friendly GUI offers four built-in tutorials and interactive visual interfaces with pdf export. Many supported data formats allow an efficient (re)analysis of data sets from different sources. An integrated interactive workflow guides the user through the quality control steps. We used this suite to reanalyze and combine already published data sets (e.g., one with about 2500 samples and 576 lipids in one run) and made additional discoveries to the published conclusions with the potential to fill gaps in the current lipid biology understanding. LipidSpace is available for Windows or Linux (https://lifs-tools.org).
    DOI:  https://doi.org/10.1021/acs.analchem.3c02449
  11. J Pharm Biomed Anal. 2023 Sep 29. pii: S0731-7085(23)00526-5. [Epub ahead of print]236 115757
      The accurate characterisation of metabolic profiles is an important prerequisite to determine the rate and the efficiency of the metabolic pathways taking place in the cells. Changes in the balance of metabolites involved in vital processes such as glycolysis, tricarboxylic acid (TCA) cycle, oxidative phosphorylation (OXPHOS), as well as in the biochemical pathways related to amino acids, lipids, nucleotides, and their precursors reflect the physiological condition of the cells and may contribute to the development of various human diseases. The feasible and reliable measurement of a wide array of metabolites and biomarkers possesses great potential to elucidate physiological and pathological mechanisms, aid preclinical drug development and highlight potential therapeutic targets. An effective, straightforward, sensitive, and selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach was developed for the simultaneous quali-quantitative analysis of 41 compounds in both cell pellet and cell growth medium obtained from brain-derived cell cultures. Sample pretreatment miniaturisation was achieved thanks to the development and optimisation of an original extraction/purification approach based on digitally programmed microextraction by packed sorbent (eVol®-MEPS). MEPS allows satisfactory and reproducible clean-up and preconcentration of both low-volume homogenate cell pellet lysate and cell growth medium with advantages including, but not limited to, minimal sample handling and method sustainability in terms of sample, solvents, and energy consumption. The MEPS-LC-MS/MS method showed good sensitivity, selectivity, linearity, and precision. As a proof of concept, the developed method was successfully applied to the analysis of both cell pellet and cell growth medium obtained from a line of mouse immortalised oligodendrocyte precursor cells (OPCs; Oli-neu cell line), leading to the unambiguous determination of all the considered target analytes. This method is thus expected to be suitable for targeted, quantitative metabolic profiling in most brain cell models, thus allowing accurate investigations on the biochemical pathways that can be altered in central nervous system (CNS) neuropathologies, including e.g., mitochondrial respiration and glycolysis, or use of specific nutrients for growth and proliferation, or lipid, amino acid and nucleotide metabolism.
    Keywords:  Biomarkers; Brain cell cultures; Cell metabolism; LC-MS/MS; Targeted metabolic profiling
    DOI:  https://doi.org/10.1016/j.jpba.2023.115757
  12. Expert Rev Proteomics. 2023 Oct 03.
      INTRODUCTION: Continuous advances in mass spectrometry (MS) technologies have enabled deeper and more reproducible proteome characterization, and a better understanding of biological systems when integrated with other 'omics data. Bioinformatic resources meeting analysis requirements of increasingly complex MS-based proteomic data, and associated multi-omic data, are critically needed. These requirements included availability of software spanning diverse types of analyses, along with scalability for large-scale, compute-intensive applications and mechanisms to ease adoption of the software.AREAS COVERED: The Galaxy ecosystem meets these requirements by offering a multitude of open-source tools for MS-based proteomics analyses and applications, all in an adaptable, scalable, and accessible computing environment. A thriving global community maintains these software and associated training resources to empower researcher-driven analyses.
    EXPERT OPINION: The community-supported Galaxy ecosystem remains a crucial contributor to basic biological and clinical studies using MS-based proteomics. In addition to the current status of Galaxy-based resources, we describe ongoing developments for meeting emerging challenges in MS-based proteomic informatics. We hope this review will catalyze increased use of Galaxy by researchers employing MS-based proteomics and inspire software developers to join the community and implement new tools, workflows, and associated training content that will add further value to this already rich ecosystem.
    Keywords:  Bioinformatics; Computational workflows; Galaxy platform; Mass-spectrometry; Multi-omics; Reproducibility; proteomics
    DOI:  https://doi.org/10.1080/14789450.2023.2265062
  13. Res Sq. 2023 Sep 11. pii: rs.3.rs-3317816. [Epub ahead of print]
      Background: Diffuse midline gliomas (DMG), including diffuse intrinsic pontine gliomas (DIPGs), are a fatal form of brain cancer. These tumors often carry a driver mutation on histone H3 converting lysine 27 to methionine (H3K27M). DMG-H3K27M are characterized by altered metabolism and resistance to standard of care radiation (RT), but how the H3K27M mediates the metabolic response to radiation and consequent treatment resistance is uncertain. Methods: We performed metabolomics on irradiated and untreated H3K27M isogenic DMG cell lines and observed an H3K27M-specific enrichment for purine synthesis pathways. We profiled the expression of purine synthesis enzymes in publicly available patient data and in our models, quantified purine synthetic flux using stable isotope tracing, and characterized the in vitro and in vivo response to de novo and salvage purine synthesis inhibition in combination with RT. Results: DMG-H3K27M cells activate purine metabolism in an H3K27M-specific fashion. In the absence of genotoxic treatment, H3K27M-expressing cells have higher relative activity of de novo synthesis and lower activity of purine salvage due to decreased expression of the purine salvage enzymes. Inhibition of de novo synthesis radiosensitized DMG-H3K27M cells in vitro and in vivo. Irradiated H3K27M cells adaptively upregulate purine salvage enzyme expression and pathway activity. Silencing the rate limiting enzyme in purine salvage, hypoxanthine guanine phosphoribosyl transferase (HGPRT) when combined with radiation markedly suppressed DMG-H3K27M tumor growth in vivo. Conclusions: H3K27M expressing cells rely on de novo purine synthesis but adaptively upregulate purine salvage in response to RT. Inhibiting purine salvage may help overcome treatment resistance in DMG-H3K27M tumors.
    DOI:  https://doi.org/10.21203/rs.3.rs-3317816/v1
  14. Environ Pollut. 2023 Oct 04. pii: S0269-7491(23)01686-X. [Epub ahead of print] 122684
      Intestinal cell metabolism plays an important role in intestine health. Perfluorooctanoic acid (PFOA) exposure could disorder intestinal cell metabolism. However, the mechanisms regarding how the three carbon sources interact under PFOA stress remined to be understood. The present study aimed to dissect the interconnections of glucose, glutamine, and fatty acids in PFOA-treated human colorectal cancer (DLD-1) cells using 13C metabolic flux analysis. The abundance of glycolysis and tricarboxylic acid (TCA) cycle metabolites was decreased in PFOA-treated cells except for succinate, whereas most of amino acids were more abundant. Beside serine and glycine, metabolites derived from 13C glucose was reduced in PFOA-treated cells, and the pentose phosphate pathway flux was 1.4-fold higher in PFOA-treated cells than in the controls. In reductive glutamine pathway, higher labeled enrichment of citrate, malate, fumarate, and succinate was observed for PFOA-treated cells. The contribution of glucose to fatty acid synthesis in PFOA-treated cells decreased while the contribution of glutamine to fatty acid synthesis increased. Additionally, synthesis of TCA intermediates from fatty acid β-oxidation was promoted in PFOA-treated cells. All results suggested that metabolic remodeling could happen in intestinal cells exposed to PFOA, which was potentially related to PFOA toxicity relevant with the loss of glucose in biomass synthesis and energy metabolism.
    Keywords:  Glucose metabolism; Glutamine metabolism; Intestine health; Metabolic flux analysis; Metabolic remodeling; Perfluorooctanoic acid
    DOI:  https://doi.org/10.1016/j.envpol.2023.122684
  15. Curr Opin Chem Biol. 2023 Sep 28. pii: S1367-5931(23)00127-8. [Epub ahead of print]77 102389
      The post-translational modification of cysteine to diverse oxidative states is understood as a critical cellular mechanism to combat oxidative stress. To study the role of cysteine oxidation, cysteine enrichments and subsequent analysis via mass spectrometry are necessary. As such, technologies and methods are rapidly developing for sensitive and efficient enrichments of cysteines to further explore its role in signaling pathways. In this review, we analyze recent developments in methods to miniaturize cysteine enrichments, analyze the underexplored disulfide bound redoxome, and quantify site-specific cysteine oxidation. We predict that further development of these methods will improve cysteine coverage across more diverse organisms than those previously studied and elicit novel roles cysteines play in stress response.
    Keywords:  Cysteine enrichments; Mass spectrometry; Proteomics; Redox proteomics
    DOI:  https://doi.org/10.1016/j.cbpa.2023.102389
  16. Int J Radiat Oncol Biol Phys. 2023 Oct 01. pii: S0360-3016(23)05329-4. [Epub ahead of print]117(2S): e113-e114
      PURPOSE/OBJECTIVE(S): Enhanced lipid metabolism has emerged as a central metabolic node in glioblastoma, serving as a 'gain of function' that allows these cells to efficiently adapt to their dynamic tumor microenvironment. Seemingly contradictory to this, pre-clinical studies have demonstrated anti-tumor activity in mice fed a high-fat/low-carbohydrate ketogenic diet (KD), both alone and in combination with radiation therapy (RT). In this study, we sought to identify mechanisms underlying the antitumor activity of a KD in glioblastoma from a metabolic perspective to better understand factors contributing to this apparent disconnect.MATERIALS/METHODS: Immunocompromised and immunocompetent mice were injected orthotopically with human and mouse-derived glioblastoma cell lines and randomized to four treatment arms. Mice were fed ad libitum a standard diet (SD), KD (Bio-Serve), or a modified unsaturated fatty acid (uFA) rich diet (MD; 60/30/10: fat/protein/carb) alone or in combination with hypofractionated RT (6 Gy x 3). Global metabolomic profiling of tumors and serum were carried out using LC/GC-MS. Lipid droplets were analyzed by flow cytometer and confocal microscopy using BODIPY staining and free fatty acids were measured using a commercially available kit.
    RESULTS: A KD demonstrated independent anti-tumor activity and potent synergy with RT in two aggressive glioblastoma models. Metabolomic profiling of tumors revealed significant changes in tumor metabolism in KD-fed mice when compared to SD, with an accumulation of uFAs being a key finding. We therefore sought to determine if this accumulation of fatty acids in KD mice contributed towards the observed anti-tumor activity. Consistent with in vivo results, in vitro studies using the uFA linoleic acid demonstrated anti-proliferative activity, reduced clonogenic capacity, and potent synergy when combined with RT in glioblastoma cells. Through a series of investigations, we went on to determine that this anti-tumor activity was attributed to the ability of uFA to override lipid storage homeostasis in glioblastoma cells, resulting in lipotoxicity. Based on these findings, we hypothesized high fat concentrations, rather than carbohydrate restriction, contributed to the anti-tumor activity of a KD. To test this, we generated a MD rich in uFA that did not require carbohydrate restriction. Similar to a KD, mice fed a MD demonstrated both independent anti-tumor activity and potent synergy when combined with RT.
    CONCLUSION: High concentrations of uFA represents a key factor underlying the anti-tumor activity of a KD in glioblastoma by targeting lipid homeostasis. A MD consisting of high concentrations of uFA without carbohydrate restriction demonstrates promising anti-tumor activity in glioblastoma models. As a major limitation of a KD is tolerability, particularly in glioblastoma patients, a MD represents a promising form of dietary modification that may be translated clinically.
    DOI:  https://doi.org/10.1016/j.ijrobp.2023.06.895
  17. Front Oncol. 2023 ;13 1289397
      
    Keywords:  bioenergetics; cancer; cancer/immune metabolism; metabolic disorder and cancer; metabolic imaging; metabolomics; tumor microenvironment
    DOI:  https://doi.org/10.3389/fonc.2023.1289397
  18. Int J Biol Sci. 2023 ;19(15): 4915-4930
      Breast cancer is the most common cancer affecting women worldwide. Investigating metabolism in breast cancer may accelerate the exploitation of new therapeutic options for immunotherapies. Metabolic reprogramming can confer breast cancer cells (BCCs) with a survival advantage in the tumor microenvironment (TME) and metabolic alterations in breast cancer, and the corresponding metabolic byproducts can affect the function of tumor-associated macrophages (TAMs). Additionally, TAMs undergo metabolic reprogramming in response to signals present in the TME, which can affect their function and breast cancer progression. Here, we review the metabolic crosstalk between BCCs and TAMs in terms of glucose, lipids, amino acids, iron, and adenosine metabolism. Summaries of inhibitors that target metabolism-related processes in BCCs or TAMs within breast cancer have also served as valuable inspiration for novel therapeutic approaches in the fight against this disease. This review provides new perspectives on targeted anticancer therapies for breast cancer that combine immunity with metabolism.
    Keywords:  breast cancer; crosstalk; metabolism; targeted therapy; tumor-associated macrophages
    DOI:  https://doi.org/10.7150/ijbs.86039
  19. Anal Bioanal Chem. 2023 Oct 07.
      Collision-induced dissociation (CID) is the most wildly used fragmentation technique for qualitative and quantitative determination of low molecular weight compounds (LMWC). Ultraviolet photodissociation (UVPD) has been mainly investigated for the analysis of peptides and lipids while only in a limited way for LMWC. A triple quadrupole linear ion trap instrument has been modified to allow ultraviolet photodissociation (UVPD) in the end of the q2 region enabling various workflows with and without data-dependent acquisition (DDA) combining CID and UVPD in the same LC-MS analysis. The performance of UVPD, with a 266-nm laser, is compared to CID for a mix of 90 molecules from different classes of LMWC including peptides, pesticides, pharmaceuticals, metabolites, and drugs of abuse. These two activation methods offer complementary fragments as well as common fragments with similar sensitivities for most analytes investigated. The versatility of UVPD and CID is also demonstrated for quantitative analysis in human plasma of bosentan and its desmethyl metabolite, used as model analytes. Different background signals are observed for both fragmentation methods as well as unique fragments which opens the possibility of developing a selective quantitative assay with improved sample throughput, in particular for analytes present in different matrices.
    Keywords:  Collision-induced dissociation; LC–MS/MS; Low molecular weight compounds; Qualitative analysis; Quantitative analysis; Ultraviolet photodissociation
    DOI:  https://doi.org/10.1007/s00216-023-04977-0
  20. Mass Spectrom (Tokyo). 2023 ;12(1): A0129
      Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.
    Keywords:  DESI-MSI; ambient mass spectrometry; cancer studies; carcinoma; mass spectrometry imaging
    DOI:  https://doi.org/10.5702/massspectrometry.A0129
  21. mSystems. 2023 Oct 05. e0076023
      Understanding the allocation of the cellular proteome to different cellular processes is central to unraveling the organizing principles of bacterial physiology. Proteome allocation to protein translation itself is maximally efficient, i.e., it represents the minimal allocation of dry mass able to sustain the observed protein production rate. In contrast, recent studies on bacteria have demonstrated that the concentrations of many proteins exceed the minimal level required to support the observed growth rate, indicating some heterogeneity across pathways in their proteome efficiency. Here, we systematically analyze the proteome efficiency of metabolic pathways, which together account for more than half of the Escherichia coli proteome during exponential growth. Comparing the predicted minimal and the observed proteome allocation to different metabolic pathways across growth conditions, we find that the protein abundance in the most costly biosynthesis pathways-those for amino acid biosynthesis and cofactor biosynthesis-is regulated for near-optimal efficiency. Overall, proteome efficiency increases along the carbon flow through the metabolic network; proteins involved in pathways of nutrient uptake and central metabolism tend to be highly over-abundant, while proteins involved in anabolic pathways and in protein translation are much closer to the expected minimal abundance across conditions. Our work thus provides a bird's-eye view of metabolic pathway efficiency, demonstrating systematic deviations from optimal cellular efficiency at the network level. IMPORTANCE Protein translation is the most expensive cellular process in fast-growing bacteria, and efficient proteome usage should thus be under strong natural selection. However, recent studies show that a considerable part of the proteome is unneeded for instantaneous cell growth in Escherichia coli. We still lack a systematic understanding of how this excess proteome is distributed across different pathways as a function of the growth conditions. We estimated the minimal required proteome across growth conditions in E. coli and compared the predictions with experimental data. We found that the proteome allocated to the most expensive internal pathways, including translation and the synthesis of amino acids and cofactors, is near the minimally required levels. In contrast, transporters and central carbon metabolism show much higher proteome levels than the predicted minimal abundance. Our analyses show that the proteome fraction unneeded for instantaneous cell growth decreases along the nutrient flow in E. coli.
    Keywords:  biosynthetic pathways; central carbon metabolism; glyoxylate shunt; growth law; growth rate; metabolic pathways; proteome efficiency; resource allocation
    DOI:  https://doi.org/10.1128/msystems.00760-23