bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2023–09–24
seventeen papers selected by
Giovanny Rodríguez Blanco, Uniklinikum Graz
  1. Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition.
  2. Improving single cell proteomics experiments: how can we best utilize latest-generation data acquisition and MS instrument architecture?
  3. Dietary fat and lipid metabolism in the tumor microenvironment.
  4. A large-scale LC-MS dataset of murine liver proteome from time course of heavy water metabolic labeling.
  5. Clinical Proteomics for Solid Organ Tissues.
  6. Tumor lipid metabolism: a mechanistic link between diet and cancer progression.
  7. Proteomics contributions to epigenetic drug discovery.
  8. Editorial: Lipid metabolism in obesity.
  9. Flash entropy search to query all mass spectral libraries in real time.
  10. A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline.
  11. Connections between metabolism and epigenetic modifications in cancer.
  12. 13CO2-labelling and Sampling in Algae for Flux Analysis of Photosynthetic and Central Carbon Metabolism.
  13. Systematic characterization of Lysergic Acid Diethylamide metabolites in Caenorhabditis elegans by ultra-high performance liquid chromatography coupled with high-resolution tandem mass spectrometry.
  14. Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells.
  15. Staging of colorectal cancer using lipid biomarkers and machine learning.
  16. In-Depth Characterization of Sphingoid Bases via Radical-Directed Dissociation Tandem Mass Spectrometry.
  17. Epigenetic meets metabolism: novel vulnerabilities to fight cancer.
  1. Nat Commun. 2023 Sep 22. 14(1): 5910
    Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition.
    Valdemaras Petrosius, Pedro Aragon-Fernandez, Nil Üresin, Gergo Kovacs, Teeradon Phlairaharn, Benjamin Furtwängler, Jeff Op De Beeck, Sarah L Skovbakke, Steffen Goletz, Simon Francis Thomsen, Ulrich Auf dem Keller, Kedar N Natarajan, Bo T Porse, Erwin M Schoof.
      Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
    DOI:  https://doi.org/10.1038/s41467-023-41602-1
  2. Expert Rev Proteomics. 2023 Sep 16.
    Improving single cell proteomics experiments: how can we best utilize latest-generation data acquisition and MS instrument architecture?
    Manuel Matzinger, Karl Mechtler.
      
    Keywords:  Wide Window Data Dependent Acquisition; Wide Window Data Independent Acquisition; quantitative accuracy; sensitivity; single-cell proteomics; throughput
    DOI:  https://doi.org/10.1080/14789450.2023.2260954
  3. Biochim Biophys Acta Rev Cancer. 2023 Sep 16. pii: S0304-419X(23)00133-6. [Epub ahead of print] 188984
    Dietary fat and lipid metabolism in the tumor microenvironment.
    Swagata Goswami, Qiming Zhang, Cigdem Elif Celik, Ethan M Reich, Ömer H Yilmaz.
      Metabolic reprogramming has been considered a core hallmark of cancer, in which excessive accumulation of lipids promote cancer initiation, progression and metastasis. Lipid metabolism is often considered as the digestion and absorption process of dietary fat, and the ways in which cancer cells utilize lipids are often influenced by the complex interactions within the tumor microenvironment. Among multiple cancer risk factors, obesity has a positive association with multiple cancer types, while diets like calorie restriction and fasting improve health and delay cancer. Impact of these diets on tumorigenesis or cancer prevention are generally studied on cancer cells, despite heterogeneity of the tumor microenvironment. Cancer cells regularly interact with these heterogeneous microenvironmental components, including immune and stromal cells, to promote cancer progression and metastasis, and there is an intricate metabolic crosstalk between these compartments. Here, we focus on discussing fat metabolism and response to dietary fat in the tumor microenvironment, focusing on both immune and stromal components and shedding light on therapeutic strategies surrounding lipid metabolic and signaling pathways.
    Keywords:  Fatty acid; High fat diet; Immunosuppression; Lipid metabolism; Obesity; Therapeutic intervention; Tumor microenvironment
    DOI:  https://doi.org/10.1016/j.bbcan.2023.188984
  4. Sci Data. 2023 09 19. 10(1): 635
    A large-scale LC-MS dataset of murine liver proteome from time course of heavy water metabolic labeling.
    Henock M Deberneh, Doaa R Abdelrahman, Sunil K Verma, Jennifer J Linares, Andrew J Murton, William K Russell, Muge N Kuyumcu-Martinez, Benjamin F Miller, Rovshan G Sadygov.
      Metabolic stable isotope labeling with heavy water followed by liquid chromatography coupled with mass spectrometry (LC-MS) is a powerful tool for in vivo protein turnover studies. Several algorithms and tools have been developed to determine the turnover rates of peptides and proteins from time-course stable isotope labeling experiments. The availability of benchmark mass spectrometry data is crucial to compare and validate the effectiveness of newly developed techniques and algorithms. In this work, we report a heavy water-labeled LC-MS dataset from the murine liver for protein turnover rate analysis. The dataset contains eighteen mass spectral data with their corresponding database search results from nine different labeling durations and quantification outputs from d2ome+ software. The dataset also contains eight mass spectral data from two-dimensional fractionation experiments on unlabeled samples.
    DOI:  https://doi.org/10.1038/s41597-023-02537-w
  5. Mol Cell Proteomics. 2023 Sep 18. pii: S1535-9476(23)00159-7. [Epub ahead of print] 100648
    Clinical Proteomics for Solid Organ Tissues.
    William S Phipps, Mark R Kilgore, Jacob J Kennedy, Jeffrey R Whiteaker, Andrew N Hoofnagle, Amanda G Paulovich.
      The evaluation of biopsied solid organ tissue has long relied on visual examination using a microscope. Immunohistochemistry is critical in this process, labeling and detecting cell lineage markers and therapeutic targets. However, while the practice of immunohistochemistry has reshaped diagnostic pathology and facilitated improvements in cancer treatment, it has also been subject to pervasive challenges with respect to standardization and reproducibility. Efforts are ongoing to improve immunohistochemistry, but for some applications, the benefit of such initiatives could be impeded by its reliance on monospecific antibody-protein reagents and limited multiplexing capacity. This perspective surveys the relevant challenges facing traditional immunohistochemistry and describes how mass spectrometry, particularly liquid chromatography-tandem mass spectrometry could help alleviate problems. In particular, targeted mass spectrometry assays could facilitate measurements of individual proteins or analyte panels, using internal standards for more robust quantification and improved interlaboratory reproducibility. Meanwhile, untargeted mass spectrometry, showcased to date clinically in the form of amyloid typing, is inherently multiplexed, facilitating the detection and crude quantification of 100s to 1000s of proteins in a single analysis. Further, data-independent acquisition has yet to be applied in clinical practice, but offers particular strengths that could appeal to clinical users. Finally, we discuss the guidance that is needed to facilitate broader utilization in clinical environments and achieve standardization.
    DOI:  https://doi.org/10.1016/j.mcpro.2023.100648
  6. Curr Opin Biotechnol. 2023 Sep 13. pii: S0958-1669(23)00103-9. [Epub ahead of print]84 102993
    Tumor lipid metabolism: a mechanistic link between diet and cancer progression.
    Yu-Jin Jeong, Thomas J Rogers, Carolyn E Anderson, Evan C Lien.
      The potential for 'anti-cancer' diets to markedly alter cancer risk and prognosis has captured the imagination of patients, physicians, and researchers alike, but many of these dietary recommendations come from correlative studies that attribute certain diets to altered cancer risk. While provocative, little is known about the molecular mechanisms behind how these dietary interventions impact cancer progression. Within this context, however, changes in tumor lipid metabolism are emerging as a key contributor. In this review, we examine the current understanding of lipid metabolism in the tumor microenvironment (TME), suggesting how diet-induced changes in lipid composition may regulate tumor progression and therapeutic efficacy. By dissecting various cellular pathways involved in lipid metabolism, we highlight how diet modulates the balance between saturated and unsaturated fatty acid (FA) species in tumors to impact cancer cell and stromal cell function. Finally, we describe how current cancer therapies may synergize with diet to improve therapeutic efficacy.
    DOI:  https://doi.org/10.1016/j.copbio.2023.102993
  7. Proteomics. 2023 Sep 19. e2200435
    Proteomics contributions to epigenetic drug discovery.
    Roberta Noberini, Tiziana Bonaldi.
      The combined activity of epigenetic features, which include histone post-translational modifications, DNA methylation, and nucleosome positioning, regulates gene expression independently from changes in the DNA sequence, defining how the shared genetic information of an organism is used to generate different cell phenotypes. Alterations in epigenetic processes have been linked with a multitude of diseases, including cancer, fueling interest in the discovery of drugs targeting the proteins responsible for writing, erasing, or reading histone and DNA modifications. Mass spectrometry (MS)-based proteomics has emerged as a versatile tool that can assist drug discovery pipelines from target validation, through target deconvolution, to monitoring drug efficacy in vivo. Here, we provide an overview of the contributions of MS-based proteomics to epigenetic drug discovery, describing the main approaches that can be used to support different drug discovery pipelines and highlighting how they contributed to the development and characterization of epigenetic drugs.
    Keywords:  drug discovery; epigenetics; histone post-translational modification; mass spectrometry; proteomics; target deconvolution
    DOI:  https://doi.org/10.1002/pmic.202200435
  8. Front Physiol. 2023 ;14 1268288
    Editorial: Lipid metabolism in obesity.
    Anna Maria Giudetti.
      
    Keywords:  diabetes; lipids; metabolism; non-alcoholic fatty liver disease; obesity
    DOI:  https://doi.org/10.3389/fphys.2023.1268288
  9. Nat Methods. 2023 Sep 21.
    Flash entropy search to query all mass spectral libraries in real time.
    Yuanyue Li, Oliver Fiehn.
      Public repositories of metabolomics mass spectra encompass more than 1 billion entries. With open search, dot product or entropy similarity, comparisons of a single tandem mass spectrometry spectrum take more than 8 h. Flash entropy search speeds up calculations more than 10,000 times to query 1 billion spectra in less than 2 s, without loss in accuracy. It benefits from using multiple threads and GPU calculations. This algorithm can fully exploit large spectral libraries with little memory overhead for any mass spectrometry laboratory.
    DOI:  https://doi.org/10.1038/s41592-023-02012-9
  10. Cell Rep Methods. 2023 Sep 13. pii: S2667-2375(23)00245-X. [Epub ahead of print] 100593
    A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline.
    Luke Reilly, Erika Lara, Daniel Ramos, Ziyi Li, Caroline B Pantazis, Julia Stadler, Marianita Santiana, Jessica Roberts, Faraz Faghri, Ying Hao, Mike A Nalls, Priyanka Narayan, Yansheng Liu, Andrew B Singleton, Mark R Cookson, Michael E Ward, Yue A Qi.
      Here, we present a standardized, "off-the-shelf" proteomics pipeline working in a single 96-well plate to achieve deep coverage of cellular proteomes with high throughput and scalability. This integrated pipeline streamlines a fully automated sample preparation platform, a data-independent acquisition (DIA) coupled with high-field asymmetric waveform ion mobility spectrometer (FAIMS) interface, and an optimized library-free DIA database search strategy. Our systematic evaluation of FAIMS-DIA showing single compensation voltage (CV) at -35 V not only yields the deepest proteome coverage but also best correlates with DIA without FAIMS. Our in-depth comparison of direct-DIA database search engines shows that Spectronaut outperforms others, providing the highest quantifiable proteins. Next, we apply three common DIA strategies in characterizing human induced pluripotent stem cell (iPSC)-derived neurons and show single-shot mass spectrometry (MS) using single-CV (-35 V)-FAIMS-DIA results in >9,000 quantifiable proteins with <10% missing values, as well as superior reproducibility and accuracy compared with other existing DIA methods.
    Keywords:  CP: Biotechnology; CP: Systems biology; DDA; DIA; FAIMS; automation; database search; mass spectrometry; proteomics; single-shot MS
    DOI:  https://doi.org/10.1016/j.crmeth.2023.100593
  11. Med Rev (Berl). 2021 Dec;1(2): 199-221
    Connections between metabolism and epigenetic modifications in cancer.
    Guangchao Wang, Jingdong J Han.
      How cells sense and respond to environmental changes is still a key question. It has been identified that cellular metabolism is an important modifier of various epigenetic modifications, such as DNA methylation, histone methylation and acetylation and RNA N6-methyladenosine (m6A) methylation. This closely links the environmental nutrient availability to the maintenance of chromatin structure and gene expression, and is crucial to regulate cellular homeostasis, cell growth and differentiation. Cancer metabolic reprogramming and epigenetic alterations are widely observed, and facilitate cancer development and progression. In cancer cells, oncogenic signaling-driven metabolic reprogramming modifies the epigenetic landscape via changes in the key metabolite levels. In this review, we briefly summarized the current evidence that the abundance of key metabolites, such as S-adenosyl methionine (SAM), acetyl-CoA, α-ketoglutarate (α-KG), 2-hydroxyglutarate (2-HG), uridine diphospho-N-acetylglucosamine (UDP-GlcNAc) and lactate, affected by metabolic reprogramming plays an important role in dynamically regulating epigenetic modifications in cancer. An improved understanding of the roles of metabolic reprogramming in epigenetic regulation can contribute to uncover the underlying mechanisms of metabolic reprogramming in cancer development and identify the potential targets for cancer therapies.
    Keywords:  DNA methylation; RNA m6A; cancer metabolic reprogramming; epigenetic modifications; histone acetylation; histone methylation
    DOI:  https://doi.org/10.1515/mr-2021-0015
  12. Bio Protoc. 2023 Sep 05. 13(17): e4808
    13CO2-labelling and Sampling in Algae for Flux Analysis of Photosynthetic and Central Carbon Metabolism.
    Or Geffen, David Achaintre, Haim Treves.
      The flux in photosynthesis can be studied by performing 13CO2 pulse labelling and analysing the temporal labelling kinetics of metabolic intermediates using gas or liquid chromatography linked to mass spectrometry. Metabolic flux analysis (MFA) is the primary approach for analysing metabolic network function and quantifying intracellular metabolic fluxes. Different MFA approaches differ based on the metabolic state (steady vs. non-steady state) and the use of stable isotope tracers. The main methodology used to investigate metabolic systems is metabolite steady state associated with stable isotope labelling experiments. Specifically, in biological systems like photoautotrophic organisms, isotopic non-stationary 113C metabolic flux analysis at metabolic steady state with transient isotopic labelling (13C-INST-MFA) is required. The common requirement for metabolic steady state, alongside its very short half-timed reactions, complicates robust MFA of photosynthetic metabolism. While custom gas chambers design has addressed these challenges in various model plants, no similar tools were developed for liquid photosynthetic cultures (e.g., algae, cyanobacteria), where diffusion and equilibration of inorganic carbon species in the medium entails a new dimension of complexity. Recently, a novel tailor-made microfluidics labelling system has been introduced, supplying short 13CO2 pulses at steady state, and resolving fluxes across most photosynthetic metabolic pathways in algae. The system involves injecting algal cultures and medium containing pre-equilibrated inorganic 13C into a microfluidic mixer, followed by rapid metabolic quenching, enabling precise seconds-level label pulses. This was complemented by a 13CO2-bubbling-based open labelling system (photobioreactor), allowing long pulses (minutes-hours) required for investigating fluxes into central C metabolism and major products. This combined labelling procedure provides a comprehensive fluxome cover for most algal photosynthetic and central C metabolism pathways, thus allowing comparative flux analyses across algae and plants.
    Keywords:  Algae; Isotope labelling; Metabolomics; Non-stationary 13C-metabolic flux analysis; Photosynthesis
    DOI:  https://doi.org/10.21769/BioProtoc.4808
  13. J Chromatogr A. 2023 Oct 11. pii: S0021-9673(23)00587-3. [Epub ahead of print]1708 464362
    Systematic characterization of Lysergic Acid Diethylamide metabolites in Caenorhabditis elegans by ultra-high performance liquid chromatography coupled with high-resolution tandem mass spectrometry.
    Christiane Martins de Vasconcellos Silveira, Vanessa Farelo Dos Santos, Isis Moraes Ornelas, Beatriz de Sá Carrilho, Matheus Antonio Vieira de Castro Ventura, Henrique Marcelo Gualberto Pereira, Stevens Kastrup Rehen, Magno Junqueira.
      Psychedelic compounds have gained renewed interest for their potential therapeutic applications, but their metabolism and effects on complex biological systems remain poorly understood. Here, we present a systematic characterization of Lysergic Acid Diethylamide (LSD) metabolites in the model organism Caenorhabditis elegans using state-of-the-art analytical techniques. By employing ultra-high performance liquid chromatography coupled with high-resolution tandem mass spectrometry, we putatively identified a range of LSD metabolites, shedding light on their metabolic pathways and offering insights into their pharmacokinetics. Our study demonstrates the suitability of Caenorhabditis elegans as a valuable model system for investigating the metabolism of psychedelic compounds and provides a foundation for further research on the therapeutic potential of LSD.
    Keywords:  C. elegans; LSD; UHPLC-HRMS/MS; metabolism
    DOI:  https://doi.org/10.1016/j.chroma.2023.464362
  14. Anal Chem. 2023 Sep 19.
    Single-Cell Lipidomics Using Analytical Flow LC-MS Characterizes the Response to Chemotherapy in Cultured Pancreatic Cancer Cells.
    Kyle D G Saunders, Johanna von Gerichten, Holly-May Lewis, Priyanka Gupta, Matt Spick, Catia Costa, Eirini Velliou, Melanie J Bailey.
      In this work, we demonstrate the development and first application of nanocapillary sampling followed by analytical flow liquid chromatography-mass spectrometry for single-cell lipidomics. Around 260 lipids were tentatively identified in a single cell, demonstrating remarkable sensitivity. Human pancreatic ductal adenocarcinoma cells (PANC-1) treated with the chemotherapeutic drug gemcitabine can be distinguished from controls solely on the basis of their single-cell lipid profiles. Notably, the relative abundance of LPC(0:0/16:0) was significantly affected in gemcitabine-treated cells, in agreement with previous work in bulk. This work serves as a proof of concept that live cells can be sampled selectively and then characterized using automated and widely available analytical workflows, providing biologically relevant outputs.
    DOI:  https://doi.org/10.1021/acs.analchem.3c02854
  15. Metabolomics. 2023 Sep 20. 19(10): 84
    Staging of colorectal cancer using lipid biomarkers and machine learning.
    Sanduru Thamarai Krishnan, David Winkler, Darren Creek, Dovile Anderson, Chandra Kirana, Guy J Maddern, Kevin Fenix, Ehud Hauben, David Rudd, Nicolas Hans Voelcker.
       INTRODUCTION: Colorectal cancer (CRC) is the third most commonly diagnosed cancer worldwide. Alteration in lipid metabolism and chemokine expression are considered hallmark characteristics of malignant progression and metastasis of CRC. Validated diagnostic and prognostic biomarkers are urgently needed to define molecular heterogeneous CRC clinical stages and subtypes, as liver dominant metastasis has poor survival outcomes.
    OBJECTIVES: The aim of this study was to integrate lipid changes, concentrations of chemokines, such as platelet factor 4 and interleukin 8, and gene marker status measured in plasma samples, with clinical features from patients at different CRC stages or who had progressed to stage-IV colorectal liver metastasis (CLM).
    METHODS: High-resolution liquid chromatography-mass spectrometry (HR-LC-MS) was used to determine the levels of candidate lipid biomarkers in each CRC patient's preoperative plasma samples and combined with chemokine, gene and clinical data. Machine learning models were then trained using known clinical outcomes to select biomarker combinations that best classify CRC stage and group.
    RESULTS: Bayesian neural net and multilinear regression-machine learning identified candidate biomarkers that classify CRC (stages I-III), CLM patients and control subjects (cancer-free or patients with polyps/diverticulitis), showing that integrating specific lipid signatures and chemokines (platelet factor-4 and interluken-8; IL-8) can improve prognostic accuracy. Gene marker status could contribute to disease prediction, but requires ubiquitous testing in clinical cohorts.
    CONCLUSION: Our findings demonstrate that correlating multiple disease related features with lipid changes could improve CRC prognosis. The identified signatures could be used as reference biomarkers to predict CRC prognosis and classify stages, and monitor therapeutic intervention.
    Keywords:  Biomarker; Cancer Subtypes; Lipidomics; Machine learning; Metastatic colorectal cancer classification; Multi-omics
    DOI:  https://doi.org/10.1007/s11306-023-02049-z
  16. J Am Soc Mass Spectrom. 2023 Sep 21.
    In-Depth Characterization of Sphingoid Bases via Radical-Directed Dissociation Tandem Mass Spectrometry.
    Jing Zhao, Lipeng Qiao, Yu Xia.
      Sphingoid base (SPH) is a basic structural unit of all classes of sphingolipids. A sphingoid base typically consists of an aliphatic chain that may be desaturated between C4 and C5, an amine group at C2, and a variable number of OH groups located at C1, C3, and C4. Variations in the chain length and the occurrence of chemical modifications, such as methyl branching, desaturation, and hydroxylation, lead to a large structural diversity and distinct functional properties of sphingoid bases. However, conventional tandem mass spectrometry (MS/MS) via collision-induced dissociation (CID) faces challenges in characterizing these modifications. Herein, we developed an MS/MS method based on CID-triggered radical-directed dissociation (RDD) for in-depth characterization of sphingoid bases. The method involves derivatizing the sphingoid amine with 3-(2,2,6,6-tetramethylpiperidin-1-yloxymethyl)-picolinic acid 2,5-dioxopyrrolidin-1-yl ester (TPN), followed by MS2 CID to unleash the pyridine methyl radical moiety for subsequent RDD. This MS/MS method was integrated on a reversed-phase liquid chromatography-mass spectrometry workflow and further applied for in-depth profiling of total sphingoid bases in bovine heart and Caenorhabditis elegans. Notably, we identified and relatively quantified a series of unusual sphingoid bases, including SPH id17:2 (4,13) and SPH it19:0 in C. elegans, revealing that the metabolic pathways of sphingolipids are more diverse than previously known.
    Keywords:  methyl branching; radical-directed dissociation; sphingoid base; tandem mass spectrometry
    DOI:  https://doi.org/10.1021/jasms.3c00274
  17. Cell Commun Signal. 2023 Sep 21. 21(1): 249
    Epigenetic meets metabolism: novel vulnerabilities to fight cancer.
    Domenica Scumaci, Qingfei Zheng.
      Histones undergo a plethora of post-translational modifications (PTMs) that regulate nucleosome and chromatin dynamics and thus dictate cell fate. Several evidences suggest that the accumulation of epigenetic alterations is one of the key driving forces triggering aberrant cellular proliferation, invasion, metastasis and chemoresistance pathways. Recently a novel class of histone "non-enzymatic covalent modifications" (NECMs), correlating epigenome landscape and metabolic rewiring, have been described. These modifications are tightly related to cell metabolic fitness and are able to impair chromatin architecture. During metabolic reprogramming, the high metabolic flux induces the accumulation of metabolic intermediate and/or by-products able to react with histone tails altering epigenome homeostasis. The accumulation of histone NECMs is a damaging condition that cancer cells counteracts by overexpressing peculiar "eraser" enzymes capable of removing these modifications preserving histones architecture. In this review we explored the well-established NECMs, emphasizing the role of their corresponding eraser enzymes. Additionally, we provide a parterre of drugs aiming to target those eraser enzymes with the intent to propose novel routes of personalized medicine based on the identification of epi-biomarkers which might be selectively targeted for therapy. Video Abstract.
    Keywords:  Cancer onset and progression; Histone non-enzymatic covalent modification; Histone post-translational modification; Metabolic reprogramming
    DOI:  https://doi.org/10.1186/s12964-023-01253-7
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