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Methodological Aspects of μLC-MS/MS for Wide-Scale Proteomic Analysis of Anthracycline-Induced Cardiomyopathy

. 2025 Apr 01 ; 10 (12) : 11980-11993. [epub] 20250318

Status PubMed-not-MEDLINE Language English Country United States Media electronic-ecollection

Document type Journal Article

The efforts to utilize microflow liquid chromatography hyphenated to tandem mass spectrometry (μLC-MS/MS) for deep-scale proteomic analysis are still growing. In this work, two-dimensional LC separation and peptide derivatization by a tandem mass tag (TMT) were used to assess the capability of μLC-MS/MS to reveal protein changes associated with the severe chronic anthracycline cardiotoxicity phenotype in comparison with nanoflow liquid chromatography (nLC-MS/MS). The analysis of the control and anthracycline-treated rabbit myocardium by μLC-MS/MS and nLC-MS/MS allowed quantification of 3956 and 4549 proteins, respectively, with 84% of these proteins shared in both data sets. Both nLC-MS/MS and μLC-MS/MS revealed marked global proteome dysregulation in severe anthracycline cardiotoxicity, with a significant change in approximately 55% of all detected proteins. The μLC-MS/MS analysis allowed less compressed and more precise determination of the TMT channel ratio and correspondingly broader fold-change protein distribution than nLC-MS/MS. The total number of significantly changed proteins was higher in nLC-MS/MS (2498 vs 2183, 1900 proteins shared), whereas the opposite was true for a number of significantly changed proteins with a fold-change cutoff ≥ 2 (535 vs 820). The profound changes concerned mainly proteins of cardiomyocyte sarcomeres, costameres, intercalated discs, mitochondria, and extracellular matrix. In addition, distinct alterations in immune and defense response were found with a remarkable involvement of type I interferon signaling that has been recently hypothesized to be essential for anthracycline cardiotoxicity pathogenesis. Hence, μLC-MS/MS was found to be a sound alternative to nLC-MS/MS that can be useful for comprehensive mapping of global myocardial proteome alterations such as those associated with severe anthracycline cardiotoxicity.

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Tüshaus J.; Sakhteman A.; Lechner S.; The M.; Mucha E.; Krisp C.; Schlegel J.; Delbridge C.; Kuster B. A Region-resolved Proteomic Map of the Human Brain Enabled by High-throughput Proteomics. EMBO J. 2023, 42 (23), e11466510.15252/embj.2023114665. PubMed DOI PMC

Bian Y.; Bayer F. P.; Chang Y. C.; Meng C.; Hoefer S.; Deng N.; Zheng R.; Boychenko O.; Kuster B. Robust Microflow LC-MS/MS for Proteome Analysis: 38 000 Runs and Counting. Anal. Chem. 2021, 93 (8), 3686–3690. 10.1021/acs.analchem.1c00257. PubMed DOI PMC

Lenco J.; Vajrychova M.; Pimkova K.; Proksova M.; Benkova M.; Klimentova J.; Tambor V.; Soukup O. Conventional-Flow Liquid Chromatography-Mass Spectrometry for Exploratory Bottom-Up Proteomic Analyses. Anal. Chem. 2018, 90 (8), 5381–5389. 10.1021/acs.analchem.8b00525. PubMed DOI

Bian Y.; Gao C.; Kuster B. On the potential of micro-flow LC-MS/MS in proteomics. Expert Rev. Proteomics 2022, 19 (3), 153–164. 10.1080/14789450.2022.2134780. PubMed DOI

Clasen S. C.; Wald J. W. Left Ventricular Dysfunction and Chemotherapeutic Agents. Curr. Cardiol. Rep. 2018, 20 (4), 20.10.1007/s11886-018-0967-x. PubMed DOI

Pudil R. The Future Role of Cardio-oncologists. Card. Fail. Rev. 2017, 3 (2), 140–142. 10.15420/cfr.2017:16:1. PubMed DOI PMC

Zamorano J. L.; Lancellotti P.; Rodriguez Munoz D.; Aboyans V.; Asteggiano R.; Galderisi M.; Habib G.; Lenihan D. J.; Lip G. Y. H.; Lyon A. R.; et al. 2016 ESC Position Paper on cancer treatments and cardiovascular toxicity developed under the auspices of the ESC Committee for Practice Guidelines: The Task Force for cancer treatments and cardiovascular toxicity of the European Society of Cardiology (ESC). Eur. Heart J. 2016, 37 (36), 2768–2801. 10.1093/eurheartj/ehw211. PubMed DOI

Ananthan K.; Lyon A. R. The Role of Biomarkers in Cardio-Oncology. J. Cardiovasc. Transl. Res. 2020, 13 (3), 431–450. 10.1007/s12265-020-10042-3. PubMed DOI PMC

Lindsey M. L.; Mayr M.; Gomes A. V.; Delles C.; Arrell D. K.; Murphy A. M.; Lange R. A.; Costello C. E.; Jin Y. F.; Laskowitz D. T.; et al. Transformative Impact of Proteomics on Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association. Circulation 2015, 132 (9), 852–872. 10.1161/CIR.0000000000000226. PubMed DOI

Brandao S. R.; Carvalho F.; Amado F.; Ferreira R.; Costa V. M. Insights on the molecular targets of cardiotoxicity induced by anticancer drugs: A systematic review based on proteomic findings. Metabolism 2022, 134, 15525010.1016/j.metabol.2022.155250. PubMed DOI

Sterba M.; Popelova O.; Lenco J.; Fucikova A.; Brcakova E.; Mazurova Y.; Jirkovsky E.; Simunek T.; Adamcova M.; Micuda S.; et al. Proteomic insights into chronic anthracycline cardiotoxicity. J. Mol. Cell. Cardiol. 2011, 50 (5), 849–862. 10.1016/j.yjmcc.2011.01.018. PubMed DOI

Kumar S. N.; Konorev E. A.; Aggarwal D.; Kalyanaraman B. Analysis of proteome changes in doxorubicin-treated adult rat cardiomyocyte. J. Proteomics 2011, 74 (5), 683–697. 10.1016/j.jprot.2011.02.013. PubMed DOI PMC

Brandao S. R.; Reis-Mendes A.; Domingues P.; Duarte J. A.; Bastos M. L.; Carvalho F.; Ferreira R.; Costa V. M. Exploring the aging effect of the anticancer drugs doxorubicin and mitoxantrone on cardiac mitochondrial proteome using a murine model. Toxicology 2021, 459, 15285210.1016/j.tox.2021.152852. PubMed DOI

Holmgren G.; Sartipy P.; Andersson C. X.; Lindahl A.; Synnergren J. Expression Profiling of Human Pluripotent Stem Cell-Derived Cardiomyocytes Exposed to Doxorubicin-Integration and Visualization of Multi-Omics Data. Toxicol. Sci. 2018, 163 (1), 182–195. 10.1093/toxsci/kfy012. PubMed DOI

Nguyen N.; Souza T.; Verheijen M. C. T.; Gmuender H.; Selevsek N.; Schlapbach R.; Kleinjans J.; Jennen D. Translational Proteomics Analysis of Anthracycline-Induced Cardiotoxicity From Cardiac Microtissues to Human Heart Biopsies. Front. Genet. 2021, 12, 69562510.3389/fgene.2021.695625. PubMed DOI PMC

Forghani P.; Rashid A.; Sun F.; Liu R.; Li D.; Lee M. R.; Hwang H.; Maxwell J. T.; Mandawat A.; Wu R.; Salaita K.; Xu C.; et al. Carfilzomib Treatment Causes Molecular and Functional Alterations of Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. J. Am. Heart Assoc. 2021, 10 (24), e02224710.1161/JAHA.121.022247. PubMed DOI PMC

Yuan Y.; Fan S.; Shu L.; Huang W.; Xie L.; Bi C.; Yu H.; Wang Y.; Li Y. Exploration the Mechanism of Doxorubicin-Induced Heart Failure in Rats by Integration of Proteomics and Metabolomics Data. Front. Pharmacol. 2020, 11, 60056110.3389/fphar.2020.600561. PubMed DOI PMC

de Freitas Germano J.; Sharma A.; Stastna M.; Huang C.; Aniag M.; Aceves A.; Van Eyk J. E.; Mentzer R. M. Jr.; Piplani H.; Andres A. M.; et al. Proteomics of Mouse Heart Ventricles Reveals Mitochondria and Metabolism as Major Targets of a Post-Infarction Short-Acting GLP1Ra-Therapy. Int. J. Mol. Sci. 2021, 22 (16), 8711. PubMed PMC

Chen A.; Chen Z.; Xia Y.; Lu D.; Jia J.; Hu K.; Sun A.; Zou Y.; Qian J.; Ge J. Proteomics Analysis of Myocardial Tissues in a Mouse Model of Coronary Microembolization. Front. Physiol. 2018, 9, 1318.10.3389/fphys.2018.01318. PubMed DOI PMC

Shibayama J.; Yuzyuk T. N.; Cox J.; Makaju A.; Miller M.; Lichter J.; Li H.; Leavy J. D.; Franklin S.; Zaitsev A. V. Metabolic remodeling in moderate synchronous versus dyssynchronous pacing-induced heart failure: integrated metabolomics and proteomics study. PLoS One 2015, 10 (3), e011897410.1371/journal.pone.0118974. PubMed DOI PMC

Xie J.; Yan X.; Xu G.; Tian X.; Dong N.; Feng J.; Liu P.; Li M.; Zhao Y.; Wei C.; et al. ITRAQ-based proteomics reveals the potential mechanism of fluoride-induced myocardial contraction function damage. Ecotoxicol. Environ. Saf. 2020, 197, 11060510.1016/j.ecoenv.2020.110605. PubMed DOI

Li H.; Hu J.; Liu Y.; Wang X.; Tang S.; Chen X.; Niu M.; Waili N.; Bai Y.; Wei Y. Effects of prenatal hypoxia on fetal sheep heart development and proteomics analysis. Int. J. Clin. Exp. Pathol. 2018, 11 (4), 1909–1922. PubMed PMC

Dawkins J. F.; Ehdaie A.; Rogers R.; Soetkamp D.; Valle J.; Holm K.; Sanchez L.; Tremmel I.; Nawaz A.; Shehata M.; et al. Biological substrate modification suppresses ventricular arrhythmias in a porcine model of chronic ischaemic cardiomyopathy. Eur. Heart J. 2022, 43 (22), 2139–2156. 10.1093/eurheartj/ehac042. PubMed DOI PMC

Barbarics B.; Eildermann K.; Kaderali L.; Cyganek L.; Plessmann U.; Bodemeyer J.; Paul T.; Ströbel P.; Urlaub H.; Tirilomis T.; Lenz C.; Bohnenberger H.; et al. Proteomic mapping of atrial and ventricular heart tissue in patients with aortic valve stenosis. Sci. Rep 2021, 11 (1), 24389.10.1038/s41598-021-03907-3. PubMed DOI PMC

Liu J.; Lian H.; Yu J.; Wu J.; Chen X.; Wang P.; Tian L.; Yang Y.; Yang J.; Li D.; et al. Study on diverse pathological characteristics of heart failure in different stages based on proteomics. J. Cell. Mol. Med. 2022, 26 (4), 1169–1182. 10.1111/jcmm.17170. PubMed DOI PMC

Hu L. Y. R.; Kontrogianni-Konstantopoulos A. Proteomic Analysis of Myocardia Containing the Obscurin R4344Q Mutation Linked to Hypertrophic Cardiomyopathy. Front. Physiol. 2020, 11, 478.10.3389/fphys.2020.00478. PubMed DOI PMC

Jirkovsky E.; Popelova O.; Krivakova-Stankova P.; Vavrova A.; Hroch M.; Haskova P.; Brcakova-Dolezelova E.; Micuda S.; Adamcova M.; Simunek T.; et al. Chronic anthracycline cardiotoxicity: molecular and functional analysis with focus on nuclear factor erythroid 2-related factor 2 and mitochondrial biogenesis pathways. J. Pharmacol. Exp. Ther. 2012, 343 (2), 468–478. 10.1124/jpet.112.198358. PubMed DOI

Lin Y.; Liu Y.; Li J.; Zhao Y.; He Q.; Han W.; Chen P.; Wang X.; Liang S. Evaluation and optimization of removal of an acid-insoluble surfactant for shotgun analysis of membrane proteome. Electrophoresis 2010, 31 (16), 2705–2713. 10.1002/elps.201000161. PubMed DOI

Zecha J.; Satpathy S.; Kanashova T.; Avanessian S. C.; Kane M. H.; Clauser K. R.; Mertins P.; Carr S. A.; Kuster B. TMT Labeling for the Masses: A Robust and Cost-efficient, In-solution Labeling Approach. Mol. Cell. Proteomics 2019, 18 (7), 1468–1478. 10.1074/mcp.TIR119.001385. PubMed DOI PMC

Cox J.; Mann M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26 (12), 1367–1372. 10.1038/nbt.1511. PubMed DOI

Cox J.; Neuhauser N.; Michalski A.; Scheltema R. A.; Olsen J. V.; Mann M. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 2011, 10 (4), 1794–1805. 10.1021/pr101065j. PubMed DOI

Tyanova S.; Temu T.; Sinitcyn P.; Carlson A.; Hein M. Y.; Geiger T.; Mann M.; Cox J. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 2016, 13 (9), 731–740. 10.1038/nmeth.3901. PubMed DOI

Szklarczyk D.; Gable A. L.; Nastou K. C.; Lyon D.; Kirsch R.; Pyysalo S.; Doncheva N. T.; Legeay M.; Fang T.; Bork P.; et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021, 49 (D1), D605–D612. 10.1093/nar/gkaa1074. PubMed DOI PMC

Smyth G. K. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat. Appl. Genet. Mol. Biol. 2004, 3, 1.10.2202/1544-6115.1027. PubMed DOI

Kammers K.; Cole R. N.; Tiengwe C.; Ruczinski I. Detecting Significant Changes in Protein Abundance. EuPA Open Proteom. 2015, 7, 11–19. 10.1016/j.euprot.2015.02.002. PubMed DOI PMC

R Core Team (2020) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing: Vienna, Austria. https://www.r-project.org/.

Cox J.; Mann M. 1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data. BMC Bioinformatics 2012, 13 Suppl 16 (Suppl 16), S12.10.1186/1471-2105-13-S16-S12. PubMed DOI PMC

Betancourt L. H.; Sanchez A.; Pla I.; Kuras M.; Zhou Q.; Andersson R.; Marko-Varga G. Quantitative Assessment of Urea In-Solution Lys-C/Trypsin Digestions Reveals Superior Performance at Room Temperature over Traditional Proteolysis at 37 degrees C. J. Proteome Res. 2018, 17 (7), 2556–2561. 10.1021/acs.jproteome.8b00228. PubMed DOI

Liu T.; Hu J.; Li H. iTRAQ-based shotgun neuroproteomics. Methods Mol. Biol. 2009, 566, 201–216. 10.1007/978-1-59745-562-6_14. PubMed DOI PMC

Nesvizhskii A. I.; Aebersold R. Interpretation of shotgun proteomic data: the protein inference problem. Mol. Cell. Proteomics 2005, 4 (10), 1419–1440. 10.1074/mcp.R500012-MCP200. PubMed DOI

Bian Y.; Zheng R.; Bayer F. P.; Wong C.; Chang Y. C.; Meng C.; Zolg D. P.; Reinecke M.; Zecha J.; Wiechmann S.; Heinzlmeir S.; Scherr J.; Hemmer B.; Baynham M.; Gingras A. C.; Boychenko O.; Kuster B.; et al. Robust, reproducible and quantitative analysis of thousands of proteomes by micro-flow LC-MS/MS. Nat. Commun. 2020, 11 (1), 157.10.1038/s41467-019-13973-x. PubMed DOI PMC

Bian Y.; The M.; Giansanti P.; Mergner J.; Zheng R.; Wilhelm M.; Boychenko A.; Kuster B. Identification of 7 000–9 000 Proteins from Cell Lines and Tissues by Single-Shot Microflow LC-MS/MS. Anal. Chem. 2021, 93 (25), 8687–8692. 10.1021/acs.analchem.1c00738. PubMed DOI

Stirm M.; Fonteyne L. M.; Shashikadze B.; Lindner M.; Chirivi M.; Lange A.; Kaufhold C.; Mayer C.; Medugorac I.; Kessler B.; et al. A scalable, clinically severe pig model for Duchenne muscular dystrophy. Dis. Model. Mech. 2021, 14 (12), dmm04928510.1242/dmm.049285. PubMed DOI PMC

Chaanine A. H.; Higgins L.; Markowski T.; Harman J.; Kachman M.; Burant C.; Navar L. G.; Busija D.; Delafontaine P. Multi-Omics Approach Profiling Metabolic Remodeling in Early Systolic Dysfunction and in Overt Systolic Heart Failure. Int. J. Mol. Sci. 2021, 23 (1), 235.10.3390/ijms23010235. PubMed DOI PMC

Kollipara L.; Zahedi R. P. Protein carbamylation: in vivo modification or in vitro artefact?. Proteomics 2013, 13 (6), 941–944. 10.1002/pmic.201200452. PubMed DOI

Chen X.; Sun Y.; Zhang T.; Shu L.; Roepstorff P.; Yang F. Quantitative Proteomics Using Isobaric Labeling: A Practical Guide. Genomics Proteomics Bioinformatics 2021, 19 (5), 689–706. 10.1016/j.gpb.2021.08.012. PubMed DOI PMC

Wenger C. D.; Lee M. V.; Hebert A. S.; McAlister G. C.; Phanstiel D. H.; Westphall M. S.; Coon J. J. Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging. Nat. Methods 2011, 8 (11), 933–935. 10.1038/nmeth.1716. PubMed DOI PMC

Lim M. Y.; Paulo J. A.; Gygi S. P. Evaluating False Transfer Rates from the Match-between-Runs Algorithm with a Two-Proteome Model. J. Proteome Res. 2019, 18 (11), 4020–4026. 10.1021/acs.jproteome.9b00492. PubMed DOI PMC

Mertins P.; Udeshi N. D.; Clauser K. R.; Mani D. R.; Patel J.; Ong S. e.; Jaffe J. D.; Carr S. A. iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics. Mol. Cell. Proteomics 2012, 11 (6), M111.014423.10.1074/mcp.M111.014423. PubMed DOI PMC

Karp N. A.; Huber W.; Sadowski P. G.; Charles P. D.; Hester S. V.; Lilley K. S. Addressing accuracy and precision issues in iTRAQ quantitation. Mol. Cell. Proteomics 2010, 9 (9), 1885–1897. 10.1074/mcp.M900628-MCP200. PubMed DOI PMC

Ting L.; Rad R.; Gygi S. P.; Haas W. MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics. Nat. Methods 2011, 8 (11), 937–940. 10.1038/nmeth.1714. PubMed DOI PMC

McAlister G. C.; Nusinow D. P.; Jedrychowski M. P.; Wuhr M.; Huttlin E. L.; Erickson B. K.; Rad R.; Haas W.; Gygi S. P. MultiNotch MS3 enables accurate, sensitive, and multiplexed detection of differential expression across cancer cell line proteomes. Anal. Chem. 2014, 86 (14), 7150–7158. 10.1021/ac502040v. PubMed DOI PMC

Deshmukh A. S.; Murgia M.; Nagaraj N.; Treebak J. T.; Cox J.; Mann M. Deep proteomics of mouse skeletal muscle enables quantitation of protein isoforms, metabolic pathways, and transcription factors. Mol. Cell. Proteomics 2015, 14 (4), 841–853. 10.1074/mcp.M114.044222. PubMed DOI PMC

Schork K.; Podwojski K.; Turewicz M.; Stephan C.; Eisenacher M.. Important Issues in Planning a Proteomics Experiment: Statistical Considerations of Quantitative Proteomic Data. In Quantitative Methods in Proteomics; Marcus K.; Eisenacher M.; Sitek B., Eds.; Methods in Molecular Biology; Springer US: New York, NY, 2021; Vol. 2228, pp 1–20. PubMed

Lei Y.; VanPortfliet J. J.; Chen Y. F.; Bryant J. D.; Li Y.; Fails D.; Torres-Odio S.; Ragan K. B.; Deng J.; Mohan A.; Wang B.; Brahms O. N.; Yates S. D.; Spencer M.; Tong C. W.; Bosenberg M. W.; West L. C.; Shadel G. S.; Shutt T. E.; Upton J. W.; Li P.; West A. P.; et al. Cooperative sensing of mitochondrial DNA by ZBP1 and cGAS promotes cardiotoxicity. Cell 2023, 186 (14), 3013–3032 e3022. 10.1016/j.cell.2023.05.039. PubMed DOI PMC

Shamseddine A.; Patel S. H.; Chavez V.; Moore Z. R.; Adnan M.; Di Bona M.; Li J.; Dang C. T.; Ramanathan L. V.; Oeffinger K. C.; et al. Innate immune signaling drives late cardiac toxicity following DNA-damaging cancer therapies. J. Exp. Med. 2023, 220 (3), e2022080910.1084/jem.20220809. PubMed DOI PMC

Barallobre-Barreiro J.; Didangelos A.; Schoendube F. A.; Drozdov I.; Yin X.; Fernandez-Caggiano M.; Willeit P.; Puntmann V. O.; Aldama-Lopez G.; Shah A. M.; et al. Proteomics analysis of cardiac extracellular matrix remodeling in a porcine model of ischemia/reperfusion injury. Circulation 2012, 125 (6), 789–802. 10.1161/CIRCULATIONAHA.111.056952. PubMed DOI

Kelso E. J.; Geraghty R. F.; McDermott B. J.; Cameron C. H.; Nicholls D. P.; Silke B. Characterisation of a cellular model of cardiomyopathy, in the rabbit, produced by chronic administration of the anthracycline, epirubicin. J. Mol. Cell. Cardiol. 1997, 29 (12), 3385–3397. 10.1006/jmcc.1997.0563. PubMed DOI

Sterba M.; Popelova O.; Vavrova A.; Jirkovsky E.; Kovarikova P.; Gersl V.; Simunek T. Oxidative stress, redox signaling, and metal chelation in anthracycline cardiotoxicity and pharmacological cardioprotection. Antioxid. Redox Signal. 2013, 18 (8), 899–929. 10.1089/ars.2012.4795. PubMed DOI PMC

Zhang S.; Liu X.; Bawa-Khalfe T.; Lu L. S.; Lyu Y. L.; Liu L. F.; Yeh E. T. Identification of the molecular basis of doxorubicin-induced cardiotoxicity. Nat. Med. 2012, 18 (11), 1639–1642. 10.1038/nm.2919. PubMed DOI

Perez-Riverol Y.; Csordas A.; Bai J.; Bernal-Llinares M.; Hewapathirana S.; Kundu D. J.; Inuganti A.; Griss J.; Mayer G.; Eisenacher M.; et al. The PRIDE database and related tools and resources in 2019: improving support for quantification data. Nucleic Acids Res. 2019, 47 (D1), D442–D450. 10.1093/nar/gky1106. PubMed DOI PMC

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