OPINION article

Front. Cardiovasc. Med., 13 May 2022

Sec. General Cardiovascular Medicine

Volume 9 - 2022 | https://doi.org/10.3389/fcvm.2022.887236

Different Effects on Protein Expression of CDR132L, an Antisense Inhibitor of miR-132, and Standard Therapies for Myocardial Infarction

  • 1. ICREC (Heart Failure and Cardiac Regeneration) Research Programme, Health Sciences Research Institute Germans Trias i Pujol (IGTP), Barcelona, Spain

  • 2. Hospital Universitari Germans Trias i Pujol, Barcelona, Spain

  • 3. Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy

  • 4. Cardiology Division, Fondazione Toscana Gabriele Monasterio, Pisa, Italy

  • 5. CIBER Cardiovascular, Instituto de Salud Carlos III, Madrid, Spain

Introduction

Heart failure (HF) development is a common complication of myocardial infarction (MI), which warrants a search for novel therapies able to prevent left ventricular remodeling after an MI. In a recent article, Batkai et al. evaluated CDR132L, a synthetic antisense inhibitor of miR-132, in a pig model of reperfused MI (1). The authors report that monthly intravenous administration of CDR132L is safe and effective in preventing HF development. They expect CDR132L to have an additive, and possibly synergistic, effect to standard-of-care therapies [beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (ACEi/ARB), and mineralocorticoid receptor antagonists (MRA)] because of their distinct first targets. Nonetheless, a degree of overlap in the final effects of CDR132L and current therapies might exist, given that ACEi/ARB and MRA ultimately modulate myocardial inflammation and fibrosis, as CDR132L do (1).

Transcriptomic and Bioinformatic Perspective on CDR132L Targeted Therapy

We assessed this point by searching for similar changes in protein expression between MI therapies and CDR132L.

We retrieved the 14 mRNAs significantly altered in the myocardium of pigs receiving CDR132L compared with control pigs: BMPR2, ADRA1D, GCLC, CD44, PRDX1, ECM1, LEP, GATA3, GPX1, EIF4G1, ACE2, HMOX1, RTN4, and LIFR. Except for RTN4, all these mRNAs were downregulated by CDR132L (1). We assumed a close correlation between changes in mRNA levels and the expression of the corresponding proteins, as previously demonstrated (2). By using massive public databases, such as Drugbank (3), the Open Targets Platform (4) and the Human Protein Atlas (5), we identified all approved, investigational and experimental drugs reported to modulate the expression of at least one of these 14 proteins in any setting (Table 1).

Table 1

Protein identifierProtein name# drugs targeting the proteinDrug nameEffect
ADRA1DAdrenoceptor alpha 5 1D25Dapiprazole
Tamsulosin
Methotrimeprazine
Doxazosin
Terazosin
Alfuzosin
Dronedarone
Silodosin
Prazosin
Nicardipine
Amitriptyline
Nortriptyline
Imipramine
Doxepin
Epinephrine
Carvedilol
Fenoldopam
Cabergoline
Methoxamine
Phenoxybenzamine
Phentolamine
Quinidine
Verapamil
Racepinephrine
Pizotifen
Downregulation
ACE2Angiotensin I converting enzyme (peptidyl-dipeptidase A) 24SPP1148 N-(2-Aminoethyl)-1-aziridineethanamine
Chloroquine
Hydroxychloroquine
Downregulation
PRDX1Peroxiredoxin 13Copper
Zinc
Artenimol
Downregulation
BMPR2Bone morphogenetic protein receptor, type II2
Dibotermin alfa
Fostamatinib
Downregulation
CD44CD44 molecule2Hyaluronic acid
Bivatuzumab
Downregulation
GCLCGlutamate-cysteine ligase1CysteineDownregulation
GATA3GATA binding protein 31PyrrothiogatainDownregulation
ECM1Extracellular matrix protein 10––
LEPLeptin0––
GPX1Glutathione peroxidase 10––
EIF4G1Eukaryotic translation initiation factor 4 gamma 10––
HMOX1Heme oxygenase 9 (decycling) 10––
LIFRLeukemia inhibitory factor receptor alpha0––
RTN4Reticulon 40––

All drugs/compounds that target one or more of the proteins encoded by the 14 mRNAs candidates.

Discussion

We did not find any drug modulating more than one of the 14 proteins at the same time. Therefore, no drug, including ACEi/ARB or MRA, proved able to mimic the effects of CDR132L on protein expression. This finding corroborates the conclusion that CDR132L might have an additive or synergistic action to standard drugs, given the different effects on the profiles of protein expression.

Next, we performed a protein-protein interaction analysis to know if the candidates were biologically related to each other. Then, by using unsupervised algorithms (K-means clustering, elbow method K = 4) we wanted to assess if these interactions corresponded to proteins grouped in the same cluster (and thus share similar biological properties or pathways) or are among proteins from distinct clusters that could indicate more complex biological mechanisms at play. Here we found that HMOX1, GPX1, GCLC, and PRDX1 work to tightly regulate endothelial cell proliferation [false discovery rate (FDR) = 0.002] and hydrogen peroxide catabolic processes (FDR = 0.001). Although we could not find any report on novel drugs or compounds acting to modulate this specific cluster (or the individual proteins), this analysis indicates that a drug targeting them could be highly specific and a possible novel treatment in HF.

Funding

This work was supported in part by grants from MICINN (PID2019-110137RB-I00 and PLEC2021-008194), Instituto de Salud Carlos III (PIC18/00014, ICI19/00039, ICI20/00135, PI21/01700, and PI21/01703), Red RICORS (PI21/01703), CIBERCV (CB16/11/00403) as a part of the Plan Nacional de I + D + I, and it was co-funded by ISCIII-SubdirecciĂłn General de EvaluaciĂłn y el Fondo Europeo de Desarrollo Regional (FEDER) and AGAUR (2017-SGR-483 and 2019PROD00122).

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Statements

Author contributions

OI-E and AA contributed to conception and design of the study. OI-E performed the in silico analysis. AA wrote the first draft of the manuscript. OI-E, AA, and AB-G wrote sections of the manuscript. AB-G supervised the study. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  • 1.

    BatkaiSGenschelCViereckJRumpSBärCBorchertTet al. CDR132L improves systolic and diastolic function in a large animal model of chronic heart failure. Eur Heart J. (2020) 42:192–201. 10.1093/eurheartj/ehaa791

  • 2.

    KoussounadisALangdonSPUmIHHarrisonDJSmithVA. Relationship between differentially expressed mRNA and mRNA-protein correlations in a xenograft model system. Sci Rep. (2015) 5:10775. 10.1038/srep10775

  • 3.

    WishartDSFeunangYDGuoACLoEJMarcuAGrantJRet al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. (2018) 46:D1074–82. 10.1093/nar/gkx1037

  • 4.

    OchoaDHerculesACarmonaMSuvegesDGonzalez-UriarteAMalangoneCet al. Open Targets platform: supporting systematic drug–target identification and prioritization. Nucleic Acids Res. (2021) 49:D1302–10. 10.1093/nar/gkaa1027

  • 5.

    ThulPJĂ…kessonLWikingMMahdessianDGeladakiAAit BlalHet al. A subcellular map of the human proteome. Science. (2017) 356:eaal3321. 10.1126/science.aal3321

Summary

Keywords

heart failure, CDR132L, therapy, myocardial infarction, models

Citation

Iborra-Egea O, Aimo A and Bayes-Genis A (2022) Different Effects on Protein Expression of CDR132L, an Antisense Inhibitor of miR-132, and Standard Therapies for Myocardial Infarction. Front. Cardiovasc. Med. 9:887236. doi: 10.3389/fcvm.2022.887236

Received

01 March 2022

Accepted

28 April 2022

Published

13 May 2022

Volume

9 - 2022

Edited by

Emma Louise Robinson, University of Colorado, United States

Reviewed by

Amela Jusic, Luxembourg Institute of Health, Luxembourg

Updates

Copyright

*Correspondence: Antoni Bayes-Genis

†These authors have contributed equally to this work

This article was submitted to General Cardiovascular Medicine, a section of the journal Frontiers in Cardiovascular Medicine

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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