IPSC Therapy for Myocardial Infarction in Large Animal Models: Land of Hope and Dreams

Myocardial infarction is the main driver of heart failure due to ischemia and subsequent cell death, and cell-based strategies have emerged as promising therapeutic methods to replace dead tissue in cardiovascular diseases. Research in this field has been dramatically advanced by the development of laboratory-induced pluripotent stem cells (iPSCs) that harbor the capability to become any cell type. Like other experimental strategies, stem cell therapy must meet multiple requirements before reaching the clinical trial phase, and in vivo models are indispensable for ensuring the safety of such novel therapies. Specifically, translational studies in large animal models are necessary to fully evaluate the therapeutic potential of this approach; to empirically determine the optimal combination of cell types, supplementary factors, and delivery methods to maximize efficacy; and to stringently assess safety. In the present review, we summarize the main strategies employed to generate iPSCs and differentiate them into cardiomyocytes in large animal species; the most critical differences between using small versus large animal models for cardiovascular studies; and the strategies that have been pursued regarding implanted cells' stage of differentiation, origin, and technical application

Mechanisms of action of sacubitril/valsartan on cardiac remodeling : a systems biology approach

Sacubitril/Valsartan, proved superiority over other conventional heart failure management treatments, but its mechanisms of action remains obscure. In this study, we sought to explore the mechanistic details for Sacubitril/Valsartan in heart failure and post-myocardial infarction remodeling, using an in silico, systems biology approach. Myocardial transcriptome obtained in response to myocardial infarction in swine was analyzed to address post-infarction ventricular remodeling. Swine transcriptome hits were mapped to their human equivalents using Reciprocal Best (blast) Hits, Gene Name Correspondence, and InParanoid database. Heart failure remodeling was studied using public data available in gene expression omnibus (accession GSE57345, subseries GSE57338), processed using the GEO2R tool. Using the Therapeutic Performance Mapping System technology, dedicated mathematical models trained to fit a set of molecular criteria, defining both pathologies and including all the information available on Sacubitril/Valsartan, were generated. All relationships incorporated into the biological network were drawn from public resources (including KEGG, REACTOME, INTACT, BIOGRID, and MINT). An artificial neural network analysis revealed that Sacubitril/Valsartan acts synergistically against cardiomyocyte cell death and left ventricular extracellular matrix remodeling via eight principal synergistic nodes. When studying each pathway independently, Valsartan was found to improve cardiac remodeling by inhibiting members of the guanine nucleotide-binding protein family, while Sacubitril attenuated cardiomyocyte cell death, hypertrophy, and impaired myocyte contractility by inhibiting PTEN. The complex molecular mechanisms of action of Sacubitril/Valsartan upon post-myocardial infarction and heart failure cardiac remodeling were delineated using a systems biology approach. Further, this dataset provides pathophysiological rationale for the use of Sacubitril/Valsartan to prevent post-infarct remodeling. The new wonder drug in heart failure management, Sacubitril/Valsartan, rejuvenates the heart by preventing its dilation. Using data from myocardial infarction and heart failure samples, we generated a mathematical model to better understand how Sacubitril/Valsartan modulates pathological heart resize and the combined effect of the drug. Our analysis revealed that Sacubitril/Valsartan mainly acts by blocking both, cell death and the pathological makeover of the outer-membrane of the cardiac cells. These two major processes occur after a heart attack. Most importantly, we discovered a core of 8 proteins that emerge as key players in this process. A better understanding of the mechanism of novel cardiovascular drugs at the most basic level may help decipher future therapies and indications

Unraveling the Molecular Mechanism of Action of Empagliflozin in Heart Failure With Reduced Ejection Fraction With or Without Diabetes

he mechanism of action of empagliflozin in heart failure with reduced ejection fraction (HFrEF) was deciphered using deep learning in silico analyses together with in vivo validation. The most robust mechanism of action involved the sodium-hydrogen exchanger (NHE)-1 co-transporter with 94.7% accuracy, which was similar for diabetics and nondiabetics. Notably, direct NHE1 blockade by empagliflozin ameliorated cardiomyocyte cell death by restoring expression of X-linked inhibitor of apoptosis (XIAP) and baculoviral IAP repeat-containing protein 5 (BIRC5). These results were independent of diabetes mellitus comorbidity, suggesting that empagliflozin may emerge as a new treatment in HFrEF

Preclinical scenario of targeting myocardial fibrosis with chimeric antigen receptor (CAR) immunotherapy

Fibrosis is present in an important proportion of myocardial disorders. Injury activates cardiac fibroblasts, which deposit excess extracellular matrix, increasing tissue stiffness, impairing cardiac function, and leading to heart failure. Clinical therapies that directly target excessive fibrosis are limited, and more effective treatments are needed. Immunotherapy based on chimeric antigen receptor (CAR) T cells is a novel technique that redirects T lymphocytes toward specific antigens to eliminate the target cells. It is currently used in haematological cancers but has demonstrated efficacy in mouse models of hypertensive cardiac fibrosis, with activated fibroblasts as the target cells. CAR T cell therapy is associated with significant toxicities, but CAR natural killer cells can overcome efficacy and safety limitations. The use of CAR immunotherapy offers a potential alternative to current therapies for fibrosis reduction and restoration of cardiac function in patients with myocardial fibrosis

Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction

Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial-mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression

Head-to-head comparison of two engineered cardiac grafts for myocardial repair: From scaffold characterization to pre-clinical testing

Cardiac tissue engineering, which combines cells and supportive scaffolds, is an emerging treatment for restoring cardiac function after myocardial infarction (MI), although, the optimal construct remains a challenge. We developed two engineered cardiac grafts, based on decellularized scaffolds from myocardial and pericardial tissues and repopulated them with adipose tissue mesenchymal stem cells (ATMSCs). The structure, macromechanical and micromechanical scaffold properties were preserved upon the decellularization and recellularization processes, except for recellularized myocardium micromechanics that was ∼2-fold stiffer than native tissue and decellularized scaffolds. Proteome characterization of the two acellular matrices showed enrichment of matrisome proteins and major cardiac extracellular matrix components, considerably higher for the recellularized pericardium. Moreover, the pericardial scaffold demonstrated better cell penetrance and retention, as well as a bigger pore size. Both engineered cardiac grafts were further evaluated in pre-clinical MI swine models. Forty days after graft implantation, swine treated with the engineered cardiac grafts showed significant ventricular function recovery. Irrespective of the scaffold origin or cell recolonization, all scaffolds integrated with the underlying myocardium and showed signs of neovascularization and nerve sprouting. Collectively, engineered cardiac grafts -with pericardial or myocardial scaffolds- were effective in restoring cardiac function post-MI, and pericardial scaffolds showed better structural integrity and recolonization capability

Deep Learning Analyses to Delineate the Molecular Remodeling Process after Myocardial Infarction

Specific proteins and processes have been identified in post-myocardial infarction (MI) pathological remodeling, but a comprehensive understanding of the complete molecular evolution is lacking. We generated microarray data from swine heart biopsies at baseline and 6, 30, and 45 days after infarction to feed machine-learning algorithms. We cross-validated the results using available clinical and experimental information. MI progression was accompanied by the regulation of adipogenesis, fatty acid metabolism, and epithelial-mesenchymal transition. The infarct core region was enriched in processes related to muscle contraction and membrane depolarization. Angiogenesis was among the first morphogenic responses detected as being sustained over time, but other processes suggesting post-ischemic recapitulation of embryogenic processes were also observed. Finally, protein-triggering analysis established the key genes mediating each process at each time point, as well as the complete adverse remodeling response. We modeled the behaviors of these genes, generating a description of the integrative mechanism of action for MI progression. This mechanistic analysis overlapped at different time points; the common pathways between the source proteins and cardiac remodeling involved IGF1R, RAF1, KPCA, JUN, and PTN11 as modulators. Thus, our data delineate a structured and comprehensive picture of the molecular remodeling process, identify new potential biomarkers or therapeutic targets, and establish therapeutic windows during disease progression

Protein-based cardiogenic shock patient classifier

Aims Cardiogenic shock (CS) is associated with high short-term mortality and a precise CS risk stratification could guide interventions to improve patient outcome. Here, we developed a circulating protein-based score to predict short-term mortality risk among patients with CS. Methods and results Mass spectrometry analysis of 2654 proteins was used for screening in the Barcelona discovery cohort (n = 48). Targeted quantitative proteomics analyses (n = 51 proteins) were used in the independent CardShock cohort (n = 97) to derive and cross-validate the protein classifier. The combination of four circulating proteins (Cardiogenic Shock 4 proteins-CS4P), discriminated patients with low and high 90-day risk of mortality. CS4P comprises the abundances of liver-type fatty acid-binding protein, beta-2-microglobulin, fructose-bisphosphate aldolase B, and SerpinG1. Within the CardShock cohort used for internal validation, the C-statistic was 0.78 for the CardShock risk score, 0.83 for the CS4P model, and 0.84 (P = 0.033 vs. CardShock risk score) for the combination of CardShock risk score with the CS4P model. The CardShock risk score with the CS4P model showed a marked benefit in patient reclassification, with a net reclassification improvement (NRI) of 0.49 (P = 0.020) compared with CardShock risk score. Similar reclassification metrics were observed in the IABP-SHOCK II risk score combined with CS4P (NRI =0.57; P = 0.032). The CS4P patient classification power was confirmed by enzyme-linked immuno-sorbent assay (ELISA). Conclusion A new protein-based CS patient classifier, the CS4P, was developed for short-term mortality risk stratification. CS4P improved predictive metrics in combination with contemporary risk scores, which may guide clinicians in selecting patients for advanced therapies.Peer reviewe