Högskolan i Skövde

Drug repurposing has emerged as an attractive strategy in contemporary pharmaceutical research, presenting an opportunity to expedite drug discovery, minimize developmental costs, and mitigate risks associated with developing new pharmaceuticals. In this study, we investigated a novel approach based on deep learning of human transcriptomic mechanisms for systematic identification of additional therapeutic potential in preexisting drugs. We trained a composite feedforward neural network model using gene expression data sourced from the ARCHS4 compilation of the GEO, encompassing extensive human datasets. Subsequently, disease-associated gene expression data were generated from our stem cell-derived in vitro model of cardiac hypertrophy induced by Endothelin-1 stimulation. These data were employed to identify latent variables associated with genes showing differential expression due to Endothelin-1 stimulation. By examining the differential expression profiles within the model's latent space, we successfully correlated the disease signal with known drug targets found in pharmaceutical compounds cataloged in DrugBank. The model accurately encoded additional disease-related genes beyond the curated gene set, demonstrating its ability to generalize disease associations. Leveraging the model, we identified potential drug candidates, such as lapatinib and amiodarone showing promise in mitigating proBNP concentration associated with cardiac hypertrophy. This study demonstrates the power of deep learning of human transcriptomic mechanisms in swiftly identifying new therapeutic potentials for existing drugs, highlighting the pivotal role of artificial intelligence technologies in accelerating drug development for other complex medical conditions.

Efficient and specific delivery of mRNA to target tissues is critical for maximising therapeutic benefits while minimising off-target effects and systemic toxicity. Systemic administration of mRNA using lipid nanoparticles (LNPs) or extracellular vesicles (EVs) typically leads to predominant accumulation in the liver. We hypothesised that cardiac-specific EVs could promote enhanced relative cardiac enrichment of delivered mRNA compared with non-cardiac EVs or LNPs. In mice, intravenous administration of cardiac progenitor cell-derived EVs (CPC-EVs) achieved the greatest relative cardiac selectivity of modified mRNA encoding vascular endothelial growth factor A (VEGF-A) to the heart, with reduced liver accumulation relative to non-cardiac EVs and LNPs. Cytokine profiling across seven organs revealed that LNP delivery triggered a widespread pro-inflammatory response, whereas CPC-EVs elicited only a localised and limited cytokine activation, suggesting a more favourable safety profile. Furthermore, direct intramyocardial injection of CPC-EVs not only led to efficient mRNA uptake by cardiac tissue and robust VEGF-A protein expression, but also minimal transcriptomic perturbation in the cardiac tissue, as confirmed by RNA-seq. In contrast, LNPs and non-cardiac EVs induced widespread perturbation in the transcriptome of cardiac tissue. Functionally, VEGF-A mRNA delivery via CPC-EVs markedly increased CD31 and α-SMA expression and vessel formation in ex vivo aortic ring assays, confirming enhanced angiogenic potential. Together, these findings support CPC-EVs as a promising platform for achieving enhanced cardiac delivery of mRNA, with reduced liver accumulation, limited off-target transcriptomic perturbation, a more selective cytokine response, and enhanced angiogenic activity in ex vivo assays.

Modern methods of molecular diagnostics and therapy have revolutionized the field of medicine in recent years by providing more precise and effective tools for detecting and treating diseases. This progress includes a growing exploration of the body's secreted vesicles, known as extracellular vesicles (EVs), for both diagnostic and therapeutic purposes. EVs are a heterogeneous population of lipid bilayer vesicles secreted by almost every cell type studied so far. They are detected in body fluids and conditioned culture media from living cells. EVs play a crucial role in communication between cells and organs, both locally and over long distances. They are recognized for their ability to transport endogenous RNA and proteins between cells, including messenger RNA (mRNA), microRNA (miRNA), misfolded neurodegenerative proteins, and several other biomolecules. This review explores the dual utilization of EVs, serving not only for diagnostic purposes but also as a platform for delivering therapeutic molecules to cells and tissues. Through an exploration of their composition, biogenesis, and selective cargo packaging, we elucidate the intricate mechanisms behind RNA transport between cells via EVs, highlighting their potential use for both diagnostic and therapeutic applications. Finally, it addresses challenges and outlines prospective directions for the clinical utilization of EVs.

Small extracellular vesicles (sEV) derived from various cell sources have been demonstrated to enhance cardiac function in preclinical models of myocardial infarction (MI). The aim of this study was to compare different sources of sEV for cardiac repair and determine the most effective one, which nowadays remains limited. We comprehensively assessed the efficacy of sEV obtained from human primary bone marrow mesenchymal stromal cells (BM-MSC), human immortalized MSC (hTERT-MSC), human embryonic stem cells (ESC), ESC-derived cardiac progenitor cells (CPC), human ESC-derived cardiomyocytes (CM), and human primary ventricular cardiac fibroblasts (VCF), in in vitro models of cardiac repair. ESC-derived sEV (ESC-sEV) exhibited the best pro-angiogenic and anti-fibrotic effects in vitro. Then, we evaluated the functionality of the sEV with the most promising performances in vitro, in a murine model of MI-reperfusion injury (IRI) and analysed their RNA and protein compositions. In vivo, ESC-sEV provided the most favourable outcome after MI by reducing adverse cardiac remodelling through down-regulating fibrosis and increasing angiogenesis. Furthermore, transcriptomic, and proteomic characterizations of sEV derived from hTERT-MSC, ESC, and CPC revealed factors in ESC-sEV that potentially drove the observed functions. In conclusion, ESC-sEV holds great promise as a cell-free treatment for promoting cardiac repair following MI. 

Lipid nanoparticles (LNPs) are currently used to transport functional mRNAs, such as COVID-19 mRNA vaccines. The delivery of angiogenic molecules, such as therapeutic VEGF-A mRNA, to ischemic tissues for producing new blood vessels is an emerging strategy for the treatment of cardiovascular diseases. Here, the authors deliver VEGF-A mRNA via LNPs and study stoichiometric quantification of their uptake kinetics and how the transport of exogenous LNP-mRNAs between cells is functionally extended by cells’ own vehicles called extracellular vesicles (EVs). The results show that cellular uptake of LNPs and their mRNA molecules occurs quickly, and that the translation of exogenously delivered mRNA begins immediately. Following the VEGF-A mRNA delivery to cells via LNPs, a fraction of internalized VEGF-A mRNA is secreted via EVs. The overexpressed VEGF-A mRNA is detected in EVs secreted from three different cell types. Additionally, RNA-Seq analysis reveals that as cells’ response to LNP-VEGF-A mRNA treatment, several overexpressed proangiogenic transcripts are packaged into EVs. EVs are further deployed to deliver VEGF-A mRNA in vitro and in vivo. Upon equal amount of VEGF-A mRNA delivery via three EV types or LNPs in vitro, EVs from cardiac progenitor cells are the most efficient in promoting angiogenesis per amount of VEGF-A protein produced. Intravenous administration of luciferase mRNA shows that EVs could distribute translatable mRNA to different organs with the highest amounts of luciferase detected in the liver. Direct injections of VEGF-A mRNA (via EVs or LNPs) into mice heart result in locally produced VEGF-A protein without spillover to liver and circulation. In addition, EVs from cardiac progenitor cells cause minimal production of inflammatory cytokines in cardiac tissue compared with all other treatment types. Collectively, the data demonstrate that LNPs transform EVs as functional extensions to distribute therapeutic mRNA between cells, where EVs deliver this mRNA differently than LNPs. 

Cardiac hypertrophy is a condition that may contribute to the development of heart failure. In this study, we compare the gene-expression patterns of our in vitro stem-cell-based cardiac hypertrophy model with the gene expression of biopsies collected from hypertrophic human hearts. Twenty-five differentially expressed genes (DEGs) from both groups were identified and the expression of selected corresponding secreted proteins were validated using ELISA and Western blot. Several biomarkers, including CCN2, THBS1, NPPA, and NPPB, were identified, which showed significant overexpressions in the hypertrophic samples in both the cardiac biopsies and in the endothelin-1-treated cells, both at gene and protein levels. The protein-interaction network analysis revealed CCN2 as a central node among the 25 overlapping DEGs, suggesting that this gene might play an important role in the development of cardiac hypertrophy. GO-enrichment analysis of the 25 DEGs revealed many biological processes associated with cardiac function and the development of cardiac hypertrophy. In conclusion, we identified important similarities between ET-1-stimulated human-stem-cell-derived cardiomyocytes and human hypertrophic cardiac tissue. Novel putative cardiac hypertrophy biomarkers were identified and validated on the protein level, lending support for further investigations to assess their potential for future clinical applications. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Cardiac hypertrophy is an important and independent risk factor for the development of cardiac myopathy that may lead to heart failure. The mechanisms underlying the development of cardiac hypertrophy are yet not well understood. To increase the knowledge about mechanisms and regulatory pathways involved in the progression of cardiac hypertrophy, we have developed a human induced pluripotent stem cell (hiPSC)-based in vitro model of cardiac hypertrophy and performed extensive characterization using a multi-omics approach. In a series of experiments, hiPSC-derived cardiomyocytes were stimulated with Endothelin-1 for 8, 24, 48, and 72 h, and their transcriptome and secreted proteome were analyzed. The transcriptomic data show many enriched canonical pathways related to cardiac hypertrophy already at the earliest time point, e.g., cardiac hypertrophy signaling. An integrated transcriptome–secretome analysis enabled the identification of multimodal biomarkers that may prove highly relevant for monitoring early cardiac hypertrophy progression. Taken together, the results from this study demonstrate that our in vitro model displays a hypertrophic response on both transcriptomic- and secreted-proteomic levels. The results also shed novel insights into the underlying mechanisms of cardiac hypertrophy, and novel putative early cardiac hypertrophy biomarkers have been identified that warrant further investigation to assess their potential clinical relevance.

Cardiac hypertrophy is an important and independent risk factor for the development of heart failure. To better understand the mechanisms and regulatory pathways involved in cardiac hypertrophy, there is a need for improved in vitro models. In this study, we investigated how hypertrophic stimulation affected human induced pluripotent stem cell (iPSC)-derived cardiomyocytes (CMs). The cells were stimulated with endothelin-1 (ET-1) for 8, 24, 48, 72, or 96 h. Parameters including cell size, ANP-, proBNP-, and lactate concentration were analyzed. Moreover, transcriptional profiling using RNA-sequencing was performed to identify differentially expressed genes following ET-1 stimulation. The results show that the CMs increase in size by approximately 13% when exposed to ET-1 in parallel to increases in ANP and proBNP protein and mRNA levels. Furthermore, the lactate concentration in the media was increased indicating that the CMs consume more glucose, a hallmark of cardiac hypertrophy. Using RNA-seq, a hypertrophic gene expression pattern was also observed in the stimulated CMs. Taken together, these results show that hiPSC-derived CMs stimulated with ET-1 display a hypertrophic response. The results from this study also provide new molecular insights about the underlying mechanisms of cardiac hypertrophy and may help accelerate the development of new drugs against this condition.