Systems-based technologies in profiling the stem cell molecular framework for cardioregenerative medicine

Abstract

Over the last decade, advancements in stem cell biology have yielded a variety of sources for stem cell-based cardiovascular investigation. Stem cell behavior, whether to maintain its stable state of pluripotency or to prime toward the cardiovascular lineage is governed by a set of coordinated interactions between epigenetic, transcriptional, and translational mechanisms. The science of incorporating genes (genomics), RNA (transcriptomics), proteins (proteomics), and metabolites (metabolomics) data in a specific biological sample is known as systems biology. Integrating systems biology in progression with stem cell biologics can contribute to our knowledge of mechanisms that underlie pluripotency maintenance and guarantee fidelity of cardiac lineage specification. This review provides a brief summarization of OMICS-based strategies including transcriptomics, proteomics, and metabolomics used to understand stem cell fate and to outline molecular processes involved in heart development. Additionally, current efforts in cardioregeneration based on the "one-size-fits-all" principle limit the potential of individualized therapy in regenerative medicine. Here, we summarize recent studies that introduced systems biology into cardiovascular clinical outcomes analysis, allowing for predictive assessment for disease recurrence and patient-specific therapeutic response.

Figure 1. Initial developments in stem cell biology in parallel with the evolution of systems biology

Unraveling DNA structure, technological development of DNA sequencing, emergence of genomics, proteomics, and the completion of the genome project has coincided with critical discoveries in stem cell isolation and reprogramming strategies, resulting in cutting-edge efforts to utilize these findings for translational applications.

Figure 2. Integration of systems biology algorithms towards clinical application

Genomics, proteomics, metabolomics, and others allow for the elucidation of novel pathways involved in the step-wise differentiation of pluripotent stem cells to cardiomyocytes. Such bioinformatics analyses in the context of clinical translation can lead to patient-specific risk stratification and therapeutic response characterization.