Creating a Pro-Regenerative Tissue Microenvironment: Local Control is the Key.

The potential of regenerative medicine to restore tissues and organs compromised or lost due to disease, injury or aging has captured the public imagination and attracted many multidisciplinary researchers to the field. However, despite significant promise, translation to the clinic has so far been modest. This slow progress might at least in part be due to the technical complexity of traditional cell-based approaches, which require in vitro manufacturing of large quantities of high-quality clinical grade cells for transplantation, ensuring targeted delivery and survival of these cells in vivo, as well as promoting functional morphogenesis of the new tissues and their integration with host tissues. The regulatory path for Food and Drug Administration (FDA) approval of such complex therapies could be arduous. While cell-based therapies remain an important goal for the future of regenerative medicine, an alternative class of therapies—referred to as autotherapies (Lumelsky et al., 2018)—that does not rely on exogenous cell transplantation, but instead attempts to pattern a pro-regenerative tissue microenvironment to optimize endogenous regeneration, might have a simplified regulatory path, and holds significant promise for achieving functional tissue regeneration in vivo. While the autotherapies idea is not new (Krzyszczyk et al., 2018; Liu and Segura, 2020; Fetz and Bowlin, 2021), it is particularly important and timely now. Many recent scientific and technical advances, including those in the basic biology of tissue regeneration, single-cell analyses, data science, and bioinformatics, as well as in material science and bioengineering, could propel the field forward and fulfill the therapeutic promise of this class of therapies. Multiple Players in the Pro-Regenerative Microenvironment It is widely recognized that tissue maintenance and regeneration in mammals is controlled by multi-component microenvironmental systems collectively referred to as stem cell niches. In these niches, stem and progenitor cells, various somatic cell types, extracellular matrices (ECMs), and signaling mediators reciprocally interact with each other (Durand et al., 2018; Ruddy and Morshead, 2018). The niches generally remain quiescent under normal adult homeostasis, but injury or disease remodel their regulatory landscapes, and in some cases, induce elements of embryonic or early postnatal regulatory states. This creates a pro-regenerative microenvironment that allows activation, proliferation and differentiation of stem and progenitor cells to build new functional tissues (Nusse et al., 2018; Abbasi et al., 2020; Fuchs and Blau, 2020; Massenet et al., 2021). The regenerative potential of tissues varies widely depending on the species, age, and type of tissue. In some lower vertebrates, new body parts can be completely reconstituted following resection. In mammals, including humans, some tissues, including skin, liver, and oral and intestinal mucosa, regenerate well, while others -such as heart, pancreas, and teeth hardly regenerate at all (Iismaa et al., 2018). Biological age is also a key factor in determining regeneration outcome independent of tissue type, with progressively diminishing regenerative capacity throughout a lifespan (Sousounis et al., 2014). An extensive body of work has identified numerous biochemical and biophysical mediators, signaling pathways and cell types responsible for control of the pro-regenerative microenvironment in the niche across different species. Many of these mediators and signaling pathways are shared among lower vertebrates and mammals Progress in this field has been greatly facilitated by recent advances in single cell analyses, bioinformatics, and system biology using a variety of organs and animal regeneration models in lower vertebrates, zebrafish and mice, as well as in vitro 3-dimensional tissue models such as organoids and tissue chips (Godwin et al., 2013; Mahmoud et al., 2015; Nowoshilow and Tanaka, 2020; Brezitski et al., 2021; Thompson and Takebe, 2021). These studies revealed that regeneration outcomes are determined by a combination of numerous interdependent niche parameters, which precisely align in a spatial and temporal fashion for maintenance and restoration of tissue structure and function. These parameters include the availability and homing of stem and other cell types, including immune cells to the site of injury (Wu et al., 2017; Yin et al., 2017), specific patterns of the ECM remodeling and degradation (Hematti et al., 2018), a timely resolution of acute inflammation and prevention of the onset of chronic inflammation (Kizil et al., 2015), and the establishment of effective vascular supply and neuronal input to the regenerating tissue (Rezza et al., 2014; Mahmoud et al., 2015; Ribatti et al., 2021). Interestingly, recent results in a variety of model systems strongly suggest that a contribution of the immune system to endogenous tissue regeneration extends beyond its modulation of post-injury inflammation, and also includes direct crosstalk between the innate and adaptive immune systems and the regenerative machinery of the niche to promote or inhibit regeneration (Naik et al., 2018). Failure to achieve a proper patterning of the pro-regenerative microenvironment results in defective regeneration, which manifests itself in tissue fibrosis and scarring instead of productive restoration of functional tissue. Given the complexity of endogenous tissue regeneration mechanisms, it is not surprising that the outcomes of regenerative medicine therapies in human populations have been variable, as it is now known that they are highly impacted by genetics, age and co-morbidities, including diabetes, obesity and disfunctions of the immune system (Fadini et al., 2020; Masson and Krawetz, 2020). Thus, for the clinical success of regenerative medicine, it will be important to develop and test promising therapies in disease-relevant animal models, including large animal models, that reflect elements of the heterogeneity of human populations (Ribitsch et al., 2020).