Cell therapy, which relies on the transplantation of healthy cells to replace the function of diseased or damaged cells, holds great promise for treating various diseases and conditions. However, one of the major limitations of this approach is the in vitro generation of functionally specific cell sub-populations for transplantation. We have developed a computational platform to guide cell engineering for cell therapy. This platform relies on a single cell gene regulatory network model to identify optimal sets of conversion factors to generate specific cell subpopulations. We are currently applying this methodology to projects relevant for cell therapies including the in vitro generation of corneal limbus stem cells from cultured epithelial keratinocytes. The derived experimental protocol will be further optimized and used for treating patients who have lost their corneal limbus stem cells due to injury or burn. Further, we will apply our platform to produce corticospinal tract neuron progenitors in vitro for transplantation in cases of spinal cord injuries. Finally, we have generated predictions for the efficient conversion of cardiac right ventricular cells into left counterparts, which are currently being experimentally validated. The outcome of this project will be essential for designing strategies to treat patients with cardiovascular diseases.

The quantification of the biological age of cells yields great promises for accelerating the discovery of novel rejuvenation strategies. In this context, we have developed the first multi-tissue RNA clock that measures the biological, rather than chronological, age of cells from their transcriptional profiles by evaluating key cellular processes. Moreover, we have also implemented a fibroblast-specific RNA clock to predict genes that can act as rejuvenation factors for human fibroblasts.

Brain rejuvenation to counteract neurodegeneration

By interrogating transcriptional changes in the old human brain compared to its young counterpart, we have identified key signalling pathways and molecules that are dysregulated during brain aging. Moreover, using a computational tool recently developed in our lab, we have predicted cocktails of chemical compounds that can potentially target these dysregulated pathways to rejuvenate the brain. Experimental validation of these predictions is currently being carried out in human cells and in animal models.

Considering that aging is an important risk factor of neurodegenerative diseases, our next goal is to apply this approach to a mouse Alzheimer’s and Parkinson’s disease model as a therapeutic strategy to counteract disease pathology.

Modulating the cytokine storm in inflammatory diseases

Dysregulations in the inflammatory response of the body could progress toward a hyperinflammatory condition associated with increased severity and mortality. In particular, in the case of COVID-19 we built a comprehensive cell-cell interaction map of the immune response in patients with mild and severe symptoms to identify positive feedback loops amplifying the immune response, which led to the discovery of two novel therapeutic targets. Further, we will apply a similar strategy to modulate hyperinflammation in the systemic inflammatory response syndrome (SIRS), which is a complex disorder with nonspecific symptoms. Currently, we lack targeted therapy for SIRS not only because triggers are often unknown, but also because host responses to triggers may vary. In this regard, we collected PBMCs from a cohort of patients in order to identify common repurposable drugs targeting key molecules to reduce inflammation. We are a part of an EU-funded consortium in which experiments will be conducted to validate the computational predictions and provide mechanistic insights into patient treatments.

Increasing the differentiation capacity of stem cells in congenital disorders

Congenital disorders affect an estimated 6% of babies worldwide resulting in hundreds of thousands of associated deaths. In this regard, mutations in specific genes can lead to abnormal organogenesis characterized by an impaired differentiation potential of progenitor cells. We have developed a network-based computational method to predict lineage-specifying transcription factors that are malfunctioning in these disorders. In particular, following this approach we identified key cell fate determinants whose failure disrupt cardiac development, providing a framework to investigate congenital heart defects. Moreover, we applied this method to one of the forms of mitochondrial DNA-associated Leigh syndrome (MILS) characterized by an impaired differentiation capacity of neural progenitor cells. Our predictions identified cell fate determinants in these cells whose upregulation increases neurogenesis as well as neuronal morphogenesis, and thus can be used as a therapeutic target in this disorder. We are part of an EU-funded consortium project in which our computational predictions are being validated with the goal of identifying repurposable compounds for treating MILS.