Systems Biology Approaches Applied to Regenerative Medicine

Clinical adoptive regulatory T Cell therapy: State of the art, challenges, and prospective

Rejection of solid organ transplant and graft versus host disease (GvHD) continue to be challenging in post transplantation management. The introduction of calcineurin inhibitors dramatically improved recipients' short-term prognosis. However, long-term clinical outlook remains poor, moreover, the lifelong dependency on these toxic drugs leads to chronic deterioration of graft function, in particular the renal function, infections and de-novo malignancies. These observations led investigators to identify alternative therapeutic options to promote long-term graft survival, which could be used concomitantly, but preferably, replace pharmacologic immunosuppression as standard of care. Adoptive T cell (ATC) therapy has evolved as one of the most promising approaches in regenerative medicine in the recent years. A range of cell types with disparate immunoregulatory and regenerative properties are actively being investigated as potential therapeutic agents for specific transplant rejection, autoimmunity or injury-related indications. A significant body of data from preclinical models pointed to efficacy of cellular therapies. Significantly, early clinical trial observations have confirmed safety and tolerability, and yielded promising data in support of efficacy of the cellular therapeutics. The first class of these therapeutic agents commonly referred to as advanced therapy medicinal products have been approved and are now available for clinical use. Specifically, clinical trials have supported the utility of CD4⁺CD25+FOXP3+ regulatory T cells (Tregs) to minimize unwanted or overshooting immune responses and reduce the level of pharmacological immunosuppression in transplant recipients. Tregs are recognized as the principal orchestrators of maintaining peripheral tolerance, thereby blocking excessive immune responses and prevent autoimmunity. Here, we summarize rationale for the adoptive Treg therapy, challenges in manufacturing and clinical experiences with this novel living drug and outline future perspectives of its use in transplantation.

Proteomic profiling the molecular signatures of plectranthoic acid in prostate cancer cells

Among cancers, prostate cancer (PCa) is frequently detected solid tumor and a growing problem for the male population, globally. Newer treatment modalities with specific targets are required for management. Plant-derived agents/drugs have historically been useful in cancer therapeutics. Natural metabolite i.e. plectranthoic acid (PA), inhibits the proliferation of PCa cells and has potent anti-cancer potential. Herein, we aim to identify the molecular signatures of PA. Proteins from control and PA-treated PCa cells were analysed using high-throughput labeled free proteomics approach. Data was processed with the SIEVE software and thoroughly analysed by using Ingenuity pathway analysis (IPA) and PANTHER. A total of 98 unique peptides, showing >2 fold change, were identified. Results indicated that PA modulates oncogenic pro-survival and pro-apoptotic signaling pathways in PCa cells. mTOR was the major canonical pathway targeted by PA, the inhibition of which was likely to induce PA mediated apoptosis. Moreover, PA interacts with the rapamycin binding domain of mTOR, demonstrated by the molecular dynamic (MD) simulation and binding free energy calculations. Furthermore, the biological process moderated by PA with a high percentage was a metabolic process. Taken together, PA appears to have pleiotropic effects, as it modulates multiple key signaling pathways, supporting the potential usefulness. SIGNIFICANCE: Studies on the mechanism of action of therapeutic agents are crucial for drug development. These studies support the selection of a therapeutic agent, appropriate models of its efficacy, and designing of further experiments. Furthermore, information on mechanism of action may suggest strategies for combination therapies. In this regard Proteomics provide the platform for comprehensive understanding of the molecular action mechanisms of newly discovered therapeutic agents. Current research highlights the new insights into mode of action of novel therapeutic metabolite i.e. Plectranthoic acid (PA). Using labeled free proteomics approach we extracted the underlying mechanisms for the anticancer activity of PA using prostate cancer model. The result of the study will pay the way for further investigations on this potent natural compound in different cancers and will provide a root for its development as a lead.

Computational Modeling and Reverse Engineering to Reveal Dominant Regulatory Interactions Controlling Osteochondral Differentiation: Potential for Regenerative Medicine

The specialization of cartilage cells, or chondrogenic differentiation, is an intricate and meticulously regulated process that plays a vital role in both bone formation and cartilage regeneration. Understanding the molecular regulation of this process might help to identify key regulatory factors that can serve as potential therapeutic targets, or that might improve the development of qualitative and robust skeletal tissue engineering approaches. However, each gene involved in this process is influenced by a myriad of feedback mechanisms that keep its expression in a desirable range, making the prediction of what will happen if one of these genes defaults or is targeted with drugs, challenging. Computer modeling provides a tool to simulate this intricate interplay from a network perspective. This paper aims to give an overview of the current methodologies employed to analyze cell differentiation in the context of skeletal tissue engineering in general and osteochondral differentiation in particular. In network modeling, a network can either be derived from mechanisms and pathways that have been reported in the literature (knowledge-based approach) or it can be inferred directly from the data (data-driven approach). Combinatory approaches allow further optimization of the network. Once a network is established, several modeling technologies are available to interpret dynamically the relationships that have been put forward in the network graph (implication of the activation or inhibition of certain pathways on the evolution of the system over time) and to simulate the possible outcomes of the established network such as a given cell state. This review provides for each of the aforementioned steps (building, optimizing, and modeling the network) a brief theoretical perspective, followed by a concise overview of published works, focusing solely on applications related to cell fate decisions, cartilage differentiation and growth plate biology. Particular attention is paid to an in-house developed example of gene regulatory network modeling of growth plate chondrocyte differentiation as all the aforementioned steps can be illustrated. In summary, this paper discusses and explores a series of tools that form a first step toward a rigorous and systems-level modeling of osteochondral differentiation in the context of regenerative medicine.

Biological computational approaches: new hopes to improve (re)programming robustness, regenerative medicine and cancer therapeutics

Hundreds of transcription factors (TFs) are expressed and work in each cell type, but the identity of the cells is defined and maintained through the activity of a small number of core TFs. Existing reprogramming strategies predominantly focus on the ectopic expression of core TFs of an intended fate in a given cell type regardless of the state of native/somatic gene regulatory networks (GRNs) of the starting cells. Interestingly, an important point is that how much products of the reprogramming, transdifferentiation and differentiation (programming) are identical to their in vivo counterparts. There is evidence that shows that direct fate conversions of somatic cells are not complete, with target cell identity not fully achieved. Manipulation of core TFs provides a powerful tool for engineering cell fate in terms of extinguishment of native GRNs, the establishment of a new GRN, and preventing installation of aberrant GRNs. Conventionally, core TFs are selected to convert one cell type into another mostly based on literature and the experimental identification of genes that are differentially expressed in one cell type compared to the specific cell types. Currently, there is not a universal standard strategy for identifying candidate core TFs. Remarkably, several biological computational platforms are developed, which are capable of evaluating the fidelity of reprogramming methods and refining existing protocols. The current review discusses some deficiencies of reprogramming technologies in the production of a pure population of authentic target cells. Furthermore, it reviews the role of computational approaches (e.g. CellNet, KeyGenes, Mogrify, etc.) in improving (re)programming methods and consequently in regenerative medicine and cancer therapeutics.