Computational Analysis of miR-140 and miR-135 as Potential Targets to Develop Combinatorial Therapeutics for Degenerative Tendinopathy

Abstract

Background: Degenerative tendinopathy, a condition causing movement restriction due to high pain, highly impacts productivity and quality of life. The healing process is a complex phenomenon and involves a series of intra-cellular and inter-cellular processes. Proliferation and differentiation of the tenocyte is a major and essential process to heal degenerative tendinopathy. The recent development in microRNA (miRNA)-mediated reprogramming of the cellular function through specific pathways opened door for the development of new regenerative therapeutics. Based on information about gene expression and regulation of tendon injury and healing, we attempted to evaluate the combinatorial effect of selected miRNAs for better healing of degenerative tendinopathy.

Methods: The present study was designed to evaluate the combinatorial effect of two miRNAs (has-miR-140 and has-miR-135) in the healing process of the tendon. Publicly available information/data were retrieved from appropriate platforms such as PubMed. Only molecular data, directly associated with tendinopathies, including genes/proteins and miRNAs, were used in this study. The miRNAs involved in tendinopathy were analyzed by a Bioinformatics tools (e.g., TargetScan, miRDB, and the RNA22v2). Interactive involvement of the miRNAs with key proteins involved in tendinopathy was predicted by the Insilco approach.

Results: Based on information available in the public domain, tendon healing-associated miRNAs were predicted to explore their therapeutic potentials. Based on computation analysis, focusing on the potential regulatory effect on tendon healing, the miR-135 and miR-140 were selected for this study. These miRNAs were found as key players in tendon healing through Rho-associated coiled-coil containing protein kinase 1 (ROCK1), IGF-1/PI3K/Akt, PIN, and Wnt signaling pathways. It was also predicted that these miRNAs may reprogram the cells to induce proliferation and differentiation activity. Many miRNAs are likely to regulate genes important for the tendinopathy healing process, and the result of this study allows an approach for miRNA-mediated regeneration of the tenocyte for tendon healing. Based on computational analysis, the role of these miRNAs in different pathways was established, and the results provided insights into the combinatorial approach of miRNA-mediated cell reprogramming.

Conclusions: In this study, the association between miRNAs and the disease was evaluated to correlate the tendinopathy genes and the relevant role of different miRNAs in their regulation. Through this study, it was established that the synergistic effect of more than one miRNA on directed reprogramming of the cell could be helpful in the regeneration of damaged tissue. It is anticipated that this study will be helpful for the design of miRNA cocktails for the orchestration of cellular reprogramming events.

Keywords: Extracellular matrix remodeling; MicroRNA; Regenerative medicine; Tendinopathy; Therapeutics.

Fig. 1. A proposed process of tendon healing based on previous studies. The three consecutive steps, namely, inflammatory, proliferative, and remodeling, were identified and showed key regulatory proteins of the respective process. IGF-1: insulin-like growth factor 1, PDGF: platelet-derived growth factor, TGF-β: transforming growth factor beta, VEGF: vascular endothelial growth factor, bFGF: basic fibroblast growth factor, GDF: growth differentiation factor, ROCK1: Rho-associated coiled-coil containing protein kinase 1.

Fig. 2. Workflow of the study, showing methodology used in this study to shortlist the proteins and corresponding microRNAs (miRNAs). KEGG: Kyoto Encyclopedia of Genes and Genomes.

Fig. 3. The key proteins, their involvement in tendinopathy, and their interaction with other proteins. These proteins collectively responsible for tendon healing were used for protein-protein interaction network analysis to predict the involvement of the major pathway. ROCK1: rho-associated coiled-coil protein kinase 1, PIN1: peptidyl-prolyl cis/trans isomerase NIMA-interacting 1, TOB1: transducer of ERBB2, 1, HMGA2: high-mobility AT-hook 2, EGR1: early growth response-1.

Fig. 4. Network analysis of microRNA (miRNA) interaction using Steiner forest network (A), minimum network algorithm (B), and network analysis on miR-135 and mir-140 (C). (A) Involvement of miRNAs used in this study and their relation in specific disease. (B) Analysis of the miRNAs and related protein interactions and their interconnections that have an impact on epigenetic regulation. (C) Overall impact on different proteins while regulating miR-140 and miR-135 on cellulation function.

Fig. 5. Predicted relationship between the role of selected microRNAs (miRNAs) in tendinopathy and significant genes to be downregulated in response to overexpression of miR-140 and miR-135. These miRNAs were also reported in other diseases than predicted tendinopathy. Network analysis of miRNA interaction in disease development. (A) has-mir-140. (B) has-mir-135a, (C) miR-135b. (D) Involvement of predicted miRNA in other diseases.