# Epigenetic Regulation of Dental Follicle Stem Cells in Odontogenic Regeneration

## TL;DR

This paper explores how microRNAs regulate dental follicle stem cells during tooth development and bone formation.

## Contribution

The study characterizes miRNA expression patterns in dental follicle stem cells during odontogenic differentiation.

## Key findings

- miR-125 is upregulated during odonto/osteogenic differentiation of dental follicle progenitor cells.
- miR-203 and miR-21 significantly downregulate odonto/osteogenic differentiation in various tissue types.
- miRNA signatures could serve as predictive tools for understanding DFSC molecular processes.

## Abstract

MicroRNAs (miRNAs) are short non‐coding RNAs essential for biological functions that control the process of translation of mRNA into protein. The discovery of miRNAs in mesenchymal stem cells (MSCs), especially in odontogenic tissues and dental follicles, has not been fully characterised. This study focused on characterising dental follicle stem cells (DFSCs) in terms of their ability to proliferate and differentiate into osteoblasts using qRT‐PCR (miR‐203, miR‐125 and miR‐21) and immunohistochemistry (OCT4 and CD133). Dental follicles are essential for tooth eruption as they envelop the enamel organ and dental papilla and control the development and breakdown of the alveolar bone. Dental follicle progenitor cells (DFPCs) are stem cells located in dental follicles that differentiate into several cell types that are essential for tooth development and eruption. We observed that miR‐125 was upregulated in fibromyxoid and myxoid tissues during odonto/osteogenic differentiation of hDFPCs (fold change values, respectively, 1.75 ± 0.98 and 2.17 ± 1.03). miR‐203 and miR‐21 significantly downregulated odonto/osteogenic differentiation in myxoid, fibromyxoid and fibroid tissues (fold change values, respectively: miR‐203: 0.57 ± 0.25, 0.38 ± 0.11, 0.21 ± 0.18; miR‐21: 0.21 ± 0.14, 0.21 ± 0.13, 0.082 ± 0.14). Ultimately, utilising miRNA signatures in humans as a predictive tool will help us understand the molecular processes involved in DFSCs.