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Current Molecular Medicine

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ISSN (Online): 1875-5666

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Review Article

Wound Healing Properties of Exosomes — A Review and Modelling of Combinatorial Analysis Strategies

Author(s): Fong Fong Liew*, Boon Cheng Chew and Der Jiun Ooi*

Volume 22, Issue 2, 2022

Published on: 05 April, 2021

Page: [165 - 191] Pages: 27

DOI: 10.2174/1566524021666210405131238

Price: $65

Abstract

Wound healing is an elaborated process, well-regulated via cell migration and proliferation. Although the physiological basics of wound healing have been thoroughly investigated and reported, much remains to be studied. Particularly, various studies have demonstrated the immunomodulatory roles of exosomes derived from plant cells, mammalian cells, and mesenchymal stem cells (MSCs) in the healing and repairing system. The paracrine and therapeutic effects of exosomes are mainly associated with the broad exosomal cargo content comprising growth factors, cytokines, enzymes, nucleic acids, proteins, and lipid signaling molecules. Nevertheless, the functional or mechanism pathway of exosomes with reference to overall exosomal cargo remains undetermined. To date, combinatorial analysis strategies employing Database for Annotation, Visualization, and Integrated Discovery (DAVID), STRING tools, Gene Ontology (GO), Kyoto Encyclopedia of Genes, Genomes (KEGG) pathway enrichment analysis, as well as Ingenuity Pathway Analysis (IPA) have been applied in elucidating network interaction and functional pathway of exosomes. In this review paper, the application of combinatorial analysis strategies is demonstrated to better understand the therapeutic potentials of exosomes in the wound healing process. In conclusion, functional modulation of exosomal cargo for specific biological treatment is achievable, and modelling of combinatorial analysis strategies will hopefully bridge the research gap and provide a paradigm shift to regenerative processes.

Keywords: Exosome, healing, combinatorial analysis, STRING tools, gene ontologY, KEGG pathway, DAVID and ingenuity pathway analysis

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