Abstract

The surgical wound creates a systemically co-ordinated response of cell stress, inflammation, endothelial activation, tissue injury and repair. The ability of Extracellular Vesicles (EVs), such as microvesicles and exosomes, to transfer biological information between cells via proteins, lipids and nucleic acids is being increasingly acknowledged. One class of compounds of particular interest is microRNAs (miRNAs), which can be selectively loaded into EVs, and represent the condition of EVs releasing cells and can mediate gene expression in recipient tissues. The findings from this narrative review highlight the new emerging concepts of EVs and EV-associated miRNAs as biomarkers and signalling agents in surgical disease. An overview of evidence related to AKI in cardiac surgery, postoperative sepsis and septic shock, postoperative delirium and neurocognitive dysfunction, congenital cardiac surgery, and tissue repair is provided. The review highlights differences between biomarker correlation and mechanistic causation and considers how EVs concentration, surface phenotype, cellular origin and molecular cargo can be used in addition to traditional clinical data analysis. This is despite methodological limitations such as the lack of a uniform method for EV isolation, pre-analytical variability, incomplete particle characterisation, miRNA normalisation, and the lack of external validation. However, new studies in the last few years have revealed that signatures derived from EVs may aid in cell non-invasive discrimination of postoperative complications and may offer an early ‘liquid-biopsy window’ into tissue injury prior to peak evolution of conventional markers. The next steps should be to test whether cargo in EVs could be manipulated in a therapeutic way to enhance postoperative recovery, to introduce multimodal phenotyping of EVs in a standardised way and change towards longitudinal sampling and validation of the EVs in terms of postoperative outcome.

Keywords: Surgical wound, MicroRNAs, Tissue injury, Inflammation, Biomarkers