Update of in vitro, in vivo and ex vivo fluoro-edenite effects on malignant mesothelioma: A systematic review (Review)

Fluoro-edenite (FE), asbestiform fiber found in Biancavilla (Sicily, Italy), presents various characteristics similar to the asbestos group, in particular two fibrous phases tremolite and actinolite. Indeed, epidemiological studies have shown that FE fibers have similar effects to those of asbestos fibers. Such studies have reported a high incidence of malignant mesothelioma (MM), an aggressive neoplasm of the serosal membranes lining the pleural cavity, in individuals residing there due to FE exposure in Biancavilla related to environmental contamination. Evidence has led to the classification of FE as a Group 1 human carcinogen by the International Agency for Research on Cancer (IARC). The aim of this systematic review is to compare the results achieved in in vitro, in vivo and ex vivo experimental studies involving FE in order to update the current knowledge on the pathogenesis and molecular mechanisms responsible for FE-mediated MM development as well as the availability of effective biomarkers for MM prevention and diagnosis. This review is focused on the pathophysiological mechanisms mediated by inflammation induced by FE fiber exposure and which are responsible for MM development. This review also discusses the discovery of new diagnostic and prognostic biomarkers for the management of this pathology. It is known that the risk of cancer development increases with chronic inflammation, arising from enhanced reactive oxygen species (ROS) and NO(•) production stimulated by the body to remove exogenous agents, causing DNA damage and enhanced signal transduction that may lead to activation of oncogenes. Studies concerning MM biomarker discovery indicate that several biomarkers have been proposed for MM, but mesothelin is the only Food and Drug Administration (FDA)-approved biomarker for MM, with limitations. In recent studies, in silico analysis to identify selected miRNAs highly deregulated in cancer samples when compared with normal control have been developed. This in silico approach could represent an effort in the field of biomarker discovery for MM.