Epithelial-to-mesenchymal transition (EMT) process has important implications for our understanding of HCC progression as its role in the development and advancement of HCC has gained increasing attention in the recent years. This multi-step reprograming process resulting in a phenotype switch from an epithelial to a mesenchymal cellular state has been closely associated with generation of aggressive population of tumour cells namely, cancer stem cells (CSCs) and circulating tumor cells (CTCs). Cancer-derived exosomes are important mediators of intercellular signaling and EMT. EMT process also influences the prognosis of cancer patients by promoting drug resistance of tumours and recurrence.
Liquid biopsies represent a series of non-invasive tests that detect cancer by-products easily accessible in peripheral blood, mainly including circulating tumor cells (CTCs), exosomes and cell-free nucleic acids that are shed into the blood from the tumor sites. CTCs are generally recognised as the “seeds” of tumors, which are shed into peripheral blood from a tumor in situ and eventually establish metastatic tumors in other organs. Cancer-derived exosomes are small membrane vesicles with a size ranging from 40 to 100nm and have a significant role in cell communication. CTCs, exosomes and cell-free nucleic acids have potent clinical utilities as novel biomarkers. Liquid biopsies have greater advantages compared to tissue biopsies with regard to the clinical risks of tumor patients and cost, as well as the feasibility of taking serial samples in order to monitor tumor changes in real time. An effective saliva and blood-based method for the diagnosis and prognosis of HCC has not yet been developed.
Given that EMT is intrinsically associated with CSCs, CTCs and exosomes, we propose that EMT biomarkers derived from CSCs and liquid biopsies will be useful biomarkers in diagnosing HCC at an early stage, monitoring recurrence and treatment response in HCC patients. The purpose of this study is to develop an effective saliva and blood-based method for the diagnosis and prognosis of HCC.