Coupled liquid biopsy and bioinformatics for pancreatic cancer early detection and precision prognostication

Abstract

Early detection and diagnosis are the key to successful clinical management of pancreatic cancer and improve the patient outcome. However, due to the absence of early symptoms and the aggressiveness of pancreatic cancer, its 5-year survival rate remains below 5 %. Compared to tissue samples, liquid biopsies are of particular interest in clinical settings with respect to minimal invasiveness, repeated sampling, complete representation of the entire or multi-site tumor bulks. The potential of liquid biopsies in pancreatic cancer has been demonstrated by many studies which prove that liquid biopsies are able to detect early emergency of pancreatic cancer cells, residual disease, and recurrence. More interestingly, they show potential to delineate the heterogeneity, spatial and temporal, of pancreatic cancer. However, the performance of liquid biopsies for the diagnosis varies largely across different studies depending of the technique employed and also the type and stage of the tumor. One approach to improve the detect performance of liquid biopsies is to intensively inspect circulome and to define integrated biomarkers which simultaneously profile circulating tumor cells and DNA, extracellular vesicles, and circulating DNA, or cell free DNA and proteins. Moreover, the diagnostic validity and accuracy of liquid biopsies still need to be comprehensively demonstrated and validated.

Keywords: Bioinformatics; Circulome; Diagnosis; Liquid biopsy; Pancreatic cancer; Prognosis.

Fig. 1

Integrated strategies for detection of tumor from liquid biopsies. Various tumor-derived circulating components can be used as a source of liquid biopsies, including circulating cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), circulating tumor RNA (ctRNA), circulating miRNA, tumor-educated platelets (TEPs), extracellular vesicles (EVs), circulating tumor-derived proteins, and circulating metabolites. Each element can extract one or more levels of information about the genome, the transcriptome, the proteome or the metabolome.