Early diagnosis of pancreatic cancer by biomolecular corona of graphene nanoflakes
To date, pancreatic ductal adenocarcinoma (PDAC) carries a poor prognosis, which is related to both tumor biology and advanced stage at the moment of detection. Avoiding delayed diagnosis is therefore crucial, but the absence of sensitive and specific biomarkers makes the early diagnosis challenging. In this regard, recent advances in nanotechnology have provided promising outcomes that could pave the way to future developments of early diagnostic tools. They are based on the study of the interactions among nanoparticles (NPs) and blood plasma biomolecules. Indeed, upon incubation with human plasma, NPs act as 'concentrators' of molecules, which adsorb on their surface and form an outer biomolecular layer, or biomolecular corona (BC). Features and composition of the BC depend on NP's physical-chemical properties (size, shape, surface chemistry), environmental factors (temperature, PH) and molecular source, i.e. the biological medium within which the NP is embedded. Hence, the detection of specific corona molecules, which are related to pathological conditions, could represent an effective way to exploit NP-blood interactions for diagnostic purposes. The main aim of this project is the development of a BC-based blood test for early cancer detection, by exploiting some peculiar properties of graphene oxide (GO) nanoparticles. The use of GO-BC in diagnostics is extremely promising since (i) GO can selectively adsorb plasma proteins which are poorly concentrated; (ii) protein patterns adsorbed can be varied by modulating size and surface oxidation and (iii) GO-BC is sensitive for early cancer detection. In this project, we will explore these properties to burst pancreatic cancer test sensitivity in the detection of minor protein changes at the very early stages of disease. We predict that a systematic investigation of GO-BC may improve our knowledge of PDAC biology and that the BC technology may offer new opportunities for PDAC detection and biomarkers identification.