Inflammatory biomarkers and nanotechnology: new insights in pancreatic cancer early detection

Poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly due to the lack of effective early-stage detection strategies. Even though the link between inflammation and PDAC has been demonstrated and inflammatory biomarkers proved their efficacy in predicting several tumours, to date they have a role only in assessing PDAC prognosis. Recently, the studies of interactions between nanosystems and easily collectable biological fluids, alone or coupled with standard laboratory tests, have proven useful in facilitating PDAC diagnosis. Notably, tests based on magnetic levitation (MagLev) of biocoronated nanosystems have demonstrated high diagnostic accuracy in compliance with the criteria stated by WHO. Herein, the author developed a synergistic analysis that combines a user-friendly MagLev-based approach and common inflammatory biomarkers for discriminating PDAC subjects from healthy ones.Plasma samples from 24 PDAC subjects and 22 non-oncological patients have been collected and let to interact with graphene oxide nanosheets.Biomolecular corona formed around graphene oxide nanosheets have been immersed in a Maglev platform to study the levitation profiles.Inflammatory biomarkers such as neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), and platelet to lymphocyte ratio have been calculated and combined with results obtained by the MagLev platform.MagLev profiles resulted significantly different between non-oncological patients and PDAC and allowed to identify a MagLev fingerprint for PDAC. Four inflammatory markers were significantly higher in PDAC subjects: neutrophils ( P =0.04), NLR ( P =4.7 ×10 -6 ), dNLR ( P =2.7 ×10 -5 ), and platelet to lymphocyte ratio ( P =0.002). Lymphocytes were appreciably lower in PDACs ( P =2.6 ×10 -6 ).Combining the MagLev fingerprint with dNLR and NLR returned global discrimination accuracy for PDAC of 95.7% and 91.3%, respectively.The multiplexed approach discriminated PDAC patients from healthy volunteers in up to 95% of cases. If further confirmed in larger-cohort studies, this approach may be used for PDAC detection.