In recent years nanotechnology has opened exciting opportunities in the struggle against cancer. In 2007 Dawson and coworkers demonstrated that nanomaterials exposed to biological fluids are coated ...with plasma proteins that form the so-called "protein corona". A few years later our joint research team made of physicists, chemists, biotechnologists, surgeons, oncologists, and bioinformaticians introduced the concept of "personalized protein corona" and demonstrated that it is unique for each human condition. This concept paved the way for the development of nano-enabled blood (NEB) tests for the diagnosis of pancreatic ductal adenocarcinoma (PDAC). These studies gave an impetus to serious work in the field that came to maturity in the late 2010s. In this special issue, we provide the reader with a comprehensive overview of the most significant discoveries of our research team in the field of PDAC detection. We focus on the main achievements with an emphasis on the fundamental aspects of this arena and how they shaped the integration of different scientific backgrounds towards the development of advanced diagnostic technologies. We conclude the review by outlining future perspectives and opportunities to transform the NEB tests into a reliable clinical diagnostic technology for early diagnosis, follow-up, and management of PDAC patients.
Introduction
Pancreatic adenocarcinoma (PDAC) has a poor prognosis since often diagnosed too late. Dyslipidemia and hyperglycemia are considered risk factors, but the presence of the tumor itself can ...determine the onset of these disorders. Therefore, it is not easy to predict which subjects with diabetes or dyslipidemia will develop or have already developed PDAC. Over the past decade, tests based on the use of nanotechnology, alone or coupled with common laboratory tests (e.g., hemoglobin levels), have proven useful in aiding the diagnosis of PDAC. Tests based on magnetic levitation (MagLev) have demonstrated high diagnostic accuracy in compliance with the REASSURED criteria. Here, we aimed to assess the ability of the MagLev test in detecting PDAC when coupled with the blood levels of glycemia, cholesterol, and triglycerides.
Methods
Blood samples from 24 PDAC patients and 22 healthy controls were collected. Human plasma was let to interact with graphene oxide (GO) nanosheets and the emerging coronated systems were put in the MagLev device. Outcomes from Maglev experiments were coupled to glycemia, cholesterol, and triglycerides levels. Linear discriminant analysis (LDA) was carried out to evaluate the classification ability of the test in terms of specificity, sensitivity, and global accuracy. Statistical analysis was performed with Matlab (MathWorks, Natick, MA, USA, Version R2022a) software.
Results
The positions of the levitating bands were measured at the starting point (i.e., as soon as the cuvette containing the sample was subjected to the magnetic field). Significant variations in the starting position of levitating nanosystems in controls and PDACs were detected. The combination of the MagLev outcomes with the blood glycemic levels returned the best value of global accuracy (91%) if compared to the coupling with those of cholesterol and triglycerides (global accuracy of ~ 77% and 84%, respectively).
Conclusion
If confirmed by further studies on larger cohorts, a multiplexed Maglev-based nanotechnology-enabled blood test could be employed as a screening tool for PDAC in populations with hyperglycemia.
The choice between upfront surgery or neoadjuvant treatments (NAT) for resectable pancreatic ductal adenocarcinoma (R-PDAC) is controversial. R-PDAC with potential nodal involvement could benefit ...from NT. Ca (Carbohydrate antigen) 19.9 and serum albumin levels, alone or in combination, have proven their efficacy in assessing PDAC prognosis. The objective of this study was to evaluate the role of Ca 19.9 serum levels in predicting nodal status in R-PDAC.
Preoperative Ca 19.9, as well as serum albumin levels, of 165 patients selected for upfront surgery have been retrospectively collected and correlated to pathological nodal status (N), resection margins status (R) and vascular resections (VR). We further performed ROC curve analysis to identify optimal Ca 19.9 cut-off for pN+, R+ and vascular resection prediction.
Increased Ca 19.9 levels in 114 PDAC patients were significantly associated with pN+ (p <0.001). This ability, confirmed in all the series by ROC curve analysis (Ca 19.9 ≥32 U/ml), was lost in the presence of hypoalbuminemia. Furthermore, Ca 19.9 at the cut off >418 U/ml was significantly associated with R+ (87% specificity, 36% sensitivity, p 0.014). Ca 19.9, at the cut-off >78 U/ml, indicated a significant trend to predict the need for VR (sensitivity 67%, specificity 53%; p = 0.059).
In R-PDAC with normal serum albumin levels, Ca 19.9 predicts pN+ and R+, thus suggesting a crucial role in deciding on NAT.
Pancreatic ductal adenocarcinoma (PDAC) is the fourth cause of cancer-related mortality in the Western world and is envisaged to become the second cause by 2030. Although our knowledge about the ...molecular biology of PDAC is continuously increasing, this progress has not been translated into better patients' outcome. Liposomes have been used to circumvent concerns associated with the low efficiency of anticancer drugs such as severe side effects and damage of healthy tissues, but they have not resulted in improved efficacy as yet. Recently, the concept is emerging that the limited success of liposomal drugs in clinical practice is due to our poor knowledge of the nano⁻bio interactions experienced by liposomes in vivo. After systemic administration, lipid vesicles are covered by plasma proteins forming a biomolecular coating, referred to as the protein corona (PC). Recent studies have clarified that just a minor fraction of the hundreds of bound plasma proteins, referred to as "PC fingerprints" (PCFs), enhance liposome association with cancer cells, triggering efficient particle internalization. In this study, we synthesized a library of 10 liposomal formulations with systematic changes in lipid composition and exposed them to human plasma (HP). Size, zeta-potential, and corona composition of the resulting liposome⁻protein complexes were thoroughly characterized by dynamic light scattering (DLS), micro-electrophoresis, and nano-liquid chromatography tandem mass spectrometry (nano-LC MS/MS). According to the recent literature, enrichment in PCFs was used to predict the targeting ability of synthesized liposomal formulations. Here we show that the predicted targeting capability of liposome⁻protein complexes clearly correlate with cellular uptake in pancreatic adenocarcinoma (PANC-1) and insulinoma (INS-1) cells as quantified by flow-assisted cell sorting (FACS). Of note, cellular uptake of the liposomal formulation with the highest abundance of PCFs was much larger than that of Onivyde
, an Irinotecan liposomal drug approved by the Food and Drug Administration in 2015 for the treatment of metastatic PDAC. Given the urgent need of efficient nanocarriers for the treatment of PDAC, we envision that our results will pave the way for the development of more efficient PC-based targeted nanomaterials. Here we also show that some BCs are enriched with plasma proteins that are associated with the onset and progression of PDAC (e.g., sex hormone-binding globulin, Ficolin-3, plasma protease C1 inhibitor, etc.). This could open the intriguing possibility to identify novel biomarkers.
Procalcitonin and Mid-regional pro Adrenomedullin have been proposed for sepsis diagnosis, antibiotic therapy guidance and prognosis. A retrospective analysis of PCT and MR-proADM on 571 consecutive ...patients with sepsis diagnosis was performed. Median values were compared using the non-parametric Mann-Whitney's test. Receiver operating characteristic analysis was performed to define cutoff points for sepsis diagnosis. Pretest odds, posttest odds, and posttest probability have been calculated. Data were analyzed using Med-Calc 11.6.1.0 software. PCT resulted excellent in gram-negative, but less performant in gram-positive and fungal etiologies. MR-proADM values resulted homogenously distributed within the different microbial classes and increased significantly in septic shock. PCT highest PPV value was found to distinguish gram-negative from fungal sepsis and septic shock (>3. 57 ng/mL, PPV 0.96 and > 8.77 ng/mL, PPV 0.96, respectively). Good diagnostic accuracy was evidenced to discriminate gram-negative from gram-positive septic shock (>3.88 ng/mL PPV 0.89). Lower diagnostic accuracy was evidenced to discriminate gram-negative and gram-positive sepsis (>0.80 ng/mL, PPV 0.78) and gram-positive from fungal septic shock (>1.74 ng/mL PPV 0.75). The lowest PCT PPV (0.28) was found in gram-positive and fungal sepsis distinction. MR-proADM discriminating cut-offs were homogeneously distributed in Gram-negative and Gram-positive sepsis and were higher in septic shock, but not influenced by pathogen etiologies. MR-proADM cut-off values > 3.39 nmol/L in sepsis and >4.33 nmol/L in septic shock were associated with significant higher risk of 90-days mortality. In conclusion, PCT and MR-proADM combination represents an advantage for sepsis diagnosis and for 90-days mortality risk stratification.
•Sepsis is a severe systemic syndrome characterized by high mortality rate.•PCT and MR-proADM can provide useful information at diagnostic and prognostic purposes.•PCT highest PPV value was evidenced to distinguish gram-negative from fungal sepsis and septic shock.•MR-proADM values was homogenously distributed within the different microbial classes increasing significantly in case of septic shock.•PCT and MR-proADM combination represents an advantage for sepsis diagnosis and for 90-days mortality risk stratification.
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