Synergistic Analysis of Protein Corona and Haemoglobin Levels Detects Pancreatic Cancer

Personalized biocorona as disease biomarker: The challenges and opportunities

It is well known that when nanoparticles interact with biological fluids, a layer of proteins and biological components forms on them. This layer may alter the biological fate and efficiency of the nanomaterial. Recent studies have shown that illness states have a major impact on the structure of the biocorona, sometimes referred to as the "personalized protein corona." Physiological factors like illness, which impact the proteome and metabolome pattern and result in conformational changes in proteins, give rise to this structure of discrimination in biocorona decoration. Improving the efficiency of precise platforms for developing new molecular biomarkers for accurate illness diagnosis is vitally necessary. The biocorona pattern's discrimination may be a diagnostic tool for designing biosensors. As a result, in this review, we summarize the most current studies on the relationship between physiological conditions and the variety of biocorona patterns that influence the biological responses of nanosystems. The biocorona pattern's flexibility may provide new research directions and be utilized to create nanoparticle-based therapeutic and diagnostic products suited to certain physiological situations.

A Review for Uncovering the "Protein-Nanoparticle Alliance": Implications of the Protein Corona for Biomedical Applications

Understanding both the physicochemical and biological interactions of nanoparticles is mandatory for the biomedical application of nanomaterials. By binding proteins, nanoparticles acquire new surface identities in biological fluids, the protein corona. Various studies have revealed the dynamic structure and nano-bio interactions of the protein corona. The binding of proteins not only imparts new surface identities to nanoparticles in biological fluids but also significantly influences their bioactivity, stability, and targeting specificity. Interestingly, recent endeavors have been undertaken to harness the potential of the protein corona instead of evading its presence. Exploitation of this 'protein-nanoparticle alliance' has significant potential to change the field of nanomedicine. Here, we present a thorough examination of the latest research on protein corona, encompassing its formation, dynamics, recent developments, and diverse bioapplications. Furthermore, we also aim to explore the interactions at the nano-bio interface, paving the way for innovative strategies to advance the application potential of the protein corona. By addressing challenges and promises in controlling protein corona formation, this review provides insights into the evolving landscape of the 'protein-nanoparticle alliance' and highlights emerging.

Advancements in Mid-Infrared spectroscopy of extracellular vesicles

Extracellular vesicles (EVs) are lipid vesicles secreted by all cells into the extracellular space and act as nanosized biological messengers among cells. They carry a specific molecular cargo, composed of lipids, proteins, nucleic acids, and carbohydrates, which reflects the state of their parent cells. Due to their remarkable structural and compositional heterogeneity, characterizing EVs, particularly from a biochemical perspective, presents complex challenges. In this context, mid-infrared (IR) spectroscopy is emerging as a valuable tool, providing researchers with a comprehensive and label-free spectral fingerprint of EVs in terms of their specific molecular content. This review aims to provide an up-to-date critical overview of the major advancements in mid-IR spectroscopy of extracellular vesicles, encompassing both fundamental and applied research achievements. We also systematically emphasize the new possibilities offered by the integration of emerging cutting-edge IR technologies, such as tip-enhanced and surface-enhanced spectroscopy approaches, along with the growing use of machine learning for data analysis and spectral interpretation. Additionally, to assist researchers in navigating this intricate subject, our manuscript includes a wide and detailed collection of the spectral peaks that have been assigned to EV molecular constituents up to now in the literature.

Graphene Oxide Nanoparticles and Organoids: A Prospective Advanced Model for Pancreatic Cancer Research

Pancreatic cancer, notorious for its grim 10% five-year survival rate, poses significant clinical challenges, largely due to late-stage diagnosis and limited therapeutic options. This review delves into the generation of organoids, including those derived from resected tissues, biopsies, pluripotent stem cells, and adult stem cells, as well as the advancements in 3D printing. It explores the complexities of the tumor microenvironment, emphasizing culture media, the integration of non-neoplastic cells, and angiogenesis. Additionally, the review examines the multifaceted properties of graphene oxide (GO), such as its mechanical, thermal, electrical, chemical, and optical attributes, and their implications in cancer diagnostics and therapeutics. GO's unique properties facilitate its interaction with tumors, allowing targeted drug delivery and enhanced imaging for early detection and treatment. The integration of GO with 3D cultured organoid systems, particularly in pancreatic cancer research, is critically analyzed, highlighting current limitations and future potential. This innovative approach has the promise to transform personalized medicine, improve drug screening efficiency, and aid biomarker discovery in this aggressive disease. Through this review, we offer a balanced perspective on the advancements and future prospects in pancreatic cancer research, harnessing the potential of organoids and GO.

Coupling magnetic levitation of graphene oxide–protein complexes with blood levels of glucose for early detection of pancreatic adenocarcinoma

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.

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

BACKGROUND

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.

MATERIALS AND METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

The influence of protein corona on Graphene Oxide: implications for biomedical theranostics

Graphene-based nanomaterials have attracted significant attention in the field of nanomedicine due to their unique atomic arrangement which allows for manifold applications. However, their inherent high hydrophobicity poses challenges in biological systems, thereby limiting their usage in biomedical areas. To address this limitation, one approach involves introducing oxygen functional groups on graphene surfaces, resulting in the formation of graphene oxide (GO). This modification enables improved dispersion, enhanced stability, reduced toxicity, and tunable surface properties. In this review, we aim to explore the interactions between GO and the biological fluids in the context of theranostics, shedding light on the formation of the "protein corona" (PC) i.e., the protein-enriched layer that formed around nanosystems when exposed to blood. The presence of the PC alters the surface properties and biological identity of GO, thus influencing its behavior and performance in various applications. By investigating this phenomenon, we gain insights into the bio-nano interactions that occur and their biological implications for different intents such as nucleic acid and drug delivery, active cell targeting, and modulation of cell signalling pathways. Additionally, we discuss diagnostic applications utilizing biocoronated GO and personalized PC analysis, with a particular focus on the detection of cancer biomarkers. By exploring these cutting-edge advancements, this comprehensive review provides valuable insights into the rapidly evolving field of GO-based nanomedicine for theranostic applications.

Stratifying Risk for Pancreatic Cancer by Multiplexed Blood Test

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease, for which mortality closely parallels incidence. So far, the available techniques for PDAC detection are either too invasive or not sensitive enough. To overcome this limitation, here we present a multiplexed point-of-care test that provides a "risk score" for each subject under investigation, by combining systemic inflammatory response biomarkers, standard laboratory tests, and the most recent nanoparticle-enabled blood (NEB) tests. The former parameters are routinely evaluated in clinical practice, whereas NEB tests have been recently proven as promising tools to assist in PDAC diagnosis. Our results revealed that PDAC patients and healthy subjects can be distinguished accurately (i.e., 88.9% specificity, 93.6% sensitivity) by the presented multiplexed point-of-care test, in a quick, non-invasive, and highly cost-efficient way. Furthermore, the test allows for the definition of a "risk threshold", which can help clinicians to trace the optimal diagnostic and therapeutic care pathway for each patient. For these reasons, we envision that this work may accelerate progress in the early detection of PDAC and contribute to the design of screening programs for high-risk populations.

Multiplexed Detection of Pancreatic Cancer by Combining a Nanoparticle-Enabled Blood Test and Plasma Levels of Acute-Phase Proteins

The development of new tools for the early detection of pancreatic ductal adenocarcinoma (PDAC) represents an area of intense research. Recently, the concept has emerged that multiplexed detection of different signatures from a single biospecimen (e.g., saliva, blood, etc.) may exhibit better diagnostic capability than single biomarkers. In this work, we develop a multiplexed strategy for detecting PDAC by combining characterization of the nanoparticle (NP)-protein corona, i.e., the protein layer that surrounds NPs upon exposure to biological fluids and circulating levels of plasma proteins belonging to the acute phase protein (APPs) family. As a first step, we developed a nanoparticle-enabled blood (NEB) test that employed 600 nm graphene oxide (GO) nanosheets and human plasma (HP) (5% vol/vol) to produce 75 personalized protein coronas (25 from healthy subjects and 50 from PDAC patients). Isolation and characterization of protein corona patterns by 1-dimensional (1D) SDS-PAGE identified significant differences in the abundance of low-molecular-weight corona proteins (20-30 kDa) between healthy subjects and PDAC patients. Coupling the outcomes of the NEB test with the circulating levels of alpha 2 globulins, we detected PDAC with a global capacity of 83.3%. Notably, a version of the multiplexed detection strategy run on sex-disaggregated data provided substantially better classification accuracy for men (93.1% vs. 77.8%). Nanoliquid chromatography tandem mass spectrometry (nano-LC MS/MS) experiments allowed to correlate PDAC with an altered enrichment of Apolipoprotein A-I, Apolipoprotein D, Complement factor D, Alpha-1-antichymotrypsin and Alpha-1-antitrypsin in the personalized protein corona. Moreover, other significant changes in the protein corona of PDAC patients were found. Overall, the developed multiplexed strategy is a valid tool for PDAC detection and paves the way for the identification of new potential PDAC biomarkers.

Sensing red blood cell nano-mechanics: Toward a novel blood biomarker for Alzheimer's disease

Red blood cells (RBCs) are characterized by a remarkable elasticity, which allows them to undergo very large deformation when passing through small vessels and capillaries. This extreme deformability is altered in various clinical conditions, suggesting that the analysis of red blood cell (RBC) mechanics has potential applications in the search for non-invasive and cost-effective blood biomarkers. Here, we provide a comparative study of the mechanical response of RBCs in patients with Alzheimer's disease (AD) and healthy subjects. For this purpose, RBC viscoelastic response was investigated using atomic force microscopy (AFM) in the force spectroscopy mode. Two types of analyses were performed: (i) a conventional analysis of AFM force-distance (FD) curves, which allowed us to retrieve the apparent Young's modulus, E; and (ii) a more in-depth analysis of time-dependent relaxation curves in the framework of the standard linear solid (SLS) model, which allowed us to estimate cell viscosity and elasticity, independently. Our data demonstrate that, while conventional analysis of AFM FD curves fails in distinguishing the two groups, the mechanical parameters obtained with the SLS model show a very good classification ability. The diagnostic performance of mechanical parameters was assessed using receiving operator characteristic (ROC) curves, showing very large areas under the curves (AUC) for selected biomarkers (AUC > 0.9). Taken all together, the data presented here demonstrate that RBC mechanics are significantly altered in AD, also highlighting the key role played by viscous forces. These RBC abnormalities in AD, which include both a modified elasticity and viscosity, could be considered a potential source of plasmatic biomarkers in the field of liquid biopsy to be used in combination with more established indicators of the pathology.

The Yin and Yang of the protein corona on the delivery journey of nanoparticles

Nanoparticles-based drug delivery systems have attracted significant attention in biomedical fields because they can deliver loaded cargoes to the target site in a controlled manner. However, tremendous challenges must still be overcome to reach the expected targeting and therapeutic efficacy in vivo. These challenges mainly arise because the interaction between nanoparticles and biological systems is complex and dynamic and is influenced by the physicochemical properties of the nanoparticles and the heterogeneity of biological systems. Importantly, once the nanoparticles are injected into the blood, a protein corona will inevitably form on the surface. The protein corona creates a new biological identity which plays a vital role in mediating the bio-nano interaction and determining the ultimate results. Thus, it is essential to understand how the protein corona affects the delivery journey of nanoparticles in vivo and what we can do to exploit the protein corona for better delivery efficiency. In this review, we first summarize the fundamental impact of the protein corona on the delivery journey of nanoparticles. Next, we emphasize the strategies that have been developed for tailoring and exploiting the protein corona to improve the transportation behavior of nanoparticles in vivo. Finally, we highlight what we need to do as a next step towards better understanding and exploitation of the protein corona. We hope these insights into the "Yin and Yang" effect of the protein corona will have profound implications for understanding the role of the protein corona in a wide range of nanoparticles.

Nanotechnology Meets Oncology: A Perspective on the Role of the Personalized Nanoparticle-Protein Corona in the Development of Technologies for Pancreatic Cancer Detection

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.

Machine Learning-Assisted FTIR Analysis of Circulating Extracellular Vesicles for Cancer Liquid Biopsy

Extracellular vesicles (EVs) are abundantly released into the systemic circulation, where they show remarkable stability and harbor molecular constituents that provide biochemical information about their cells of origin. Due to this characteristic, EVs are attracting increasing attention as a source of circulating biomarkers for cancer liquid biopsy and personalized medicine. Despite this potential, none of the discovered biomarkers has entered the clinical practice so far, and novel approaches for the label-free characterization of EVs are highly demanded. In this regard, Fourier Transform Infrared Spectroscopy (FTIR) has great potential as it provides a quick, reproducible, and informative biomolecular fingerprint of EVs. In this pilot study, we investigated, for the first time in the literature, the capability of FTIR spectroscopy to distinguish between EVs extracted from sera of cancer patients and controls based on their mid-IR spectral response. For this purpose, EV-enriched suspensions were obtained from the serum of patients diagnosed with Hepatocellular Carcinoma (HCC) of nonviral origin and noncancer subjects. Our data point out the presence of statistically significant differences in the integrated intensities of major mid-IR absorption bands, including the carbohydrate and nucleic acids band, the protein amide I and II bands, and the lipid CH stretching band. Additionally, we used Principal Component Analysis combined with Linear Discriminant Analysis (PCA-LDA) for the automated classification of spectral data according to the shape of specific mid-IR spectral signatures. The diagnostic performances of the proposed spectral biomarkers, alone and combined, were evaluated using multivariate logistic regression followed by a Receiving Operator Curve analysis, obtaining large Areas Under the Curve (AUC = 0.91, 95% CI 0.81–1.0). Very interestingly, our analyses suggest that the discussed spectral biomarkers can outperform the classification ability of two widely used circulating HCC markers measured on the same groups of subjects, namely alpha-fetoprotein (AFP), and protein induced by the absence of vitamin K or antagonist-II (PIVKA-II).

Nanoparticle personalized biomolecular corona: implications of pre-existing conditions for immunomodulation and cancer

Nanoparticles (NPs) have demonstrated great promise as immunotherapies for applications ranging from cancer, autoimmunity, and infectious disease. Upon encountering biological fluids, NPs rapidly adsorb biomolecules, forming the "biomolecular corona" (BC), and the altered character of NPs due to their newly acquired biological identity can impact their in vivo fate. Recently, it has been shown that the NP-BC is person-specific, and even minute differences in the biomolecule composition can give rise to altered immune recognition, cellular interactions, pharmacokinetics, and biodistribution. Given the current rise in the development of NP-based therapeutics, it is of utmost importance to better understand how pre-existing conditions, that result in the formation of a personalized BC, can be leveraged to aid in the prediction of the therapeutic outcomes of NPs. In this minireview, we will discuss the formation of the BC, implications of the BC for NP-biological interactions, and its clinical importance in the context of immunomodulation and cancer therapeutics.

The Janus of Protein Corona on nanoparticles for tumor targeting, immunotherapy and diagnosis

The therapeutics based on nanoparticles (NPs) are considered as the promising strategy for tumor detection and treatment. However, one of the most challenges is the adsorption of biomolecules on NPs after their exposition to biological medium, leading unpredictable in vivo behaviors. The interactions caused by protein corona (PC) will influence the biological fate of NPs in either negative or positive ways, including (i) blood circulation, accumulation and penetration of NPs at targeting sites, and further cellular uptake in tumor targeting delivery; (ii) interactions between NPs and receptors on immune cells for immunotherapy. Besides, PC on NPs could be utilized as new biomarker in tumor diagnosis by identifying the minor change of protein concentration led by tumor growth and invasion in blood. Herein, the mechanisms of these PC-mediated effects will be introduced. Moreover, the recent advances about the strategies will be reviewed to reduce negative effects caused by PC and/or utilize positive effects of PC on tumor targeting, immunotherapy and diagnosis, aiming to provide a reasonable perspective to recognize PC with their applications.

The Diagnostic Value of the CA19-9 and Bilirubin Ratio in Patients with Pancreatic Cancer, Distal Bile Duct Cancer and Benign Periampullary Diseases, a Novel Approach

Distinction of pancreatic ductal adenocarcinoma (PDAC) in the head of the pancreas, distal cholangiocarcinoma (dCCA), and benign periampullary conditions, is complex as they often share similar clinical symptoms. However, these diseases require specific management strategies, urging improvement of non-invasive tools for accurate diagnosis. Recent evidence has shown that the ratio between CA19-9 and bilirubin levels supports diagnostic distinction of benign or malignant hepatopancreaticobiliary diseases. Here, we investigate the diagnostic value of this ratio in PDAC, dCCA and benign diseases of the periampullary region in a novel fashion. To address this aim, we enrolled 265 patients with hepatopancreaticobiliary diseases and constructed four logistic regression models on a subset of patients (n = 232) based on CA19-9, bilirubin and the ratio of both values: CA19-9/(bilirubin^-1). Non-linearity was investigated using restricted cubic splines and a final model, the 'Model Ratio', based on these three variables was fitted using multivariable fractional polynomials. The performance of this model was consistently superior in terms of discrimination and calibration compared to models based on CA19-9 combined with bilirubin and CA19-9 or bilirubin alone. The 'Model Ratio' accurately distinguished between malignant and benign disease (AUC [95% CI], 0.91 [0.86-0.95]), PDAC and benign disease (AUC 0.91 [0.87-0.96]) and PDAC and dCCA (AUC 0.83 [0.74-0.92]) which was confirmed by internal validation using 1000 bootstrap replicates. These findings provide a foundation to improve minimally-invasive diagnostic procedures, ultimately ameliorating effective therapy for PDAC and dCCA.

Detection of Pancreatic Ductal Adenocarcinoma by Ex Vivo Magnetic Levitation of Plasma Protein-Coated Nanoparticles

Pancreatic Ductal Adeno Carcinoma (PDAC) is one of the most lethal malignancies worldwide, and the development of sensitive and specific technologies for its early diagnosis is vital to reduce morbidity and mortality rates. In this proof-of-concept study, we demonstrate the diagnostic ability of magnetic levitation (MagLev) to detect PDAC by using levitation of graphene oxide (GO) nanoparticles (NPs) decorated by a biomolecular corona of human plasma proteins collected from PDAC and non-oncological patients (NOP). Levitation profiles of corona-coated GO NPs injected in a MagLev device filled with a paramagnetic solution of dysprosium(III) nitrate hydrate in water enables to distinguish PDAC patients from NOP with 80% specificity, 100% sensitivity, and global classification accuracy of 90%. Our findings indicate that Maglev could be a robust and instrumental tool for the early detection of PDAC and other cancers.

CA19.9 Serum Level Predicts Lymph-Nodes Status in Resectable Pancreatic Ductal Adenocarcinoma: A Retrospective Single-Center Analysis

BACKGROUND

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.

METHODS

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.

RESULTS

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).

CONCLUSIONS

In R-PDAC with normal serum albumin levels, Ca 19.9 predicts pN+ and R+, thus suggesting a crucial role in deciding on NAT.