Improving the accuracy of pancreatic cancer clinical staging by exploitation of nanoparticle-blood interactions: A pilot study

The Protein Corona on Nanoparticles for Tumor Targeting in Prostate Cancer-A Review of the Literature and Experimental Trial Protocol

The National Cancer Institute (NCI) recognizes the potential of technologies based on the use of nanoparticles (NPs) in revolutionizing clinical approaches to the diagnosis and prognosis of cancer. Recent research suggests that once NPs come into contact with the biological fluid of cancer patients, they are covered by proteins, forming a "protein corona" composed of hundreds of plasma proteins. The concept of a personalized, disease-specific protein corona, demonstrating substantial differences in NP corona profiles between patients with and without cancer, has been introduced. We developed the design of an experimental prospective single-center study with patients allocated in a 1:1:1 ratio of one of three arms: untreated patients with benign prostatic hyperplasia (BPH), untreated patients with non-metastatic prostate cancer (PCa), and metastatic prostate cancer patients starting systemic therapies with new androgen-targeted agents or taxanes. The protocol aims to develop and implement sensitive nanotools with two distinct objectives: First, to design NPs capable of selectively binding and detecting biomarkers in order to build a predictive diagnostic model to effectively discriminate between patient sera affected by BPH and PCa. Secondly, within the population with PCa, in the case of initial advanced metastatic diagnosis, the objective is to find biomarkers capable of predicting the response to systemic treatments to improve the precision and efficiency of monitoring treatment outcomes. For protein and metabolite corona experiments, we developed a cross-reactive sensor array platform with cancer detection capacity made of three liposomal formulations with different surface charges. For proteomic-NP studies, proteins were identified and quantified using nano-high-performance LC (nanoHPLC) coupled with MS/MS (nanoHPLC-MS/MS). Metabolites were instead analyzed using an untargeted metabolomic approach. Compared with previous review articles, the novelty of this review is represented by the analysis of the possible clinical applications of protein corona NPs focused on PCa and the presentation of a new clinical protocol in the metastatic phase of PCa.

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.

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.

Self-Therapeutic Nanomaterials: Applications in Biology and Medicine

Over past decades, nanotechnology has contributed to the biomedical field in areas including detection, diagnosis, and drug delivery via opto-electronic properties or enhancement of biological effects. Though generally considered inert delivery vehicles, a plethora of past and present evidence demonstrates that nanomaterials also exude unique intrinsic biological activity based on composition, shape, and surface functionalization. These intrinsic biological activities, termed self-therapeutic properties, take several forms, including mediation of cell-cell interactions, modulation of interactions between biomolecules, catalytic amplification of biochemical reactions, and alteration of biological signal transduction events. Moreover, study of biomolecule-nanomaterial interactions offers a promising avenue for uncovering the molecular mechanisms of biology and the evolution of disease. In this review, we observe the historical development, synthesis, and characterization of self-therapeutic nanomaterials. Next, we discuss nanomaterial interactions with biological systems, starting with administration and concluding with elimination. Finally, we apply this materials perspective to advances in intrinsic nanotherapies across the biomedical field, from cancer therapy to treatment of microbial infections and tissue regeneration. We conclude with a description of self-therapeutic nanomaterials in clinical trials and share our perspective on the direction of the field in upcoming years.

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.

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.

Nanomedicine for overcoming therapeutic and diagnostic challenges associated with pancreatic cancer

Pancreatic cancer is the second leading cause of cancer-related death in the USA. The 5-year survival rate for pancreatic cancer is as low as 10%, making it one of the most deadly cancers. This dismal prognosis is caused, in part, by the lack of early detection and screening options, leading to late-stage detection of the disease, at a point at which chemotherapy is no longer effective. However, nanoparticle (NP) drug delivery systems have increased the efficacy of chemotherapeutics by improving the targeting ability of drugs to the tumor site, while also decreasing the risk of local and systemic toxicity. Such efforts can contribute to the development of early diagnosis and routine screening tests, which will drastically improve the survival rates and prognosis of patients with pancreatic cancer.

Nanotechnology Tools Enabling Biological Discovery

Over the years, the engineering aspect of nanotechnology has been significantly exploited. Medical intervention strategies have been developed by leveraging existing molecular biology knowledge and combining it with nanotechnology tools to improve outcomes. However, little attention has been paid to harnessing the strengths of nanotechnology as a biological discovery tool. Fundamental understanding of controlling dynamic biological processes at the subcellular level is key to developing personalized therapeutic and diagnostic interventions. Single-cell analyses using intravital microscopy, expansion microscopy, and microfluidic-based platforms have been helping to better understand cell heterogeneity in healthy and diseased cells, a major challenge in oncology. Also, single-cell analysis has revealed critical signaling pathways and biological intracellular components with key biological functions. The physical manipulation enabled by nanotools can allow real-time monitoring of biological changes at a single-cell level by sampling intracellular fluid from the same cell. The formation of intercellular highways by nanotube-like structures has important clinical implications such as metastasis development. The integration of nanomaterials into optical and molecular imaging techniques has rendered valuable morphological, structural, and biological information. Nanoscale imaging unravels mechanisms of temporality by enabling the visualization of nanoscale dynamics never observed or measured between individual cells with standard biological techniques. The exceptional sensitivity of nanozymes, artificial enzymes, make them perfect components of the next-generation mobile diagnostics devices. Here, we highlight these impactful cancer-related biological discoveries enabled by nanotechnology and producing a paradigm shift in cancer research and oncology.

A Proteomic Study on the Personalized Protein Corona of Liposomes. Relevance for Early Diagnosis of Pancreatic DUCTAL Adenocarcinoma and Biomarker Detection

Due to late diagnosis, high incidence of metastasis, and poor survival rate, pancreatic cancer is one of the most leading cause of cancer-related death. Although manifold recent efforts have been done to achieve an early diagnosis of pancreatic cancer, CA-19.9 is currently the unique biomarker that is adopted for the detection, despite its limits in terms of sensitivity and specificity. To identify potential protein biomarkers for pancreatic ductal adenocarcinoma (PDAC), we used three model liposomes as nanoplatforms that accumulate proteins from human plasma and studied the composition of this biomolecular layer, which is known as protein corona. Indeed, plasma proteins adsorb on nanoparticle surface according to their abundance and affinity to the employed nanomaterial, thus even small differences between healthy and PDAC protein expression levels can be, in principle, detected. By mass spectrometry experiments, we quantified such differences and identified possible biomarkers for PDAC. Some of them are already known to exhibit different expressions in PDAC proteomes, whereas the role of other relevant proteins is still not clear. Therefore, we predict that the employment of nanomaterials and their protein corona may represent a useful tool to amplify the detection sensitivity of cancer biomarkers, which may be used for the early diagnosis of PDAC, with clinical implication for the subsequent therapy in the context of personalized medicine.

Nanotechnology and pancreatic cancer management: State of the art and further perspectives

Pancreatic ductal adenocarcinoma (PDAC) represents a leading cause of cancer death and is often diagnosticated too late to allow adequate treatments. Lots of biomarkers have been discovered in lasts years but, to date, there is a lack of low-cost and non-invasive tools for PDAC early detection. Nonetheless, drugs commonly used in PDAC treatment do not allow achieving long-term satisfying results. Nanotechnology is gaining importance in both PDAC early detection and treatment. The main implications of nanotechnology in cancer diagnosis lay in the ability that nanoparticles have on concentrate the alteration in human proteome caused by cancer. Nanoparticle-enabled blood tests have been demonstrated to reach high rate of sensitivity (up to 85%) and specificity (up to 100%). In the field of cancer therapy nanoparticles can be used as nanocarriers able to reach specific tumour's cells and selectively release the drug they contain into them. A literature review was carried out with the aim to assess the state of the art and highlight the future perspectives of nanotechnology in PDAC early detection and therapy.

Analysing the nanoparticle-protein corona for potential molecular target identification

When nanoparticles are introduced into biological systems, host proteins tend to associate on the particle surface to form a protein layer termed the "protein corona" (PC). Identifying the proteins that constitute the PC can yield useful information about nanoparticle processing, bio-distribution, toxicity and clearance. Similarly, characterizing and identifying proteins within the PC from patient samples provides opportunities to probe disease proteomes and identify molecules that influence the disease process. Thus, nanoparticles represent unique probing tools for discovery of molecular targets for diseases. Here, we report a first review on target identification using nanoparticles in biological samples based on analysing physico chemical interactions. We also summarize the evolution of the PC surrounding various nano-systems, comment on PC signature, address PC complexity in fluids, and outline challenges associated with analysing the PC. In addition, the influence on PC formation of various nanoparticle parameters is summarized; nanoparticle characteristics considered include size, charge, temperature, and surface modifications for both organic and inorganic nanomaterials. We also discuss the advantages of nanotechnology, over other more invasive and laborious methods, for identifying potential diagnostic and therapeutic targets.

Personalized Graphene Oxide-Protein Corona in the Human Plasma of Pancreatic Cancer Patients

The protein corona (PC) that forms around nanomaterials upon exposure to human biofluids (e.g., serum, plasma, cerebral spinal fluid etc.) is personalized, i.e., it depends on alterations of the human proteome as those occurring in several cancer types. This may relevant for early cancer detection when changes in concentration of typical biomarkers are often too low to be detected by blood tests. Among nanomaterials under development for in vitro diagnostic (IVD) testing, Graphene Oxide (GO) is regarded as one of the most promising ones due to its intrinsic properties and peculiar behavior in biological environments. While recent studies have explored the binding of single proteins to GO nanoflakes, unexplored variables (e.g., GO lateral size and protein concentration) leading to formation of GO-PC in human plasma (HP) have only marginally addressed so far. In this work, we studied the PC that forms around GO nanoflakes of different lateral sizes (100, 300, and 750 nm) upon exposure to HP at several dilution factors which extend over three orders of magnitude from 1 (i.e., undiluted HP) to 103. HP was collected from 20 subjects, half of them being healthy donors and half of them diagnosed with pancreatic ductal adenocarcinoma (PDAC) a lethal malignancy with poor prognosis and very low 5-year survival rate after diagnosis. By dynamic light scattering (DLS), electrophoretic light scattering (ELS), sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and nano liquid chromatography tandem mass spectrometry (nano-LC MS/MS) experiments we show that the lateral size of GO has a minor impact, if any, on PC composition. On the other side, protein concentration strongly affects PC of GO nanoflakes. In particular, we were able to set dilution factor of HP in a way that maximizes the personalization of PC, i.e., the alteration in the protein profile of GO nanoflakes between cancer vs. non-cancer patients. We believe that this study shall contribute to a deeper understanding of the interactions among GO and HP, thus paving the way for the development of IVD tools to be used at every step of the patient pathway, from prognosis, screening, diagnosis to monitoring the progression of disease.

Nanoparticle-enabled blood tests for early detection of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is often detected too late to allow adequate treatments with the result that patients are condemned to sufferings and early death. Most efforts have been therefore aimed at identifying sensitive PDAC biomarkers. Although biomarkers have numerous advantages, sample size, intra-individual variability, existence of several biases and confounding variables and cost of investigation make their clinical application challenging. In recent years, nanotechnology is providing new options for early cancer detection. Among recent discoveries, the concept is emerging that the protein corona, i.e. the layer of plasma proteins that surrounds nanomaterials in bodily fluids, is personalized. In particular, the protein corona of cancer patients is significantly different from that of healthy individuals. Herein, we review this concept with a particular focus on clinical relevance. We also discuss the recently developed nanoparticle-enabled blood (NEB) tests that demonstrated to be promising in discriminating PDAC patients from healthy volunteers by global change of the nanoparticle-protein corona. We conclude with a critical discussion of research perspectives aimed at further improving the prediction ability of the test.

The biomolecular corona of gold nanoparticles in a controlled microfluidic environment

Nanoparticles (NPs) exposed to biological media are coated by proteins and other biomolecules forming a biomolecular corona (BC) on the particle surface. Recent studies have shown that shear stress as that created by laminar fluid flow generates more complex coronas with systematic changes in composition with respect to counterparts formed under static incubation. However, in most studies reported so far, dynamic environments have been produced by peristaltic pumps and comparing experimental results appears challenging. On the other side, generating shear stress by microfluidic devices could help to remove user variability and ensure better reproducibility of experimental data. This study was therefore aimed at exploring formation of NP-BC in a microfluidic environment. To this end, 100 nm gold nanoparticles and human plasma (HP) were used as models for nano-formulation and biological medium. We injected gold nanoparticles and HP in each of the islets of a remote-controlled microfluidic cartridge. Static incubation was used as a reference. BC-decorated NPs were thoroughly characterized by dynamic light scattering (DLS), micro-electrophoresis (ME), sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS PAGE) and nano-liquid chromatography tandem mass spectrometry (nano-LC MS/MS). By varying the incubation time from 30 s to 2.5 min we demonstrate that BC is already determined by the earliest exposure time point and does not appreciably evolve in time. DLS and ME results demonstrate that the BC formed in a microfluidic chip is thicker and more negatively charged than its counterpart formed under static incubation. SDS-PAGE and nano-LC MS/MS revealed that the incubation procedure had a major effect on BC composition. As an example, immunoglobulins are the most abundant plasma proteins of the BC generated in a microfluidic environment (relative protein abundance ∼30%), while tissue leakage proteins (relative protein abundance ∼26%) are the most enriched proteins when the BC is formed upon static incubation. Potential implications in emerging biomedical research arenas are discussed.

Disease-specific protein corona sensor arrays may have disease detection capacity

Protein corona sensor array technology identifies diseases through specific proteomics pattern recognition.