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.
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.
Pancreatic cancer (PC) is a clinically challenging tumor to combat due to its advanced stage at diagnosis as well as its resistance to currently available therapies. The absence of early symptoms and ...known detectable biomarkers renders this disease incredibly difficult to detect/manage. Recent advances in the understanding of PC biology have highlighted the importance of cancer-immune cell interactions, not only in the tumor micro-environment but also in distant systemic sites, like the bone marrow, spleen and circulating immune cells, the so-called macro-environment. The response of the macro-environment is emerging as a determining factor in tumor development by contributing to the formation of an increasingly immunogenic micro-environment promoting tumor homeostasis and progression. We will summarize the key events associated with the feedback loop between the tumor immune micro-environment (TIME) and the tumor immune macroenvironment (TIMaE) in pancreatic precancerous lesions along with how it regulates disease development and progression. In addition, liquid biopsy biomarkers capable of diagnosing PC at an early stage of onset will also be discussed. A clearer understanding of the early crosstalk between micro-environment and macro-environment could contribute to identifying new molecular therapeutic targets and biomarkers, consequently improving early PC diagnosis and treatment. Keywords: Pancreatic cancer, Macro-environment, Micro-environment, Immune landscape, Circulating biomarkers
hERG1 potassium channels are widely expressed in human cancers of different origins, where they affect several key aspects of cellular behaviour. The present study was designed to evaluate the ...expression and clinical relevance of hERG1 protein in cancer tissues from patients suffering from neuroendocrine tumours (NETs) of ileal (iNETs) and pancreatic (pNETs) origin, with available clinicopathological history and follow-up. The study was carried out by immunohistochemistry with an anti-hERG1 monoclonal antibody. In a subset of samples, a different antibody directed against the hERG1/β1 integrin complex was also used. The analysis showed for the first time that hERG1 is expressed in human NETs originating from either the ileum or the pancreas. hERG1 turned out to have a prognostic value in NETs, showing (i) a statistically significant positive impact on OS of patients affected by ileal NETs, regardless the TNM stage; (ii) a statistically significant positive impact on OS of patients affected by aggressive (TNM stage IV) disease, either ileal or pancreatic; (iii) a trend to a negative impact on OS of patients affected by less aggressive (TNM stage I-III) disease, either ileal or pancreatic. Moreover, in order to evaluate whether ERG1 was functionally expressed in a cellular model of pNET, the INS1E rat insulinoma cell line was used, and it emerged that blocking ERG1 with a specific inhibitor of the channel (E4031) turned out in a significant reduction in cell proliferation.
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.
•Pancreatic ductal adenocarcinoma (PDAC) is a lethal gastrointestinal malignancy.•The absence of early symptoms and inadequate detection tools lead to poor prognoses.•Many biomarkers do not meet ASSURED criteria of the World Health Organization.•The protein corona that forms around nanomaterials in bodily fluids is personalized.•Nanoparticle-enabled blood tests have great sensitivity and specificity.
Unprecedented opportunities for early stage cancer detection have recently emerged from the characterization of the personalized protein corona (PC), i.e., the protein cloud that surrounds ...nanoparticles (NPs) upon exposure to a patients' bodily fluids. Most of these methods require "direct characterization" of the PC., i.e., they necessitate protein isolation, identification, and quantification. Each of these steps can introduce bias and affect reproducibility and inter-laboratory consistency of experimental data. To fulfill this gap, here we develop a nanoparticle-enabled blood (NEB) test based on the indirect characterization of the personalized PC by magnetic levitation (MagLev). The MagLev NEB test works by analyzing the levitation profiles of PC-coated graphene oxide (GO) NPs that migrate along a magnetic field gradient in a paramagnetic medium. For the test validation, we employed human plasma samples from 15 healthy individuals and 30 oncological patients affected by four cancer types, namely breast cancer, prostate cancer, colorectal cancer, and pancreatic ductal adenocarcinoma (PDAC). Over the last 15 years prostate cancer, colorectal cancer, and PDAC have continuously been the second, third, and fourth leading sites of cancer-related deaths in men, while breast cancer, colorectal cancer, and PDAC are the second, third and fourth leading sites for women. This proof-of-concept investigation shows that the sensitivity and specificity of the MagLev NEB test depend on the cancer type, with the global classification accuracy ranging from 70% for prostate cancer to an impressive 93.3% for PDAC. We also discuss how this tool could benefit from several tunable parameters (e.g., the intensity of magnetic field gradient, NP type, exposure conditions, etc.) that can be modulated to optimize the detection of different cancer types with high sensitivity and specificity.
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
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 10
. 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.
Simultaneous detection of multiple analytes from a single biological sample is gaining more attention in the development of more reliable and point-of-care diagnostic devices. We developed a ...multiplexed strategy that combined outcomes of clinical biomarkers with analysis of the protein corona that forms around graphene oxide sheets upon exposure to patient's plasma. As a paradigmatic case study, we selected pancreatic ductal adenocarcinoma (PDAC), mainly because of the absence of effective detection strategies that resulted in an extremely low five-year survival rate after diagnosis (<10%). Association of protein corona analysis and haemoglobin levels discriminated PDAC patients from healthy volunteers in up to 90% of cases. If further confirmed in larger-cohort studies, this approach may be used in the detection of PDAC.
Background and Objectives: The aim of this study was to evaluate the diagnostic accuracy and prognostic value of neutrophil-to-lymphocyte (NLR) and platelet-to-lymphocyte (PLR) ratios and to compare ...them with other biomarkers and clinical scores of sepsis outside the intensive care unit. Materials and methods: In this retrospective study, 251 patients with sepsis and 126 patients with infection other than sepsis were enrolled. NLR and PLR were calculated as the ratio between absolute values of neutrophils, lymphocytes, and platelets by complete blood counts performed on whole blood by Sysmex XE-9000 (Dasit, Italy) following the manufacturer’s instruction. Results: The best NLR value in diagnosis of sepsis was 7.97 with sensibility, specificity, AUC, PPV, and NPV of 64.26%, 80.16%, 0.74 (p < 0.001), 86.49%, and 53.18%, respectively. The diagnostic role of NLR significantly increases when PLR, C-reactive protein (PCR), procalcitonin (PCT), and mid-regional pro-adrenomedullin (MR-proADM) values, as well as systemic inflammatory re-sponse syndrome (SIRS), sequential organ failure assessment (SOFA), and quick-sequential organ failure assessment (qSOFA) scores, were added to the model. The best value of NLR in predicting 90-day mortality was 9.05 with sensibility, specificity, AUC, PPV, and NPV of 69.57%, 61.44%, 0.66 (p < 0.0001), 28.9%, and 89.9%, respectively. Sensibility, specificity, AUC, PPV, and NPV of NLR increase if PLR, PCR, PCT, MR-proADM, SIRS, qSOFA, and SOFA scores are added to NLR. Conclusions: NLR and PLR represent a widely useful and cheap tool in diagnosis and in predict-ing 90-day mortality in patients with sepsis.
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