The development of engineered nanomaterials is growing exponentially, despite concerns over their potential similarities to environmental nanoparticles that are associated with significant cardiorespiratory morbidity and mortality. The mechanisms through which inhalation of nanoparticles could trigger acute cardiovascular events are emerging, but a fundamental unanswered question remains: Do inhaled nanoparticles translocate from the lung in man and directly contribute to the pathogenesis of cardiovascular disease? In complementary clinical and experimental studies, we used gold nanoparticles to evaluate particle translocation, permitting detection by high-resolution inductively coupled mass spectrometry and Raman microscopy. Healthy volunteers were exposed to nanoparticles by acute inhalation, followed by repeated sampling of blood and urine. Gold was detected in the blood and urine within 15 min to 24 h after exposure, and was still present 3 months after exposure. Levels were greater following inhalation of 5 nm (primary diameter) particles compared to 30 nm particles. Studies in mice demonstrated the accumulation in the blood and liver following pulmonary exposure to a broader size range of gold nanoparticles (2–200 nm primary diameter), with translocation markedly greater for particles <10 nm diameter. Gold nanoparticles preferentially accumulated in inflammation-rich vascular lesions of fat-fed apolipoproteinE-deficient mice. Furthermore, following inhalation, gold particles could be detected in surgical specimens of carotid artery disease from patients at risk of stroke. Translocation of inhaled nanoparticles into the systemic circulation and accumulation at sites of vascular inflammation provides a direct mechanism that can explain the link between environmental nanoparticles and cardiovascular disease and has major implications for risk management in the use of engineered nanomaterials.

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ObjectivesTo develop a risk classifier using urine‐derived extracellular vesicle (EV)‐RNA capable of providing diagnostic information on disease status prior to biopsy, and prognostic information for men on active surveillance (AS).Patients and MethodsPost‐digital rectal examination urine‐derived EV‐RNA expression profiles (n = 535, multiple centres) were interrogated with a curated NanoString panel. A LASSO‐based continuation ratio model was built to generate four prostate urine risk (PUR) signatures for predicting the probability of normal tissue (PUR‐1), D'Amico low‐risk (PUR‐2), intermediate‐risk (PUR‐3), and high‐risk (PUR‐4) prostate cancer. This model was applied to a test cohort (n = 177) for diagnostic evaluation, and to an AS sub‐cohort (n = 87) for prognostic evaluation.ResultsEach PUR signature was significantly associated with its corresponding clinical category (P < 0.001). PUR‐4 status predicted the presence of clinically significant intermediate‐ or high‐risk disease (area under the curve = 0.77, 95% confidence interval [CI] 0.70–0.84). Application of PUR provided a net benefit over current clinical practice. In an AS sub‐cohort (n = 87), groups defined by PUR status and proportion of PUR‐4 had a significant association with time to progression (interquartile range hazard ratio [HR] 2.86, 95% CI 1.83–4.47; P < 0.001). PUR‐4, when used continuously, dichotomized patient groups with differential progression rates of 10% and 60% 5 years after urine collection (HR 8.23, 95% CI 3.26–20.81; P < 0.001).ConclusionUrine‐derived EV‐RNA can provide diagnostic information on aggressive prostate cancer prior to biopsy, and prognostic information for men on AS. PUR represents a new and versatile biomarker that could result in substantial alterations to current treatment of patients with prostate cancer.

Development and manufacture of nanomaterials is growing at an exponential rate, despite an incomplete understanding of how their physicochemical characteristics affect their potential toxicity. Redox activity has been suggested to be an important physicochemical property of nanomaterials to predict their biological activity. This study assessed the influence of redox activity by modification of cerium dioxide nanoparticles (CeO NPs) via zirconium (Zr) doping on the biodistribution, pulmonary and cardiovascular effects in mice following inhalation. Healthy mice (C57BL/6 J), mice prone to cardiovascular disease (ApoE, western-diet fed) and a mouse model of neurological disease (5 × FAD) were exposed via nose-only inhalation to CeO NPs with varying amounts of Zr-doping (0%, 27% or 78% Zr), or clean air, over a four-week period (4 mg/m for 3 h/day, 5 days/week). Effects were assessed four weeks post-exposure. In all three mouse models CeO NP exposure had no major toxicological effects apart from some modest inflammatory histopathology in the lung, which was not related to the amount of Zr-doping. In ApoE mice CeO did not change the size of atherosclerotic plaques, but there was a trend towards increased inflammatory cell content in relation to the Zr content of the CeO NPs. These findings show that subacute inhalation of CeO NPs causes minimal pulmonary and cardiovascular effect four weeks post-exposure and that Zr-doping of CeO NPs has limited effect on these responses. Further studies with nanomaterials with a higher inherent toxicity or a broader range of redox activities are needed to fully assess the influence of redox activity on the toxicity of nanomaterials.

In biological fluids nanoparticles bind a range of molecules, particularly proteins, on their surface. The resulting protein corona influences biological activity and fate of nanoparticle in vivo. Corona composition is often determined by the biological milieu encountered at the entry portal into the body, and, can therefore, depend on the route of exposure to the nanoparticle. For environmental nanoparticles where exposure is by inhalation, this will be lung lining fluid. This study examined plasma and bronchoalveolar fluid (BALF) protein binding to engineered and environmental nanoparticles. We hypothesized that protein corona on nanoparticles would influence nanoparticle uptake and subsequent pro-inflammatory biological response in macrophages. All nanoparticles bound plasma and BALF proteins, but the profile of bound proteins varied between nanoparticles. Focusing on diesel exhaust nanoparticles (DENP), we identified proteins bound from plasma to include fibrinogen, and those bound from BALF to include albumin and surfactant proteins A and D. The presence on DENP of a plasma-derived corona or one of purified fibrinogen failed to evoke an inflammatory response in macrophages. However, coronae formed in BALF increased DENP uptake into macrophages two fold, and increased nanoparticulate carbon black (NanoCB) uptake fivefold. Furthermore, a BALF-derived corona increased IL-8 release from macrophages in response to DENP from 1720 ± 850 pg/mL to 5560 ± 1380 pg/mL (p = 0.014). These results demonstrate that the unique protein corona formed on nanoparticles plays an important role in determining biological reactivity and fate of nanoparticle in vivo. Importantly, these findings have implications for the mechanism of detrimental properties of environmental nanoparticles since the principle route of exposure to such particles is via the lung.

Exposure to high aspect ratio nanomaterials, such as multi-walled carbon nanotubes (MWCNTs) may be associated with increased risk of atherosclerosis, pulmonary disease, and cancer. In the present study, we investigated the cardiovascular and pulmonary health effects of 10 weeks of repeated oral or pulmonary exposures to MWCNTs (4 or 40μg each week) in Apolipoprotein E-deficient (ApoE) mice fed a Western-type diet. Intratracheal instillation of MWCNTs was associated with oxidative damage to DNA in lung tissue and elevated levels of lipid peroxidation products in plasma, whereas the exposure only caused a modest pulmonary inflammation in terms of increased numbers of lymphocytes in bronchoalveolar lavage fluid. Ultrasound imaging in live animals revealed an increase in the inner and outer wall thickness of the aortic arch at 10 weeks after pulmonary exposure to MWCNTs, which may suggest artery remodelling. However, we did not find accelerated plaque progression in the aorta or the brachiocephalic artery by histopathology. Furthermore, repeated oral exposure to MWCNTs did not cause changes in the composition of gut microbiota of exposed mice. Collectively, this study indicates that repeated pulmonary exposure to MWCNTs was associated with oxidative stress, whereas cardiovascular effects encompassed remodelling of the aorta wall.

Background Prostate cancer exhibits severe clinical heterogeneity and there is a critical need for clinically implementable tools able to precisely and noninvasively identify patients that can either be safely removed from treatment pathways or those requiring further follow up. Our objectives were to develop a multivariable risk prediction model through the integration of clinical, urine‐derived cell‐free messenger RNA (cf‐RNA) and urine cell DNA methylation data capable of noninvasively detecting significant prostate cancer in biopsy naïve patients. Methods Post‐digital rectal examination urine samples previously analyzed separately for both cellular methylation and cf‐RNA expression within the Movember GAP1 urine biomarker cohort were selected for a fully integrated analysis (n = 207). A robust feature selection framework, based on bootstrap resampling and permutation, was utilized to find the optimal combination of clinical and urinary markers in a random forest model, deemed ExoMeth. Out‐of‐bag predictions from ExoMeth were used for diagnostic evaluation in men with a clinical suspicion of prostate cancer (PSA ≥ 4 ng/mL, adverse digital rectal examination, age, or lower urinary tract symptoms). Results As ExoMeth risk score (range, 0‐1) increased, the likelihood of high‐grade disease being detected on biopsy was significantly greater (odds ratio = 2.04 per 0.1 ExoMeth increase, 95% confidence interval [CI]: 1.78‐2.35). On an initial TRUS biopsy, ExoMeth accurately predicted the presence of Gleason score ≥3 + 4, area under the receiver‐operator characteristic curve (AUC) = 0.89 (95% CI: 0.84‐0.93) and was additionally capable of detecting any cancer on biopsy, AUC = 0.91 (95% CI: 0.87‐0.95). Application of ExoMeth provided a net benefit over current standards of care and has the potential to reduce unnecessary biopsies by 66% when a risk threshold of 0.25 is accepted. Conclusion Integration of urinary biomarkers across multiple assay methods has greater diagnostic ability than either method in isolation, providing superior predictive ability of biopsy outcomes. ExoMeth represents a more holistic view of urinary biomarkers and has the potential to result in substantial changes to how patients suspected of harboring prostate cancer are diagnosed.

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