19 research outputs found
Glucose-coated gold nanoparticles transfer across human brain endothelium and enter astrocytes in vitro
The blood-brain barrier prevents the entry of many therapeutic agents into the brain. Various nanocarriers have been developed to help agents to cross this barrier, but they all have limitations, with regard to tissue-selectivity and their ability to cross the endothelium. This study investigated the potential for 4 nm coated gold nanoparticles to act as selective carriers across human brain endothelium and subsequently to enter astrocytes. The transfer rate of glucose-coated gold nanoparticles across primary human brain endothelium was at least three times faster than across non-brain endothelia. Movement of these nanoparticles occurred across the apical and basal plasma membranes via the cytosol with relatively little vesicular or paracellular migration; antibiotics that interfere with vesicular transport did not block migration. The transfer rate was also dependent on the surface coating of the nanoparticle and incubation temperature. Using a novel 3-dimensional co-culture system, which includes primary human astrocytes and a brain endothelial cell line hCMEC/D3, we demonstrated that the glucose-coated nanoparticles traverse the endothelium, move through the extracellular matrix and localize in astrocytes. The movement of the nanoparticles through the matrix was >10 µm/hour and they appeared in the nuclei of the astrocytes in considerable numbers. These nanoparticles have the correct properties for efficient and selective carriers of therapeutic agents across the blood-brain barrier
Identification of potential serum biomarkers of glioblastoma: serum osteopontin levels correlate with poor prognosis
Background: The aim of this study is to identify serum biomarkers with classification and prognosis utility for astrocytoma, in particular glioblastoma (GBM). Methods: Our previous glioma microarray database was mined to identify genes that encode secreted or membrane-localized proteins. Subsequent analysis was done using significant analysis of microarrays, followed by reverse transcription-quantitative PCR (RT-qPCR) and immunohistochemical validation in tumor tissues, ELISA and Western blot validation in sera, and correlation with survival of GBM patients. Results: Significant analysis of microarrays identified 31 upregulated and 3 downregulated genes specifically in GBMs. RT-qPCR validation on an independent set of samples confirmed the GBM-specific differential expression of several genes, including three upregulated (CALU, CXCL9, and TIMP1) and two downregulated (GPX3 and TIMP3) novel genes. With respect to osteopontin (OPN), we show the GBM-specific upregulation by RT-qPCR and immunohistochemical staining of tumor tissues. Elevated serum OPN levels in GBM patients were also shown by ELISA and Western blot. GBM patients with high serum OPN levels had poorer survival than those with low serum OPN levels (median survival 9 versus 22 months respectively; P = 0.0001). Further, we also show high serum TIMP1 levels in GBM patients compared with grade II/III patients by ELISA and downregulation of serum GPX3 and TIMP3 proteins in GBMs compared with normal control by Western blot analysis. Conclusions: Several novel potential serum biomarkers of GBM are identified and validated. High serum OPN level is found as a poor prognostic indicator in GBMs. Impact: Identified serum biomarkers may have potential utility in astrocytoma classification and GBM prognosis
Association of Cutibacterium acnes with human thyroid cancer
IntroductionThe diverse subtypes of thyroid carcinoma have distinct clinical outcomes despite a comparable spectrum of underlying genetic alterations. Beyond genetic alterations, sparse efforts have been made to characterize the microbes associated with thyroid cancer. In this study, we examine the microbial profile of thyroid cancer.MethodsWe sequenced the whole transcriptome of 70 thyroid cancers (40 papillary and 30 anaplastic). Using Infectious Pathogen Detector IPD 2.0, we analysed the relative abundance of 1060 microbes across 70 tumours from patients with thyroid cancer against 118 tumour samples from patients with breast, cervical, colorectal, and tongue cancer.ResultsOur analysis reveals a significant prevalence of Cutibacterium acnes in 58.6% thyroid cancer samples compared to other cancer types (p=0.00038). Immune cell fraction analysis between thyroid cancer samples with high and low Cutibacterium loads identify enrichment of immunosuppressive cells, including Tregs (p=0.015), and other anti-inflammatory cytokines in the tumour microenvironment, suggesting an immune evasion/immunosuppression milieu is associated with the infection. A higher burden of Cutibacterium acnes was also found to be associated with poor survival defining a distinct sub-group of thyroid cancer.ConclusionCutibacterium acnes is associated with immune suppression and poor prognosis in a subpopulation of thyroid cancer. This study may help design novel therapeutic measures involving appropriate antibiotics to manage the disease better
The rate of transport of different gold nanoparticles.
<p>TEM of (a) 30 nm colloidal gold (Au30), (b) 4 nm glucose-coated nanoparticles (Glu) and (c) 4 nm glutathione-coated nanoparticles (Gln). (d) Rate of transport of the nanoparticles into and across hCMEC/D3 cells 22 hours after application. Values represent mean ± SEM of the number of nanoparticles located beneath the basal plasma membrane or in the cytosol, based on at least 50 TEM images. Data were analysed by Anova (P<0.01 for the basal membrane data), followed by two-tailed t-tests. *P<0.05, ***P<0.001.</p
Viability of hCMEC/D3 cells treated with gold nanoparticles.
<p>Confluent monolayers of hCMEC/D3 cells were treated for 24 hr with different levels of either glucose-coated or glutathione-coated gold nanoparticles and viability was assessed by MTT assay. Values are mean and SEM of quadruplicate determinations (n = 4). The values were analysed by Anova (p<0.001) followed by Dunnet’s multiple comparison test, comparing each nanoparticle treatment with the untreated cells (Con). Only one treatment was significantly different from the control (*P<0.001). Digitonin-treated cells (Dig) were a positive control for cell death.</p
Location of glucose-coated gold nanoparticles in co-cultures.
a<p>Nanoparticles per mm located in sections 85 nm deep at 8 hrs, in brain endothelium or astrocytes (mean ± SEM, n = 3 or 4). Data-points were obtained by counting all nanoparticles in strips of 1–2 mm.</p
The rate of transfer of glucose-coated gold nanoparticles across brain endothelium compared with non-brain endothelium.
<p>(a) Brain endothelial hCMEC/D3 cells and human primary brain endothelium (1-BEC) were compared with a human bone marrow endothelial cell line (BMEC) and human primary coronary artery endothelium (CoAEC). The values show the number of nanoparticles per cell, located between the basal plasma membrane and the transwell insert 8 hrs after application to the apical surface. Values show mean ±SEM from at least 50 different cells, and two separate cultures. Note that the scale of the y-axis is expanded for the two non-brain endothelial cell types. (b) The bar chart shows the number of nanoparticles per micron of the basal membrane after 8 hrs (mean ±SEM) from the four different cell types. Data was analysed by Anova (P<0.05) followed by Tukey’s test to compare each pair of points. **P<0.01, ***P<0.001.</p
The categories that were established to sort localization of glucose-coated gold nanoparticles in cells.
*<p>even though nanoparticles were not definitely observed in mitochondria, we cannot exclude them from this category as during sectioning it is not always possible to unambiguously identify every membrane surrounded organelle or granule.</p
Electron micrographs of brain endothelial cells with glucose-coated gold nanoparticles.
<p>(a) hCMEC/D3 cells and (b) primary human brain endothelium 8 hours after application of glucose-nanoparticles to the apical surface. Nanoparticles are located between the basal plasma membrane and the transwell insert (arrows), for (b) the lower area is also magnified in the top left corner ×2. (c) A gold nanoparticle in the intercellular junction of hCMEC/D3 cells (arrow) 3 hours after application of nanoparticles to the apical surface (detailed magnification of the junction with nanoparticle is in the top left corner ×7). The nanoparticles are also seen in the cytosol and vesicles. (d) Detail of nanoparticles located in the cytosol and beneath the basal membrane. (e) Detail of nanoparticles in a vesicle. Scale bars = 500 nm.</p
A Fourteen Gene GBM Prognostic Signature Identifies Association of Immune Response Pathway and Mesenchymal Subtype with High Risk Group
<div><p>Background</p><p>Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature.</p><p>Methods</p><p>Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort.</p><p>Results</p><p>A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2<sup>.</sup>507; B = 0<sup>.</sup>919; p<0<sup>.</sup>001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0<sup>.</sup>001) and TCGA cohort (p = 0<sup>.</sup>001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group.</p><p>Conclusion</p><p>We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.</p></div