Anti-viral state segregates two molecular phenotypes of pancreatic adenocarcinoma: potential relevance for adenoviral gene therapy

<p>Abstract</p> <p>Background</p> <p>Pancreatic ductal adenocarcinoma (PDAC) remains a leading cause of cancer mortality for which novel gene therapy approaches relying on tumor-tropic adenoviruses are being tested.</p> <p>Methods</p> <p>We obtained the global transcriptional profiling of primary PDAC using RNA from eight xenografted primary PDAC, three primary PDAC bulk tissues, three chronic pancreatitis and three normal pancreatic tissues. The Affymetrix GeneChip HG-U133A was used. The results of the expression profiles were validated applying immunohistochemical and western blot analysis on a set of 34 primary PDAC and 10 established PDAC cell lines. Permissivity to viral vectors used for gene therapy, Adenovirus 5 and Adeno-Associated Viruses 5 and 6, was assessed on PDAC cell lines.</p> <p>Results</p> <p>The analysis of the expression profiles allowed the identification of two clearly distinguishable phenotypes according to the expression of interferon-stimulated genes. The two phenotypes could be readily recognized by immunohistochemical detection of the Myxovirus-resistance A protein, whose expression reflects the activation of interferon dependent pathways. The two molecular phenotypes discovered in primary carcinomas were also observed among established pancreatic adenocarcinoma cell lines, suggesting that these phenotypes are an intrinsic characteristic of cancer cells independent of their interaction with the host's microenvironment. The two pancreatic cancer phenotypes are characterized by different permissivity to viral vectors used for gene therapy, as cell lines expressing interferon stimulated genes resisted to Adenovirus 5 mediated lysis in vitro. Similar results were observed when cells were transduced with Adeno-Associated Viruses 5 and 6.</p> <p>Conclusion</p> <p>Our study identified two molecular phenotypes of pancreatic cancer, characterized by a differential expression of interferon-stimulated genes and easily recognized by the expression of the Myxovirus-resistance A protein. We suggest that the detection of these two phenotypes might help the selection of patients enrolled in virally-mediated gene therapy trials.</p

Early diagnosis of bladder cancer by photoacoustic imaging of tumor-targeted gold nanorods

Detection and removal of bladder cancer lesions at an early stage is crucial for preventing tumor relapse and progression. This study aimed to develop a new technological platform for the visualization of small and flat urothelial lesions of high-grade bladder carcinoma in situ (CIS). We found that the integrin alpha 581, overexpressed in bladder cancer cell lines, murine orthotopic bladder cancer and human bladder CIS, can be exploited as a receptor for targeted delivery of GNRs functionalized with the cyclic CphgisoDGRG peptide (Iso4). The GNRs@Chit-Iso4 was stable in urine and selectively recognized alpha 581 positive neoplastic urothelium, while low frequency ultrasound-assisted shaking of intravesically instilled GNRs@Chit-Iso4 allowed the distribution of nanoparticles across the entire volume of the bladder. Photoacoustic imaging of GNRs@Chit-Iso4 bound to tumor cells allowed for the detection of neoplastic lesions smaller than 0.5 mm that were undetectable by ultrasound imaging and bioluminescence

A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models

This paper presents a cross-country comparison of significant predictors of small business failure between Italy and the UK. Financial measures of profitability, leverage, coverage, liquidity, scale and non-financial information are explored, some commonalities and differences are highlighted. Several models are considered, starting with the logistic regression which is a standard approach in credit risk modelling. Some important improvements are investigated. Generalised Extreme Value (GEV) regression is applied in contrast to the logistic regression in order to produce more conservative estimates of default probability. The assumption of non-linearity is relaxed through application of BGEVA, non-parametric additive model based on the GEV link function. Two methods of handling missing values are compared: multiple imputation and Weights of Evidence (WoE) transformation. The results suggest that the best predictive performance is obtained by BGEVA, thus implying the necessity of taking into account the low volume of defaults and non-linear patterns when modelling SME performance. WoE for the majority of models considered show better prediction as compared to multiple imputation, suggesting that missing values could be informative

Remission, minimal disease activity, and acceptable symptom state in juvenile idiopathic arthritis: Defining criteria based on the juvenile arthritis disease activity score

To determine cutoff values for defining remission, minimal disease activity, and parent and child acceptable symptom state in juvenile idiopathic arthritis (JIA) using the Juvenile Arthritis Disease Activity Score (JADAS).For the selection of cutoff values, data from a clinical database including 609 children with JIA were used. Optimal cutoff values were determined against external criteria by calculating the 75th percentile of cumulative score distribution and through receiver operating characteristic curve analysis. External criteria included formal definitions of inactive disease and minimal disease activity, subjective rating of remission by physicians, parents, and children, and rating of acceptable symptom state by parents and children. The choice of cutoffs was made based on clinical and statistical grounds. Cross-validation was performed using 4 JIA patient samples that included a total of 1,323 patients, and was based on assessment of construct, discriminant, and predictive validity.With all versions of the JADAS, the cutoff score for classifying a patient as having inactive disease was 1, whereas the cutoff for classification of minimal disease activity was 2 for oligoarticular JIA and 3.8 for polyarticular JIA. Cutoffs for physicians', parents', and children's subjective rating of remission ranged from 2 to 2.3. Cutoffs for acceptable symptom state ranged from 3.2 to 5.4 for parents and from 3 to 4.5 for children. Results of cross-validation analyses strongly supported the selected cutoff values.Cutoff values for classifying various disease states in JIA using the JADAS were developed. In cross-validation analyses, they proved to have good construct and discriminant validity and ability to predict disease outcome

Immune performance profile in pancreatic adenocarcinoma patients.

Cancer patients immuneprofile can discriminate subgroups of patients with a different fit of the immunesystem either functionally or phenotypically

Pancreatic resections for cystic neoplasms: from the surgeon's presumption to the pathologist's reality

Background. Current guidelines for the management of pancreatic cystic neoplasms are based on the assumption that these lesions can be classified correctly on the basis of features of cross-sectional imaging. However, a certain degree of overlap between different lesions exists, and little is known about the rate of inaccurate preoperative diagnoses. To address this issue, preoperative and final pathologic diagnoses of patients resected for a presumed pancreatic cystic neoplasm were compared. Methods. Retrospective analysis was undertaken of patients managed operatively between 2000 and 2010. Preoperative workup was reviewed to identify diagnostic pitfalls and potential risk fact ins for incorrect preoperative characterization of cystic lesions presumed to be neoplastic. Results. We analyzed 476 patients. Final pathologic diagnosis matched the preoperative diagnosis in 78% of cases. The highest accuracy was reached for solid pseudopapillary neoplasms (95%) and for main duct/mixed duct intraductal papillary mucinous neoplasms (81%). Surprisingly, 23 cysts (5%) were found to be ductal adenocarcinoma, whereas 45 patients (9%) underwent a pancreatic resection for a non-neoplastic condition. The use of a routine radiologic workup, including contrast-enhanced ultrasonography and magnetic resonance imaging, was associated with a favorably correct characterization of the cystic lesion. Endoscopic ultrasonography did not seem to improve diagnostic accuracy. Increased levels of serum carbohydrate antigen (CA)19-9 resulted as risk factors for an incorrect diagnosis as well as for a final diagnosis of a ductal adenocarcinoma. Conclusion. The overall rate of inaccurate preoperative diagnoses in a tertiary care center with a broad experience in pancreatology approached 22%. Serum CA19-9 is an important complementary tool within the context of preoperative investigation of cystic neoplasms of the pancreas

Novel automated system for Magnetic Resonance Imaging quantification of the inflamed synovial membrane volume in patients with juvenile idiopathic arthritis.

Objective To introduce a novel automated method for the quantification of the inflamed synovial membrane volume (SV) using magnetic resonance imaging (MRI), and to investigate its feasibility and validity in patients with juvenile idiopathic arthritis (JIA). Methods The tool was tested on 58 patients with JIA and wrist involvement. Thirty-six patients had a 1-year MRI followup. MRI of the clinically more affected wrist was performed using a 1.5T scanner and a Flex small coil. An algorithmic approach, based on supervised voxel classification for automatic estimation of SV in a 3-dimensional MRI, was developed. The SV was estimated as the number of positively classified voxels and then normalized by the patient's body surface (NSV). Validation procedures included the analysis of reliability, construct validity, responsiveness to change, discriminant validity, and the predictive value. Results The agreement between the automated estimation of NSV and the manual measurements was excellent (intraclass correlation coefficient 0.93, 95% confidence interval 0.79-0.98). The automatic NSV demonstrated good construct validity by yielding strong correlations with local signs of disease activity and a moderate correlation with global physician assessment of disease activity and with the Rheumatoid Arthritis Magnetic Resonance Imaging Scoring system synovitis score. NSV showed a strong responsiveness to clinical change (standardized response mean values &gt;1) and satisfactory discriminant validity. High baseline NSV (&gt;4.6) had high predictive value (100%) with respect to erosive progression. Conclusion The proposed automated method allowed reliable quantification of NSV, which represents a promising imaging biomarker of disease activity in JIA. The automated system has the potential to improve the longitudinal assessment of JIA and to predict progressive joint destruction

Digital Subtraction of Magnetic Resonance Images Improves Detection and Characterization of Pancreatic Neuroendocrine Neoplasms

The aim of this study was to evaluate the usefulness of digital image subtraction of contrast-enhanced magnetic resonance (MR) images for detection and characterization of pancreatic neuroendocrine neoplasms (PanNENs)