Ex Vivo Metrics™, a preclinical tool in new drug development

Among the challenges facing translational medicine today is the need for greater productivity and safety during the drug development process. To meet this need, practitioners of translational medicine are developing new technologies that can facilitate decision making during the early stages of drug discovery and clinical development. Ex Vivo Metrics™ is an emerging technology that addresses this need by using intact human organs ethically donated for research. After hypothermic storage, the organs are reanimated by blood perfusion, providing physiologically and biochemically stable preparations. In terms of emulating human exposure to drugs, Ex Vivo Metrics is the closest biological system available for clinical trials. Early application of this tool for evaluating drug targeting, efficacy, and toxicity could result in better selection among promising drug candidates, greater drug productivity, and increased safety

Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p

EBV-Infection in Cardiac and Non-Cardiac Gastric Adenocarcinomas is Associated with Promoter Methylation of p16, p14 and APC, but not hMLH1

Background: Epstein–Barr virus (EBV)-associated gastric carcinomas (GC) constitute a distinct clinicopathological entity of gastric cancer. In order to determine underlying distinct aberrant promoter methylation we tested cardiac and non-cardiac GC with regard to the presence of EBV

The influence of the pituitary tumor transforming gene-1 (PTTG-1) on survival of patients with small cell lung cancer and non-small cell lung cancer

<p>Abstract</p> <p>Background</p> <p>PTTG-1 (pituitary tumor transforming gene) is a novel oncogene that is overexpressed in tumors, such as pituitary adenoma, breast and gastrointestinal cancers as well as in leukemia. In this study, we examined the role of PTTG-1 expression in lung cancer with regard to histological subtype, the correlation of PTTG-1 to clinical parameters and relation on patients' survival.</p> <p>Methods</p> <p>Expression of PTTG-1 was examined immunohistochemically on formalin-fixed, paraffin-embedded tissue sections of 136 patients with small cell lung cancer (SCLC) and 91 patients with non-small cell lung cancer (NSCLC), retrospectively. The intensity of PTTG-1 expression as well as the proportion of PTTG-1 positive cells within a tumor was used for univariate and multivariate analysis.</p> <p>Results</p> <p>PTTG-1 expression was observed in 64% of SCLC tumors and in 97.8% of NSCLC tumors. In patients with SCLC, negative or low PTTG-1 expression was associated with a shorter mean survival time compared with patients with strong PTTG-1 expression (265 ± 18 days vs. 379 ± 66 days; p = 0.0291). Using the Cox regression model for multivariate analysis, PTTG-1 expression was a significant predictor for survival next to performance status, tumor stage, LDH and hemoglobin.</p> <p>In contrast, in patients with NSCLC an inverse correlation between survival and PTTG-1 expression was seen. Strong PTTG-1 expression was associated with a shorter mean survival of 306 ± 58 days compared with 463 ± 55 days for those patients with no or low PTTG-1 intensities (p = 0.0386). Further, PTTG-1 expression was associated with a more aggressive NSCLC phenotype with an advanced pathological stage, extensive lymph node metastases, distant metastases and increased LDH level. Multivariate analysis using Cox regression confirmed the prognostic relevance of PTTG-1 expression next to performance status and tumor stage in patients with NSCLC.</p> <p>Conclusion</p> <p>Lung cancers belong to the group of tumors expressing PTTG-1. Dependent on the histological subtype of lung cancer, PTTG-1 expression was associated with a better outcome in patients with SCLC and a rather unfavourable outcome for patients with NSCLCs. These results may reflect the varying role of PTTG-1 in the pathophysiology of the different histological subtypes of lung cancer.</p