The role of the pathologist in tissue banking: European Consensus Expert Group Report

Human tissue biobanking encompasses a wide range of activities and study designs and is critical for application of a wide range of new technologies (-“omics”) to the discovery of molecular patterns of disease and for implementation of novel biomarkers into clinical trials. Pathology is the cornerstone of hospital-based tissue biobanking. Pathologists not only provide essential information identifying the specimen but also make decisions on what should be biobanked, making sure that the timing of all operations is consistent with both the requirements of clinical diagnosis and the optimal preservation of biological products. This document summarizes the conclusions of a Pathology Expert Group Meeting within the European Biological and Biomolecular Research Infrastructure (BBMRI) Program. These recommendations are aimed at providing guidance for pathologists as well as for institutions hosting biobanks on how to better integrate and support pathological activities within the framework of biobanks that fulfill international standards

Comparison of DNA histograms by standard flow cytometry and image cytometry on sections in Barrett's adenocarcinoma

<p>Abstract</p> <p>Background</p> <p>The purpose of this study was to compare DNA histograms obtained by standard flow cytometry (FC) and high fidelity image cytometry on sections (ICS) in normal gastrointestinal mucosa and Barrett's adenocarcinoma (BAC).</p> <p>Methods</p> <p>Archival formalin-fixed paraffin-embedded tissue blocks of 10 normal controls from 10 subjects and 42 BAC tissues from 17 patients were examined. DNA FC was performed using standard techniques and ICS was carried out by Automated Cellular Imaging System (ACIS). DNA ploidy histograms were classified into diploid with peak DNA index (DI) at 0.9–1.1, and aneuploid with peak DI > 1.1. DI values of aneuploid peaks were determined. Additionally, for DNA ICS, heterogeneity index (HI) representing DNA content heterogeneity, and histograms containing cells with DI > G2 were also identified.</p> <p>Results</p> <p>All control samples were diploid by both FC and ICS analyses. In BAC, FC showed diploid peaks in 29%, diploid peaks with additional aneuploid or tetraploid peaks in 57%, and 14% of the samples, respectively. In contrast, ICS showed aneuploid peaks in all the cases with peak DI > 1.25; 37 cases had peak DI between 1.25 and 2.25; and 5 cases had peak DI > 2.25. HI values (mean ± SD) were 11.3 ± 1.1 in controls and 32.4 ± 8.5 in BAC (p < 0.05). Controls had no G2 exceeding cells. However, 19/37 (51%) of the cases with primary peak DI < 2.25 had cells exceeding 9N.</p> <p>Conclusion</p> <p>ICS detects DNA aneuploidy in all BAC samples while FC missed the diagnosis of aneuploidy in 29%. In addition, ICS provides more information on HI and G2 exceeding rates.</p

Metabolomic Profiling Reveals a Role for Androgen in Activating Amino Acid Metabolism and Methylation in Prostate Cancer Cells

Prostate cancer is the second leading cause of cancer related death in American men. Development and progression of clinically localized prostate cancer is highly dependent on androgen signaling. Metastatic tumors are initially responsive to anti-androgen therapy, however become resistant to this regimen upon progression. Genomic and proteomic studies have implicated a role for androgen in regulating metabolic processes in prostate cancer. However, there have been no metabolomic profiling studies conducted thus far that have examined androgen-regulated biochemical processes in prostate cancer. Here, we have used unbiased metabolomic profiling coupled with enrichment-based bioprocess mapping to obtain insights into the biochemical alterations mediated by androgen in prostate cancer cell lines. Our findings indicate that androgen exposure results in elevation of amino acid metabolism and alteration of methylation potential in prostate cancer cells. Further, metabolic phenotyping studies confirm higher flux through pathways associated with amino acid metabolism in prostate cancer cells treated with androgen. These findings provide insight into the potential biochemical processes regulated by androgen signaling in prostate cancer. Clinically, if validated, these pathways could be exploited to develop therapeutic strategies that supplement current androgen ablative treatments while the observed androgen-regulated metabolic signatures could be employed as biomarkers that presage the development of castrate-resistant prostate cancer

Integrated Expression Profiling and ChIP-seq Analyses of the Growth Inhibition Response Program of the Androgen Receptor

Background: The androgen receptor (AR) plays important roles in the development of male phenotype and in different human diseases including prostate cancers. The AR can act either as a promoter or a tumor suppressor depending on cell types. The AR proliferative response program has been well studied, but its prohibitive response program has not yet been thoroughly studied. Methodology/Principal Findings: Previous studies found that PC3 cells expressing the wild-type AR inhibit growth and suppress invasion. We applied expression profiling to identify the response program of PC3 cells expressing the AR (PC3-AR) under different growth conditions (i.e. with or without androgens and at different concentration of androgens) and then applied the newly developed ChIP-seq technology to identify the AR binding regions in the PC3 cancer genome. A surprising finding was that the comparison of MOCK-transfected PC3 cells with AR-transfected cells identified 3,452 differentially expressed genes (two fold cutoff) even without the addition of androgens (i.e. in ethanol control), suggesting that a ligand independent activation or extremely low-level androgen activation of the AR. ChIP-Seq analysis revealed 6,629 AR binding regions in the cancer genome of PC3 cells with an FDR (false discovery rate) cut off of 0.05. About 22.4 % (638 o

Transcriptional upregulation of human tissue kallikrein 6 in ovarian cancer: clinical and mechanistic aspects

The human tissue kallikrein family (KLK for protein; KLK for gene) includes 15 members. Twelve kallikreins, including KLK6, are concurrently upregulated in ovarian cancer. However, the mechanism of this phenomenon remains unclear. In this study, we measured KLK6 expression in a large series of ovarian tissue cytosols and examined possible mechanisms of KLK6 up-regulation in ovarian cancer. Using a newly developed enzyme-linked immunosorbent assay (ELISA) with two monoclonal antibodies, we quantified KLK6 expression in ovarian tissue cytosols, and confirmed the upregulation of KLK6 in ovarian cancer and its unfavourable prognostic value. We then examined KLK6 mRNA expression using reverse transcription–polymerase chain reaction and established its good concordance with KLK6 protein expression. This finding suggested that the KLK6 gene is under transcriptional regulation. We then scrutinised a few mechanisms that could explain KLK6 upregulation. The relative abundance of two KLK6 mRNA transcripts was studied; we found the same differential expression pattern in all samples, regardless of KLK6 levels. Genomic mutation screening of all exons and the 5′-flanking region of the KLK6 gene identified two linked single-nucleotide polymorphisms in the 5′-untranslated region, but neither correlated with KLK6 expression. Ovarian cell lines were separately treated with five steroid hormones. None of the treatments produced significant effects on KLK6 expression. We conclude that KLK6 is transcriptionally upregulated in ovarian cancer, but probably not through alternative mRNA transcript expression, genomic mutation, or steroid hormone induction

Institutional shared resources and translational cancer research

The development and maintenance of adequate shared infrastructures is considered a major goal for academic centers promoting translational research programs. Among infrastructures favoring translational research, centralized facilities characterized by shared, multidisciplinary use of expensive laboratory instrumentation, or by complex computer hardware and software and/or by high professional skills are necessary to maintain or improve institutional scientific competitiveness. The success or failure of a shared resource program also depends on the choice of appropriate institutional policies and requires an effective institutional governance regarding decisions on staffing, existence and composition of advisory committees, policies and of defined mechanisms of reporting, budgeting and financial support of each resource. Shared Resources represent a widely diffused model to sustain cancer research; in fact, web sites from an impressive number of research Institutes and Universities in the U.S. contain pages dedicated to the SR that have been established in each Center, making a complete view of the situation impossible. However, a nation-wide overview of how Cancer Centers develop SR programs is available on the web site for NCI-designated Cancer Centers in the U.S., while in Europe, information is available for individual Cancer centers. This article will briefly summarize the institutional policies, the organizational needs, the characteristics, scientific aims, and future developments of SRs necessary to develop effective translational research programs in oncology

LNCaP Atlas: Gene expression associated with in vivo progression to castration-recurrent prostate cancer

<p>Abstract</p> <p>Background</p> <p>There is no cure for castration-recurrent prostate cancer (CRPC) and the mechanisms underlying this stage of the disease are unknown.</p> <p>Methods</p> <p>We analyzed the transcriptome of human LNCaP prostate cancer cells as they progress to CRPC <it>in vivo </it>using replicate LongSAGE libraries. We refer to these libraries as the LNCaP atlas and compared these gene expression profiles with current suggested models of CRPC.</p> <p>Results</p> <p>Three million tags were sequenced using <it>in vivo </it>samples at various stages of hormonal progression to reveal 96 novel genes differentially expressed in CRPC. Thirty-one genes encode proteins that are either secreted or are located at the plasma membrane, 21 genes changed levels of expression in response to androgen, and 8 genes have enriched expression in the prostate. Expression of 26, 6, 12, and 15 genes have previously been linked to prostate cancer, Gleason grade, progression, and metastasis, respectively. Expression profiles of genes in CRPC support a role for the transcriptional activity of the androgen receptor (<it>CCNH, CUEDC2, FLNA, PSMA7</it>), steroid synthesis and metabolism (<it>DHCR24, DHRS7</it>, <it>ELOVL5, HSD17B4</it>, <it>OPRK1</it>), neuroendocrine (<it>ENO2, MAOA, OPRK1, S100A10, TRPM8</it>), and proliferation (<it>GAS5</it>, <it>GNB2L1</it>, <it>MT-ND3</it>, <it>NKX3-1</it>, <it>PCGEM1</it>, <it>PTGFR</it>, <it>STEAP1</it>, <it>TMEM30A</it>), but neither supported nor discounted a role for cell survival genes.</p> <p>Conclusions</p> <p>The <it>in vivo </it>gene expression atlas for LNCaP was sequenced and support a role for the androgen receptor in CRPC.</p