TAMEE: data management and analysis for tissue microarrays

BACKGROUND: With the introduction of tissue microarrays (TMAs) researchers can investigate gene and protein expression in tissues on a high-throughput scale. TMAs generate a wealth of data calling for extended, high level data management. Enhanced data analysis and systematic data management are required for traceability and reproducibility of experiments and provision of results in a timely and reliable fashion. Robust and scalable applications have to be utilized, which allow secure data access, manipulation and evaluation for researchers from different laboratories. RESULTS: TAMEE (Tissue Array Management and Evaluation Environment) is a web-based database application for the management and analysis of data resulting from the production and application of TMAs. It facilitates storage of production and experimental parameters, of images generated throughout the TMA workflow, and of results from core evaluation. Database content consistency is achieved using structured classifications of parameters. This allows the extraction of high quality results for subsequent biologically-relevant data analyses. Tissue cores in the images of stained tissue sections are automatically located and extracted and can be evaluated using a set of predefined analysis algorithms. Additional evaluation algorithms can be easily integrated into the application via a plug-in interface. Downstream analysis of results is facilitated via a flexible query generator. CONCLUSION: We have developed an integrated system tailored to the specific needs of research projects using high density TMAs. It covers the complete workflow of TMA production, experimental use and subsequent analysis. The system is freely available for academic and non-profit institutions from

Optimisation of the RT-PCR detection of immunomagnetically enriched carcinoma cells

BACKGROUND: Immunomagnetic enrichment followed by RT-PCR (immunobead RT-PCR) is an efficient methodology to identify disseminated carcinoma cells in the blood and bone marrow. The RT-PCR assays must be both specific for the tumor cells and sufficiently sensitive to enable detection of single tumor cells. We have developed a method to test RT-PCR assays for any cancer. This has been investigated using a panel of RT-PCR markers suitable for the detection of breast cancer cells. METHODS: In the assay, a single cell line-derived tumor cell is added to 100 peripheral blood mononuclear cells (PBMNCs) after which mRNA is isolated and reverse transcribed for RT-PCR analysis. PBMNCs without added tumor cells are used as specificity controls. The previously studied markers epidermal growth factor receptor (EGFR), mammaglobin 1 (MGB1), epithelial cell adhesion molecule (EpCAM/TACSTD1), mucin 1 (MUC1), carcinoembryonic antigen (CEA) were tested. Two new epithelial-specific markers ELF3 and EphB4 were also tested. RESULTS: MUC1 was unsuitable as strong amplification was detected in 100 cell PBMNC controls. Expression of ELF3, EphB4, EpCAM, EGFR, CEA and MGB1 was found to be both specific for the tumor cell, as demonstrated by the absence of a signal in most 100 cell PBMNC controls, and sensitive enough to detect a single tumor cell in 100 PBMNCs using a single round of RT-PCR. CONCLUSIONS: ELF3, EphB4, EpCAM, EGFR, CEA and MGB1 are appropriate RT-PCR markers for use in a marker panel to detect disseminated breast cancer cells after immunomagnetic enrichment

Biomarkers of apoptosis

Within the era of molecularly targeted anticancer agents, it has become increasingly important to provide proof of mechanism as early on as possible in the drug development cycle, especially in the clinic. Selective activation of apoptosis is often cited as one of the major goals of cancer chemotherapy. Thus, the present minireview focuses on a discussion of the pros and cons of a variety of methodological approaches to detect different components of the apoptotic cascade as potential biomarkers of programmed cell death. The bulk of the discussion centres on serological assays utilising the technique of ELISA, since here there is an obvious advantage of sampling multiple time points. Potential biomarkers of apoptosis including circulating tumour cells, cytokeratins and DNA nucleosomes are discussed at length. However, accepting that a single biomarker may not have the power to predict proof of concept and patient outcome, it is clear that in the future more emphasis will be placed on technologies that can analyse panels of biomarkers in small volumes of samples. To this end the increased throughput afforded by multiplex ELISA technologies is discussed

Presence of apoptotic and nonapoptotic disseminated tumor cells reflects the response to neoadjuvant systemic therapy in breast cancer

INTRODUCTION: Neoadjuvant systemic therapy (NST) is an established strategy to reduce tumor size in breast cancer patients prior to breast-conserving therapy. The effect of NST on tumor cell dissemination in these patients is not known. The aim of this study was to investigate the incidence of disseminated tumor cells (DTC), including apoptotic DTC, in breast cancer patients after NST, and to investigate the correlation of DTC status with therapy response. METHODS: Bone marrow aspiration was performed in 157 patients after NST. DTC were detected by immunocytochemistry using the A45–B/B3 anticytokeratin antibody. To detect apoptotic DTC the antibody M30 (Roche Diagnostics, Germany) was used, which detects a neo-epitope expressed only after caspase cleavage of cytokeratin 18 during early apoptosis. RESULTS: The incidence of DTC in breast cancer patients was 53% after completion of NST. Tumor dissemination was observed more frequently in patients with no change/progressive disease (69%) than in patients with partial remission or complete remission of the primary tumor (46%) (P < 0.05). Ten out of 24 patients with complete remission, however, were still bone marrow positive. Apoptotic DTC were present in 36 of 157 (23%) breast cancer patients. Apoptotic cells only were detected in 14% of the patients with partial remission or complete remission, but were detected in just 5% of the patients with stable disease. Apoptotic DTC were detectable in none of the patients with tumor progression. CONCLUSION: The pathological therapy response in breast cancer patients is reflected by the presence of apoptotic DTC. Patients with complete remission, however, may still have nonapoptotic DTC. These patients may also benefit from secondary adjuvant therapy

Extended Field Laser Confocal Microscopy (EFLCM): Combining automated Gigapixel image capture with in silico virtual microscopy

<p>Abstract</p> <p>Background</p> <p>Confocal laser scanning microscopy has revolutionized cell biology. However, the technique has major limitations in speed and sensitivity due to the fact that a single laser beam scans the sample, allowing only a few microseconds signal collection for each pixel. This limitation has been overcome by the introduction of parallel beam illumination techniques in combination with cold CCD camera based image capture.</p> <p>Methods</p> <p>Using the combination of microlens enhanced Nipkow spinning disc confocal illumination together with fully automated image capture and large scale <it>in silico </it>image processing we have developed a system allowing the acquisition, presentation and analysis of maximum resolution confocal panorama images of several Gigapixel size. We call the method Extended Field Laser Confocal Microscopy (EFLCM).</p> <p>Results</p> <p>We show using the EFLCM technique that it is possible to create a continuous confocal multi-colour mosaic from thousands of individually captured images. EFLCM can digitize and analyze histological slides, sections of entire rodent organ and full size embryos. It can also record hundreds of thousands cultured cells at multiple wavelength in single event or time-lapse fashion on fixed slides, in live cell imaging chambers or microtiter plates.</p> <p>Conclusion</p> <p>The observer independent image capture of EFLCM allows quantitative measurements of fluorescence intensities and morphological parameters on a large number of cells. EFLCM therefore bridges the gap between the mainly illustrative fluorescence microscopy and purely quantitative flow cytometry. EFLCM can also be used as high content analysis (HCA) instrument for automated screening processes.</p

New indicators and indexes for benchmarking university–industry–government innovation in medical and life science clusters: results from the European FP7 Regions of Knowledge HealthTIES project

Background: While the European Union is striving to become the ‘Innovation Union’, there remains a lack of quantifiable indicators to compare and benchmark regional innovation clusters. To address this issue, a HealthTIES (Healthcare, Technology and Innovation for Economic Success) consortium was funded by the European Union’s Regions of Knowledge initiative, research and innovation funding programme FP7. HealthTIES examined whether the health technology innovation cycle was functioning differently in five European regional innovation clusters and proposed regional and joint actions to improve their performance. The clusters included BioCat (Barcelona, Catalonia, Spain), Medical Delta (Leiden, Rotterdam and Delft, South Holland, Netherlands), Oxford and Thames Valley (United Kingdom), Life Science Zürich (Switzerland), and Innova Észak-Alföld (Debrecen, Hungary). Methods: Appreciation of the ‘triple helix’ of university–industry–government innovation provided the impetus for the development of two quantifiable innovation indexes and related indicators. The HealthTIES H-index is calculated for disease and technology platforms based on the h-index proposed by Hirsch. The HealthTIES Innovation Index is calculated for regions based on 32 relevant quantitative and discriminative indicators grouped into 12 categories and 3 innovation phases, namely ‘Input’ (n = 12), ‘Innovation System’ (n = 9) and ‘Output’ (n = 11). Results: The HealthTIES regions had developed relatively similar disease and technology platform profiles, yet with distinctive strengths and weaknesses. The regional profiles of the innovation cycle in each of the three phases were surprisingly divergent. Comparative assessments based on the indicators and indexes helped identify and share best practice and inform regional and joint action plans to strengthen the competitiveness of the HealthTIES regions. Conclusion: The HealthTIES indicators and indexes provide useful practical tools for the measurement and benchmarking of university–industry–government innovation in European medical and life science clusters. They are validated internally within the HealthTIES consortium and appear to have a degree of external prima facie validity. Potentially, the tools and accompanying analyses can be used beyond the HealthTIES consortium to inform other regional governments, researchers and, possibly, large companies searching for their next location, analyse and benchmark ‘triple helix’ dynamics within their own networks over time, and to develop integrated public–private and cross-regional research and innovation strategies in Europe and beyond

International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee

Neuroblastoma serves as a paradigm for utilising tumour genomic data for determining patient prognosis and treatment allocation. However, before the establishment of the International Neuroblastoma Risk Group (INRG) Task Force in 2004, international consensus on markers, methodology, and data interpretation did not exist, compromising the reliability of decisive genetic markers and inhibiting translational research efforts. The objectives of the INRG Biology Committee were to identify highly prognostic genetic aberrations to be included in the new INRG risk classification schema and to develop precise definitions, decisive biomarkers, and technique standardisation. The review of the INRG database (n=8800 patients) by the INRG Task Force finally enabled the identification of the most significant neuroblastoma biomarkers. In addition, the Biology Committee compared the standard operating procedures of different cooperative groups to arrive at international consensus for methodology, nomenclature, and future directions. Consensus was reached to include MYCN status, 11q23 allelic status, and ploidy in the INRG classification system on the basis of an evidence-based review of the INRG database. Standardised operating procedures for analysing these genetic factors were adopted, and criteria for proper nomenclature were developed. Neuroblastoma treatment planning is highly dependant on tumour cell genomic features, and it is likely that a comprehensive panel of DNA-based biomarkers will be used in future risk assignment algorithms applying genome-wide techniques. Consensus on methodology and interpretation is essential for uniform INRG classification and will greatly facilitate international and cooperative clinical and translational research studies