Genetic variation in Coffea canephora L. (Var. Robusta) accessions from the founder gene pool evaluated with ISSR and RAPD

Discovered in Congo in 1898, Coffea canefora var. robusta accounts for 25 to 40% of the coffee grown in the world. Most genetic diversity of robusta coffee accessions conserved in ex situ collections hasbeen estimated from morphological characteristics. There are limited studies on genetic variability and diversity in C. robusta. Inter-simple sequence repeat (ISSR) and random amplified polymorphic DNA(RAPD) markers were used to assess the level of genetic variability among robusta coffee accessions from the founder gene pool in the Democratic Republic of Congo (DRC). The present study clearlyestablished the high variability in the Congolese genepool. RAPD primers detected a higher level of polymorphic loci (95%) than ISSR markers (52%). Each accession could be genotyped using RAPDmarkers and both markers were efficient in revealing the genetic variability. Jaccard’s similarity coefficients generated to determine the genetic distances among accessions, revealed that most of theaccessions were genetically distant from each other. The accessions tested represent useful genetic materials for breeding for resistance to tracheomycose and other traits in DRC

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