Targeting tumor cells based on Phosphodiesterase 3A expression.

We and others have previously reported a correlation between high phosphodiesterase 3A (PDE3A) expression and selective sensitivity to phosphodiesterase (PDE) inhibitors. This indicates that PDE3A could serve both as a drug target and a biomarker of sensitivity to PDE3 inhibition. In this report, we explored publicly available mRNA gene expression data to identify cell lines with different PDE3A expression. Cell lines with high PDE3A expression showed marked in vitro sensitivity to PDE inhibitors zardaverine and quazinone, when compared with those having low PDE3A expression. Immunofluorescence and immunohistochemical stainings were in agreement with PDE3A mRNA expression, providing suitable alternatives for biomarker analysis of clinical tissue specimens. Moreover, we here demonstrate that tumor cells from patients with ovarian carcinoma show great variability in PDE3A protein expression and that level of PDE3A expression is correlated with sensitivity to PDE inhibition. Finally, we demonstrate that PDE3A is highly expressed in subsets of patient tumor cell samples from different solid cancer diagnoses and expressed at exceptional levels in gastrointestinal stromal tumor (GIST) specimens. Importantly, vulnerability to PDE3 inhibitors has recently been associated with co-expression of PDE3A and Schlafen family member 12 (SLFN12). We here demonstrate that high expression of PDE3A in clinical specimens, at least on the mRNA level, seems to be frequently associated with high SLFN12 expression. In conclusion, PDE3A seems to be both a promising biomarker and drug target for individualized drug treatment of various cancers.

Label free high throughput screening for apoptosis inducing chemicals using time-lapse microscopy signal processing.

Label free time-lapse microscopy has opened a new avenue to the study of time evolving events in living cells. When combined with automated image analysis it provides a powerful tool that enables automated large-scale spatiotemporal quantification at the cell population level. Very few attempts, however, have been reported regarding the design of image analysis algorithms dedicated to the detection of apoptotic cells in such time-lapse microscopy images. In particular, none of the reported attempts is based on sufficiently fast signal processing algorithms to enable large-scale detection of apoptosis within hours/days without access to high-end computers. Here we show that it is indeed possible to successfully detect chemically induced apoptosis by applying a two-dimensional linear matched filter tailored to the detection of objects with the typical features of an apoptotic cell in phase-contrast images. First a set of recorded computational detections of apoptosis was validated by comparison with apoptosis specific caspase activity readouts obtained via a fluorescence based assay. Then a large screen encompassing 2,866 drug like compounds was performed using the human colorectal carcinoma cell line HCT116. In addition to many well known inducers (positive controls) the screening resulted in the detection of two compounds here reported for the first time to induce apoptosis.

Approaches for Producing Fungal Cellulases Through Submerged Fermentation.

Fungal cellulases are the most sought-after biological molecules produced from microbial sources in the last four decades. Owing to their emerging applications in the bioenergy industry for hydrolyzing cellulose, for which they are the most abundant source on this planet, research trends are shifting heavily toward adapting to submerged fermentation. However, filamentous fungal species, which are efficient cellulase producers, are well-adapted to low-moisture solid support as the substrate, such as in nature. Therefore, various fermentation strategies are currently being investigated to adapt them to submerged fermentation for large and high-quality production of cellulases. Emerging research trends, such as the use of inexpensive feedstocks, nutrient and/or culture optimization, innovative bioreactor designs, microparticle-assisted fungal growth, and innovative genetic engineering approaches, are some of the recent efforts by researchers to exploit the full potential of these biological molecules. This review discusses some of these strategies and their success rates in various research conditions. In addition, specific focus was provided to both increasing the market value of cellulases and the innovative strategies required to enhance their production on an industrial scale.