Bioassays to Monitor Taspase1 Function for the Identification of Pharmacogenetic Inhibitors

Background: Threonine Aspartase 1 (Taspase1) mediates cleavage of the mixed lineage leukemia (MLL) protein and leukemia provoking MLL-fusions. In contrast to other proteases, the understanding of Taspase1's (patho)biological relevance and function is limited, since neither small molecule inhibitors nor cell based functional assays for Taspase1 are currently available. Methodology/Findings: Efficient cell-based assays to probe Taspase1 function in vivo are presented here. These are composed of glutathione S-transferase, autofluorescent protein variants, Taspase1 cleavage sites and rational combinations of nuclear import and export signals. The biosensors localize predominantly to the cytoplasm, whereas expression of biologically active Taspase1 but not of inactive Taspase1 mutants or of the protease Caspase3 triggers their proteolytic cleavage and nuclear accumulation. Compared to in vitro assays using recombinant components the in vivo assay was highly efficient. Employing an optimized nuclear translocation algorithm, the triple-color assay could be adapted to a high-throughput microscopy platform (Z'factor = 0.63). Automated high-content data analysis was used to screen a focused compound library, selected by an in silico pharmacophor screening approach, as well as a collection of fungal extracts. Screening identified two compounds, N-[2-[(4-amino-6-oxo-3H-pyrimidin-2-yl)sulfanyl]ethyl]benzenesulfonamideand 2-benzyltriazole-4,5-dicarboxylic acid, which partially inhibited Taspase1 cleavage in living cells. Additionally, the assay was exploited to probe endogenous Taspase1 in solid tumor cell models and to identify an improved consensus sequence for efficient Taspase1 cleavage. This allowed the in silico identification of novel putative Taspase1 targets. Those include the FERM Domain-Containing Protein 4B, the Tyrosine-Protein Phosphatase Zeta, and DNA Polymerase Zeta. Cleavage site recognition and proteolytic processing of these substrates were verified in the context of the biosensor. Conclusions: The assay not only allows to genetically probe Taspase1 structure function in vivo, but is also applicable for high-content screening to identify Taspase1 inhibitors. Such tools will provide novel insights into Taspase1's function and its potential therapeutic relevance

Multigene prognostic tests in breast cancer: past, present, future

There is growing consensus that multigene prognostic tests provide useful complementary information to tumor size and grade in estrogen receptor (ER)-positive breast cancers. The tests primarily rely on quantification of ER and proliferation-related genes and combine these into multivariate prediction models. Since ER-negative cancers tend to have higher proliferation rates, the prognostic value of current multigene tests in these cancers is limited. First-generation prognostic signatures (Oncotype DX, MammaPrint, Genomic Grade Index) are substantially more accurate to predict recurrence within the first 5 years than in later years. This has become a limitation with the availability of effective extended adjuvant endocrine therapies. Newer tests (Prosigna, EndoPredict, Breast Cancer Index) appear to possess better prognostic value for late recurrences while also remaining predictive of early relapse. Some clinical prediction problems are more difficult to solve than others: there are no clinically useful prognostic signatures for ER-negative cancers, and drug-specific treatment response predictors also remain elusive. Emerging areas of research involve the development of immune gene signatures that carry modest but significant prognostic value independent of proliferation and ER status and represent candidate predictive markers for immune-targeted therapies. Overall metrics of tumor heterogeneity and genome integrity (for example, homologue recombination deficiency score) are emerging as potential new predictive markers for platinum agents. The recent expansion of high-throughput technology platforms including low-cost sequencing of circulating and tumor-derived DNA and RNA and rapid reliable quantification of microRNA offers new opportunities to build extended prediction models across multiplatform data

Expression of prostasin and its inhibitors during colorectal cancer carcinogenesis

<p>Abstract</p> <p>Background</p> <p>Clinical trials where cancer patients were treated with protease inhibitors have suggested that the serine protease, prostasin, may act as a tumour suppressor. Prostasin is proteolytically activated by the serine protease, matriptase, which has a very high oncogenic potential. Prostasin is inhibited by protease nexin-1 (PN-1) and the two isoforms encoded by the mRNA splice variants of <it>hepatocyte growth factor activator inhibitor-1 </it>(<it>HAI-1</it>), <it>HAI-1A</it>, and <it>HAI-1B</it>.</p> <p>Methods</p> <p>Using quantitative RT-PCR, we have determined the mRNA levels for <it>prostasin </it>and <it>PN-1 </it>in colorectal cancer tissue (n = 116), severe dysplasia (n = 13), mild/moderate dysplasia (n = 93), and in normal tissue from the same individuals. In addition, corresponding tissues were examined from healthy volunteers (n = 23). A part of the cohort was further analysed for the mRNA levels of the two variants of HAI-1, here denoted <it>HAI-1A </it>and <it>HAI-1B</it>. mRNA levels were normalised to <it>β-actin</it>. Immunohistochemical analysis of prostasin and HAI-1 was performed on normal and cancer tissue.</p> <p>Results</p> <p>The mRNA level of prostasin was slightly but significantly decreased in both mild/moderate dysplasia (p < 0.001) and severe dysplasia (p < 0.01) and in carcinomas (p < 0.05) compared to normal tissue from the same individual. The mRNA level of <it>PN-1 </it>was more that two-fold elevated in colorectal cancer tissue as compared to healthy individuals (p < 0.001) and elevated in both mild/moderate dysplasia (p < 0.01), severe dysplasia (p < 0.05) and in colorectal cancer tissue (p < 0.001) as compared to normal tissue from the same individual. The mRNA levels of <it>HAI-1A </it>and <it>HAI-1B </it>mRNAs showed the same patterns of expression. Immunohistochemistry showed that prostasin is located mainly on the apical plasma membrane in normal colorectal tissue. A large variation was found in the degree of polarization of prostasin in colorectal cancer tissue.</p> <p>Conclusion</p> <p>These results show that the mRNA level of <it>PN-1 </it>is significantly elevated in colorectal cancer tissue. Future studies are required to clarify whether down-regulation of prostasin activity via up regulation of PN-1 is causing the malignant progression or if it is a consequence of it.</p

The three major axes of terrestrial ecosystem function.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8

'Omic approaches to preventing or managing metastatic breast cancer

Early detection of metastasis-prone breast cancers and characterization of residual metastatic cancers are important in efforts to improve management of breast cancer. Applications of genome-scale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate development of anatomic, histological and blood-based strategies that may enable detection prior to metastatic spread. Knowledge of these features also will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response