EGFR/HER2 inhibitor AEE788 increases ER-mediated transcription in HER2/ER-positive breast cancer cells but functions synergistically with endocrine therapy

BACKGROUND: Cross-talk between receptor tyrosine kinases and the oestrogen receptor (ER) is implicated in resistance to endocrine therapy. We investigated whether AEE788 (a combined inhibitor of EGFR, HER2 and VEGFR) plus tamoxifen or letrozole enhanced the individual anti-tumour effects of these agents. METHODS: Breast cancer cell lines modelling endocrine-resistant and -sensitive disease were engineered to express aromatase (A) and examined using proliferation, western blotting and ER-alpha transcription assays. RESULTS: AEE788 enhanced the anti-proliferative effect of tamoxifen and letrozole in ER+ cell lines (MCF-7 2A, ZR75.1 A3 and BT474 A3). This associated with an elevated G1 arrest and nuclear accumulation of p27. It is noteworthy that AEE788 alone or in combination with endocrine therapy increased the expression of progesterone receptor (PGR) and TFF1 in BT474 A3 cells. This may indicate a mechanism of resistance to AEE788 in ER+/HER2(+) breast cancers. In a ZR75.1 A3 xenograft, AEE788 alone or in combination with tamoxifen provided no further benefit compared with letrozole. However, letrozole plus AEE788 produced a significantly greater inhibition of tumour growth compared with letrozole alone. CONCLUSION: These data suggest that AEE788 plus letrozole in breast cancer overexpressing HER2 may provide superior anti-tumour activity, compared with single agents. British Journal of Cancer (2010) 102, 1235-1243. doi: 10.1038/sj.bjc.6605641 www.bjcancer.com (C) 2010 Cancer Research U

Stability of Metabolic Correlations under Changing Environmental Conditions in Escherichia coli – A Systems Approach

Background: Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches

Transcriptional Regulator PerA Influences Biofilm-Associated, Platelet Binding, and Metabolic Gene Expression in Enterococcus faecalis

Enterococcus faecalis is an opportunistic pathogen and a leading cause of nosocomial infections, traits facilitated by the ability to quickly acquire and transfer virulence determinants. A 150 kb pathogenicity island (PAI) comprised of genes contributing to virulence is found in many enterococcal isolates and is known to undergo horizontal transfer. We have shown that the PAI-encoded transcriptional regulator PerA contributes to pathogenicity in the mouse peritonitis infection model. In this study, we used whole-genome microarrays to determine the PerA regulon. The PerA regulon is extensive, as transcriptional analysis showed 151 differentially regulated genes. Our findings reveal that PerA coordinately regulates genes important for metabolism, amino acid degradation, and pathogenicity. Further transcriptional analysis revealed that PerA is influenced by bicarbonate. Additionally, PerA influences the ability of E. faecalis to bind to human platelets. Our results suggest that PerA is a global transcriptional regulator that coordinately regulates genes responsible for enterococcal pathogenicity

Investigating the use of sensor-based IoET to facilitate learning for children in rural Thailand

A novel sensor-based Internet of Educational Things (IoET) platform named OBSY was iteratively designed, developed and evaluated to support education in rural regions in Thailand. To assess the effectiveness of this platform, a study was carried out at four primary schools located near the Thai northern border with 244 students and 8 teachers. Participants were asked to carry out three science-based learning activities and were measured for improvements in learning outcome and learning engagement. Overall, the results showed that students in the IoET group who had used OBSY to learn showed significantly higher learning outcome and had better learning engagement than those in the control condition. In addition, for those in the IoET group, there was no significant effect regarding gender, home location (Urban or Rural), age, prior experience with technology and ethnicity on learning outcome. For learning engagement, only age was found to influence interest/enjoyment. The study demonstrated the potential of IoET technologies in underprivileged area, through a co-design approach with teachers and students, taking into account the local contexts

The critical current densities of some Tl-based superconductors: Influence of the various atomic compositions

We investigate the correlation between the critical current density and the critical temperatures of five Tl-based superconductors with T-c varying from 88 to 115 K. We find that for some of the samples J(c) is as high as 10(7)A/cm(2) at T = 4.2 K and H = 0. Perhaps, much more interestingly, for our best samples J(c)(H=0) exceeds 10(5)A/cm(2) at 100 K. It is also very important to emphasize that, contrary to Bi-based materials, the critical current density is not very sensitive to the magnetic field here. For instance, at T = 77 K and H = 20 kG, J(c) is still as high as 2x10(4)A/cm(2) while it is virtually zero in Bi-based systems