In vitro functional characterisation of IGF-I : VN-induced breast cancer progression

Members of the insulin-like growth factor (IGF) family have been shown to play critical roles in normal growth and development, as well as in tumour biology. The IGF system is complex and the biological effects of the IGFs are determined by their diverse interactions between many molecules, including their interactions with extracellular matrix (ECM) proteins. Recent studies have demonstrated that IGFs associate with the ECM protein vitronectin (VN) through IGF-binding proteins (IGFBP) and that this interaction modulates IGF-stimulated biological functions, namely cell migration and cell survival through the cooperative involvement of the type-I IGF receptor (IGF-1R) and VN-binding integrins. Since IGFs play important roles in the transformation and progression of breast cancer and VN has been found to be over-expressed at the leading edge of breast tumours, this project aimed to describe the effects of IGF-I:VN interactions on breast cell function. This was undertaken to dissect the molecular mechanisms underlying IGF-I:VN-induced responses and to design inhibitors to block the effects of such interactions. The studies described herein demonstrate that the increase in migration of MCF-7 breast cancer cells in response to the IGF-I:IGFBP-5:VN complex is accompanied by differential expression of genes known to be involved in migration, invasion and/or survival, including Tissue-factor (TF), Stratifin (SFN), Ephrin-B2, Sharp-2 and PAI-1. This „migration gene signature‟ was confirmed using real-time PCR analysis. Substitution of the native IGF-I within the IGF-I:IGFBP:VN complex with the IGF-I analogue, \[L24]\[A31]-IGF-I, which has a reduced affinity for the IGF-1R, failed to stimulate cell migration and interestingly, also failed to induce the differential gene expression. This supports the involvement of the IGF-1R in mediating these changes in gene expression. Furthermore, lentiviral shRNA-mediated stable knockdown of TF and SFN completely abrogated the increased cell migration induced by IGF-I:IGFBP:VN complexes in MCF-7 cells. Indeed, when these cells were grown in 3D Matrigel™ cultures a decrease in the overall size of the 3D spheroids in response to the IGF-I:IGFBP:VN complexes was observed compared to the parental MCF-7 cells. This suggests that TF and SFN have a role in complex-stimulated cell survival. Moreover, signalling studies performed on cells with the reduced expression of either TF or SFN had a decreased IGF-1R activation, suggesting the involvement of signalling pathways downstream of IGF-1R in TF- and/or SFN-mediated cell migration and cell survival. Taken together, these studies provide evidence for a common mechanism activated downstream of the IGF-1R that induces the expression of the „migration gene signature‟ in response to the IGF-I:IGFBP:VN complex that confers breast cancer cells the propensity to migrate and survive. Given the functional significance of the interdependence of ECM and growth factor (GF) interactions in stimulating processes key to breast cancer progression, this project aimed at developing strategies to prevent such growth factor:ECM interactions in an effort to inhibit the downstream functional effects. This may result in the reduction in the levels of ECM-bound IGF-I present in close proximity to the cells, thereby leading to a reduction in the stimulation of IGF-1R present on the cell surface. Indeed, the inhibition of IGF-I-mediated effects through the disruption of its association with ECM would not alter the physiological levels of IGF-I and potentially only exert effects in situations where abnormal over expression of ECM proteins are found; namely carcinomas and hyperproliferative diseases. In summary, this PhD project has identified novel, innovative and realistic strategies that can be used in vitro to inhibit the functions exerted by the IGF-I:IGFBP:VN multiprotein complexes critical for cancer progression, with a potential to be translated into in vivo investigations. Furthermore, TF and SFN were found to mediate IGF-I:IGFBP:VN-induced effects, thereby revealing their potential to be used as therapeutic targets or as predictive biomarkers for the efficacy of IGF-1R targeting therapies in breast cancer patients. In addition to its therapeutic and clinical scope, this PhD project has significantly contributed to the understanding of the role of the IGF system in breast tumour biology by providing valuable new information on the mechanistic events underpinning IGF-I:VN-mediated effects on breast cell functions. Furthermore, this is the first instance where favourable binding sites for IGF-II, IGFBP-3 and IGFBP-5 on VN have been identified. Taken together, this study has functionally characterised the interactions between IGF-I and VN and through innovative strategies has provided a platform for the development of novel therapies targeting these interactions and their downstream effects.

Differential entrainment of neuroelectric delta oscillations in developmental dyslexia

Oscillatory entrainment to the speech signal is important for language processing, but has not yet been studied in developmental disorders of language. Developmental dyslexia, a difficulty in acquiring efficient reading skills linked to difficulties with phonology (the sound structure of language), has been associated with behavioural entrainment deficits. It has been proposed that the phonological ‘deficit’ that characterises dyslexia across languages is related to impaired auditory entrainment to speech at lower frequencies via neuroelectric oscillations (<10 Hz, ‘temporal sampling theory’). Impaired entrainment to temporal modulations at lower frequencies would affect the recovery of the prosodic and syllabic structure of speech. Here we investigated event-related oscillatory EEG activity and contingent negative variation (CNV) to auditory rhythmic tone streams delivered at frequencies within the delta band (2 Hz, 1.5 Hz), relevant to sampling stressed syllables in speech. Given prior behavioural entrainment findings at these rates, we predicted functionally atypical entrainment of delta oscillations in dyslexia. Participants performed a rhythmic expectancy task, detecting occasional white noise targets interspersed with tones occurring regularly at rates of 2 Hz or 1.5 Hz. Both groups showed significant entrainment of delta oscillations to the rhythmic stimulus stream, however the strength of inter-trial delta phase coherence (ITC, ‘phase locking’) and the CNV were both significantly weaker in dyslexics, suggestive of weaker entrainment and less preparatory brain activity. Both ITC strength and CNV amplitude were significantly related to individual differences in language processing and reading. Additionally, the instantaneous phase of prestimulus delta oscillation predicted behavioural responding (response time) for control participants only.

A finite volume method for solving the two-sided time-space fractional advection-dispersion equation

We present a finite volume method to solve the time-space two-sided fractional advection-dispersion equation on a one-dimensional domain. The spatial discretisation employs fractionally-shifted Grünwald formulas to discretise the Riemann-Liouville fractional derivatives at control volume faces in terms of function values at the nodes. We demonstrate how the finite volume formulation provides a natural, convenient and accurate means of discretising this equation in conservative form, compared to using a conventional finite difference approach. Results of numerical experiments are presented to demonstrate the effectiveness of the approach.

A comparison of finite difference and finite volume methods for solving the space-fractional advection-dispersion equation with variable coefficients

Transport processes within heterogeneous media may exhibit non- classical diffusion or dispersion which is not adequately described by the classical theory of Brownian motion and Fick’s law. We consider a space-fractional advection-dispersion equation based on a fractional Fick’s law. Zhang et al. [Water Resources Research, 43(5)(2007)] considered such an equation with variable coefficients, which they dis- cretised using the finite difference method proposed by Meerschaert and Tadjeran [Journal of Computational and Applied Mathematics, 172(1):65-77 (2004)]. For this method the presence of variable coef- ficients necessitates applying the product rule before discretising the Riemann–Liouville fractional derivatives using standard and shifted Gru ̈nwald formulas, depending on the fractional order. As an alternative, we propose using a finite volume method that deals directly with the equation in conservative form. Fractionally-shifted Gru ̈nwald formulas are used to discretise the Riemann–Liouville fractional derivatives at control volume faces, eliminating the need for product rule expansions. We compare the two methods for several case studies, highlighting the convenience of the finite volume approach.

A new plasmid display technology for the in vitro selection of functional phenotype-genotype linked proteins

Background Display technologies which allow peptides or proteins to be physically associated with the encoding DNA are central to procedures which involve screening of protein libraries in vitro for new or altered function. Here we describe a new system designed specifically for the display of libraries of diverse, functional proteins which utilises the DNA binding protein nuclear factor κB (NF-κB) p50 to establish a phenotype-genotype link between the displayed protein and the encoding gene. Results A range of model fusion proteins to either the amino- or carboxy-terminus of NF-κB p50 have been constructed and shown to retain the picomolar affinity and DNA specificity of wild-type NF-κB p50. Through use of an optimal combination of binding buffer and DNA target sequence, the half-life of p50-DNA complexes could be increased to over 47 h, enabling the competitive selection of a variety of protein-plasmid complexes with enrichment factors of up to 6000-fold per round. The p50-based plasmid display system was used to enrich a maltose binding protein complex to homogeneity in only three rounds from a binary mixture with a starting ratio of 1:108 and to enrich to near homogeneity a single functional protein from a phenotype-genotype linked Escherichia coli genomic library using in vitro functional selections. Conclusions A new display technology is described which addresses the challenge of functional protein display. The results demonstrate that plasmid display is sufficiently sensitive to select a functional protein from large libraries and that it therefore represents a useful addition to the repertoire of display technologies.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.

Differential processing of thematic and categorical conceptual relations in spoken word production

Studies of semantic context effects in spoken word production have typically distinguished between categorical (or taxonomic) and associative relations. However, associates tend to confound semantic features or morphological representations, such as whole-part relations and compounds (e.g., BOAT-anchor, BEE-hive). Using a picture-word interference paradigm and functional magnetic resonance imaging (fMRI), we manipulated categorical (COW-rat) and thematic (COW-pasture) TARGET-distractor relations in a balanced design, finding interference and facilitation effects on naming latencies, respectively, as well as differential patterns of brain activation compared with an unrelated distractor condition. While both types of distractor relation activated the middle portion of the left middle temporal gyrus (MTG) consistent with retrieval of conceptual or lexical representations, categorical relations involved additional activation of posterior left MTG, consistent with retrieval of a lexical cohort. Thematic relations involved additional activation of the left angular gyrus. These results converge with recent lesion evidence implicating the left inferior parietal lobe in processing thematic relations and may indicate a potential role for this region during spoken word production.

Functional evaluation of genetic variants associated with endometriosis near GREB1

STUDY QUESTION: Do DNA variants in the growth regulation by estrogen in breast cancer 1 (GREB1) region regulate endometrial GREB1 expression and increase the risk of developing endometriosis in women? SUMMARY ANSWER: We identified new single nucleotide polymorphisms (SNPs) with strong association with endometriosis at the GREB1 locus although we did not detect altered GREB1 expression in endometriosis patients with defined genotypes. WHAT IS ALREADY KNOWN: Genome-wide association studies have identified the GREB1 region on chromosome 2p25.1 for increasing endometriosis risk. The differential expression of GREB1 has also been reported by others in association with endometriosis disease phenotype. STUDY DESIGN, SIZE, DURATION: Fine mapping studies comprehensively evaluated SNPs within the GREB1 region in a large-scale data set (>2500 cases and >4000 controls). Publicly available bioinformatics tools were employed to functionally annotate SNPs showing the strongest association signal with endometriosis risk. Endometrial GREB1 mRNA and protein expression was studied with respect to phases of the menstrual cycle (n = 2-45 per cycle stage) and expression quantitative trait loci (eQTL) analysis for significant SNPs were undertaken for GREB1 [mRNA (n = 94) and protein (n = 44) in endometrium]. PARTICIPANTS/MATERIALS, SETTING, METHODS: Participants in this study are females who provided blood and/or endometrial tissue samples in a hospital setting. The key SNPs were genotyped using Sequenom MassARRAY. The functional roles and regulatory annotations for identified SNPs are predicted by various publicly available bioinformatics tools. Endometrial GREB1 expression work employed qRT-PCR, western blotting and immunohistochemistry studies. MAIN RESULTS AND THE ROLE OF CHANCE: Fine mapping results identified a number of SNPs showing stronger association (0.004 < P < 0.032) with endometriosis risk than the original GWAS SNP (rs13394619) (P = 0.034). Some of these SNPs were predicted to have functional roles, for example, interaction with transcription factor motifs. The haplotype (a combination of alleles) formed by the risk alleles from two common SNPs showed significant association (P = 0.026) with endometriosis and epistasis analysis showed no evidence for interaction between the two SNPs, suggesting an additive effect of SNPs on endometriosis risk. In normal human endometrium, GREB1 protein expression was altered depending on the cycle stage (significantly different in late proliferative versus late secretory, P < 0.05) and cell type (glandular epithelium, not stromal cells). However, GREB1 expression in endometriosis cases versus controls and eQTL analyses did not reveal any significant changes. LIMITATIONS, REASONS FOR CAUTION: In silico prediction tools are generally based on cell lines different to our tissue and disease of interest. Functional annotations drawn from these analyses should be considered with this limitation in mind. We identified cell-specific and hormone-specific changes in GREB1 protein expression. The lack of a significant difference observed following our GREB1 expression studies may be the result of moderate power on mixed cell populations in the endometrial tissue samples. WIDER IMPLICATIONS OF THE FINDINGS: This study further implicates the GREB1 region on chromosome 2p25.1 and the GREB1 gene with involvement in endometriosis risk. More detailed functional studies are required to determine the role of the novel GREB1 transcripts in endometriosis pathophysiology. STUDY FUNDING/COMPETING INTERESTS: Funding for this work was provided by NHMRC Project Grants APP1012245, APP1026033, APP1049472 and APP1046880. There are no competing interests.

Forecasting day-ahead electricity load using a multiple equation time series approach

The quality of short-term electricity load forecasting is crucial to the operation and trading activities of market participants in an electricity market. In this paper, it is shown that a multiple equation time-series model, which is estimated by repeated application of ordinary least squares, has the potential to match or even outperform more complex nonlinear and nonparametric forecasting models. The key ingredient of the success of this simple model is the effective use of lagged information by allowing for interaction between seasonal patterns and intra-day dependencies. Although the model is built using data for the Queensland region of Australia, the method is completely generic and applicable to any load forecasting problem. The model’s forecasting ability is assessed by means of the mean absolute percentage error (MAPE). For day-ahead forecast, the MAPE returned by the model over a period of 11 years is an impressive 1.36%. The forecast accuracy of the model is compared with a number of benchmarks including three popular alternatives and one industrial standard reported by the Australia Energy Market Operator (AEMO). The performance of the model developed in this paper is superior to all benchmarks and outperforms the AEMO forecasts by about a third in terms of the MAPE criterion.