Prognostic significance of IGF and ECM induced signalling proteins in breast cancer patients

Breast cancer is a leading contributor to the burden of disease in Australia. Fortunately, the recent introduction of diverse therapeutic strategies have improved the survival outcome for many women. Despite this, the clinical management of breast cancer remains problematic as not all approaches are sufficiently sophisticated to take into account the heterogeneity of this disease and are unable to predict disease progression, in particular, metastasis. As such, women with good prognostic outcomes are exposed to the side effects of therapies without added benefit. Furthermore, women with aggressive disease for whom these advanced treatments would deliver benefit cannot be distinguished and opportunities for more intensive or novel treatment are lost. This study is designed to identify novel factors associated with disease progression, and the potential to inform disease prognosis. Frequently overlooked, yet common mediators of disease are the interactions that take place between the insulin-like growth factor (IGF) system and the extracellular matrix (ECM). Our laboratory has previously demonstrated that multiprotein insulin-like growth factor-I (IGF-I): insulin-like growth factor binding protein (IGFBP): vitronectin (VN) complexes stimulate migration of breast cancer cells in vitro, via the cooperative involvement of the insulin-like growth factor type I receptor (IGF-IR) and VN-binding integrins. However, the effects of IGF and ECM protein interactions on the dissemination and progression of breast cancer in vivo are unknown. It was hypothesised that interactions between proteins required for IGF induced signalling events and those within the ECM contribute to breast cancer metastasis and are prognostic and predictive indicators of patient outcome. To address this hypothesis, semiquantitative immunohistochemistry (IHC) analyses were performed to compare the extracellular and subcellular distribution of IGF and ECM induced signalling proteins between matched normal, primary cancer, and metastatic cancer among archival formalin-fixed paraffin-embedded (FFPE) breast tissue samples collected from women attending the Princess Alexandra Hospital, Brisbane. Multivariate Cox proportional hazards (PH) regression survival models in conjunction with a modified „purposeful selection of covariates. method were applied to determine the prognostic potential of these proteins. This study provides the first in-depth, compartmentalised analysis of the distribution of IGF and ECM induced signalling proteins. As protein function and protein localisation are closely correlated, these findings provide novel insights into IGF signalling and ECM protein function during breast cancer development and progression. Distinct IGF signalling and ECM protein immunoreactivity was observed in the stroma and/or in subcellular locations in normal breast, primary cancer and metastatic cancer tissues. Analysis of the presence and location of stratifin (SFN) suggested a causal relationship in ECM remodelling events during breast cancer development and progression. The results of this study have also suggested that fibronectin (FN) and ¥â1 integrin are important for the formation of invadopodia and epithelial-to-mesenchymal transition (EMT) events. Our data also highlighted the importance of the temporal and spatial distribution of IGF induced signalling proteins in breast cancer metastasis; in particular, SFN, enhancer-of-split and hairy-related protein 2 (SHARP-2), total-akt/protein kinase B 1 (Total-AKT1), phosphorylated-akt/protein kinase B (P-AKT), extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (ERK1/2) and phosphorylated-extracellular signal-related kinase-1 and extracellular signal-related kinase-2 (P-ERK1/2). Multivariate survival models were created from the immunohistochemical data. These models were found to fit well with these data with very high statistical confidence. Numerous prognostic confounding effects and effect modifications were identified among elements of the ECM and IGF signalling cascade and corroborate the survival models. This finding provides further evidence for the prognostic potential of IGF and ECM induced signalling proteins. In addition, the adjusted measures of associations obtained in this study have strengthened the validity and utility of the resulting models. The findings from this study provide insights into the biological interactions that occur during the development of breast tissue and contribute to disease progression. Importantly, these multivariate survival models could provide important prognostic and predictive indicators that assist the clinical management of breast disease, namely in the early identification of cancers with a propensity to metastasise, and/or recur following adjuvant therapy. The outcomes of this study further inform the development of new therapeutics to aid patient recovery. The findings from this study have widespread clinical application in the diagnosis of disease and prognosis of disease progression, and inform the most appropriate clinical management of individuals with breast cancer.

The porcine circovirus type 1 capsid gene promoter improves antigen expression and immunogenicity in a HIV-1 plasmid vaccine

Background. One of the promising avenues for development of vaccines against Human immunodeficiency virus type 1 (HIV-1) and other human pathogens is the use of plasmid-based DNA vaccines. However, relatively large doses of plasmid must be injected for a relatively weak response. We investigated whether genome elements from Porcine circovirus type 1 (PCV-1), an apathogenic small ssDNA-containing virus, had useful expression-enhancing properties that could allow dose-sparing in a plasmid vaccine. Results. The linearised PCV-1 genome inserted 5' of the CMV promoter in the well-characterised HIV-1 plasmid vaccine pTHgrttnC increased expression of the polyantigen up to 2-fold, and elicited 3-fold higher CTL responses in mice at 10-fold lower doses than unmodified pTHgrttnC. The PCV-1 capsid gene promoter (Pcap) alone was equally effective. Enhancing activity was traced to a putative composite host transcription factor binding site and a "Conserved Late Element" transcription-enhancing sequence previously unidentified in circoviruses. Conclusions. We identified a novel PCV-1 genome-derived enhancer sequence that significantly increased antigen expression from plasmids in in vitro assays, and improved immunogenicity in mice of the HIV-1 subtype C vaccine plasmid, pTHgrttnC. This should allow significant dose sparing of, or increased responses to, this and other plasmid-based vaccines. We also report investigations of the potential of other circovirus-derived sequences to be similarly used. © 2011 Tanzer et al; licensee BioMed Central Ltd.

Prediction of transcriptional regulatory interactions in bacteria : a comparative genomics approach

Exponential growth of genomic data in the last two decades has made manual analyses impractical for all but trial studies. As genomic analyses have become more sophisticated, and move toward comparisons across large datasets, computational approaches have become essential. One of the most important biological questions is to understand the mechanisms underlying gene regulation. Genetic regulation is commonly investigated and modelled through the use of transcriptional regulatory network (TRN) structures. These model the regulatory interactions between two key components: transcription factors (TFs) and the target genes (TGs) they regulate. Transcriptional regulatory networks have proven to be invaluable scientific tools in Bioinformatics. When used in conjunction with comparative genomics, they have provided substantial insights into the evolution of regulatory interactions. Current approaches to regulatory network inference, however, omit two additional key entities: promoters and transcription factor binding sites (TFBSs). In this study, we attempted to explore the relationships among these regulatory components in bacteria. Our primary goal was to identify relationships that can assist in reducing the high false positive rates associated with transcription factor binding site predictions and thereupon enhance the reliability of the inferred transcription regulatory networks. In our preliminary exploration of relationships between the key regulatory components in Escherichia coli transcription, we discovered a number of potentially useful features. The combination of location score and sequence dissimilarity scores increased de novo binding site prediction accuracy by 13.6%. Another important observation made was with regards to the relationship between transcription factors grouped by their regulatory role and corresponding promoter strength. Our study of E.coli ��70 promoters, found support at the 0.1 significance level for our hypothesis | that weak promoters are preferentially associated with activator binding sites to enhance gene expression, whilst strong promoters have more repressor binding sites to repress or inhibit gene transcription. Although the observations were specific to �70, they nevertheless strongly encourage additional investigations when more experimentally confirmed data are available. In our preliminary exploration of relationships between the key regulatory components in E.coli transcription, we discovered a number of potentially useful features { some of which proved successful in reducing the number of false positives when applied to re-evaluate binding site predictions. Of chief interest was the relationship observed between promoter strength and TFs with respect to their regulatory role. Based on the common assumption, where promoter homology positively correlates with transcription rate, we hypothesised that weak promoters would have more transcription factors that enhance gene expression, whilst strong promoters would have more repressor binding sites. The t-tests assessed for E.coli �70 promoters returned a p-value of 0.072, which at 0.1 significance level suggested support for our (alternative) hypothesis; albeit this trend may only be present for promoters where corresponding TFBSs are either all repressors or all activators. Nevertheless, such suggestive results strongly encourage additional investigations when more experimentally confirmed data will become available. Much of the remainder of the thesis concerns a machine learning study of binding site prediction, using the SVM and kernel methods, principally the spectrum kernel. Spectrum kernels have been successfully applied in previous studies of protein classification [91, 92], as well as the related problem of promoter predictions [59], and we have here successfully applied the technique to refining TFBS predictions. The advantages provided by the SVM classifier were best seen in `moderately'-conserved transcription factor binding sites as represented by our E.coli CRP case study. Inclusion of additional position feature attributes further increased accuracy by 9.1% but more notable was the considerable decrease in false positive rate from 0.8 to 0.5 while retaining 0.9 sensitivity. Improved prediction of transcription factor binding sites is in turn extremely valuable in improving inference of regulatory relationships, a problem notoriously prone to false positive predictions. Here, the number of false regulatory interactions inferred using the conventional two-component model was substantially reduced when we integrated de novo transcription factor binding site predictions as an additional criterion for acceptance in a case study of inference in the Fur regulon. This initial work was extended to a comparative study of the iron regulatory system across 20 Yersinia strains. This work revealed interesting, strain-specific difierences, especially between pathogenic and non-pathogenic strains. Such difierences were made clear through interactive visualisations using the TRNDifi software developed as part of this work, and would have remained undetected using conventional methods. This approach led to the nomination of the Yfe iron-uptake system as a candidate for further wet-lab experimentation due to its potential active functionality in non-pathogens and its known participation in full virulence of the bubonic plague strain. Building on this work, we introduced novel structures we have labelled as `regulatory trees', inspired by the phylogenetic tree concept. Instead of using gene or protein sequence similarity, the regulatory trees were constructed based on the number of similar regulatory interactions. While the common phylogentic trees convey information regarding changes in gene repertoire, which we might regard being analogous to `hardware', the regulatory tree informs us of the changes in regulatory circuitry, in some respects analogous to `software'. In this context, we explored the `pan-regulatory network' for the Fur system, the entire set of regulatory interactions found for the Fur transcription factor across a group of genomes. In the pan-regulatory network, emphasis is placed on how the regulatory network for each target genome is inferred from multiple sources instead of a single source, as is the common approach. The benefit of using multiple reference networks, is a more comprehensive survey of the relationships, and increased confidence in the regulatory interactions predicted. In the present study, we distinguish between relationships found across the full set of genomes as the `core-regulatory-set', and interactions found only in a subset of genomes explored as the `sub-regulatory-set'. We found nine Fur target gene clusters present across the four genomes studied, this core set potentially identifying basic regulatory processes essential for survival. Species level difierences are seen at the sub-regulatory-set level; for example the known virulence factors, YbtA and PchR were found in Y.pestis and P.aerguinosa respectively, but were not present in both E.coli and B.subtilis. Such factors and the iron-uptake systems they regulate, are ideal candidates for wet-lab investigation to determine whether or not they are pathogenic specific. In this study, we employed a broad range of approaches to address our goals and assessed these methods using the Fur regulon as our initial case study. We identified a set of promising feature attributes; demonstrated their success in increasing transcription factor binding site prediction specificity while retaining sensitivity, and showed the importance of binding site predictions in enhancing the reliability of regulatory interaction inferences. Most importantly, these outcomes led to the introduction of a range of visualisations and techniques, which are applicable across the entire bacterial spectrum and can be utilised in studies beyond the understanding of transcriptional regulatory networks.

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.

The association of single nucleotide polymorphisms with endometrial cancer risk and prognosis

Endometrial cancer is one of the most common female diseases in developed nations and is the most commonly diagnosed gynaecological cancer in Australia. The disease is commonly classified by histology: endometrioid or non-endometrioid endometrial cancer. While non-endometrioid endometrial cancers are accepted to be high-grade, aggressive cancers, endometrioid cancers (comprising 80% of all endometrial cancers diagnosed) generally carry a favourable patient prognosis. However, endometrioid endometrial cancer patients endure significant morbidity due to surgery and radiotherapy used for disease treatment, and patients with recurrent disease have a 5-year survival rate of less than 50%. Genetic analysis of women with endometrial cancer could uncover novel markers associated with disease risk and/or prognosis, which could then be used to identify women at high risk and for the use of specialised treatments. Proteases are widely accepted to play an important role in the development and progression of cancer. This PhD project hypothesised that SNPs from two protease gene families, the matrix metalloproteases (MMPs, including their tissue inhibitors, TIMPs) and the tissue kallikrein-related peptidases (KLKs) would be associated with endometrial cancer susceptibility and/or prognosis. In the first part of this study, optimisation of the genotyping techniques was performed. Results from previously published endometrial cancer genetic association studies were attempted to be validated in a large, multicentre replication set (maximum cases n = 2,888, controls n = 4,483, 3 studies). The rs11224561 progesterone receptor SNP (PGR, A/G) was observed to be associated with increased endometrial cancer risk (per A allele OR 1.31, 95% CI 1.12-1.53; p-trend = 0.001), a result which was initially reported among a Chinese sample set. Previously reported associations for the remaining 8 SNPs investigated for this section of the PhD study were not confirmed, thereby reinforcing the importance of validation of genetic association studies. To examine the effect of SNPs from the MMP and KLK families on endometrial cancer risk, we selected the most significantly associated MMP and KLK SNPs from genome-wide association study analysis (GWAS) to be genotyped in the GWAS replication set (cases n = 4,725, controls n = 9,803, 13 studies). The significance of the MMP24 rs932562 SNP was unchanged after incorporation of the stage 2 samples (Stage 1 per allele OR 1.18, p = 0.002; Combined Stage 1 and 2 OR 1.09, p = 0.002). The rs10426 SNP, located 3' to KLK10 was predicted by bioinformatic analysis to effect miRNA binding. This SNP was observed in the GWAS stage 1 result to exhibit a recessive effect on endometrial cancer risk, a result which was not validated in the stage 2 sample set (Stage 1 OR 1.44, p = 0.007; Combined Stage 1 and 2 OR 1.14, p = 0.08). Investigation of the regions imputed surrounding the MMP, TIMP and KLK genes did not reveal any significant targets for further analysis. Analysis of the case data from the endometrial cancer GWAS to identify genetic variation associated with cancer grade did not reveal SNPs from the MMP, TIMP or KLK genes to be statistically significant. However, the representation of SNPs from the MMP, TIMP and KLK families by the GWAS genotyping platform used in this PhD project was examined and observed to be very low, with the genetic variation of four genes (MMP23A, MMP23B, MMP28 and TIMP1) not captured at all by this technique. This suggests that comprehensive candidate gene association studies will be required to assess the role of SNPs from these genes with endometrial cancer risk and prognosis. Meta-analysis of gene expression microarray datasets curated as part of this PhD study identified a number of MMP, TIMP and KLK genes to display differential expression by endometrial cancer status (MMP2, MMP10, MMP11, MMP13, MMP19, MMP25 and KLK1) and histology (MMP2, MMP11, MMP12, MMP26, MMP28, TIMP2, TIMP3, KLK6, KLK7, KLK11 and KLK12). In light of these findings these genes should be prioritised for future targeted genetic association studies. Two SNPs located 43.5 Mb apart on chromosome 15 were observed from the GWAS analysis to be associated with increased endometrial cancer grade, results that were validated in silico in two independent datasets. One of these SNPs, rs8035725 is located in the 5' untranslated region of a MYC promoter binding protein DENND4A (Stage 1 OR 1.15, p = 9.85 x 10P -5 P, combined Stage 1 and in silico validation OR 1.13, p = 5.24 x 10P -6 P). This SNP has previously been reported to alter the expression of PTPLAD1, a gene involved in the synthesis of very long fatty acid chains and in the Rac1 signaling pathway. Meta-analysis of gene expression microarray data found PTPLAD1 to display increased expression in the aggressive non-endometrioid histology compared with endometrioid endometrial cancer, suggesting that the causal SNP underlying the observed genetic association may influence expression of this gene. Neither rs8035725 nor significant SNPs identified by imputation were predicted bioinformatically to affect transcription factor binding sites, indicating that further studies are required to assess their potential effect on other regulatory elements. The other grade- associated SNP, rs6606792, is located upstream of an inferred pseudogene, ELMO2P1 (Stage 1 OR 1.12, p = 5 x 10P -5 P; combined Stage 1 and in silico validation OR 1.09, p = 3.56 x 10P -5 P). Imputation of the ±1 Mb region surrounding this SNP revealed a cluster of significantly associated variants which are predicted to abolish various transcription factor binding sites, and would be expected to decrease gene expression. ELMO2P1 was not included on the microarray platforms collected for this PhD, and so its expression could not be investigated. However, the high sequence homology of ELMO2P1 with ELMO2, a gene important to cell motility, indicates that ELMO2 could be the parent gene for ELMO2P1 and as such, ELMO2P1 could function to regulate the expression of ELMO2. Increased expression of ELMO2 was seen to be associated with increasing endometrial cancer grade, as well as with aggressive endometrial cancer histological subtypes by microarray meta-analysis. Thus, it is hypothesised that SNPs in linkage disequilibrium with rs6606792 decrease the transcription of ELMO2P1, reducing the regulatory effect of ELMO2P1 on ELMO2 expression. Consequently, ELMO2 expression is increased, cell motility is enhanced leading to an aggressive endometrial cancer phenotype. In summary, these findings have identified several areas of research for further study. The results presented in this thesis provide evidence that a SNP in PGR is associated with risk of developing endometrial cancer. This PhD study also reports two independent loci on chromosome 15 to be associated with increased endometrial cancer grade, and furthermore, genes associated with these SNPs to be differentially expressed according in aggressive subtypes and/or by grade. The studies reported in this thesis support the need for comprehensive SNP association studies on prioritised MMP, TIMP and KLK genes in large sample sets. Until these studies are performed, the role of MMP, TIMP and KLK genetic variation remains unclear. Overall, this PhD study has contributed to the understanding of genetic variation involvement in endometrial cancer susceptibility and prognosis. Importantly, the genetic regions highlighted in this study could lead to the identification of novel gene targets to better understand the biology of endometrial cancer and also aid in the development of therapeutics directed at treating this disease.

Prognostic significance of platelet and microvessel counts in operable non-small cell lung cancer

Background: Microvessel density, an indirect measure of angiogenesis, has been shown to be an independent prognostic marker in many solid tumours including non-small cell lung cancer (NSCLC). Platelets transport and release angiogenic growth factors. Platelets are increasingly likely to adhere to tumour microvessels due to raised expression of platelet-binding proteins and stasis in blood-flow. Increased vascular permeability in tumour microvessels facilitates platelet extravasation into the extracellular matrix. Adherence and extravasation both lead to platelet activation and release of growth factors capable of instigating the angiogenic process. Methods: A total of 181 patients were identified who underwent resection of stage I-IIIa NSCLC with a post-operative survival >60 days. Patients were followed-up for a minimum of 24 months. Sections from the tumour periphery were stained for the endothelial marker CD34 (Novocastra NCL-END) using standard ABC immunohistochemistry. Chalkley counting was used to assess microvessel density. Results: A pre-operative platelet count greater than the median and above the normal range (>400) was associated with a poor outcome (P = 0.01 and P = 0.04, respectively). Tumours with an above median and high Chalkley count (upper tertile) had a worse prognosis (P = 0.007 and P = 0.0006, respectively). There was no association between platelet count and Chalkley count. Conclusions: Platelet and microvessel counts are both potential prognostic markers for NSCLC. The role of platelets in the angiogenic process needs to be further investigated. (C) 2000 Elsevier Science Ireland Ltd.

Translational approaches to medication development

Alcohol accounts for major disability worldwide and available treatments are insufficient. A massive growth in the area of addiction neuroscience over the last several decades has not resulted in a corresponding expansion of treatment options available to patients. In this chapter, we describe our experience with building translational research programs aimed at developing novel pharmacotherapies for alcoholism. The narrative is based on experience and considerations made in the course of building these programs, and work on four mechanisms targeted by our libraries: cholinergic nicotine receptors, receptors for corticotropin-releasing hormone (CRH), neurokinin 1 (NK1) receptors for substance P (SP) and hypocretin/orexin receptors. Around this experience, we discuss issues we believe to be critical for successful translation of basic addiction neuroscience into treatments, and complementarities between academic and other actors that in our assessment need to be harnessed in order to bring treatments to the clinic.

Oestrogen and progestin responses in human endometrium

Our understanding of the mechanisms of the actions of oestrogens and progestins have evolved from the simple concept of nuclear receptor-mediated regulation of transcription to a highly sophisticated, finely tuned interplay between various coregulators, other signaling cascades and transcription factors. The net result of these complex regulatory mechanisms is a steroid-, cell-, or tissue-specific action of oestrogens and progestins. their antagonists or selective modulators of their receptors. In this review, we have attempted to shed some light on the regulation of the actions of oestrogens and progestins on the human endometrium. (C) 2003 Elsevier Science Ltd. All rights reserved.

Computational epigenetic profiling of CpG islets in MTHFR

Computational epigenetics is a new area of research focused on exploring how DNA methylation patterns affect transcription factor binding that affect gene expression patterns. The aim of this study was to produce a new protocol for the detection of DNA methylation patterns using computational analysis which can be further confirmed by bisulfite PCR with serial pyrosequencing. The upstream regulatory element and pre-initiation complex relative to CpG islets within the methylenetetrahydrofolate reductase gene were determined via computational analysis and online databases. The 1,104 bp long CpG island located near to or at the alternative promoter site of methylenetetrahydrofolate reductase gene was identified. The CpG plot indicated that CpG islets A and B, within the island, contained 62 and 75 % GC content CpG ratios of 0.70 and 0.80–0.95, respectively. Further exploration of the CpG islets A and B indicates that the transcription start sites were GGC which were absent from the TATA boxes. In addition, although six PROSITE motifs were identified in CpG B, no motifs were detected in CpG A. A number of cis-regulatory elements were found in different regions within the CpGs A and B. Transcription factors were predicted to bind to CpGs A and B with varying affinities depending on the DNA methylation status. In addition, transcription factor binding may influence the expression patterns of the methylenetetrahydrofolate reductase gene by recruiting chromatin condensation inducing factors. These results have significant implications for the understanding of the architecture of transcription factor binding at CpG islets as well as DNA methylation patterns that affect chromatin structure.

A Mammalian Circadian Clock Model Incorporating Daytime Expression Elements

Models of the mammalian clock have traditionally been based around two feedback loops-the self-repression of Per/Cry by interfering with activation by BMAL/CLOCK, and the repression of Bmal/Clock by the REV-ERB proteins. Recent experimental evidence suggests that the D-box, a transcription factor binding site associated with daytime expression, plays a larger role in clock function than has previously been understood. We present a simplified clock model that highlights the role of the D-box and illustrate an approach for finding maximum-entropy ensembles of model parameters, given experimentally imposed constraints. Parameter variability can be mitigated using prior probability distributions derived from genome-wide studies of cellular kinetics. Our model reproduces predictions concerning the dual regulation of Cry1 by the D-box and Rev-ErbA/ROR response element (RRE) promoter elements and allows for ensemble-based predictions of phase response curves (PRCs). Nonphotic signals such as Neuropeptide Y (NPY) may act by promoting Cry1 expression, whereas photic signals likely act by stimulating expression from the E/E' box. Ensemble generation with parameter probability restraints reveals more about a model's behavior than a single optimal parameter set.

Identifying the molecular mediators of VN and the IGF:VN complex-stimulated breast cancer cell survival

This project has identified a molecular signature involved in functions critical to breast cancer progression and metastasis mediated by vitronectin, an abundant protein in human plasma and victornectin:insulin-like growth factor complexes. This may have significant implications in designing future therapeutic targets for patient with tumours overexpressing vitronectin and/or the components of the insulin-like growth factor system:vitronectin axis. In particular, the findings from this project have identified Cyr61 and CTGF as key mediators involved in vitroncetin- and insulin-like growth factor I: Insulin-like growth factor-binding protein:vitronectin-induced breast cancer cell survival and migration.

Growth hormone resistance and somatomedins in children with end-stage liver disease awaiting transplantation

Background: The success of orthotopic liver transplantation as treatment for end-stage liver disease has prompted investigation of strategies to maintain or improve nutrition and growth in children awaiting transplantation, because malnutrition is an adverse prognostic factor. The purpose of this study was to evaluate the effect of recombinant human growth hormone therapy on body composition and indices of liver function in patients awaiting transplant. Methods: The study was designed as a placebo- controlled, double-blind, crossover trial. Patients received 0.2 U/kg growth hormone, subcutaneously, or placebo daily for 28 days during two treatment periods, separated by a 2-week washout period. Ten patients (mean age, 3.06 ± 1.15 years; range, 0.51-11.65 years, five men), with extrahepatic biliary atresia (n = 8) or two with Alagille's syndrome (n = 2), with end-stage liver disease, completed the trial while awaiting orthotopic liver transplantation. Height, weight, total body potassium, total body fat, resting energy expenditure, respiratory quotient, hematologic and multiple biochemical profile, number of albumin infusions, insulin-like growth factor-1 and 1, growth hormone binding protein (GHBP), and insulin-like growth factor binding protein-1 (IGFBP-1) and insulin-like growth factor binding protein (IGFBP-3) were measured at the beginning and end of each treatment period. Results: Growth hormone treatment was associated with a significant decline in serum bilirubin (-34.6 ± 16.5 μmol/l vs. 18.2 ± 11.59 μmol/l; p < 0.02) but there was no significant effect on any anthropometric or body composition measurements, or on any biochemical or hematologic parameters. Conclusions: These children with end-stage liver disease displayed growth hormone resistance, particularly in relation to the somatomedin axis. Exogenous growth hormone administration may be of limited value in these patients

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Cytochrome P450 aromatase in grey mullet: cDNA and promoter isolation; brain, pituitary and ovarian expression during puberty.

In a study towards elucidating the role of aromatases during puberty in female grey mullet, the cDNAs of the brain (muCyp19b) and ovarian (muCyp19a) aromatase were isolated by RT-PCR and their relative expression levels were determined by quantitative real-time RT-PCR. The muCyp19a ORF of 1515 bp encoded 505 predicted amino acid residues, while that of muCyp19b was 1485 bp and encoded 495 predicted amino acid residues. The expression level of muCyp19b significantly increased in the brain as puberty advanced; however, its expression level in the pituitary increased only slightly with pubertal development. In the ovary, the muCyp19a expression level markedly increased as puberty progressed. The promoter regions of the two genes were also isolated and their functionality evaluated in vitro using luciferase as the reporter gene. The muCyp19a promoter sequence (650 bp) contained a consensus TATA box and putative transcription factor binding sites, including two half EREs, an SF-1, an AhR/Arnt, a PR and two GATA-3s. The muCyp19b promoter sequence (2500 bp) showed consensus TATA and CCAAT boxes and putative transcription binding sites, namely: a PR, an ERE, a half ERE, a SP-1, two GATA-binding factor, one half GATA-1, two C/EBPs, a GRE, a NFkappaB, three STATs, a PPAR/RXR, an Ahr/Arnt and a CRE. Basal activity of serially deleted promoter constructs transiently transfected into COS-7, [alpha]T3 and TE671 cells demonstrated the enhancing and silencing roles of the putative transcription factor binding sites. Quinpirole, a dopamine agonist, significantly reduced the promoter activity of muCyp19b in TE671. The results suggest tissue-specific regulation of the muCyp19 genes and a putative alternative promoter for muCyp19b.

Fine mapping of variants associated with endometriosis in the WNT4 region on chromosome 1p36

Genome-wide association studies show strong evidence of association with endometriosis for markers on chromosome 1p36 spanning the potential candidate genes WNT4, CDC42 and LINC00339. WNT4 is involved in development of the uterus, and the expression of CDC42 and LINC00339 are altered in women with endometriosis. We conducted fine mapping to examine the role of coding variants in WNT4 and CDC42 and determine the key SNPs with strongest evidence of association in this region. We identified rare coding variants in WNT4 and CDC42 present only in endometriosis cases. The frequencies were low and cannot account for the common signal associated with increased risk of endometriosis. Genotypes for five common SNPs in the region of chromosome 1p36 show stronger association signals when compared with rs7521902 reported in published genome scans. Of these, three SNPs rs12404660, rs3820282, and rs55938609 were located in DNA sequences with potential functional roles including overlap with transcription factor binding sites for FOXA1, FOXA2, ESR1, and ESR2. Functional studies will be required to identify the gene or genes implicated in endometriosis risk.