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.

Understanding the function and mechanisms of intestinal cell kinase in the growth and survival of prostate cancer cells

This project was a step forward in discovering the potential role of intestinal cell kinase in prostate cancer development. Intestinal cell kinase was shown to be upregulated in prostate cancer cells and altered expression led to changes in key cell survival proteins. This study used in vitro experiments to monitor changes in cell growth, protein and RNA expression.

Surgical fusion of early onset severe scoliosis increases survival in the child with rett syndrome: A population based study

Introduction. Rett Syndrome is a rare genetic neurodevelopmental disorder usually affecting females. Scoliosis is a common comorbidity and spinal fusion may be recommended if severe. Little is known about long term outcomes. We examined the impact of spinal fusion on survival and risk of severe lower respiratory tract infection (LRTI) in Rett Syndrome. Methods Data were ascertained from hospital medical records, the Australian Rett Syndrome Database, a longitudinal and population-based registry of Rett Syndrome cases established in 1993, and the Australian Institute of Health and Welfare National Death Index database. An extended Cox regression model was used to estimate the effect of spinal surgery on survival in females who developed severe scoliosis (Cobb angle > 45 degrees). Generalized estimating equation modelling was used to estimate the effect of spinal surgery on the odds of developing severe LRTI. Results Severe scoliosis was identified in 140 cases (60.3%) of whom slightly fewer than half (48.6%) developed scoliosis prior to eight years of age. Scoliosis surgery was performed in 98 (69.0%) of those at a median age of 13 years 3 months (IQR 11 years 5 months – 14 years 10 months). After adjusting for mutation type and age of scoliosis onset, the rate of death was lower in the surgery group (HR 0.30, 95% CI 0.12, 0.74, P = 0.009) compared to those without surgery. Rate of death was particularly reduced for those with early onset scoliosis (HR 0.17, 95% CI 0.06, 0.52, P = 0.002). Spinal fusion was not associated with reduction in the occurrence of a severe LRTI overall (OR 0.60, 95%CI 0.27, 1.33, P=0.206) but was associated with a large reduction in odds of severe LRTI among those with early onset scoliosis (OR 0.32, 95%CI 0.11, 0.93, P=0.036). Conclusion With appropriate cautions, spinal fusion confers an advantage to life expectancy in Rett syndrome.

Comparing multilevel and Bayesian spatial random effects survival models to assess geographical inequalities in colorectal cancer survival: a case study

Background Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Methods Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20–84 years diagnosed during 1997–2007 from Queensland, Australia. Results Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the between-area variability in survival using multilevel discrete-time models was no longer significant. Spatial inequalities in survival were also markedly reduced after adjusting for aggregated area-level covariates. Only the multilevel approach however, provided an estimation of the contribution of geographical variation to the total variation in survival between individual patients. Conclusions With little difference observed between the two approaches in the estimation of fixed effects, multilevel models should be favored if there is a clear hierarchical data structure and measuring the independent impact of individual- and area-level effects on survival differences is of primary interest. Bayesian spatial analyses may be preferred if spatial correlation between areas is important and if the priority is to assess small-area variations in survival and map spatial patterns. Both approaches can be readily fitted to geographically enabled survival data from international settings

Estimation of the time of a linear trend in monitoring survival time

Change point estimation is recognized as an essential tool of root cause analyses within quality control programs as it enables clinical experts to search for potential causes of change in hospital outcomes more effectively. In this paper, we consider estimation of the time when a linear trend disturbance has occurred in survival time following an in-control clinical intervention in the presence of variable patient mix. To model the process and change point, a linear trend in the survival time of patients who underwent cardiac surgery is formulated using hierarchical models in a Bayesian framework. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. We use Markov Chain Monte Carlo to obtain posterior distributions of the change point parameters including the location and the slope size of the trend and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time cumulative sum control chart (CUSUM) control charts for different trend scenarios. In comparison with the alternatives, step change point model and built-in CUSUM estimator, more accurate and precise estimates are obtained by the proposed Bayesian estimator over linear trends. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Induced smoothing for rank regression with censored survival times

Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.

Survival, growth and quality of life in children after orthotopic liver transplantation: A 5 year experience

The aims of this study were to investigate outcome and to evaluate areas of potential ongoing concern after orthotopic liver transplantation (OLT) in children. Actuarial survival in relation to age and degree of undernutrition at the time of OLT was evaluated in 53 children (age 0.58-14.2 years) undergoing OLT for endstage liver disease. Follow-up studies of growth and quality of life were undertaken in those with a minimum follow-up period of 12 months (n = 26). The overall 3 year actuarial survival was 70%. Survival rates did not differ between age groups (actuarial 2 year survival for ages <1, 1-5 and >5 years were 70, 70 and 69% respectively) but did differ according to nutritional status at OLT (actuarial 2 year survival for children with Z scores for weight <-1 was 57%, >-1 was 95%; P = 0.004). Significant catch-up weight gain was observed by 18 months post-transplant, while height improved less rapidly. Quality of life (assessed by Vineland Adaptive Behaviour Scales incorporating socialization, daily living skills, communication and motor skills) was good (mean composite score 91 ± 19). All school-aged children except one were attending normal school. Two children had mild to moderate intellectual handicap related to post-operative intracerebral complications. Satisfactory long-term survival can be achieved after OLT in children regardless of age but the importance of pre-operative nutrition is emphasized. Survivors have an excellent chance of a good quality of life and of satisfactory catch-up weight gain and growth.

Exact calculations of survival probability for diffusion on growing lines, disks, and spheres: The role of dimension

Unlike standard applications of transport theory, the transport of molecules and cells during embryonic development often takes place within growing multidimensional tissues. In this work, we consider a model of diffusion on uniformly growing lines, disks, and spheres. An exact solution of the partial differential equation governing the diffusion of a population of individuals on the growing domain is derived. Using this solution, we study the survival probability, S(t). For the standard nongrowing case with an absorbing boundary, we observe that S(t) decays to zero in the long time limit. In contrast, when the domain grows linearly or exponentially with time, we show that S(t) decays to a constant, positive value, indicating that a proportion of the diffusing substance remains on the growing domain indefinitely. Comparing S(t) for diffusion on lines, disks, and spheres indicates that there are minimal differences in S(t) in the limit of zero growth and minimal differences in S(t) in the limit of fast growth. In contrast, for intermediate growth rates, we observe modest differences in S(t) between different geometries. These differences can be quantified by evaluating the exact expressions derived and presented here.

Survival probability for a diffusive process on a growing domain

We consider the motion of a diffusive population on a growing domain, 0 < x < L(t ), which is motivated by various applications in developmental biology. Individuals in the diffusing population, which could represent molecules or cells in a developmental scenario, undergo two different kinds of motion: (i) undirected movement, characterized by a diffusion coefficient, D, and (ii) directed movement, associated with the underlying domain growth. For a general class of problems with a reflecting boundary at x = 0, and an absorbing boundary at x = L(t ), we provide an exact solution to the partial differential equation describing the evolution of the population density function, C(x,t ). Using this solution, we derive an exact expression for the survival probability, S(t ), and an accurate approximation for the long-time limit, S = limt→∞ S(t ). Unlike traditional analyses on a nongrowing domain, where S ≡ 0, we show that domain growth leads to a very different situation where S can be positive. The theoretical tools developed and validated in this study allow us to distinguish between situations where the diffusive population reaches the moving boundary at x = L(t ) from other situations where the diffusive population never reaches the moving boundary at x = L(t ). Making this distinction is relevant to certain applications in developmental biology, such as the development of the enteric nervous system (ENS). All theoretical predictions are verified by implementing a discrete stochastic model.

Phylogenetic lineage and pilus protein Spb1/SAN1518 affect opsonin-independent phagocytosis and intracellular survival of Group B Streptococcus

Opsonin-independent phagocytosis of Group B Streptococcus (GBS) is important in defense against neonatal GBS infections. A recent study indicated a role for GBS pilus in macrophage phagocytosis (Maisey et al Faseb J 22 2008 1715-24). We studied 163 isolates from different phylogenetic backgrounds and those possessing or lacking the gene encoding the pilus backbone protein, Spb1 (SAN1518, PI-2b) and spb1-deficient mutants of wild-type (WT) serotype III-3 GBS 874391 in non-opsonic phagocytosis assays using J774A.1 macrophages. Numbers of GBS phagocytosed differed up to 23-fold depending on phylogenetic background; isolates possessing spb1 were phagocytosed more than isolates lacking spb1. Comparing WT GBS and isogenic spb1-deficient mutants showed WT was phagocytosed better compared to mutants; Spb1 also enhanced intracellular survival as mutants were killed more efficiently. Complementation of mutants restored phagocytosis and resistance to killing in J774A.1 macrophages. Spb1 antiserum revealed surface expression in WT GBS and spatial distribution relative to capsular polysaccharide. spb1 did not affect macrophage nitric oxide and TNF-alpha responses; differences in phagocytosis did not correlate with N-acetyl d-glucosamine (from GBS cell-wall) according to enzyme-linked lectin-sorbent assay. Together, these findings support a role for phylogenetic lineage and Spb1 in opsonin-independent phagocytosis and intracellular survival of GBS in J774A.1 macrophages.

Surgical fusion of early onset severe scoliosis increases survival in Rett syndrome: A cohort study

Aim Scoliosis is a common co-morbidity in Rett syndrome and spinal fusion may be recommended if severe. We investigated the impact of spinal fusion on survival and risk of severe lower respiratory tract infection in Rett syndrome. Method Data were ascertained from hospital medical records, the Australian Rett Syndrome Database, a longitudinal and population-based registry, and from the Australian Institute of Health and Welfare National Death Index database. Cox regression and generalized estimating equation models were used to estimate the effects of spinal surgery on survival and severe respiratory infection respectively in 140 females who developed severe scoliosis (Cobb angle ≥45°) before adulthood. Results After adjusting for mutation type and age of scoliosis onset, the rate of death was lower in the surgery group (hazard ratio [HR] 0.30, 95% confidence interval [CI] 0.12–0.74; p=0.009) compared to those without surgery. Rate of death was particularly reduced for those with early onset scoliosis (HR 0.17, 95% CI 0.06–0.52; p=0.002). There was some evidence to suggest that spinal fusion was associated with a reduction in risk of severe respiratory infection among those with early onset scoliosis (risk ratio 0.41, 95% CI 0.16–1.03; p=0.06). Interpretation With appropriate cautions, spinal fusion confers an advantage to life expectancy in Rett syndrome.

Complete cytogenetic response and major molecular response as surrogate outcomes for overall survival in first-line treatment of chronic myelogenous leukemia: A case study for technology appraisal on the basis of surrogate outcomes evidence

Objectives In 2012, the National Institute for Health and Care Excellence assessed dasatinib, nilotinib, and standard-dose imatinib as first-line treatment of chronic phase chronic myelogenous leukemia (CML). Licensing of these alternative treatments was based on randomized controlled trials assessing complete cytogenetic response (CCyR) and major molecular response (MMR) at 12 months as primary end points. We use this case study to illustrate the validation of CCyR and MMR as surrogate outcomes for overall survival in CML and how this evidence was used to inform National Institute for Health and Care Excellence’s recommendation on the public funding of these first-line treatments for CML. Methods We undertook a systematic review and meta-analysis to quantify the association between CCyR and MMR at 12 months and overall survival in patients with chronic phase CML. We estimated life expectancy by extrapolating long-term survival from the weighted overall survival stratified according to the achievement of CCyR and MMR. Results Five studies provided data on the observational association between CCyR or MMR and overall survival. Based on the pooled association between CCyR and MMR and overall survival, our modeling showed comparable predicted mean duration of survival (21–23 years) following first-line treatment with imatinib, dasatinib, or nilotinib. Conclusions This case study illustrates the consideration of surrogate outcome evidence in health technology assessment. Although it is often recommended that the acceptance of surrogate outcomes be based on randomized controlled trial data demonstrating an association between the treatment effect on both the surrogate outcome and the final outcome, this case study shows that policymakers may be willing to accept a lower level of evidence (i.e., observational association).

Survival analysis of time-to-event data in respiratory health research studies

This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the Kaplan–Meier survival plot and the Cox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time-varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.

The role of MicroRNAs in stress response in the resurrection plant Tripogon loliiformis

Research in this thesis focussed on the improvement of agricultural crops in increasing water use efficiency that impacts global crop productivity. The study identified key genetic regulatory mechanisms that the resurrection plant Tripogon loliiformis utilises to tolerate desiccation. Due to the conserved nature of the pathways involved, this information can be transferred for the enhancement of drought tolerance and water use efficiency in agricultural crops. Specifically this study used high throughput sequencing, microscopy and plant transformation to further the understanding of post-transcriptional regulatory mechanisms. It was shown that T. loliiformis uses microRNAs to regulate pro-survival autophagy pathways to tolerate desiccation.

Development of salinity tolerance in rice by constitutive-overexpression of genes involved in the regulation of programmed cell death

Environmental factors contribute to over 70% of crop yield losses worldwide. Of these drought and salinity are the most significant causes of crop yield reduction. Rice is an important staple crop that feeds more than half of the world’s population. However among the agronomically important cereals rice is the most sensitive to salinity. In the present study we show that exogenous expression of anti-apoptotic genes from diverse origins, AtBAG4 (Arabidopsis), Hsp70 (Citrus tristeza virus) and p35 (Baculovirus), significantly improves salinity tolerance in rice at the whole plant level. Physiological, biochemical and agronomical analyses of transgenic rice expressing each of the anti-apoptotic genes subjected to salinity treatment demonstrated traits associated with tolerant varieties including, improved photosynthesis, membrane integrity, ion and ROS maintenance systems, growth rate, and yield components. Moreover, FTIR analysis showed that the chemical composition of salinity-treated transgenic plants is reminiscent of non-treated, unstressed controls. In contrast, wild type and vector control plants displayed hallmark features of stress, including pectin degradation upon subjection to salinity treatment. Interestingly, despite their diverse origins, transgenic plants expressing the anti-apoptotic genes assessed in this study displayed similar physiological and biochemical characteristics during salinity treatment thus providing further evidence that cell death pathways are conserved across broad evolutionary kingdoms. Our results reveal that anti-apoptotic genes facilitate maintenance of metabolic activity at the whole plant level to create favorable conditions for cellular survival. It is these conditions that are crucial and conducive to the plants ability to tolerate/adapt to extreme environments.