An improved model of tumour-immune system interactions

The immune system plays an important role in defending the body against tumours and other threats. Currently, mechanisms involved in immune system interactions with tumour cells are not fully understood. Here we develop a mathematical tool that can be used in aiding to address this shortfall in understanding. This paper de- scribes a hybrid cellular automata model of the interaction between a growing tumour and cells of the innate and specific immune system including the effects of chemokines that builds on previous models of tumour-immune system interactions. In particular, the model is focused on the response of immune cells to tumour cells and how the dynamics of the tumour cells change due to the immune system of the host. We present results and predictions of in silico experiments including simulations of Kaplan-Meier survival-like curves.

Zoledronic acid preserves bone structure and increases survival but does not limit tumour incidence in a prostate cancer bone metastasis model

Background The bisphosphonate, zoledronic acid (ZOL), can inhibit osteoclasts leading to decreased osteoclastogenesis and osteoclast activity in bone. Here, we used a mixed osteolytic/osteoblastic murine model of bone-metastatic prostate cancer, RM1(BM), to determine how inhibiting osteolysis with ZOL affects the ability of these cells to establish metastases in bone, the integrity of the tumour-bearing bones and the survival of the tumour-bearing mice. Methods The model involves intracardiac injection for arterial dissemination of the RM1(BM) cells in C57BL/6 mice. ZOL treatment was given via subcutaneous injections on days 0, 4, 8 and 12, at 20 and 100 µg/kg doses. Bone integrity was assessed by micro-computed tomography and histology with comparison to untreated mice. The osteoclast and osteoblast activity was determined by measuring serum tartrate-resistant acid phosphatase 5b (TRAP 5b) and osteocalcin, respectively. Mice were euthanased according to predetermined criteria and survival was assessed using Kaplan Meier plots. Findings Micro-CT and histological analysis showed that treatment of mice with ZOL from the day of intracardiac injection of RM1(BM) cells inhibited tumour-induced bone lysis, maintained bone volume and reduced the calcification of tumour-induced endochondral osteoid material. ZOL treatment also led to a decreased serum osteocalcin and TRAP 5b levels. Additionally, treated mice showed increased survival compared to vehicle treated controls. However, ZOL treatment did not inhibit the cells ability to metastasise to bone as the number of bone-metastases was similar in both treated and untreated mice. Conclusions ZOL treatment provided significant benefits for maintaining the integrity of tumour-bearing bones and increased the survival of tumour bearing mice, though it did not prevent establishment of bone-metastases in this model. From the mechanistic view, these observations confirm that tumour-induced bone lysis is not a requirement for establishment of these bone tumours.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.

Molecular characterisation of environmental enterococci derived from water samples and assessment of associated public health hazards

Enterococci are versatile Gram-positive bacteria that can survive under extreme conditions. Most enterococci are non-virulent and found in the gastrointestinal tract of humans and animals. Other strains are opportunistic pathogens that contribute to a large number of nosocomial infections globally. Epidemiological studies demonstrated a direct relationship between the density of enterococci in surface waters and the risk of swimmer-associated gastroenteritis. The distribution of infectious enterococcal strains from the hospital environment or other sources to environmental water bodies through sewage discharge or other means, could increase the prevalence of these strains in the human population. Environmental water quality studies may benefit from focusing on a subset of Enterococcus spp. that are consistently associated with sources of faecal pollution such as domestic sewage, rather than testing for the entire genus. E. faecalis and E. faecium are potentially good focal species for such studies, as they have been consistently identified as the dominant Enterococcus spp. in human faeces and sewage. On the other hand enterococcal infections are predominantly caused by E. faecalis and E. faecium. The characterisation of E. faecalis and E. faecium is important in studying their population structures, particularly in environmental samples. In developing and implementing rapid, robust molecular genotyping techniques, it is possible to more accurately establish the relationship between human and environmental enterococci. Of particular importance, is to determine the distribution of high risk enterococcal clonal complexes, such as E. faecium clonal complex 17 and E. faecalis clonal complexes 2 and 9 in recreational waters. These clonal complexes are recognized as particularly pathogenic enterococcal genotypes that cause severe disease in humans globally. The Pimpama-Coomera watershed is located in South East Queensland, Australia and was investigated in this study mainly because it is used intensively for agriculture and recreational purposes and has a strong anthropogenic impact. The primary aim of this study was to develop novel, universally applicable, robust, rapid and cost effective genotyping methods which are likely to yield more definitive results for the routine monitoring of E. faecalis and E. faecium, particularly in environmental water sources. To fullfill this aim, new genotyping methods were developed based on the interrogation of highly informative single nucleotide polymorphisms (SNPs) located in housekeeping genes of both E. faecalis and E. faecium. SNP genotyping was successfully applied in field investigations of the Coomera watershed, South-East Queensland, Australia. E. faecalis and E. faecium isolates were grouped into 29 and 23 SNP profiles respectively. This study showed the high longitudinal diversity of E. faecalis and E. faecium over a period of two years, and both human-related and human-specific SNP profiles were identified. Furthermore, 4.25% of E. faecium strains isolated from water was found to correspond to the important clonal complex-17 (CC17). Strains that belong to CC17 cause the majority of hospital outbreaks and clinical infections globally. Of the six sampling sites of the Coomera River, Paradise Point had the highest number of human-related and human-specific E. faecalis and E. faecium SNP profiles. The secondary aim of this study was to determine the antibiotic-resistance profiles and virulence traits associated with environmental E. faecalis and E. faecium isolates compared to human pathogenic E. faecalis and E. faecium isolates. This was performed to predict the potential health risks associated with coming into contact with these strains in the Coomera watershed. In general, clinical isolates were found to be more resistant to all the antibiotics tested compared to water isolates and they harbored more virulence traits. Multi-drug resistance was more prevalent in clinical isolates (71.18% of E. faecalis and 70.3 % of E. faecium) compared to water isolates (only 5.66 % E. faecium). However, tetracycline, gentamicin, ciprofloxacin and ampicillin resistance was observed in water isolates. The virulence gene esp was the most prevalent virulence determinant observed in clinical isolates (67.79% of E. faecalis and 70.37 % of E. faecium), and this gene has been described as a human-specific marker used for microbial source tracking (MST). The presence of esp in water isolates (16.36% of E. faecalis and 19.14% of E. faecium) could be indicative of human faecal contamination in these waterways. Finally, in order to compare overall gene expression between environmental and clinical strains of E. faecalis, a comparative gene hybridization study was performed. The results of this investigation clearly demonstrated the up-regulation of genes associated with pathogenicity in E. faecalis isolated from water. The expression study was performed at physiological temperatures relative to ambient temperatures. The up-regulation of virulence genes demonstrates that environmental strains of E. faecalis can pose an increased health risk which can lead to serious disease, particularly if these strains belong to the virulent CC17 group. The genotyping techniques developed in this study not only provide a rapid, robust and highly discriminatory tool to characterize E. faecalis and E. faecium, but also enables the efficient identification of virulent enterococci that are distributed in environmental water sources.

Chemical variability of groundwater samples collected from a Coal Seam Gas exploration well, Maramarua, New Zealand

A pilot study has produced 31 groundwater samples from a coal seam gas (CSG) exploration well located in Maramarua, New Zealand. This paper describes sources of CSG water chemistry variations, and makes sampling and analytical recommendations to minimize these variations. The hydrochemical character of these samples is studied using factor analysis, geochemical modelling, and a sparging experiment. Factor analysis unveils carbon dioxide (CO2) degassing as the principal cause of sample variation (about 33%). Geochemical modelling corroborates these results and identifies minor precipitation of carbonate minerals with degassing. The sparging experiment confirms the effect of CO2 degassing by showing a steady rise in pH while maintaining constant alkalinity. Factor analysis correlates variations in the major ion composition (about 17%) to changes in the pumping regime and to aquifer chemistry variations due to cation exchange reactions with argillaceous minerals. An effective CSG water sampling program can be put into practice by measuring pH at the well head and alkalinity at the laboratory; these data can later be used to calculate the carbonate speciation at the time the sample was collected. In addition, TDS variations can be reduced considerably if a correct drying temperature of 180°C is consistently implemented.

Kallikrein 14 is down-regulated by androgen receptor signalling and harbours genetic variation that is associated with prostate tumour aggressiveness

Kallikrein 14 (KLK14) has been proposed as a useful prognostic marker in prostate cancer, with expression reported to be associated with tumour characteristics such as higher stage and Gleason score. KLK14 tumour expression has also shown the potential to predict prostate cancer patients at risk of disease recurrence after radical prostatectomy. The KLKs are a remarkably hormone-responsive family of genes, although detailed studies of androgen regulation of KLK14 in prostate cancer have not been undertaken to date. Using in vitro studies, we have demonstrated that unlike many other prostatic KLK genes that are strictly androgen responsive, KLK14 is more broadly expressed and inversely androgen regulated in prostate cancer cells. Given these results and evidence that KLK14 may play a role in prostate cancer prognosis, we also investigated whether common genetic variants in the KLK14 locus are associated with risk and/or aggressiveness of prostate cancer in approximately 1200 prostate cancer cases and 1300 male controls. Of 41 single nucleotide polymorphisms assessed, three were associated with higher Gleason score (≥7): rs17728459 and rs4802765, both located upstream of KLK14, and rs35287116, which encodes a p.Gln33Arg substitution in the KLK14 signal peptide region. Our findings provide further support for KLK14 as a marker of prognosis in prostate cancer.

Paradoxical roles of tumour necrosis factor-alpha in prostate cancer biology

Tumour necrosis factor (TNF) is a pleiotropic cytokine with dual roles in cancer biology including prostate cancer (PCa). On the one hand, there is evidence that it stimulates tumour angiogenesis, is involved in the initiation of PCa from an androgen-dependent to a castrate resistant state, plays a role in epithelial to mesenchymal plasiticity, and may contribute to the aberrant regulation of eicosanoid pathways. On the other hand, TNF has also been reported to inhibit neovascularisation, induce apoptosis of PCa cells, and stimulate anti-tumour immunity. Much of the confusion surrounding its seemingly paradoxical roles in cancer biology stems from the dependence of its effects on the biological model within which TNF is investigated. This review will address some of these issues, and also discuss on the therapeutic implications.

mCOPA: analysis of heterogeneous features in cancer expression data

Background Cancer outlier profile analysis (COPA) has proven to be an effective approach to analyzing cancer expression data, leading to the discovery of the TMPRSS2 and ETS family gene fusion events in prostate cancer. However, the original COPA algorithm did not identify down-regulated outliers, and the currently available R package implementing the method is similarly restricted to the analysis of over-expressed outliers. Here we present a modified outlier detection method, mCOPA, which contains refinements to the outlier-detection algorithm, identifies both over- and under-expressed outliers, is freely available, and can be applied to any expression dataset. Results We compare our method to other feature-selection approaches, and demonstrate that mCOPA frequently selects more-informative features than do differential expression or variance-based feature selection approaches, and is able to recover observed clinical subtypes more consistently. We demonstrate the application of mCOPA to prostate cancer expression data, and explore the use of outliers in clustering, pathway analysis, and the identification of tumour suppressors. We analyse the under-expressed outliers to identify known and novel prostate cancer tumour suppressor genes, validating these against data in Oncomine and the Cancer Gene Index. We also demonstrate how a combination of outlier analysis and pathway analysis can identify molecular mechanisms disrupted in individual tumours. Conclusions We demonstrate that mCOPA offers advantages, compared to differential expression or variance, in selecting outlier features, and that the features so selected are better able to assign samples to clinically annotated subtypes. Further, we show that the biology explored by outlier analysis differs from that uncovered in differential expression or variance analysis. mCOPA is an important new tool for the exploration of cancer datasets and the discovery of new cancer subtypes, and can be combined with pathway and functional analysis approaches to discover mechanisms underpinning heterogeneity in cancers

Circulating tumour cells, their role in metastasis and their clinical utility in lung cancer

Circulating tumour cells (CTCs) have attracted much recent interest in cancer research as a potential biomarker and as a means of studying the process of metastasis. It has long been understood that metastasis is a hallmark of malignancy, and conceptual theories on the basis of metastasis from the nineteenth century foretold the existence of a tumour "seed" which is capable of establishing discrete tumours in the "soil" of distant organs. This prescient "seed and soil" hypothesis accurately predicted the existence of CTCs; microscopic tumour fragments in the blood, at least some of which are capable of forming metastases. However, it is only in recent years that reliable, reproducible methods of CTC detection and analysis have been developed. To date, the majority of studies have employed the CellSearch™ system (Veridex LLC), which is an immunomagnetic purification method. Other promising techniques include microfluidic filters, isolation of tumour cells by size using microporous polycarbonate filters and flow cytometry-based approaches. While many challenges still exist, the detection of CTCs in blood is becoming increasingly feasible, giving rise to some tantalizing questions about the use of CTCs as a potential biomarker. CTC enumeration has been used to guide prognosis in patients with metastatic disease, and to act as a surrogate marker for disease response during therapy. Other possible uses for CTC detection include prognostication in early stage patients, identifying patients requiring adjuvant therapy, or in surveillance, for the detection of relapsing disease. Another exciting possible use for CTC detection assays is the molecular and genetic characterization of CTCs to act as a "liquid biopsy" representative of the primary tumour. Indeed it has already been demonstrated that it is possible to detect HER2, KRAS and EGFR mutation status in breast, colon and lung cancer CTCs respectively. In the course of this review, we shall discuss the biology of CTCs and their role in metastagenesis, the most commonly used techniques for their detection and the evidence to date of their clinical utility, with particular reference to lung cancer.

Cellular model systems to study the tumor biological role of kallikrein-related peptidases in ovarian and prostate cancer

Since the identification of the gene family of kallikrein related peptidases (KLKs), their function has been robustly studied at the biochemical level. In vitro biochemical studies have shown that KLK proteases are involved in a number of extracellular processes that initiate intracellular signaling pathways by hydrolysis, as reviewed in Chapters 8, 9, and 15, Volume 1. These events have been associated with more invasive phenotypes of ovarian, prostate, and other cancers. Concomitantly, aberrant expression of KLKs has been associated with poor prognosis of patients with ovarian and prostate cancer (Borgoño and Diamandis, 2004; Clements et al., 2004; Yousef and Diamandis, 2009), with prostate-specific antigen (PSA, KLK3) being a long standing, clinically employed biomarker for prostate cancer (Lilja et al., 2008). Data generated from patient samples in clinical studies, alongwith biochemical activity, suggests that KLKs function in the development and progression of these diseases. To bridge the gap between their function at the molecular level and the clinical need for efficacious treatment and prognostic biomarkers, functional assessment at the in vitro cellular level, using various culture models, is increasing, particularly in a three-dimensional (3D) context (Abbott, 2003; Bissell and Radisky, 2001; Pampaloni et al., 2007; Yamada and Cukierman, 2007).

Possible comet samples : The NASA Cosmic Dust Program

Beginning in 1974, a limited effort to collect extraterrestrial dust samples from the stratosphere using impactors mounted on NASA U-2 aircraft was initiated at NASA Ames Research Center (1). Subsequent studies (e.g. 1-9) have clearly established an extraterrestrial origin for some of the material. Attrition of comets is considered to be one of the potential sources of extraterrestrial dust(1,5). Additionally, some of the particles appear to represent a type of primitive material not represented in meteorite collections. In order to provide a greater availability of these samples to the scientific community, NASA-Johnson Space Center (JSC) began in May of 1981 a program dedicated to the systematic collection and curation of cosmic dust for scientific investigation. Collections were made at 18 to 20 km altitude by means of collectors mounted under the wings of a WB57F. When the aircraft reaches operating altitude, the collector plates (impactors) are extended into the ambient airstream with the collection surface normal to the airflow. To prevent particles from bouncing off the surface, the impactors are coated with a film of high viscosity silicone oil. The impactors are sealed in canisters to minimize contamination when not collecting.

Aerosol mass spectrometric analysis of the chemical composition of non- refractory PM1 samples from school environments in Brisbane, Australia

Long term exposure to vehicle emissions has been associated with harmful health effects. Children are amongst the most susceptible group and schools represent an environment where they can experience significant exposure to vehicle emissions. However, there are limited studies on children’s exposure to vehicle emissions in schools. The aim of this study was to quantify the concentration of organic aerosol and in particular, vehicle emissions that children are exposed to during school hours. Therefore an Aerodyne compact time-of-flight aerosol mass spectrometer (TOF-AMS) was deployed at five urban schools in Brisbane, Australia. The TOF-AMS enabled the chemical composition of the non- refractory (NR-PM1) to be analysed with a high temporal resolution to assess the concentration of vehicle emissions and other organic aerosols during school hours. At each school the organic fraction comprised the majority of NR-PM1 with secondary organic aerosols as the main constitute. At two of the schools, a significant source of the organic aerosol (OA) was slightly aged vehicle emissions from nearby highways. More aged and oxidised OA was observed at the other three schools, which also recorded strong biomass burning influences. Primary emissions were found to dominate the OA at only one school which had an O:C ratio of 0.17, due to fuel powered gardening equipment used near the TOF-AMS. The diurnal cycle of OA concentration varied between schools and was found to be at a minimum during school hours. The major organic component that school children were exposed to during school hours was secondary OA. Peak exposure of school children to HOA occurred during school drop off and pick up times. Unless a school is located near major roads, children are exposed predominately to regional secondary OA as opposed to local emissions during schools hours in urban environments.

Changes in markers of muscle damage, inflammation and HSP70 after an Ironman triathlon race

We investigated the effects of an Ironman triathlon race on markers of muscle damage, inflammation and heat shock protein 70 (HSP70). Nine well-trained male triathletes (mean +/- SD age 34 +/- 5 years; VO(2peak) 66.4 ml kg(-1) min(-1)) participated in the 2004 Western Australia Ironman triathlon race (3.8 km swim, 180 km cycle, 42.2 km run). We assessed jump height, muscle strength and soreness, and collected venous blood samples 2 days before the race, within 30 min and 14-20 h after the race. Plasma samples were analysed for muscle proteins, acute phase proteins, cytokines, heat shock protein 70 (HSP70), and clinical biochemical variables related to dehydration, haemolysis, liver and renal functions. Muscular strength and jump height decreased significantly (P < 0.05) after the race, whereas muscle soreness and the plasma concentrations of muscle proteins increased. The cytokines interleukin (IL)-1 receptor antagonist, IL-6 and IL-10, and HSP70 increased markedly after the race, while IL-12p40 and granulocyte colony-stimulating factor (G-CSF) were also elevated. IL-4, IL-1beta and tumour necrosis factor-alpha did not change significantly, despite elevated C-reactive protein and serum amyloid protein A on the day after the race. Plasma creatinine, uric acid and total bilirubin concentrations and gamma-glutamyl transferase activity also changed after the race. In conclusion, despite evidence of muscle damage and an acute phase response after the race, the pro-inflammatory cytokine response was minimal and anti-inflammatory cytokines were induced. HSP70 is released into the circulation as a function of exercise duration.

A tumour-derived mutant allele of XRCC2 preferentially suppresses homologous recombination at DNA replication forks

Homologous recombination repair (HRR) is required for both the repair of DNA double strand breaks (DSBs) and the maintenance of the integrity of DNA replication forks. To determine the effect of a mutant allele of the RAD51 paralog XRCC2 (342delT) found in an HRR-defective tumour cell line, 342delT was introduced into HRR proficient cells containing a recombination reporter substrate. In one set of transfectants, expression of 342delT conferred sensitivity to thymidine and mitomycin C and suppressed HRR induced at the recombination reporter by thymidine but not by DSBs. In a second set of transfectants, the expression of 342delT was accompanied by a decreased level of the full-length XRCC2. These cells were defective in the induction of HRR by either thymidine or DSBs. Thus 342delT suppresses recombination induced by thymidine in a dominant negative manner while recombination induced by DSBs appears to depend upon the level of XRCC2 as well as the expression of the mutant XRCC2 allele. These results suggest that HRR pathways responding to stalled replication forks or DSBs are genetically distinguishable. They further suggest a critical role for XRCC2 in HRR at replication forks, possibly in the loading of RAD51 onto gapped DNA.