[Show abstract][Hide abstract] ABSTRACT: Cells are constantly exposed to Reactive Oxygen Species (ROS) produced both endogenously to meet phys- iological requirements and from exogenous sources. While endogenous ROS are considered as important signalling molecules, high uncontrollable ROS are detrimental. It is unclear how cells can achieve a bal- ance between maintaining physiological redox homeostasis and robustly activate the antioxidant system to remove exogenous ROS. We have utilised a Systems Biology approach to understand how this robust adaptive system fulfils homeostatic requirements of maintaining steady-state ROS and growth rate, while undergoing rapid readjustment under challenged conditions. Using a panel of human ovarian and normal cell lines, we experimentally quantified and established interrelationships between key elements of ROS homeostasis. The basal levels of NRF2 and KEAP1 were cell line specific and maintained in tight corre- lation with their growth rates and ROS. Furthermore, perturbation of this balance triggered cell specific kinetics of NRF2 nuclear–cytoplasmic relocalisation and sequestration of exogenous ROS. Our experi- mental data were employed to parameterise a mathematical model of the NRF2 pathway that elucidated key response mechanisms of redox regulation and showed that the dynamics of NRF2-H2O2 regulation defines a relationship between half-life, total and nuclear NRF2 level and endogenous H2O2 that is cell line specific.
[Show abstract][Hide abstract] ABSTRACT: Proliferation is coupled metabolic competence and environmental circumstance of a cell. Reactive oxygen species (ROS) are modulators of intracellular signalling that govern cellular proliferation. High uncontrollable ROS lead to mutation and acceleration of disease, ageing, or death. Anticancer radio/chemotherapy depends on ROS to induce cytotoxicity. Paradoxically, adaptation to ROS promotes proliferation and therapeutic resistance in cancers. Thus ROS manipulation could control proliferation depending on individual and heterogeneous net redox status which requires accurate means of quantification.
We followed and characterise the proliferation of normal and a panel of ovarian cancer cell lines under basal and perturbed redox status. We quantified the dynamics of ROS and the NRF2-KEAP 1 redox sensor system in these cells.
Intracellular ROS levels correlated with H2O2 during exponential expansion, as well as with growth constants (μ). The H2O2 levels correlated with the constitutive total NRF2 and KEAP as did NRF2 and KEAP1 levels. N-acetylcysteine slowed the proliferation of cancer cells. Increased hierarchical pro-oxidant sequestration observed with cancer cells only. H2O2 influenced NRF2, KEAP1, and proliferation. It is feasible to mathematically fit and model proliferation behaviour of cells.
[Show abstract][Hide abstract] ABSTRACT: Flavonoids are a large group of ubiquitous polyphenolic secondary metabolites in plants with a wide range
of properties, including a widely reported anti-cancer effect. The present review focuses on the different
known mechanisms partaking in said anti-tumour effects, with particular emphasis on breast cancer. Their
structure and reactivity allows flavonoids to work as antioxidant agents and phyto-oestrogens, modulating
oestrogen signalling and metabolism to induce an overall anti-proliferative response. Other effects include
the ability of flavonoids to modulate the CYP1 (cytochrome P450 1) and ABC (ATP-binding cassette) protein
families, involved in carcinogenesis and drug delivery respectively. They can also induce apoptosis and
cell cycle arrest and regulate other signalling pathways involved in the development and progression of
cancer. In conclusion, there is accumulating evidence on the versatility of flavonoids and the numerous
activities contributing to their anti-tumour effect. This complex, yet effective, mechanism of action of
flavonoids, together with their interesting pharmacological properties, has set the basis for their potential
application in breast and other cancers. This rationale has led to the current interest in the application
of flavonoids, including clinical trials currently underway and the development of novel flavonoids with
improved properties, which hold great promise for tackling breast cancer.
Biochemical Society Transactions 08/2014; 42(4):1017-1023. · 2.59 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Tumour budding (TB), lymphatic vessel density (LVD) and lymphatic vessel invasion (LVI) have shown promise as prognostic factors in colorectal cancer (CRC) but reproducibility using conventional histopathology is challenging. We demonstrate image analysis methodology to quantify the histopathological features which could permit standardisation across institutes and aid risk stratification of Dukes B patients.
Journal of translational medicine. 06/2014; 12(1):156.
[Show abstract][Hide abstract] ABSTRACT: There is a lack of biomarkers to predict outcome with targeted therapy in metastatic clear cell renal cancer (mccRCC). This may be because dynamic molecular changes occur with therapy.
To explore if dynamic, targeted-therapy-driven molecular changes correlate with mccRCC outcome.
Multiple frozen samples from primary tumours were taken from sunitinib-naïve (n=22) and sunitinib-treated mccRCC patients (n=23) for protein analysis. A cohort (n=86) of paired, untreated and sunitinib/pazopanib-treated mccRCC samples was used for validation. Array comparative genomic hybridisation (CGH) analysis and RNA interference (RNAi) was used to support the findings.
Three cycles of sunitinib 50mg (4 wk on, 2 wk off).
Reverse phase protein arrays (training set) and immunofluorescence automated quantitative analysis (validation set) assessed protein expression.
Differential expression between sunitinib-naïve and treated samples was seen in 30 of 55 proteins (p<0.05 for each). The proteins B-cell CLL/lymphoma 2 (BCL2), mutL homolog 1 (MLH1), carbonic anhydrase 9 (CA9), and mechanistic target of rapamycin (mTOR) (serine/threonine kinase) had both increased intratumoural variance and significant differential expression with therapy. The validation cohort confirmed increased CA9 expression with therapy. Multivariate analysis showed high CA9 expression after treatment was associated with longer survival (hazard ratio: 0.48; 95% confidence interval, 0.26-0.87; p=0.02). Array CGH profiles revealed sunitinib was associated with significant CA9 region loss. RNAi CA9 silencing in two cell lines inhibited the antiproliferative effects of sunitinib. Shortcomings of the study include selection of a specific protein for analysis, and the specific time points at which the treated tissue was analysed.
CA9 levels increase with targeted therapy in mccRCC. Lower CA9 levels are associated with a poor prognosis and possible resistance, as indicated by the validation cohort.
Drug treatment of advanced kidney cancer alters molecular markers of treatment resistance. Measuring carbonic anhydrase 9 levels may be helpful in determining which patients benefit from therapy.
[Show abstract][Hide abstract] ABSTRACT: The receptor tyrosine kinases (RTKs) are key drivers of cancer progression and targets for drug therapy. A major challenge in anti-RTK treatment is the dependence of drug effectiveness on co-expression of multiple RTKs which defines resistance to single drug therapy. Reprogramming of the RTK network leading to alteration in RTK co-expression in response to drug intervention is a dynamic mechanism of acquired resistance to single drug therapy in many cancers. One route to overcome this resistance is combination therapy. We describe the results of a joint in silico, in vitro, and in vivo investigations on the efficacy of trastuzumab, pertuzumab and their combination to target the HER2 receptors. Computational modelling revealed that these two drugs alone and in combination differentially suppressed RTK network activation depending on RTK co-expression. Analyses of mRNA expression in SKOV3 ovarian tumour xenograft showed up-regulation of HER3 following treatment. Considering this in a computational model revealed that HER3 up-regulation reprograms RTK kinetics from HER2 homodimerisation to HER3/HER2 heterodimerisation. The results showed synergy of the trastuzumab and pertuzumab combination treatment of the HER2 overexpressing tumour can be due to an independence of the combination effect on HER3/HER2 composition when it changes due to drug-induced RTK reprogramming.
[Show abstract][Hide abstract] ABSTRACT: Drug resistance, de novo and acquired, pervades cellular signaling networks (SNs) from one signaling motif to another as a result of cancer progression and/or drug intervention. This resistance is one of the key determinants of efficacy in targeted anti-cancer drug therapy. Although poorly understood, drug resistance is already being addressed in combination therapy by selecting drug targets where SN sensitivity increases due to combination components or as a result of de novo or acquired mutations. Additionally, successive drug combinations have shown low resistance potential. To promote a rational, systematic development of combination therapies, it is necessary to establish the underlying mechanisms that drive the advantages of combination therapies, and design methods to determine drug targets for combination regimens. Based on a joint systems analysis of cellular SN response and its sensitivity to drug action and oncogenic mutations, we describe an in silico method to analyze the targets of drug combinations. Our method explores mechanisms of sensitizing the SN through a combination of two drugs targeting vertical signaling pathways. We propose a paradigm of SN response customization by one drug to both maximize the effect of another drug in combination and promote a robust therapeutic response against oncogenic mutations. The method was applied to customize the response of the ErbB/PI3K/PTEN/AKT pathway by combination of drugs targeting HER2 receptors and proteins in the down-stream pathway. The results of a computational experiment showed that the modification of the SN response from hyperbolic to smooth sigmoid response by manipulation of two drugs in combination leads to greater robustness in therapeutic response against oncogenic mutations determining cancer heterogeneity. The application of this method in drug combination co-development suggests a combined evaluation of inhibition effects together with the capability of drug combinations to suppress resistance mechanisms before they become clinically manifest.
[Show abstract][Hide abstract] ABSTRACT: Proteomic profiling of the estrogen/tamoxifen-sensitive MCF-7 cell line and its partially sensitive (MCF-7/LCC1) and fully resistant (MCF-7/LCC9) variants was performed to identify modifiers of endocrine sensitivity in breast cancer. Analysis of the expression of 120 paired phosphorylated and non-phosphorylated epitopes in key oncogenic and tumor suppressor pathways revealed that STAT1 and several phosphorylated epitopes (phospho-STAT1(Tyr701) and phospho-STAT3(Ser727)) were differentially expressed between endocrine resistant and parental controls, confirmed by qRT-PCR and western blotting. The STAT1 inhibitor EGCG was a more effective inhibitor of the endocrine resistant MCF-7/LCC1 and MCF-7/LCC9 lines than parental MCF-7 cells, while STAT3 inhibitors Stattic and WP1066 were equally effective in endocrine-resistant and parental lines. The effects of the STAT inhibitors were additive, rather than synergistic, when tested in combination with tamoxifen in vitro. Expression of STAT1 and STAT3 were measured by quantitative immunofluorescence in invasive breast cancers and matched lymph nodes. When lymph node expression was compared to its paired primary breast cancer expression, there was greater expression of cytoplasmic STAT1 (∼3.1 fold), phospho-STAT3(Ser727) (∼1.8 fold), and STAT5 (∼1.5 fold) and nuclear phospho-STAT3(Ser727) (∼1.5 fold) in the nodes. Expression levels of STAT1 and STAT3 transcript were analysed in 550 breast cancers from publicly available gene expression datasets (GSE2990, GSE12093, GSE6532). When treatment with tamoxifen was considered, STAT1 gene expression was nearly predictive of distant metastasis-free survival (DMFS, log-rank p = 0.067), while STAT3 gene expression was predictive of DMFS (log-rank p<0.0001). Analysis of STAT1 and STAT3 protein expression in a series of 546 breast cancers also indicated that high expression of STAT3 protein was associated with improved survival (DMFS, p = 0.006). These results suggest that STAT signaling is important in endocrine resistance, and that STAT inhibitors may represent potential therapies in breast cancer, even in the resistant setting.
PLoS ONE 01/2014; 9(4):e94226. · 3.53 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: DNA methylation is widely studied in the context of cancer. However, the rediscovery of 5-hydroxymethylation of DNA adds a new layer of complexity to understanding the epigenetic basis of development and disease, including carcinogenesis. There have been significant advances in techniques for the detection of 5-hydroxymethylcytosine and, with this, greater insight into the distribution, regulation and function of this mark, which are reviewed here. Better understanding of the associated pathways involved in regulation of, and by, 5-hydroxymethylcytosine may give promise to new therapeutic targets. We discuss evidence to support the view of 5-hydroxymethylcytosine as a unique and dynamic mark of cellular state. These 5-hydroxymethylcytosine profiles may offer optimism for the development of diagnostic, prognostic and predictive biomarkers.
[Show abstract][Hide abstract] ABSTRACT: Histopathology, the examination of an architecturally artefactual, two dimensional, static image remains a potent tool allowing diagnosis and empirical expectation of prognosis. Considerable optimism exists that the advent of molecular genetic testing and other biomarker strategies will improve or even replace this ancient technology. A number of biomarkers add considerable value for prediction of whether a treatment will work. This short review argues that a systems medicine approach to pathology will not seek to replace traditional pathology, but rather augment it. Systems approaches need to incorporate quantitative morphological, protein, mRNA and DNA. A significant challenge for clinical implementation of systems pathology is how to optimise information available from tissue, which is frequently sub-optimal in quality and amount, and yet generate useful predictive models which work. The transition of histopathology to systems pathophysiology and the use of multiscale datasets ushers in a new era in diagnosis, prognosis and prediction based on analysis of human tissue. This article is protected by copyright. All rights reserved.
[Show abstract][Hide abstract] ABSTRACT: Tissue microarrays (TMAs) allow multiplexed analysis of tissue samples and are frequently used to estimate biomarker protein expression in tumour biopsies. TMA Navigator (www.tmanavigator.org) is an open access web application for analysis of TMA data and related information, accommodating categorical, semi-continuous and continuous expression scores. Non-biological variation, or batch effects, can hinder data analysis and may be mitigated using the ComBat algorithm, which is incorporated with enhancements for automated application to TMA data. Unsupervised grouping of samples (patients) is provided according to Gaussian mixture modelling of marker scores, with cardinality selected by Bayesian information criterion regularization. Kaplan-Meier survival analysis is available, including comparison of groups identified by mixture modelling using the Mantel-Cox log-rank test. TMA Navigator also supports network inference approaches useful for TMA datasets, which often constitute comparatively few markers. Tissue and cell-type specific networks derived from TMA expression data offer insights into the molecular logic underlying pathophenotypes, towards more effective and personalized medicine. Output is interactive, and results may be exported for use with external programs. Private anonymous access is available, and user accounts may be generated for easier data management.
Nucleic Acids Research 06/2013; · 8.81 Impact Factor