[Show abstract][Hide abstract] ABSTRACT: Current clinical practice in cancer stratifies patients based on tumour histology to determine prognosis. Molecular profiling has been hailed as the path towards personalised care, but molecular data are still typically analysed independently of known clinical information. Conventional clinical and histopathological data, if used, are added only to improve a molecular prediction, placing a high burden upon molecular data to be informative in isolation. Here, we develop a novel Monte Carlo analysis to evaluate the usefulness of data assemblages. We applied our analysis to varying assemblages of clinical data and molecular data in an ovarian cancer dataset, evaluating their ability to discriminate one-year progression-free survival (PFS) and three-year overall survival (OS). We found that Cox proportional hazard regression models based on both data types together provided greater discriminative ability than either alone. In particular, we show that proteomics data assemblages that alone were uninformative (p = 0.245 for PFS, p = 0.526 for OS) became informative when combined with clinical information (p = 0.022 for PFS, p = 0.048 for OS). Thus, concurrent analysis of clinical and molecular data enables exploitation of prognosis-relevant information that may not be accessible from independent analysis of these data types. Most current clinical oncology practice stratifies patients based on tumour histology to inform prognosis. Molecular analyses are heralded as the solution for personalised medicine 1 , yet most such analyses view patients in segmented populations, either comparing molecular signatures across clinical and pathological categories 2–6 or evaluating clinicopathological characteristics of clusters based upon molecular features 7–10. This tends to underestimate the proven value of clinical and pathological information. When clinical and pathological information is used in combination with molecular analyses, it is typically in a post-hoc manner, that is, attempting to improve a molecular model with clinical information 11. This places a high burden on molecular data, as it is required to be useful in isolation before the sequential addition of clinicopathological data. Here, we investigate a more integrative approach, using ovarian cancer as an example, where we analyse molecular and clinical data in concert. We take the point of view that molecular data should not replace traditional clinical pathology, but instead add to it. We show the added value of molecular data in ovarian cancer, a disease with particularly poor prognosis: despite often initially good responses to chemotherapy, 65% die by 5 years 12,13. There are no
[Show abstract][Hide abstract] ABSTRACT: Triple negative, resistant or metastatic disease are major factors in breast cancer mortality, warranting novel approaches. Carbonic anhydrase IX (CAIX) is implicated in survival, migration and invasion of breast cancer cells and inhibition provides an innovative therapeutic strategy. The efficacy of 5 novel ureido-substituted sulfamate CAIX inhibitors were assessed in increasingly complex breast cancer models, including cell lines in normoxia and hypoxia, 3D spheroids and an ex-vivo explant model utilizing fresh biopsy tissue from different breast cancer subtypes. CAIX expression was evaluated in a tissue microarray (TMA) of 92 paired lymph node and primary breast cancers and 2 inhibitors were appraised in vivo using MDA-MB-231 xenografts. FC11409B, FC9398A, FC9403, FC9396A and S4 decreased cell proliferation and migration and inhibited 3D spheroid invasion. S4, FC9398A and FC9403A inhibited or prevented invasion into collagen. FC9403A significantly reversed established invasion whilst FC9398A and DTP348 reduced xenograft growth. TMA analysis showed increased CAIX expression in triple negative cancers. These data establish CAIX inhibition as a relevant therapeutic goal in breast cancer, targeting the migratory, invasive, and metastatic potential of this disease. The use of biopsy tissue suggests efficacy against breast cancer subtypes, and should provide a useful tool in drug testing against invasive cancers.
[Show abstract][Hide abstract] ABSTRACT: Differential mRNA expression studies implicitly assume that changes in mRNA expression have biological meaning, most likely mediated by corresponding changes in protein levels. Yet studies into mRNA-protein correspondence have shown notoriously poor correlation between mRNA and protein expression levels, creating concern for inferences from only mRNA expression data. However, none of these studies have examined in particular differentially expressed mRNA. Here, we examined this question in an ovarian cancer xenograft model. We measured protein and mRNA expression for twenty-nine genes in four drug-treatment conditions and in untreated controls. We identified mRNAs differentially expressed between drug-treated xenografts and controls, then analysed mRNA-protein expression correlation across a five-point time-course within each of the four experimental conditions. We evaluated correlations between mRNAs and their protein products for mRNAs differentially expressed within an experimental condition compared to those that are not. We found that differentially expressed mRNAs correlate significantly better with their protein product than non-differentially expressed mRNAs. This result increases confidence for the use of differential mRNA expression for biological discovery in this system, as well as providing optimism for the usefulness of inferences from mRNA expression in general.
[Show abstract][Hide abstract] ABSTRACT: Conventional two dimensional (2D) monolayer cell culture has been considered the ‘gold standard’ technique for in vitro cellular experiments. However, the need for a model that better mimics the three dimensional (3D) architecture of tissue in vivo has led to the development of Multicellular Tumour Spheroids (MTS) as a 3D tissue culture model. To some extent MTS mimic the environment of in vivo tumours where, for example, oxygen and nutrient gradients develop, protein changes and cells form a spherical structure with regions of proliferation, senescence and necrosis. This review focuses on the development of techniques for chemical analysis of MTS as a tool for understanding in vivo tumours and a platform for more effective drug and therapy discovery. While traditional monolayer techniques can be translated to 3D models, these often fail to provide the desired spatial resolution and z-penetration for live cell imaging. More recently developed techniques for overcoming these problems will be discussed with particular reference to advances in instrument technology for achieving the increased spatial resolution and imaging depth required.
The Analyst 04/2015; 140(12). DOI:10.1039/C5AN00524H · 4.11 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Introduction:
The aim of this study was to validate a molecular expression signature [cell cycle progression (CCP) score] that identifies patients with a higher risk of cancer-related death after surgical resection of early stage (I-II) lung adenocarcinoma in a large patient cohort and evaluate the effectiveness of combining CCP score and pathological stage for predicting lung cancer mortality.
Formalin-fixed paraffin-embedded surgical tumor samples from 650 patients diagnosed with stage I and II adenocarcinoma who underwent definitive surgical treatment without adjuvant chemotherapy were analyzed for 31 proliferation genes by quantitative real-time polymerase chain reaction. The prognostic discrimination of the expression score was assessed by Cox proportional hazards analysis using 5-year lung cancer-specific death as primary outcome.
The CCP score was a significant predictor of lung cancer-specific mortality above clinical covariates [hazard ratio (HR) = 1.46 per interquartile range (95% confidence interval = 1.12–1.90; p = 0.0050)]. The prognostic score, a combination of CCP score and pathological stage, was a more significant indicator of lung cancer mortality risk than pathological stage in the full cohort (HR = 2.01; p = 2.8 × 10−11) and in stage I patients (HR = 1.67; p = 0.00027). Using the 85th percentile of the prognostic score as a threshold, there was a significant difference in lung cancer survival between low-risk and high-risk patient groups (p = 3.8 × 10−7).
This study validates the CCP score and the prognostic score as independent predictors of lung cancer death in patients with early stage lung adenocarcinoma treated with surgery alone. Patients with resected stage I lung adenocarcinoma and a high prognostic score may be candidates for adjuvant therapy to reduce cancer-related mortality.
Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 11/2014; 10(1). DOI:10.1097/JTO.0000000000000365 · 5.28 Impact Factor
[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.
Journal of Biotechnology 11/2014; DOI:10.1016/j.jbiotec.2014.09.027 · 2.87 Impact Factor
[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. DOI:10.1042/BST20140073 · 3.19 Impact Factor