[Show abstract][Hide abstract] ABSTRACT: Chromatin undergoes structural changes in response to extracellular and environmental signals. We observed changes in nuclear morphology in cancer tissue biopsied after chemotherapy and hypothesised that these DNA damage-induced changes are mediated by histone deacetylases (HDACs). Nuclear morphological changes in cell lines (PE01 and PE04 models) and a xenograft model (OV1002) were measured in response to platinum chemotherapy by image analysis of nuclear texture. HDAC2 expression increased in PEO1 cells treated with cisplatin at 24h, which was accompanied by increased expression of heterochromatin protein 1 (HP1). HDAC2 and HP1 expression were also increased after carboplatin treatment in the OV1002 carboplatin-sensitive xenograft model but not in the insensitive HOX424 model. Expression of DNA damage response pathways (pBRCA1, γH2AX, pATM, pATR) showed time-dependent changes after cisplatin treatment. HDAC2 knockdown by siRNA reduced HP1 expression, induced DNA double strand breaks (DSB) measured by γH2AX, and interfered with the activation of DNA damage response induced by cisplatin. Furthermore, HDAC2 depletion affected γH2AX foci formation, cell cycle distribution, and apoptosis triggered by cisplatin, and was additive to the inhibitory effect of cisplatin in cell lines. By inhibiting expression of HDAC2, reversible alterations in chromatin patterns during cisplatin treatment were observed. These results demonstrate quantifiable alterations in nuclear morphology after chemotherapy, and implicate HDAC2 in higher order chromatin changes and cellular DNA damage responses in ovarian cancer cells in vitro and in vivo.
[Show abstract][Hide abstract] ABSTRACT: The field of pathology is rapidly transforming from a semiquantitative and empirical science toward a big data discipline. Large data sets from across multiple omics fields may now be extracted from a patient's tissue sample. Tissue is, however, complex, heterogeneous, and prone to artifact. A reductionist view of tissue and disease progression, which does not take this complexity into account, may lead to single biomarkers failing in clinical trials. The integration of standardized multi-omics big data and the retention of valuable information on spatial heterogeneity are imperative to model complex disease mechanisms. Mathematical modeling through systems pathology approaches is the ideal medium to distill the significant information from these large, multi-parametric, and hierarchical data sets. Systems pathology may also predict the dynamical response of disease progression or response to therapy regimens from a static tissue sample. Next-generation pathology will incorporate big data with systems medicine in order to personalize clinical practice for both prognostic and predictive patient care.
No preview · Article · Dec 2015 · Methods in molecular biology (Clifton, N.J.)
[Show abstract][Hide abstract] ABSTRACT: Selecting colorectal cancer (CRC) patients likely to respond to therapy remains a clinical challenge. The objectives of this study were to establish which genes were differentially expressed with respect to treatment sensitivity and relate this to copy number in a panel of 15 CRC cell lines. Copy number variations of the identified genes were assessed in a cohort of CRCs. IC50’s were measured for 5-fluorouracil, oxaliplatin, and BEZ-235, a PI3K/mTOR inhibitor. Cell lines were profiled using array comparative genomic hybridisation, Illumina gene expression analysis, reverse phase protein arrays, and targeted sequencing of KRAS hotspot mutations. Frequent gains were observed at 2p, 3q, 5p, 7p, 7q, 8q, 12p, 13q, 14q, and 17q and losses at 2q, 3p, 5q, 8p, 9p, 9q, 14q, 18q, and 20p. Frequently gained regions contained EGFR, PIK3CA, MYC, SMO, TRIB1, FZD1, and BRCA2, while frequently lost regions contained FHIT and MACROD2. TRIB1 was selected for further study. Gene enrichment analysis showed that differentially expressed genes with respect to treatment response were involved in Wnt signalling, EGF receptor signalling, apoptosis, cell cycle, and angiogenesis. Stepwise integration of copy number and gene expression data yielded 47 candidate genes that were significantly correlated. PDCD6 was differentially expressed in all three treatment responses. Tissue microarrays were constructed for a cohort of 118 CRC patients and TRIB1 and MYC amplifications were measured using fluorescence in situ hybridisation. TRIB1 and MYC were amplified in 14.5% and 7.4% of the cohort, respectively, and these amplifications were significantly correlated (p≤0.0001). TRIB1 protein expression in the patient cohort was significantly correlated with pERK, Akt, and Caspase 3 expression. In conclusion, a set of candidate predictive biomarkers for 5-fluorouracil, oxaliplatin, and BEZ235 are described that warrant further study. Amplification of the putative oncogene TRIB1 has been described for the first time in a cohort of CRC patients.
[Show abstract][Hide abstract] ABSTRACT: Background:
Glandular metastases (GMs) (pancreas, breast, parotid, thyroid, or contralateral adrenal) are rare in metastatic clear cell renal cell carcinoma (mccRCC). In a multicenter study we have assessed outcome from mccRCC with or without GMs.
Patients and methods:
Patients with mccRCC and GM or non-GM (NGM) at first presentation of mccRCC, treated at 9 European centers (5 French, 3 UK, and 1 Belgian centers) between January 2004 and October 2013, were retrospectively analyzed. Association between overall survival (OS) and site of metastases was assessed using the log-rank test for univariate analysis and the chi-square test for multivariable Cox regression.
In all, 138 patients with GM mccRCC and 420 with NGM mccRCC were included; 37.2% patients with GM had Memorial Sloan-Kettering Cancer Center (MSKCC)-favorable risk vs. 18% NGM patients; 10.7% patients with GM had MSKCC-poor risk vs. 27% NGM patients (P<0.0001). Median interval from metastases to treatment was 4.2 months (range: 0-221.3mo). Median OS was 61.5 months (51.4-81.6mo) for GM and 37.4 months (31.3-42mo) for NGM (hazard ratio [HR] = 1.7; 95% CI = 1.3-2.2, P<0.001). In univariate OS analysis, age, delay between initial diagnosis and metastases, MSKCC, bone/lung metastases, and GM or NGM group were significant parameters (P<0.001). In multivariate analysis, adjusted according to MSKCC risk group, NGM vs. GM was a strong prognostic factor (HR = 1.4; 95% CI = 1.0-1.8, P=0.026); bone or liver metastases were also significant (HR = 1.3; 95% CI = 1.1-1.7, P<0.02; HR = 1.4; 95% CI = 1.1-1.7, P<0.02, respectively). Even in patients without bone or liver metastases, GM status was significant (HR = 1.8; 95% CI = 1.2-2.7, P<0.004).
This large retrospective study shows that the presence of at least 1 GM site in development of mccRCC was associated with a significantly longer OS. The presence of GMs vs. NGM disease was an independent prognostic factor for survival irrespective of the presence or absence of bone or liver metastases. This finding could affect daily practice in which patients with mccRCC and GMs should receive more aggressive treatment with a potential for long-term survival. The causal mechanisms for this improved prognosis in GM mccRCC would be evaluated in translational studies.
No preview · Article · Dec 2015 · Urologic Oncology
[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.
Full-text · Article · Nov 2015 · Scientific Reports
[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.
Full-text · Article · Jun 2015 · Scientific Reports
[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.
[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.
Full-text · Article · Nov 2014 · Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer
[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.
Full-text · Article · Nov 2014 · Journal of Biotechnology
[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.