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In JoVE (2)
- Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
- The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Other Publications (38)
- Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology
- The Journal of Steroid Biochemistry and Molecular Biology
- European Heart Journal
- Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
- Nature Reviews. Clinical Oncology
- Cancer Research
- Proceedings of the National Academy of Sciences of the United States of America
- Molecular Cancer Research : MCR
- Discovery Medicine
- Expert Opinion on Biological Therapy
- Breast Cancer Research : BCR
- Methods in Molecular Biology (Clifton, N.J.)
- Cancer Research
- International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society
- Breast Cancer Research : BCR
- European Journal of Cancer (Oxford, England : 1990)
- BMC Cancer
- European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences
- Nature Reviews. Urology
- Clinical Cancer Research : an Official Journal of the American Association for Cancer Research
- Clinical & Experimental Metastasis
- Breast Cancer Research and Treatment
- PloS One
- Cellular Signalling
- Breast Cancer Research and Treatment
- Cellular Signalling
- PloS One
- Journal of Clinical Pathology
- PloS One
- Endocrine-related Cancer
- Cellular Signalling
Articles by Dana Faratian in JoVE
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Dana Faratian1, Jason Christiansen2, Mark Gustavson2, Christine Jones2, Christopher Scott2, InHwa Um1, David J. Harrison1
1Division of Pathology, University of Edinburgh, 2HistoRx Inc.
Here we describe a method to quantify molecular heterogeneity in histological sections of tumor material using quantitative immunofluorescence, image analysis, and a statistical measure of heterogeneity. The method is intended for use in clinical biomarker development and analysis.
The Use of Reverse Phase Protein Arrays (RPPA) to Explore Protein Expression Variation within Individual Renal Cell Cancers
Fiach C. O'Mahony1, Jyoti Nanda1, Alexander Laird1, Peter Mullen2, Helen Caldwell3, Ian M. Overton4, Lel Eory4, Marie O'Donnell1,5, Dana Faratian6, Thomas Powles7, David J. Harrison1,2, Grant D. Stewart1
1Edinburgh Urological Cancer Group, University of Edinburgh, 2School of Medicine, University of St Andrews, 3Division of Pathology, University of Edinburgh, 4MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, 5Department of Pathology, Western General Hospital, 6Breakthrough Breast Cancer Research Unit, University of Edinburgh, 7St Bartholomew's Cancer Institute, Experimental Cancer Medicine Centre, Queen Mary University of London
RPPA enables the protein expression of hundreds of samples, printed on nitrocellulose slides to be interrogated simultaneously, using fluorescently labelled antibodies. This technique has been applied to study the effect of drug treatment heterogeneity within clear cell renal carcinoma.
Other articles by Dana Faratian on PubMed
Estrogen-independent Proliferation is Present in Estrogen-receptor HER2-positive Primary Breast Cancer After Neoadjuvant Letrozole
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology. Jul, 2006 | Pubmed ID: 16754938
To investigate the impact of human epidermal growth factor receptor (HER) 1 and HER2 gene amplification on endocrine therapy responsiveness, a fluorescence in situ hybridization (FISH) study was conducted on tumor samples from 305 postmenopausal patients with stage II and III estrogen receptor (ER) -positive (ER > or = 10%) breast cancers treated on two independent neoadjuvant endocrine therapy trials.
The Journal of Steroid Biochemistry and Molecular Biology. Aug-Sep, 2007 | Pubmed ID: 17604618
In patients with hormone receptor positive DCIS tamoxifen reduces recurrence rates by almost 50%. Few data are available with aromatase inhibitors from randomised studies. In the ATAC study there were three DCIS lesions in the anastrozole arm and four in the tamoxifen arm in the women with ER positive invasive cancer. In the MA17 study which randomised patients to up to 5 years of letrozole or placebo there was only one DCIS event in the contralateral breast in patients taking letrozole and five on placebo. There were also four patients in this study who had DCIS in the conserved breast on placebo and none in the letrozole treated group. The few clinical data that are available therefore suggest the aromatase inhibitors are likely to be effective in DCIS. A histological review of a study of 206 postmenopausal women with invasive oestrogen receptor positive breast cancer who were randomised as part of a 14 day preoperative study to receive 2.5mg of letrozole or 1mg of anastrozole identified 27 patients with 28 pairs of tumours in whom there was sufficient ER positive DCIS in invasive cancer in the initial core biopsy and in the subsequent surgery specimen, to evaluate for PgR activity and proliferation. Within the DCIS both aromatase inhibitors significantly reduced PgR expression and both drugs also produced a significant fall in proliferation. There was a moderate degree of agreement between the fall in PgR in both the invasive cancer and DCIS (Kappa=0.5; p=0.0013) and between the fall in proliferation and between the invasive and in situ components (correlation coefficient=0.68; p<0.001). This study has shown significant effects of aromatase inhibitors on DCIS indicating that these agents are therapeutically active in this condition.
Pharmacogenomics. Dec, 2007 | Pubmed ID: 18086005
Breast cancer is an excellent disease paradigm for systems biology. At the time of writing, a simple PubMed search for 'breast cancer' returns nearly 99,000 hits, compared with 51,000 or 16,000 for lung and colon cancer respectively, even though in terms of mortality lung and colon cancers are responsible for four-times more deaths per annum in the UK. These figures reflect the effort and money invested in breast cancer research. It is because breast cancer research is data-rich, crowded and competitive (often perceived as a negative for clinical and basic scientific researchers) that it is such an appealing area of research for systems biologists. For systems biologists, data is currency, and they scavenge diverse and multilayered datasets, from biochemical through genomics and transcriptomics to proteomics, in order to populate computational models. We discuss how dynamic modeling can be used as a tool for predicting responses to new and existing drugs, and what needs to be done to make systems biology a useful tool in the clinic.
European Heart Journal. Dec, 2008 | Pubmed ID: 18952612
Although the mechanism is unclear, exposure to traffic-derived air pollution is a trigger for acute myocardial infarction (MI). The aim of this study is to investigate the effect of diesel exhaust inhalation on platelet activation and thrombus formation in men.
Membranous and Cytoplasmic Staining of Ki67 is Associated with HER2 and ER Status in Invasive Breast Carcinoma
Histopathology. Jan, 2009 | Pubmed ID: 19207951
Membranous and cytoplasmic Ki67 immunoreactivity has recently been observed in a number of histopathological entities, but frequency of occurrence and relationship to prognosis in more common cancers have not been described. The aim was to describe the pattern and frequency of membranous/cytoplasmic Ki67 in a cohort of invasive breast carcinomas, and their associations with grade, HER2 amplification and oestrogen receptor (ER) expression.
Histopathology. Feb, 2009 | Pubmed ID: 19236522
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research. Apr, 2009 | Pubmed ID: 19293255
To identify therapeutic targets in ovarian clear cell carcinomas, a chemoresistant and aggressive type of ovarian cancer.
Rapid Screening of Tissue Microarrays for Her-2 Fluorescence in Situ Hybridization Testing is an Accurate, Efficient and Economic Method of Providing an Entirely in Situ Hybridization-based Her-2 Testing Service
Histopathology. Mar, 2009 | Pubmed ID: 19309394
Fluorescence in situ hybridization (FISH) testing is the 'gold standard' method for Her-2 status assessment in breast cancer patients, yet is only employed in about 30% of tests carried out because of cost and labour considerations. We have previously described tissue microarray (TMA)-based testing to eliminate cost constraints, and now describe a rapid screening approach to reduce time spent testing.
Nature Reviews. Clinical Oncology. Aug, 2009 | Pubmed ID: 19581910
The wealth of morphological, histological, and molecular data from human cancers available to pathologists means that pathology is poised to become a truly quantitative systems science. By measuring morphological parameters such as tumor stage and grade, and by measuring molecular biomarkers such as hormone receptor status, pathologists have sometimes accurately predicted what will happen to a patient's tumor. While 'omic' technologies have seemingly improved prognostication and prediction, some molecular 'signatures' are not useful in clinical practice because of the failure to independently validate these approaches. Many associations between gene 'signatures' and clinical response are correlative rather than mechanistic, and such associations are poor predictors of how cellular biochemical networks will behave in perturbed, diseased cells. Using systems biology, the dynamics of reactions in cells and the behavior between cells can be integrated into models of cancer. The challenge is how to integrate multiple data from the clinic into tractable models using mathematical models and systems biology, and how to make the resultant model sufficiently robust to be of practical use. We discuss the difficulties in using mathematics to model cancer, and review some approaches that may be used to allow systems biology to be successfully applied in the clinic.
Systems Biology Reveals New Strategies for Personalizing Cancer Medicine and Confirms the Role of PTEN in Resistance to Trastuzumab
Cancer Research. Aug, 2009 | Pubmed ID: 19638581
Resistance to targeted cancer therapies such as trastuzumab is a frequent clinical problem not solely because of insufficient expression of HER2 receptor but also because of the overriding activation states of cell signaling pathways. Systems biology approaches lend themselves to rapid in silico testing of factors, which may confer resistance to targeted therapies. Inthis study, we aimed to develop a new kinetic model that could be interrogated to predict resistance to receptor tyrosine kinase (RTK) inhibitor therapies and directly test predictions in vitro and in clinical samples. The new mathematical model included RTK inhibitor antibody binding, HER2/HER3 dimerization and inhibition, AKT/mitogen-activated protein kinase cross-talk, and the regulatory properties of PTEN. The model was parameterized using quantitative phosphoprotein expression data from cancer cell lines using reverse-phase protein microarrays. Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V). When measured in cancer cell lines, PTEN expression predicts sensitivity to anti-HER2 therapy; furthermore, this quantitative measurement is more predictive of response (relative risk, 3.0; 95% confidence interval, 1.6-5.5; P < 0.0001) than other pathway components taken in isolation and when tested by multivariate analysis in a cohort of 122 breast cancers treated with trastuzumab. For the first time, a systems biology approach has successfully been used to stratify patients for personalized therapy in cancer and is further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti-HER2 therapies.
Residual Breast Cancers After Conventional Therapy Display Mesenchymal As Well As Tumor-initiating Features
Proceedings of the National Academy of Sciences of the United States of America. Aug, 2009 | Pubmed ID: 19666588
Some breast cancers have been shown to contain a small fraction of cells characterized by CD44(+)/CD24(-/low) cell-surface antigen profile that have high tumor-initiating potential. In addition, breast cancer cells propagated in vitro as mammospheres (MSs) have also been shown to be enriched for cells capable of self-renewal. In this study, we have defined a gene expression signature common to both CD44(+)/CD24(-/low) and MS-forming cells. To examine its clinical significance, we determined whether tumor cells surviving after conventional treatments were enriched for cells bearing this CD44(+)/CD24(-/low)-MS signature. The CD44(+)/CD24(-/low)-MS signature was found mainly in human breast tumors of the recently identified "claudin-low" molecular subtype, which is characterized by expression of many epithelial-mesenchymal-transition (EMT)-associated genes. Both CD44(+)/CD24(-/low)-MS and claudin-low signatures were more pronounced in tumor tissue remaining after either endocrine therapy (letrozole) or chemotherapy (docetaxel), consistent with the selective survival of tumor-initiating cells posttreatment. We confirmed an increased expression of mesenchymal markers, including vimentin (VIM) in cytokeratin-positive epithelial cells metalloproteinase 2 (MMP2), in two separate sets of postletrozole vs. pretreatment specimens. Taken together, these data provide supporting evidence that the residual breast tumor cell populations surviving after conventional treatment may be enriched for subpopulations of cells with both tumor-initiating and mesenchymal features. Targeting proteins involved in EMT may provide a therapeutic strategy for eliminating surviving cells to prevent recurrence and improve long-term survival in breast cancer patients.
Modulation of HER3 is a Marker of Dynamic Cell Signaling in Ovarian Cancer: Implications for Pertuzumab Sensitivity
Molecular Cancer Research : MCR. Sep, 2009 | Pubmed ID: 19737968
This study was designed to evaluate the expression of HER receptors as a marker of sensitivity to the humanized anti-HER2 monoclonal antibody pertuzumab in ovarian cancer cells. In a recent clinical trial, low levels of HER3 mRNA have been shown to associate with pertuzumab response when combined with gemcitabine. We sought to define how pertuzumab modulated HER expression levels in ovarian cancer using cell line models to better understand differential and dynamic receptor expression in therapeutic response. Changes in HER3 mRNA expression were also assessed in pertuzumab-treated xenografts. HER3 mRNA and, to a lesser extent, HER2, were down-regulated after stimulation both with heregulin-beta1 and epidermal growth factor in a range of ovarian cancer cell lines either growth sensitive or growth resistant to pertuzumab. Pertuzumab reversed this down-regulation and the magnitude of the reversal correlated with pertuzumab sensitivity. The change in HER3 mRNA expression correlated inversely to how much the extracellular signal-regulated kinase and phosphoinositide 3-kinase pathways were dynamically activated with stimulation. Finally, up-regulation of HER3 mRNA was found in cancer xenografts treated with pertuzumab. We conclude that HER3 mRNA is down-regulated by both heregulin-beta1 and epidermal growth factor activation. This suggests that in some tumors, low HER3 mRNA expression is driven by, or dependent on, growth factor. HER3 mRNA expression is effectively reversed in pertuzumab-sensitive tumors. These data are consistent with low HER3 mRNA identifying a pertuzumab-sensitive phenotype.
Discovery Medicine. Aug, 2009 | Pubmed ID: 19788873
Cancer is a complex and heterogeneous disease which changes over time, and in the face of therapeutic intervention. Single tissue biomarkers, while partially successful in helping us understand which patients will respond to therapy, cannot hope to capture this amazing complexity. Systems pathology, which combines measurements made on tissues with new mathematical modeling approaches, permits the testing of new agents and biomarkers in silico through computational analysis. These approaches help us to refine pathological measurements and improve decision making about therapies for clinical trial planning and ultimately personalized therapy.
Onkologie. Nov, 2009 | Pubmed ID: 19887864
Automated Image Analysis for High-throughput Quantitative Detection of ER and PR Expression Levels in Large-scale Clinical Studies: the TEAM Trial Experience
Histopathology. Nov, 2009 | Pubmed ID: 19912364
Routine immunohistochemistry is regarded as a semiquantitative method for the evaluation of in situ protein expression. Analysis of tissue biomarkers in large clinical trials is central to the development of novel targeted approaches to therapy, requires the analysis of tens of thousands of data points, and frequently makes use of high-throughput analysis of tissue microarrays (TMAs). The aim of this study was to investigate the potential of image analysis for accurate and reproducible quantitative evaluation of biomarkers.
Expert Opinion on Biological Therapy. Jul, 2010 | Pubmed ID: 20465533
Pertuzumab is a humanized monoclonal antibody that inhibits human epidermal growth factor receptor 2 (HER2) heterodimerization and has demonstrated clinical activity against both breast and ovarian cancer. To date, it is the most extensively studied HER2 inhibitor in ovarian cancer.
Dynamic Changes in Gene Expression in Vivo Predict Prognosis of Tamoxifen-treated Patients with Breast Cancer
Breast Cancer Research : BCR. 2010 | Pubmed ID: 20569502
Tamoxifen is the most widely prescribed anti-estrogen treatment for patients with estrogen receptor (ER)-positive breast cancer. However, there is still a need for biomarkers that reliably predict endocrine sensitivity in breast cancers and these may well be expressed in a dynamic manner.
Methods in Molecular Biology (Clifton, N.J.). 2010 | Pubmed ID: 20824475
Cancer is a complex and heterogeneous disease, not only at a genetic and biochemical level, but also at a tissue, organism, and population level. Multiple data streams, from reductionist biochemistry in vitro to high-throughput "-omics" from clinical material, have been generated with the hope that they encode useful information about phenotype and, ultimately, tumour behaviour in response to drugs. While these data stand alone in terms of the biology they represent, there is the enticing prospect that if incorporated into systems biology models, they can help understand complex systems behaviour and provide a predictive framework as an additional tool in understanding how tumours change and respond to treatment over time. Since these biological data are heterogeneous and frequently qualitative rather than quantitative, at the present time a single systems biology approach is unlikely to be effective; instead, different computational and mathematical approaches should be tailored to different types of data, and to each other, in order to test and re-test hypotheses. In time, these models might converge and result in usable tractable models which accurately represent human cancer. Likewise, biologists and clinicians need to understand what the requirements of systems biology are so that compatible data are produced for computational modelling. In this review, we describe some theoretical approaches (data-driven and process-driven) and experimental methodologies which are being used in cancer research and the clinical context where they might be applied.
Tyrosine Phosphorylation Profiling Reveals the Signaling Network Characteristics of Basal Breast Cancer Cells
Cancer Research. Nov, 2010 | Pubmed ID: 20861192
To identify therapeutic targets and prognostic markers for basal breast cancers, breast cancer cell lines were subjected to mass spectrometry-based profiling of protein tyrosine phosphorylation events. This revealed that luminal and basal breast cancer cells exhibit distinct tyrosine phosphorylation signatures that depend on pathway activation as well as protein expression. Basal breast cancer cells are characterized by elevated tyrosine phosphorylation of Met, Lyn, EphA2, epidermal growth factor receptor (EGFR), and FAK, and Src family kinase (SFK) substrates such as p130Cas. SFKs exert a prominent role in these cells, phosphorylating key regulators of adhesion and migration and promoting tyrosine phosphorylation of the receptor tyrosine kinases EGFR and Met. Consistent with these observations, SFK inhibition attenuated cellular proliferation, survival, and motility. Basal breast cancer cell lines exhibited differential responsiveness to small molecule inhibitors of EGFR and Met that correlated with the degree of target phosphorylation, and reflecting kinase coactivation, inhibiting two types of activated network kinase (e.g., EGFR and SFKs) was more effective than single agent approaches. FAK signaling enhanced both proliferation and invasion, and Lyn was identified as a proinvasive component of the network that is associated with a basal phenotype and poor prognosis in patients with breast cancer. These studies highlight multiple kinases and substrates for further evaluation as therapeutic targets and biomarkers. However, they also indicate that patient stratification based on expression/activation of drug targets, coupled with use of multi-kinase inhibitors or combination therapies, may be required for effective treatment of this breast cancer subgroup.
Higher Incidence of Isolated Brain Metastases in Ovarian Cancer Patients with Previous Early Breast Cancer
International Journal of Gynecological Cancer : Official Journal of the International Gynecological Cancer Society. Dec, 2010 | Pubmed ID: 21370594
The pathogenesis of brain metastasis as a relatively rare complication of epithelial ovarian cancer is poorly understood. Some observations suggest that brain metastases from ovarian cancer are becoming more common and that ovarian cancers, which metastasize to the brain, may have a different biological pattern.
Phosphoprotein Pathway Profiling of Ovarian Carcinoma for the Identification of Potential New Targets for Therapy
European Journal of Cancer (Oxford, England : 1990). Jun, 2011 | Pubmed ID: 21334202
Advances in predicting responses to therapies in ovarian cancer have not matched progress seen in other solid-organ tumours: ovarian cancer remains a poor-prognosis disease. There has been a paradigm shift in molecular therapeutics away from targeting individual molecules to whole biological pathways. The aim of this study was to quantitatively measure the activation state of druggable oncogenic pathways by generating a phosphoprotein profile in cancer tissues, in order to establish associations with clinicopathological parameters and to identify treatment groups for targeted therapy. In total we analysed the expression of ten phosphoproteins within eight signalling pathways (PI3K, MAPK, β-catenin, STAT, NFκB, ER, cell cycle and DNA damage response), proliferation (phospho-histone H3 and Ki67) and apoptosis (activated caspase 3), in two independent cohorts of ovarian cancers using quantitative immunofluorescence image analysis. Data were analysed by unsupervised and K-means clustering to determine new biologically relevant groups. Expression of markers of the five main pathways deregulated by mutation or copy number changes was different between histological subtypes. Four main clusters with distinct phosphoprotein profiles were identified, which were significantly associated with survival in univariate analysis, and which had distinct patterns of pathway expression reproducible between clinical cohorts. These pathway profiles suggest novel therapeutic regimens for the treatment of ovarian cancer, such as MAPK-inhibition in serous or clear cell carcinomas, or combined inhibition of STAT, NFκB and WNT signalling.
GnRH Receptor Activation Competes at a Low Level with Growth Signaling in Stably Transfected Human Breast Cell Lines
BMC Cancer. 2011 | Pubmed ID: 22051164
Gonadotrophin releasing hormone (GnRH) analogs lower estrogen levels in pre-menopausal breast cancer patients. GnRH receptor (GnRH-R) activation also directly inhibits the growth of certain cells. The applicability of GnRH anti-proliferation to breast cancer was therefore analyzed.
Model-based Global Sensitivity Analysis As Applied to Identification of Anti-cancer Drug Targets and Biomarkers of Drug Resistance in the ErbB2/3 Network
European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences. Nov, 2011 | Pubmed ID: 22085636
High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a refining tool in combinatorial anti-cancer drug discovery.
Nature Reviews. Urology. May, 2011 | Pubmed ID: 21487387
The incidence of renal cell carcinoma (RCC) is increasing and outcomes remain poor. One-third of patients with localized disease will relapse, and 5-year survival for patients with metastatic disease is less than 10%. No molecular test is currently available to identify which patients who have undergone 'curative' surgery will relapse, and which patients will respond to targeted therapy. Some well characterized biochemical pathways, such as those associated with von Hippel-Lindau disease, are aberrantly regulated in RCC and are associated with histological subtype, but the understanding of these pathways contributes little to the clinical management of patients with RCC. Gene expression and sequencing studies have increased our understanding of the genetic basis of the disease but have failed to establish any unified classification to improve molecular stratification or to predict which patients are likely to relapse or respond to targeted therapy. Instead, they have served to highlight that RCC is heterogeneous at histological, morphological, and molecular levels, and that novel approaches are required to resolve the complexity of RCC prognostication and prediction of treatment response.
Trastuzumab and Pertuzumab Produce Changes in Morphology and Estrogen Receptor Signaling in Ovarian Cancer Xenografts Revealing New Treatment Strategies
Clinical Cancer Research : an Official Journal of the American Association for Cancer Research. Jul, 2011 | Pubmed ID: 21571868
The aim of this study was to investigate the antitumor effects of HER2-directed combination therapy in ovarian cancer xenograft models to evaluate their potential. The combinations of trastuzumab and pertuzumab, and trastuzumab and aromatase inhibitor therapy were investigated.
Clinical & Experimental Metastasis. Dec, 2011 | Pubmed ID: 21789718
Epithelial to mesenchymal transition (EMT) occurs in embryogenesis and normal development. It has been predominantly described in vitro and in animal studies, but EMT is also implicated in the progression of many cancers with proposed roles in invasion, metastasis and resistance to treatment. It is closely associated with loss of epithelial-specific protein expression and up-regulation of mesenchymal proteins, but several pathways are implicated in its execution. We explored what are the expression patterns of EMT proteins in human breast cancer. We interrogated two independent cohorts enriched for high-grade, invasive, ductal breast cancers. We used quantitative immunofluorescence to study the expression of key EMT proteins. Statistical associations to define protein profiles were based on Pearson's correlations. E-cadherin down-regulation in breast cancer was associated with β-catenin down-regulation, but not with up-regulation of mesenchymal markers. While EMT-related transcription repressors were expressed in some breast cancers, their expression did not negatively correlate with E-cadherin. Instead, an additional EMT profile was identified, composing Snail and Slug. In conclusion, EMT occurs in human breast cancer in a manner distinct to that seen in vitro. Certain EMT events are uncoupled from E-cadherin down-regulation and may constitute a novel EMT profile, which warrants further exploration.
Co-expression of SNAIL and TWIST Determines Prognosis in Estrogen Receptor-positive Early Breast Cancer Patients
Breast Cancer Research and Treatment. Jul, 2011 | Pubmed ID: 21796367
Epithelial mesenchymal transition (EMT) plays an important role in the development of metastases. One of the hallmarks of EMT is loss of E-cadherin and gain of N-cadherin expression, which are regulated by transcription factors, such as SNAIL, SLUG, and TWIST. We examined the prognostic value of these factors as well as E-cadherin and N-cadherin, in a well-described large cohort of breast cancer patients treated with primary surgery. Analyses were stratified by estrogen receptor (ER) status, because of its crucial role in the regulation of these transcription factors. SNAIL, SLUG, and TWIST expression were examined on a TMA containing 575 breast tumors using immunohistochemistry. Nuclear expression was quantified using a weighted histoscore and classified as high versus low expression, based on the median histoscore. High expression of SNAIL, SLUG, and TWIST was seen in 54, 50, and 50% of tumors, respectively. The level of SNAIL (P = 0.014) and TWIST (P = 0.006) expression was associated with a worse patient relapse-free period, specifically in patients with ER-positive tumors (interaction Cox proportional hazards P = 0.039). Combining both factors resulted in an independent prognostic factor with high discriminative power (both low versus either high: HR 1.15; both low versus both high HR 1.84; P = 0.010). Co-expression of SNAIL-TWIST was associated with low-E-cadherin and high-N-cadherin expression, especially in ER-positive tumors (P = 0.009), suggesting that, through interactions with ER, SNAIL and TWIST may regulate E- and N-cadherin expression, thereby inducing EMT. Our results are indicative that SNAIL and TWIST play a crucial role in EMT through regulation of E- and N-cadherin expression, exclusively in ER-positive breast cancer patients.
Sprouty 2 is an Independent Prognostic Factor in Breast Cancer and May Be Useful in Stratifying Patients for Trastuzumab Therapy
PloS One. 2011 | Pubmed ID: 21909357
Resistance to trastuzumab is a clinical problem, partly due to overriding activation of MAPK/PI3K signalling. Sprouty-family proteins are negative regulators of MAPK/PI3K signalling, but their role in HER2-therapy resistance is unknown.
Compensatory Effects in the PI3K/PTEN/AKT Signaling Network Following Receptor Tyrosine Kinase Inhibition
Cellular Signalling. Feb, 2011 | Pubmed ID: 20951800
Overcoming de novo and acquired resistance to anticancer drugs that target signaling networks is a formidable challenge for drug design and effective cancer therapy. Understanding the mechanisms by which this resistance arises may offer a route to addressing the insensitivity of signaling networks to drug intervention and restore the efficacy of anticancer therapy. Extending our recent work identifying PTEN as a key regulator of Herceptin sensitivity, we present an integrated theoretical and experimental approach to study the compensatory mechanisms within the PI3K/PTEN/AKT signaling network that afford resistance to receptor tyrosine kinase (RTK) inhibition by anti-HER2 monoclonal antibodies. In a computational model representing the dynamics of the signaling network, we define a single control parameter that encapsulates the balance of activities of the enzymes involved in the PI3K/PTEN/AKT cycle. By varying this control parameter we are able to demonstrate both distinct dynamic regimes of behavior of the signaling network and the transitions between those regimes. We demonstrate resistance, sensitivity, and suppression of RTK signals by the signaling network. Through model analysis we link the sensitivity-to-resistance transition to specific compensatory mechanisms within the signaling network. We study this transition in detail theoretically by variation of activities of PTEN, PI3K, AKT enzymes, and use the results to inform experiments that perturb the signaling network using combinatorial inhibition of RTK, PTEN, and PI3K enzymes in human ovarian carcinoma cell lines. We find good alignment between theoretical predictions and experimental results. We discuss the application of the results to the challenges of hypersensitivity of the signaling network to RTK signals, suppression of drug resistance, and efficacy of drug combinations in anticancer therapy.
Breast Cancer Research and Treatment. Feb, 2011 | Pubmed ID: 20358279
In breast cancer, the prognostic impact of COX2 expression varies widely between studies. We examined the prognostic value of COX2 expression in a large cohort of breast cancer patients treated with primary surgery between 1985 and 1994 and explained the variable results of COX2 expression found in the literature. A tissue microarray was constructed of available tumour material, and ER, PgR, HER2, Ki67 and COX2 were examined by immunohistochemistry. Median follow-up was 19 years. Fifty-five percent (n = 369/677) of patients received no systemic treatment. COX2 was scored using a weighted histoscore. Analysis of COX2 expression in two groups based on the median (148; below vs. above) showed an increased hazard ratio (HR) of 1.35 (95% CI 1.05-1.75, P = 0.021) for disease-free survival (DFS) and of 1.39 (95% CI 1.03-1.82, P = 0.016) for overall survival (OS). However, COX2 did not remain independent in multivariate analysis. In patients with hormone receptor positive tumours, COX2 expression had a negative influence on outcome (low vs. high: DFS: HR 1.37, 95% CI 1.07-1.76, P = 0.013). This effect disappeared when endocrine therapy was administered (low vs. high: DFS: HR 0.93, 95% CI 0.51-1.70, P = 0.811) while it remained statistically significant when endocrine therapy was omitted (low vs. high: DFS: HR 1.48, 95% CI 1.12-1.94, P = 0.005). Our results show that COX2 plays a role in hormonal pathways. Our results can explain the results found in previously published studies.
Features of the Reversible Sensitivity-resistance Transition in PI3K/PTEN/AKT Signalling Network After HER2 Inhibition
Cellular Signalling. Feb, 2012 | Pubmed ID: 21996585
Systems biology approaches that combine experimental data and theoretical modelling to understand cellular signalling network dynamics offer a useful platform to investigate the mechanisms of resistance to drug interventions and to identify combination drug treatments. Extending our work on modelling the PI3K/PTEN/AKT signalling network (SN), we analyse the sensitivity of the SN output signal, phospho-AKT, to inhibition of HER2 receptor. We model typical aberrations in this SN identified in cancer development and drug resistance: loss of PTEN activity, PI3K and AKT mutations, HER2 overexpression, and overproduction of GSK3β and CK2 kinases controlling PTEN phosphorylation. We show that HER2 inhibition by the monoclonal antibody pertuzumab increases SN sensitivity, both to external signals and to changes in kinetic parameters of the proteins and their expression levels induced by mutations in the SN. This increase in sensitivity arises from the transition of SN functioning from saturation to non-saturation mode in response to HER2 inhibition. PTEN loss or PIK3CA mutation causes resistance to anti-HER2 inhibitor and leads to the restoration of saturation mode in SN functioning with a consequent decrease in SN sensitivity. We suggest that a drug-induced increase in SN sensitivity to internal perturbations, and specifically mutations, causes SN fragility. In particular, the SN is vulnerable to mutations that compensate for drug action and this may result in a sensitivity-to-resistance transition. The combination of HER2 and PI3K inhibition does not sensitise the SN to internal perturbations (mutations) in the PI3K/PTEN/AKT pathway: this combination treatment provides both synergetic inhibition and may prevent the SN from acquired mutations causing drug resistance. Through combination inhibition treatments, we studied the impact of upstream and downstream interventions to suppress resistance to the HER2 inhibitor in the SN with PTEN loss. Comparison of experimental results of PI3K inhibition in the PTEN upstream pathway with PDK1 inhibition in the PTEN downstream pathway shows that upstream inhibition abrogates resistance to pertuzumab more effectively than downstream inhibition. This difference in inhibition effect arises from the compensatory mechanism of an activation loop induced in the downstream pathway by PTEN loss. We highlight that drug target identification for combination anti-cancer therapy needs to account for the mutation effects on the upstream and downstream pathways.
Histopathology. Jan, 2012 | Pubmed ID: 22168172
The Use of Automated Quantitative Analysis to Evaluate Epithelial-to-mesenchymal Transition Associated Proteins in Clear Cell Renal Cell Carcinoma
PloS One. 2012 | Pubmed ID: 22363672
Epithelial-to-mesenchymal transition (EMT) has recently been implicated in the initiation and progression of renal cell carcinoma (RCC). Some mRNA gene expression studies have suggested a link between the EMT phenotype and poorer clinical outcome from RCC. This study evaluated expression of EMT-associated proteins in RCC using in situ automated quantitative analysis immunofluorescence (AQUA) and compared expression levels with clinical outcome.
Journal of Clinical Pathology. Jul, 2012 | Pubmed ID: 22412045
PloS One. 2012 | Pubmed ID: 22514623
Overexpression of matriptase has been reported in a variety of human cancers and is sufficient to trigger tumor formation in mice, but the importance of matriptase in breast cancer remains unclear. We analysed matriptase expression in 16 human breast cancer cell lines and in 107 primary breast tumors. The data revealed considerable diversity in the expression level of this protein indicating that the significance of matriptase may vary from case to case. Matriptase protein expression was correlated with HER2 expression and highest expression was seen in HER2-positive cell lines, indicating a potential role in this subgroup. Stable overexpression of matriptase in two breast cancer cell lines had different consequences. In MDA-MB-231 human breast carcinoma cells the only noted consequence of matriptase overexpression was modestly impaired growth in vivo. In contrast, overexpression of matriptase in 4T1 mouse breast carcinoma cells resulted in visible changes in morphology, actin staining and cell to cell contacts. This correlated with downregulation of the cell-cell adhesion molecule E-cadherin. These results suggest that the functions of matriptase in breast cancer are likely to be variable and cell context dependent.
Transcript and Protein Profiling Identify Signaling, Growth Arrest, Apoptosis and NFκB-survival Signatures Following GnRH Receptor Activation
Endocrine-related Cancer. Nov, 2012 | Pubmed ID: 23202794
Gonadotrophin-releasing hormone (GnRH) significantly inhibits proliferation of a proportion of cancer cell lines by activating GnRH receptor-G protein signaling. Therefore, manipulation of GnRH receptor signaling may have an under-utilized role in treating certain breast and ovarian cancers. However, the precise signaling pathways necessary for the effect and the features of cellular responses remain poorly defined. We used transcriptomic and proteomic profiling approaches to characterize the effects of GnRH receptor activation in sensitive cells (HEK293-GnRHR, SCL60) in in vitro and in vivo settings, compared to unresponsive HEK293. Analyses of gene expression demonstrated a dynamic SCL60 response to the GnRH super-agonist Triptorelin. Early and mid-phase changes (0.5-1.0 h) comprised mainly transcription factors. Later changes (8-24 h) included a GnRH target gene, CGA, and up or down-regulation of transcripts encoding signaling and cell division machinery. Pathway analysis exposed identified altered mitogen-activated protein kinase and cell cycle pathways, consistent with occurrence of G2/M arrest and apoptosis. NFκB pathway gene transcripts were differentially expressed between control and Triptorelin-treated SCL60 cultures. Reverse phase protein and phospho-proteomic array analyses profiled responses in cultured cells and SCL60 xenografts in vivo during Triptorelin anti-proliferation. Increased phosphorylated NFκB (p65) occurred in SCL60 in vitro, and p-NFκB and IκBε were higher in treated xenografts than controls after 4 days Triptorelin. NFκB inhibition enhanced the anti-proliferative effect of Triptorelin in SCL60 cultures. This study reveals details of pathways interacting with intense GnRH receptor signaling, identifies potential anti-proliferative target genes and implicates the NFκB survival pathway as a node for enhancing GnRH agonist-induced anti-proliferation.
Cellular Signalling. Jan, 2013 | Pubmed ID: 23000339
Although the theoretical possibility of oscillations in MAPK signalling has long been described, experimental validation has proven more elusive. In this study we observed oscillations in MAPK and PI3K signalling in breast cancer cells in response to epidermal growth factor receptor-family stimulation. Using systems level analysis with a kinetic model, we demonstrate that receptor amplification, loss of transcriptional feedback, or pathway crosstalk, are responsible for oscillations in MAPK and PI3K signalling. Transcriptional profiling reveals architectural motifs likely to be responsible for feedback control of oscillations. Overexpression of the HER2 oncogene and inhibition of transcriptional feedback increase the amplitude of oscillations and provide experimental validation of the computational findings.