The role of HDAC2 in chromatin remodelling and response to chemotherapy in ovarian cancer.

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.

Multi-Scale Genomic, Transcriptomic and Proteomic Analysis of Colorectal Cancer Cell Lines to Identify Novel Biomarkers.

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.

Novel Monte Carlo approach quantifies data assemblage utility and reveals power of integrating molecular and clinical information for cancer prognosis.

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.

Increased STAT1 signaling in endocrine-resistant breast cancer.

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.

Predicting response to the anti-estrogen fulvestrant in recurrent ovarian cancer.

BACKGROUND: Anti-estrogen therapy appears to have efficacy in a subset of ovarian cancers, as demonstrated in multiple phase II studies. Identifying sensitive patients early in treatment may allow for targeted, low-toxicity primary therapy or prevention of recurrence. We have previously demonstrated that the likelihood of response to letrozole could be improved by patient selection based on estrogen-pathway marker expression. We sought to identify ovarian cancer biomarkers that might indicate sensitivity to fulvestrant, an estrogen receptor antagonist. METHODS: Tissue samples from the primary tumors of patients enrolled in a phase II study of fulvestrant for the treatment of multiply-recurrent ovarian cancer were embedded randomly in a tissue microarray (TMA). Estrogen receptor alpha (ERα) expression was assessed by both conventional immunohistochemistry (IHC) and quantitative immunofluorescence (IF) (AQUA) while expression of 14 other estrogen-regulated markers was assessed by quantitative IF and correlated with clinical outcomes. RESULTS: Almost half of patients experienced clinical benefit (CR+PR+SD) at 90 days despite a median of 5 previous treatment regimens. 24 of 26 patient samples were available and included in the TMA. ERα expression, measured either by conventional IHC or by AQUA analysis, was associated with clinical benefit, while TFF1 and vimentin expression (measured by IF AQUA score) was predictive of progression-free survival. CONCLUSIONS: These results confirm our previous observation that clinical ovarian cancer includes a subset of tumors with sensitivity to estrogen pathway blockade. Expression profile of sensitive tumors appears to be detectably different from insensitive tumors, suggesting that further improvements in treatment efficacy can be obtained through appropriate patient selection.

Endogenous tissue plasminogen activator enhances fibrinolysis and limits thrombus formation in a clinical model of thrombosis.

OBJECTIVE: Using a clinical model of deep arterial injury, we assessed the ability of exogenous and endogenous tissue plasminogen activator (t-PA) to limit acute in situ thrombus formation. APPROACH AND RESULTS: Ex vivo thrombus formation was assessed in the Badimon chamber at low and high shear rates in 2 double-blind randomized cross-over studies of 20 healthy volunteers during extracorporeal administration of recombinant t-PA (0, 40, 200, and 1000 ng/mL) or during endogenous t-PA release stimulated by intra-arterial bradykinin infusion in the presence or absence of oral enalapril. Recombinant t-PA caused a dose-dependent reduction in thrombus area under low and high shear conditions (P<0.001 for all). Intra-arterial bradykinin increased plasma t-PA concentrations in the chamber effluent (P<0.01 for all versus saline) that was quadrupled in the presence of enalapril (P<0.0001 versus placebo). These increases were accompanied by an increase in plasma D-dimer concentration (P<0.005 for all versus saline) and, in the presence of enalapril, a reduction in thrombus area in the low shear (16±5; P=0.03) and a trend toward a reduction in the high shear chamber (13±7%; P=0.07). CONCLUSIONS: Using a well-characterized clinical model of coronary arterial injury, we demonstrate that endogenous t-PA released from the vascular endothelium enhances fibrinolysis and limits in situ thrombus propagation. These data support a crucial role for the endogenous fibrinolytic system in vivo and suggest that continued exploration and manipulation of its therapeutic potential are warranted.

The use of reverse phase protein arrays (RPPA) to explore protein expression variation within individual renal cell cancers.

Currently there is no curative treatment for metastatic clear cell renal cell cancer, the commonest variant of the disease. A key factor in this treatment resistance is thought to be the molecular complexity of the disease. Targeted therapy such as the tyrosine kinase inhibitor (TKI)-sunitinib have been utilized, but only 40% of patients will respond, with the overwhelming majority of these patients relapsing within 1 year. As such the question of intrinsic and acquired resistance in renal cell cancer patients is highly relevant. In order to study resistance to TKIs, with the ultimate goal of developing effective, personalized treatments, sequential tissue after a specific period of targeted therapy is required, an approach which had proved successful in chronic myeloid leukaemia. However the application of such a strategy in renal cell carcinoma is complicated by the high level of both inter- and intratumoral heterogeneity, which is a feature of renal cell carcinoma as well as other solid tumors. Intertumoral heterogeneity due to transcriptomic and genetic differences is well established even in patients with similar presentation, stage and grade of tumor. In addition it is clear that there is great morphological (intratumoral) heterogeneity in RCC, which is likely to represent even greater molecular heterogeneity. Detailed mapping and categorization of RCC tumors by combined morphological analysis and Fuhrman grading allows the selection of representative areas for proteomic analysis. Protein based analysis of RCC is attractive due to its widespread availability in pathology laboratories; however, its application can be problematic due to the limited availability of specific antibodies. Due to the dot blot nature of the Reverse Phase Protein Arrays (RPPA), antibody specificity must be pre-validated; as such strict quality control of antibodies used is of paramount importance. Despite this limitation the dot blot format does allow assay miniaturization, allowing for the printing of hundreds of samples onto a single nitrocellulose slide. Printed slides can then be analyzed in a similar fashion to Western analysis with the use of target specific primary antibodies and fluorescently labelled secondary antibodies, allowing for multiplexing. Differential protein expression across all the samples on a slide can then be analyzed simultaneously by comparing the relative level of fluorescence in a more cost-effective and high-throughput manner.

Feedforward and feedback regulation of the MAPK and PI3K oscillatory circuit in breast cancer.

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.

Transcript and protein profiling identifies signaling, growth arrest, apoptosis, and NF-κB survival signatures following GNRH receptor activation.

GNRH significantly inhibits proliferation of a proportion of cancer cell lines by activating GNRH receptor (GNRHR)-G protein signaling. Therefore, manipulation of GNRHR 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 GNRHR activation in sensitive cells (HEK293-GNRHR, SCL60) in vitro and in vivo, compared to unresponsive HEK293. Analyses of gene expression demonstrated a dynamic response to the GNRH superagonist 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 downregulation of transcripts encoding signaling and cell division machinery. Pathway analysis identified altered MAPK and cell cycle pathways, consistent with occurrence of G(2)/M arrest and apoptosis. Nuclear factor kappa B (NF-κB) 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 NF-κB (p65) occurred in SCL60 in vitro, and p-NF-κB and IκBε were higher in treated xenografts than controls after 4 days Triptorelin. NF-κB inhibition enhanced the anti-proliferative effect of Triptorelin in SCL60 cultures. This study reveals details of pathways interacting with intense GNRHR signaling, identifies potential anti-proliferative target genes, and implicates the NF-κB survival pathway as a node for enhancing GNRH agonist-induced anti-proliferation.

Diversity of matriptase expression level and function in breast cancer.

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.

The use of automated quantitative analysis to evaluate epithelial-to-mesenchymal transition associated proteins in clear cell renal cell carcinoma.

BACKGROUND: 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. METHODS/PRINCIPAL FINDINGS: Unsupervised hierarchical cluster analysis of pre-existing RCC gene expression array data (GSE16449) from 36 patients revealed the presence of an EMT transcriptional signature in RCC [E-cadherin high/SLUG low/SNAIL low]. As automated immunofluorescence technology is dependent on accurate definition of the tumour cells in which measurements take place is critical, extensive optimisation was carried out resulting in a novel pan-cadherin based tumour mask that distinguishes renal cancer cells from stromal components. 61 patients with ccRCC and clinical follow-up were subsequently assessed for expression of EMT-associated proteins (WT1, SNAIL, SLUG, E-cadherin and phospho-ß-catenin) on tissue microarrays. Using Kaplan-Meier analysis both SLUG (p = 0.029) and SNAIL (p = 0.024) (log rank Mantel-Cox) were significantly associated with prolonged progression free survival (PFS). Using Cox regression univariate and multivariate analysis none of the biomarkers were significantly correlated with outcome. 14 of the 61 patients expressed the gene expression analysis predicted EMT-protein signature [E-cadherin high/SLUG low/SNAIL low], which was not found to be associated to PFS when measured at the protein level. A combination of high expression of SNAIL and low stage was able to stratify patients with greater significance (p = 0.001) then either variable alone (high SNAIL p = 0.024, low stage p = 0.029). CONCLUSIONS: AQUA has been shown to have the potential to identify EMT related protein targets in RCC allowing for stratification of patients into high and low risk groups, as well the ability to assess the association of reputed EMT signatures to progression of the disease.

Co-expression of SNAIL and TWIST determines prognosis in estrogen receptor-positive early breast cancer patients.

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.

Features of the reversible sensitivity-resistance transition in PI3K/PTEN/AKT signalling network after HER2 inhibition.

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 GSK3ß 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.

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network.

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.

GnRH receptor activation competes at a low level with growth signaling in stably transfected human breast cell lines.

BACKGROUND: 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. METHODS: GnRH-R expression in 298 primary breast cancer samples was measured by quantitative immunofluorescence. Levels of functional GnRH-R in breast-derived cell lines were assessed using 125I-ligand binding and stimulation of 3H-inositol phosphate production. Elevated levels of GnRH-R were stably expressed in cells by transfection. Effects of receptor activation on in vitro cell growth were investigated in comparison with IGF-I and EGF receptor inhibition, and correlated with intracellular signaling using western blotting. RESULTS: GnRH-R immunoscoring was highest in hormone receptor (triple) negative and grade 3 breast tumors. However prior to transfection, functional endogenous GnRH-R were undetectable in four commonly studied breast cancer cell lines (MCF-7, ZR-75-1, T47D and MDA-MB-231). After transfection with GnRH-R, high levels of cell surface GnRH-R were detected in SVCT and MDA-MB-231 clones while low-moderate levels of GnRH-R occurred in MCF-7 clones and ZR-75-1 clones. MCF-7 sub-clones with high levels of GnRH-R were isolated following hygromycin phosphotransferase transfection. High level cell surface GnRH-R enabled induction of high levels of 3H-inositol phosphate and modest growth-inhibition in SVCT cells. In contrast, growth of MCF-7, ZR-75-1 or MDA-MB-231 clones was unaffected by GnRH-R activation. Cell growth was inhibited by IGF-I or EGF receptor inhibitors. IGF-I receptor inhibitor lowered levels of p-ERK1/2 in MCF-7 clones. Washout of IGF-I receptor inhibitor resulted in transient hyper-elevation of p-ERK1/2, but co-addition of GnRH-R agonist did not alter the dynamics of ERK1/2 re-phosphorylation. CONCLUSIONS: Breast cancers exhibit a range of GnRH-R immunostaining, with higher levels of expression found in triple-negative and grade 3 cancers. However, functional cell surface receptors are rare in cultured cells. Intense GnRH-R signaling in transfected breast cancer cells did not markedly inhibit growth, in contrast to transfected HEK 293 cells indicating the importance of intracellular context. GnRH-R signaling could not counteract IGF-I receptor-tyrosine kinase addiction in MCF-7 cells. These results suggest that combinatorial strategies with growth factor inhibitors will be needed to enhance GnRH anti-proliferative effects in breast cancer.

Heterogeneity mapping of protein expression in tumors using quantitative immunofluorescence.

Morphologic heterogeneity within an individual tumor is well-recognized by histopathologists in surgical practice. While this often takes the form of areas of distinct differentiation into recognized histological subtypes, or different pathological grade, often there are more subtle differences in phenotype which defy accurate classification (Figure 1). Ultimately, since morphology is dictated by the underlying molecular phenotype, areas with visible differences are likely to be accompanied by differences in the expression of proteins which orchestrate cellular function and behavior, and therefore, appearance. The significance of visible and invisible (molecular) heterogeneity for prognosis is unknown, but recent evidence suggests that, at least at the genetic level, heterogeneity exists in the primary tumor(1,2), and some of these sub-clones give rise to metastatic (and therefore lethal) disease. Moreover, some proteins are measured as biomarkers because they are the targets of therapy (for instance ER and HER2 for tamoxifen and trastuzumab (Herceptin), respectively). If these proteins show variable expression within a tumor then therapeutic responses may also be variable. The widely used histopathologic scoring schemes for immunohistochemistry either ignore, or numerically homogenize the quantification of protein expression. Similarly, in destructive techniques, where the tumor samples are homogenized (such as gene expression profiling), quantitative information can be elucidated, but spatial information is lost. Genetic heterogeneity mapping approaches in pancreatic cancer have relied either on generation of a single cell suspension(3), or on macrodissection(4). A recent study has used quantum dots in order to map morphologic and molecular heterogeneity in prostate cancer tissue(5), providing proof of principle that morphology and molecular mapping is feasible, but falling short of quantifying the heterogeneity. Since immunohistochemistry is, at best, only semi-quantitative and subject to intra- and inter-observer bias, more sensitive and quantitative methodologies are required in order to accurately map and quantify tissue heterogeneity in situ. We have developed and applied an experimental and statistical methodology in order to systematically quantify the heterogeneity of protein expression in whole tissue sections of tumors, based on the Automated QUantitative Analysis (AQUA) system(6). Tissue sections are labeled with specific antibodies directed against cytokeratins and targets of interest, coupled to fluorophore-labeled secondary antibodies. Slides are imaged using a whole-slide fluorescence scanner. Images are subdivided into hundreds to thousands of tiles, and each tile is then assigned an AQUA score which is a measure of protein concentration within the epithelial (tumor) component of the tissue. Heatmaps are generated to represent tissue expression of the proteins and a heterogeneity score assigned, using a statistical measure of heterogeneity originally used in ecology, based on the Simpson's biodiversity index(7). To date there have been no attempts to systematically map and quantify this variability in tandem with protein expression, in histological preparations. Here, we illustrate the first use of the method applied to ER and HER2 biomarker expression in ovarian cancer. Using this method paves the way for analyzing heterogeneity as an independent variable in studies of biomarker expression in translational studies, in order to establish the significance of heterogeneity in prognosis and prediction of responses to therapy.

Sprouty 2 is an independent prognostic factor in breast cancer and may be useful in stratifying patients for trastuzumab therapy.

BACKGROUND: 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. PATIENTS AND METHODS: Associations between Sprouty gene expression and clinicopathological features were investigated in a breast cancer microarray meta-analysis. Changes in expression of Spry2 and feedback inhibition on trastuzumab resistance were studied in SKBr3 and BT474 breast carcinoma cell lines using cell viability assays. Spry2 protein expression was measured by quantitative immunofluorescence in a cohort of 122 patients treated with trastuzumab. RESULTS: Low gene expression of Spry2 was associated with increased pathological grade, high HER2 expression, and was a significant independent prognostic factor. Overexpression of Spry2 in SKBr3s resulted in enhanced inhibition of cell viability after trastuzumab treatment, and the PI3K-inhibitor LY294002 had a similar effect. Low Spry2 expression was associated with increased risk of death (HR = 2.28, 95% CI 1.22-4.26; p = 0.008) in trastuzumab-treated patients, including in multivariate analysis. Stratification of trastuzumab-treated patients using PTEN and Spry2 was superior to either marker in isolation. CONCLUSION: In breast cancers with deficient feedback inhibition, combinatorial therapy with negative regulators of growth factor signalling may be an effective therapeutic strategy.