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-β-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

Evaluation of the dual mTOR / PI3K inhibitors Gedatolisib (PF-05212384) and PF-04691502 against ovarian cancer xenograft models

We are grateful to Wyeth/Pfizer (ONC-EU-150) and to the Scottish Funding Council (SRDG HR07005) for support of this study.This study investigated the antitumour effects of two dual mTOR/PI3K inhibitors, gedatolisib (WYE-129587/PKI-587/PF-05212384) and PF-04691502 against a panel of six human patient derived ovarian cancer xenograft models. Both dual mTOR/PI3K inhibitors demonstrated antitumour activity against all xenografts tested. The compounds produced tumour stasis during the treatment period and upon cessation of treatment, tumours re-grew. In several models, there was an initial rapid reduction of tumour volume over the first week of treatment before tumour stasis. No toxicity was observed during treatment. Biomarker studies were conducted in two xenograft models; phospho-S6 (Ser235/236) expression (as a readout of mTOR activity) was reduced over the treatment period in the responding xenograft but expression increased to control (no treatment) levels on cessation of treatment. Phospho-AKT (Ser473) expression (as a readout of PI3K) was inhibited by both drugs but less markedly so than phospho-S6 expression. Initial tumour volume reduction on treatment and regrowth rate after treatment cessation was associated with phospho-S6/total S6 expression ratio. Both drugs produced apoptosis but minimally influenced markers of proliferation (Ki67, phospho-histone H3). These results indicate that mTOR/PI3K inhibition can produce broad spectrum tumour growth stasis in ovarian cancer xenograft models during continuous chronic treatment and this is associated with apoptosis.Publisher PDFPeer reviewe

C35 overexpression defines subsets of human breast cancer and its immunoreceptor tyrosine-based activation motif represents a novel treatment target

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

WV is a SULSA Systems Biology Prize PhD Student; VAS is supported by the BBSRC Research Council [grant number BB/F001398/1] and Medical Research Scotland [grant number FRG353]. DJH is supported by CASyM Concerted Action [grant number EU HEALTH-F4-2012-305033] and the Chief Scientist Office of Scotland.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.Publisher PDFPeer reviewe

Expression of steroid receptor coactivator 3 in ovarian epithelial cancer is a poor prognostic factor and a marker for platinum resistance

BACKGROUND: Steroid receptor coactivator 3 (SRC3) is an important coactivator of a number of transcription factors and is associated with a poor outcome in numerous tumours. Steroid receptor coactivator 3 is amplified in 25% of epithelial ovarian cancers (EOCs) and its expression is higher in EOCs compared with non-malignant tissue. No data is currently available with regard to the expression of SRC-3 in EOC and its influence on outcome or the efficacy of treatment. METHODS: Immunohistochemistry was performed for SRC3, oestrogen receptor-α, HER2, PAX2 and PAR6, and protein expression was quantified using automated quantitative immunofluorescence (AQUA) in 471 EOCs treated between 1991 and 2006 with cytoreductive surgery followed by first-line treatment platinum-based therapy, with or without a taxane. RESULTS: Steroid receptor coactivator 3 expression was significantly associated with advanced stage and was an independent prognostic marker. High expression of SRC3 identified patients who have a significantly poorer survival with single-agent carboplatin chemotherapy, while with carboplatin/paclitaxel treatment such a difference was not seen. CONCLUSION: Steroid receptor coactivator 3 is a poor prognostic factor in EOCs and appears to identify a population of patients who would benefit from the addition of taxanes to their chemotherapy regimen, due to intrinsic resistance to platinum therapy

A gene on the HER2 amplicon, C35, is an oncogene in breast cancer whose actions are prevented by inhibition of Syk

BACKGROUND: C35 is a 12 kDa membrane-anchored protein endogenously over-expressed in many invasive breast cancers. C35 (C17orf37) is located on the HER2 amplicon, between HER2 and GRB7. The function of over-expressed C35 in invasive breast cancer is unknown. METHODS: Tissue microarrays containing 122 primary human breast cancer specimens were used to examine the association of C35 with HER2 expression. Cell lines over-expressing C35 were generated and tested for evidence of cell transformation in vitro. RESULTS: In primary breast cancers high levels of C35 mRNA expression were associated with HER2 gene amplification. High levels of C35 protein expression were associated with hallmarks of transformation, such as, colony growth in soft agar, invasion into collagen matrix and formation of large acinar structures in three-dimensional (3D) cell cultures. The transformed phenotype was also associated with characteristics of epithelial to mesenchymal transition, such as adoption of spindle cell morphology and down-regulation of epithelial markers, such as E-cadherin and keratin-8. Furthermore, C35-induced transformation in 3D cell cultures was dependent on Syk kinase, a downstream mediator of signalling from the immunoreceptor tyrosine-based activation motif, which is present in C35. CONCLUSION: C35 functions as an oncogene in breast cancer cell lines. Drug targeting of C35 or Syk kinase might be helpful in treating a subset of patients with HER2-amplified breast cancers

Drug Inhibition Profile Prediction for NFκB Pathway in Multiple Myeloma

Nuclear factor κB (NFκB) activation plays a crucial role in anti-apoptotic responses in response to the apoptotic signaling during tumor necrosis factor (TNFα) stimulation in Multiple Myeloma (MM). Although several drugs have been found effective for the treatment of MM by mainly inhibiting NFκB pathway, there are not any quantitative or qualitative results of comparison assessment on inhibition effect between different drugs either used alone or in combinations. Computational modeling is becoming increasingly indispensable for applied biological research mainly because it can provide strong quantitative predicting power. In this study, a novel computational pathway modeling approach is employed to comparably assess the inhibition effects of specific drugs used alone or in combinations on the NFκB pathway in MM and to predict the potential synergistic drug combinations

Relationship between differentially expressed mRNA and mRNA-protein correlations in a xenograft model system

This work was supported by Medical Research Scotland (FRG353 to VAS), the FP7- Directorate-General for Research and Innovation of the European Commission (EU HEALTHF4-2012-305033 to Coordinating Action Systems Medicine to DJH); the Chief Scientist Office of Scotland (to DJH) and the Scottish Funding Council (to DJH and SPL).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.Publisher PDFPeer reviewe

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