Corticosteroid co-treatment induces resistance to chemotherapy in surgical resections, xenografts and established cell lines of pancreatic cancer

BACKGROUND: Chemotherapy for pancreatic carcinoma often has severe side effects that limit its efficacy. The glucocorticoid (GC) dexamethasone (DEX) is frequently used as co-treatment to prevent side effects of chemotherapy such as nausea, for palliative purposes and to treat allergic reactions. While the potent pro-apoptotic properties and the supportive effects of GCs to tumour therapy in lymphoid cells are well studied, the impact of GCs to cytotoxic treatment of pancreatic carcinoma is unknown. METHODS: A prospective study of DEX-mediated resistance was performed using a pancreatic carcinoma xenografted to nude mice, 20 surgical resections and 10 established pancreatic carcinoma cell lines. Anti-apoptotic signaling in response to DEX was examined by Western blot analysis. RESULTS: In vitro, DEX inhibited drug-induced apoptosis and promoted the growth in all of 10 examined malignant cells. Ex vivo, DEX used in physiological concentrations significantly prevented the cytotoxic effect of gemcitabine and cisplatin in 18 of 20 freshly isolated cell lines from resected pancreatic tumours. No correlation with age, gender, histology, TNM and induction of therapy resistance by DEX co-treatment could be detected. In vivo, DEX totally prevented cytotoxicity of chemotherapy to pancreatic carcinoma cells xenografted to nude mice. Mechanistically, DEX upregulated pro-survival factors and anti-apoptotic genes in established pancreatic carcinoma cells. CONCLUSION: These data show that DEX induces therapy resistance in pancreatic carcinoma cells and raise the question whether GC-mediated protection of tumour cells from cancer therapy may be dangerous for patients

Google Goes Cancer: Improving Outcome Prediction for Cancer Patients by Network-Based Ranking of Marker Genes

Predicting the clinical outcome of cancer patients based on the expression of marker genes in their tumors has received increasing interest in the past decade. Accurate predictors of outcome and response to therapy could be used to personalize and thereby improve therapy. However, state of the art methods used so far often found marker genes with limited prediction accuracy, limited reproducibility, and unclear biological relevance. To address this problem, we developed a novel computational approach to identify genes prognostic for outcome that couples gene expression measurements from primary tumor samples with a network of known relationships between the genes. Our approach ranks genes according to their prognostic relevance using both expression and network information in a manner similar to Google's PageRank. We applied this method to gene expression profiles which we obtained from 30 patients with pancreatic cancer, and identified seven candidate marker genes prognostic for outcome. Compared to genes found with state of the art methods, such as Pearson correlation of gene expression with survival time, we improve the prediction accuracy by up to 7%. Accuracies were assessed using support vector machine classifiers and Monte Carlo cross-validation. We then validated the prognostic value of our seven candidate markers using immunohistochemistry on an independent set of 412 pancreatic cancer samples. Notably, signatures derived from our candidate markers were independently predictive of outcome and superior to established clinical prognostic factors such as grade, tumor size, and nodal status. As the amount of genomic data of individual tumors grows rapidly, our algorithm meets the need for powerful computational approaches that are key to exploit these data for personalized cancer therapies in clinical practice

The dynamics of expanding mangroves in New Zealand

In contrast to the global trend of mangrove decline, New Zealand mangroves are rapidly expanding, facilitated by elevated sediment inputs in coastal waters as a consequence of large-scale land use changes following European settlement. New Zealand mangroves are at the southern limit of the global mangrove extent, which limits the tree height of Avicennia marina var. australasica, the only mangrove species present. Mangroves in New Zealand thrive in the sheltered environments of infilling drowned river valleys with abundant supply of fine terrigenous sediments, showing various stages of mangrove succession and expansion dynamics. Bio-physical interactions and carbon dynamics in these expanding temperate mangrove systems show similarities to, but also differ from those in tropical mangrove forests, for instance due to the limited height and complexity of the mangrove communities. Likewise, ecosystem services provided by New Zealand mangroves deviate from those offered by tropical mangroves. In particular, the association of mangrove expansion with the accumulation of (the increased supply of) fine sediments and the consequent change of estuarine ecosystems, has provoked a negative perception of mangrove expansion and subsequently led to mangrove clearance. Over recent decades, a body of knowledge has been developed regarding the planning and decision making relating to mangrove removal, yet there are still effects that are unknown, for example with respect to the post-clearance recovery of the original sandflat ecosystems. In this chapter we discuss the dynamics of New Zealand’s expanding mangroves from a range of viewpoints, with the aim of elucidating the possible contributions of expanding mangroves to coastal ecosystem services, now and in the future. This chapter also reviews current policies and practice regarding mangrove removal in New Zealand and addresses the (un)known effects of mangrove clearance. These combined insights may contribute to the development of integrated coastal management strategies that recognise the full potential of expanding mangrove ecosystems

ErbB3 expression promotes tumorigenesis in pancreatic adenocarcinoma

Historically, ErbB3 has been overlooked within the ErbB receptor family due to its perceived lack of tyrosine kinase activity. We have previously demonstrated that in pancreatic cancer ErbB3 is the preferred dimerization partner of EGFR, ErbB3 protein expression level directly correlates with the anti-proliferative effect of erlotinib (an EGFR-specific tyrosine kinase inhibitor), and transient knockdown of ErbB3 expression results in acquired resistance to EGFR-targeted therapy. In this study, we develop a stable isogenic model of ErbB3 expression in an attempt to decipher ErbB3's true contribution to pancreatic cancer tumorigenesis and to examine how this receptor affects cellular sensitivity to EGFR-targeted therapy. Analysis of the EGFR-ErbB3 heterodimer demonstrates that ligand-induced PI3K-AKT signaling is limited to ErbB3-expressing cells and that this signaling cascade can be partially abrogated by inhibiting EGFR function with erlotinib. Using our model of exogenous ErbB3 expression we showed a direct relationship between ErbB3 protein levels and increased pancreatic cancer cell proliferation in vitro. In vivo, ErbB3+PANC-1 xenografts had a significantly larger tumor volume than PANC-1 control xenografts (ErbB3-PANC-1) and displayed increased sensitivity to EGFR-targeted therapy. In pancreatic cancer, ErbB3 appears to be critically involved in EGFR signaling as evidenced by its profound effect on cellular proliferation and its ability to influence response to EGFR-targeted therapy