The Raf/MEK/ERK (extracellular regulated kinase) signal transduction pathway controls the ability of cells to respond to proliferative, apoptotic, migratory and differentiation signals. We have investigated the combined contribution of A-Raf and Raf-1 isotypes to signalling through this pathway by generating mice with knockout mutations of both A-raf and raf-1 genes. Double knockout (DKO) mice have a more severe phenotype than single null mutations of either gene, dying in embryogenesis at E10.5. The DKO embryos show no changes in apoptosis, but staining for Ki67 indicates a generalized reduction in proliferation. DKO mouse embryonic fibroblasts (MEFs) exhibit a delayed ability to enter S phase of the cell cycle. This is associated with a reduction in levels of transiently induced MEK and ERK phosphorylation and reduced expression of c-Fos and cyclin Dl. Levels of sustained ERK phosphorylation are not significantly altered. Thus, Raf-1 and A-Raf have a combined role in controlling physiological transient ERK activation and in maintenance of cell cycle progression at its usual rate.

We compare extreme learning machines with cascade correlation on a standard benchmark dataset for comparing cascade networks along with another commonly used dataset. We introduce a number of hybrid cascade extreme learning machine topologies ranging from simple shallow cascade ELM networks to full cascade ELM networks. We found that the simplest cascade topology provided surprising benefit with a cascade correlation style cascade for small extreme learning machine layers. Our full cascade ELM architecture achieved high performance with even a single neuron per ELM cascade, suggesting that our approach may have general utility, though further work needs to be done using more datasets. We suggest extensions of our cascade ELM approach, with the use of network analysis, addition of noise, and unfreezing of weights.

BACKGROUND: Prostate cancer is one of the most common cancer worldwide with limited treatment options and very poor prognosis. Surgery, chemo therapy such as docetaxel (Taxotere®) and targeted therapies such as abiraterone (Zytiga®) and enzalutamide (Xtandi®) are the options available for prostate cancer patients but they all have their limitations. The development of new prostate cancer therapy has been slow due to the lack or preclinical models that adequately represent the spectrum of benign, latent, aggressive, and metastatic forms of the human disease. PDX have been reported to be more clinically relevant that cell lines but the generation of prostate PDX models has always been challenging. Here we report the establishment and validation of a panel of prostate PDX models and their utilization in preclinical studies which will help prostate cancer research. MATERIAL & METHODS: Primary prostate cancer samples from patients undergoing radical prostatectomy in the UK were collected with ethical consent. These samples were then inoculated subcutaneously in Rag2-/-gC-/- mice (Jackson Laboratory) to generate PDX models. Subcutaneous tumor growth was evaluated and monitored by electronic callipers. Successfully established PDX tissue were collected for RNA sequencing and immunohistochemistry (IHC) for key prostate markers. PDX were also tested for sensitivity to docetaxel (Taxotere®), abiraterone and enzalutamide in vivo in mice bearing subcutaneous tumours. Tumours were samples pre and post dosing as well as blood samples collected. RESULTS: A panel of prostate PDX models have been established and expanded. Two models were established using tumour tissue from patients diagnosed with castrate resistant prostate cancer (CRPC) and two models were from patients who showed hormone sensitivity. Histologically the structure of the original patient sample was retained in the PDX models. These models also showed high KLK3 (PSA) expression levels by RNA sequencing and IHC staining as well as androgen receptor expression. One of the CRPC models showed a TMPRSS-ETS fusion, response to docetaxel (p<0.0001, Two way ANOVA) in vivo and poor response to abiraterone and enzalutamide, whereas the second CRPC model showed no response to any of the agents tested. CONCLUSIONS: We have established and characterised a panel of prostate PDX models which provide unique and clinically relevant models for preclinical drug evaluation for prostate cancer. Citation Format: Jason Davis, Anthony Oakden, Jane Wrigley, Chira Roberts, W Qian, Bin Fan, A Collins, Davy Ouyang, Jie Cai, Rajendra Kumari, Yinfei Yin. Establishment of a panel of prostate patient derived xenograft (PDX) models and evaluation of anti-androgen therapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1060.

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