Deregulated expression of c-MYC occurs in a broad range of human cancers and is often associated with poor prognosis, indicating a key role for this oncogene in tumour progression. However, as established human tumours often bear multiple genetic lesions, it is difficult to determine whether c-MYC is instrumental in the initiation/progression of the tumour, or indeed whether inactivating c-MYC would lead to tumour regression. Regulatable transgenic mouse models of oncogenesis have shed light on these issues and provide hope for effective cancer therapies.

To explore the role of c-Myc in carcinogenesis, we have developed a reversible transgenic model of pancreatic beta cell oncogenesis using a switchable form of the c-Myc protein. Activation of c-Myc in adult, mature beta cells induces uniform beta cell proliferation but is accompanied by overwhelming apoptosis that rapidly erodes beta cell mass. Thus, the oncogenic potential of c-Myc in beta cells is masked by apoptosis. Upon suppression of c-Myc-induced beta cell apoptosis by coexpression of Bcl-x(L), c-Myc triggers rapid and uniform progression into angiogenic, invasive tumors. Subsequent c-Myc deactivation induces rapid regression associated with vascular degeneration and beta cell apoptosis. Our data indicate that highly complex neoplastic lesions can be both induced and maintained in vivo by a simple combination of two interlocking molecular lesions.

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The protooncogene c-myc regulates cell growth, differentiation, and apoptosis, and its aberrant expression is frequently observed in human cancer. However, the consequences of activating c-Myc in an adult tissue, in which these cellular processes are part of normal homeostasis, remain unknown. In order to achieve this, we have targeted expression of a switchable form of the c-Myc protein to the skin epidermis, a well characterized homeostatic tissue. We show that activation of c-MycER in adult suprabasal epidermis rapidly triggers proliferation and disrupts differentiation of postmitotic keratinocytes. Sustained activation of c-Myc is sufficient to induce papillomatosis together with angiogenesis--changes that resemble hyperplastic actinic keratosis, a commonly observed human precancerous epithelial lesion. All these premalignant changes spontaneously regress upon deactivation of c-MycER.

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Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy images. The proposed network can be used to segment cells, nuclei and glands in fluorescence microscopy and histology images after slight tuning of input parameters. The network trains at multiple resolutions of the input image, connects the intermediate layers for better localization and context and generates the output using multi-resolution deconvolution filters.The extra convolutional layers which bypass the max-pooling operation allow the network to train for variable input intensities and object size and make it robust to noisy data. We compare our results on publicly available data sets and show that the proposed network outperforms recent deep learning algorithms.

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