Pancreatic ductal adenocarcinoma (PDAC) and its precursor lesions, pancreatic intraepithelial neoplasia (PanIN), display a ductal phenotype. However, there is evidence in genetically defined mouse models for PDAC harbouring a mutated kras under the control of a pancreas-specific promoter that ductal cancer might arise in the centroacinar-acinar region, possibly through a process of acinar-ductal metaplasia (ADM). In order to further elucidate this model of PDAC development, an extensive expression analysis and molecular characterization of the putative and already established (PanIN) precursor lesions were performed in the Kras(G12D/+) ; Ptf1a-Cre(ex1/+) mouse model and in human tissues, focusing on lineage markers, developmental pathways, cell cycle regulators, apomucins, and stromal activation markers. The results of this study show that areas of ADM are very frequent in the murine and human pancreas and represent regions of increased proliferation of cells with precursor potential. Moreover, atypical flat lesions originating in areas of ADM are the most probable precursors of PDAC in the Kras(G12D/+); Ptf1a-Cre(ex1/+) mice and similar lesions were also found in the pancreas of three patients with a strong family history of PDAC. In conclusion, PDAC development in Kras(G12D/+); Ptf1a-Cre(ex1/+) mice starts from ADM and a similar process might also take place in patients with a strong family history of PDAC.

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Matzke-Ogi, A. et al. (2016) Inhibition of tumor growth and metastasis in pancreatic cancer models by interference with CD44v6 signaling. Gastroenterology, 150(2), 513-525.e10. (doi:10.1053/j.gastro.2015.10.020) This is the author's final accepted version.There may be differences between this version and the published version. You are advised to consult the publisher's version if you wish to cite from it.http://eprints.gla.ac.uk/116680/

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In clinical ion beam therapy, protons as well as heavier ions such as carbon are used for treatment. For protons, β(+)-emitters are only induced by fragmentation reactions in the target (target fragmentation), whereas for heavy ions, they are additionally induced by fragmentations of the projectile (further referred to as autoactivation). An approach utilizing these processes for treatment verification, by comparing measured Positron Emission Tomography (PET) data to predictions from Monte Carlo simulations, has already been clinically implemented. For an accurate simulation, it is important to consider the biological washout of β(+)-emitters due to vital functions. To date, mathematical expressions for washout have mainly been determined by using radioactive beams of (10)C- and (11)C-ions, both β(+)-emitters, to enhance the counting statistics in the irradiated area. Still, the question of how the choice of projectile (autoactivating or non-autoactivating) influences the washout coefficients, has not been addressed. In this context, an experiment was carried out at the Heidelberg Ion Beam Therapy Center with the purpose of directly comparing irradiation-induced biological washout coefficients in mice for protons and (12)C-ions. To this aim, mice were irradiated in the brain region with protons and (12)C-ions and measured after irradiation with a PET/CT scanner (Siemens Biograph mCT). After an appropriate waiting time, the mice were sacrificed, then irradiated and measured again under similar conditions. The resulting data were processed and fitted numerically to deduce the main washout parameters. Despite the very low PET counting statistics, a consistent difference could be identified between (12)C-ion and proton irradiated mice, with the (12)C data being described best by a two component fit with a combined medium and slow washout fraction of 0.50 ± 0.05 and the proton mice data being described best by a one component fit with only one (slow) washout fraction of 0.73 ± 0.06.

Neoangiogenesis is a pivotal therapeutic target in glioblastoma. Tumor monitoring requires imaging methods to assess treatment effects and disease progression. Until now mapping of the tumor vasculature has been difficult. We have developed a combined magnetic resonance and optical toolkit to study neoangiogenesis in glioma models. We use in vivo magnetic resonance imaging (MRI) and correlative ultramicroscopy (UM) of ex vivo cleared whole brains to track neovascularization. T2* imaging allows the identification of single vessels in glioma development and the quantification of neovessels over time. Pharmacological VEGF inhibition leads to partial vascular normalization with decreased vessel caliber, density, and permeability. To further resolve the tumor microvasculature, we performed correlated UM of fluorescently labeled microvessels in cleared brains. UM resolved typical features of neoangiogenesis and tumor cell invasion with a spatial resolution of ~5 µm. MR-UM can be used as a platform for three-dimensional mapping and high-resolution quantification of tumor angiogenesis.DOI: http://dx.doi.org/10.7554/eLife.11712.001

BackgroundQuantitative analysis of transcriptional regulation of genes is a prerequisite for a better understanding of the molecular mechanisms of action of different radiation qualities such as photon, proton or carbon ion irradiation. Microarrays and real-time quantitative RT-PCR (qRT-PCR) are considered the two cornerstones of gene expression analysis. In interpreting these results it is critical to normalize the expression levels of the target genes by that of appropriately selected endogenous control genes (ECGs) or housekeeping genes. We sought to systematically investigate common ECG candidates for their stability after different radiation modalities in different human cell lines by qRT-PCR. We aimed to identify the most robust set of ECGs or housekeeping genes for transcriptional analysis in irradiation studies.MethodsWe tested the expression stability of 32 ECGs in three human cancer cell lines. The epidermoid carcinoma cells (A431), the non small cell lung carcinoma cells (A549) and the pancreatic adenocarincoma cells (BxPC3) were irradiated with photon, proton and carbon ions. Expression Heat maps, clustering and statistic algorithms were employed using SUMO software package. The expression stability was evaluated by computing: mean, standard deviation, ANOVA, coefficient of variation and the stability measure (M) given by the geNorm algorithm.ResultsExpression analysis revealed significant cell type specific regulation of 18 out of 32 ECGs (p < 0.05). A549 and A431 cells shared a similar pattern of ECG expression as the function of different radiation qualities as compared to BxPC3. Of note, the ribosomal protein 18S, one of the most frequently used ECG, was differentially regulated as the function of different radiation qualities (p ≤ 0.01). A comprehensive search for the most stable ECGs using the geNorm algorithm identified 3 ECGs for A431 and BxPC3 to be sufficient for normalization. In contrast, 6 ECGs were required to properly normalize expression data in the more variable A549 cells. Considering both variables tested, i.e. cell type and radiation qualities, 5 genes-- RPLP0, UBC, PPIA, TBP and PSMC4-- were identified as the consensus set of stable ECGs.ConclusionsCaution is warranted when selecting the internal control gene for the qRT-PCR gene expression studies. Here, we provide a template of stable ECGs for investigation of radiation induced gene expression.