Genetic mouse models as in vivo tools for cholangiocarcinoma research

Cholangiocarcinoma (CCA) is a genetically and histologically complex disease with a highly dismal prognosis. A deeper understanding of the underlying cellular and molecular mechanisms of human CCA will increase our current knowledge of the disease and expedite the eventual development of novel therapeutic strategies for this fatal cancer. This endeavor is effectively supported by genetic mouse models, which serve as sophisticated tools to systematically investigate CCA pathobiology and treatment response. These in vivo models feature many of the genetic alterations found in humans, recapitulate multiple hallmarks of cholangiocarcinogenesis (encompassing cell transformation, preneoplastic lesions, established tumors and metastatic disease) and provide an ideal experimental setting to study the interplay between tumor cells and the surrounding stroma. This review is intended to serve as a compendium of CCA mouse models, including traditional transgenic models but also genetically flexible approaches based on either the direct introduction of DNA into liver cells or transplantation of pre-malignant cells, and is meant as a resource for CCA researchers to aid in the selection of the most appropriate in vivo model system

Blood and brain biochemistry and behaviour in NTBC and dietary treated tyrosinemia type 1 mice

Tyrosinemia type 1 (TT1) is a rare metabolic disease caused by a defect in the tyrosine degradation pathway. Neurocognitive deficiencies have been described in TT1 patients, that have, among others, been related to changes in plasma large neutral amino acids (LNAA) that could result in changes in brain LNAA and neurotransmitter concentrations. Therefore, this project aimed to investigate plasma and brain LNAA, brain neurotransmitter concentrations and behavior in C57 Bl/6 fumarylacetoacetate hydrolase deficient (FAH-/-) mice treated with 2-(2-nitro-4-trifluoromethylbenoyl)-1,3-cyclohexanedione (NTBC) and/or diet and wild-type mice. Plasma and brain tyrosine concentrations were clearly increased in all NTBC treated animals, even with diet (p <0.001). Plasma and brain phenylalanine concentrations tended to be lower in all FAH-/- mice. Other brain LNAA, were often slightly lower in NTBC treated FAH-/- mice. Brain neurotransmitter concentrations were usually within a normal range, although serotonin was negatively correlated with brain tyrosine concentrations (p <0.001). No clear behavioral differences between the different groups of mice could be found. To conclude, this is the first study measuring plasma and brain biochemistry in FAH-/- mice. Clear changes in plasma and brain LNAA have been shown. Further research should be done to relate the biochemical changes to neurocognitive impairments in TT1 patients

Slow dynamics near glass transitions in thin polymer films

The $\alpha$-process (segmental motion) of thin polystyrene films supported on glass substrate has been investigated in a wider frequency range from 10$^{-3}$ Hz to 10$^4$ Hz using dielectric relaxation spectroscopy and thermal expansion spectroscopy. The relaxation rate of the $\alpha$-process increases with decreasing film thickness at a given temperature above the glass transition. This increase in the relaxation rate with decreasing film thickness is much more enhanced near the glass transition temperature. The glass transition temperature determined as the temperature at which the relaxation time of the $\alpha$-process becomes a macroscopic time scale shows a distinct molecular weight dependence. It is also found that the Vogel temperature has the thickness dependence, i.e., the Vogel temperature decreases with decreasing film thickness. The expansion coefficient of the free volume $\alpha_f$ is extracted from the temperature dependence of the relaxation time within the free volume theory. The fragility index $m$ is also evaluated as a function of thickness. Both $\alpha_f$ and $m$ are found to decrease with decreasing film thickness.Comment: 9 pages, 7 figures, and 2 table

Prediction of survival among patients receiving transarterial chemoembolization for hepatocellular carcinoma: A response-based approach

Background and aims: The heterogeneity of intermediate-stage hepatocellular carcinoma (HCC) and the widespread use of transarterial chemoembolization (TACE) outside recommended guidelines have encouraged the development of scoring systems that predict patient survival. The aim of this study was to build and validate statistical models that offer individualized patient survival prediction using response to TACE as a variable. Approach and results: Clinically relevant baseline parameters were collected for 4,621 patients with HCC treated with TACE at 19 centers in 11 countries. In some of the centers, radiological responses (as assessed by modified Response Evaluation Criteria in Solid Tumors [mRECIST]) were also accrued. The data set was divided into a training set, an internal validation set, and two external validation sets. A pre-TACE model ("Pre-TACE-Predict") and a post-TACE model ("Post-TACE-Predict") that included response were built. The performance of the models in predicting overall survival (OS) was compared with existing ones. The median OS was 19.9 months. The factors influencing survival were tumor number and size, alpha-fetoprotein, albumin, bilirubin, vascular invasion, cause, and response as assessed by mRECIST. The proposed models showed superior predictive accuracy compared with existing models (the hepatoma arterial embolization prognostic score and its various modifications) and allowed for patient stratification into four distinct risk categories whose median OS ranged from 7 months to more than 4 years. Conclusions: A TACE-specific and extensively validated model based on routinely available clinical features and response after first TACE permitted patient-level prognosticatio

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa

Atlas of prostate cancer heritability in European and African-American men pinpoints tissue-specific regulation.

Although genome-wide association studies have identified over 100 risk loci that explain ∼33% of familial risk for prostate cancer (PrCa), their functional effects on risk remain largely unknown. Here we use genotype data from 59,089 men of European and African American ancestries combined with cell-type-specific epigenetic data to build a genomic atlas of single-nucleotide polymorphism (SNP) heritability in PrCa. We find significant differences in heritability between variants in prostate-relevant epigenetic marks defined in normal versus tumour tissue as well as between tissue and cell lines. The majority of SNP heritability lies in regions marked by H3k27 acetylation in prostate adenoc7arcinoma cell line (LNCaP) or by DNaseI hypersensitive sites in cancer cell lines. We find a high degree of similarity between European and African American ancestries suggesting a similar genetic architecture from common variation underlying PrCa risk. Our findings showcase the power of integrating functional annotation with genetic data to understand the genetic basis of PrCa.This work was supported by NIH fellowship F32 GM106584 (AG), NIH grants R01 MH101244(A.G.), R01 CA188392 (B.P.), U01 CA194393(B.P.), R01 GM107427 (M.L.F.), R01 CA193910 (M.L.F./M.P.) and Prostate Cancer Foundation Challenge Award (M.L.F./M.P.). This study makes use of data generated by the Wellcome Trust Case Control Consortium and the Wellcome Trust Sanger Institute. A full list of the investigators who contributed to the generation of the Wellcome Trust Case Control Consortium data is available on www.wtccc.org.uk. Funding for the Wellcome Trust Case Control Consortium project was provided by the Wellcome Trust under award 076113. This study makes use of data generated by the UK10K Consortium. A full list of the investigators who contributed to the generation of the data is available online (http://www.UK10K.org). The PRACTICAL consortium was supported by the following grants: European Commission's Seventh Framework Programme grant agreement n° 223175 (HEALTH-F2-2009-223175), Cancer Research UK Grants C5047/A7357, C1287/A10118, C5047/A3354, C5047/A10692, C16913/A6135 and The National Institute of Health (NIH) Cancer Post-Cancer GWAS initiative Grant: no. 1 U19 CA 148537-01 (the GAME-ON initiative); Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007 and C5047/A10692), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112—the GAME-ON initiative), the Department of Defense (W81XWH-10-1-0341), A Linneus Centre (Contract ID 70867902), Swedish Research Council (grant no K2010-70X-20430-04-3), the Swedish Cancer Foundation (grant no 09-0677), grants RO1CA056678, RO1CA082664 and RO1CA092579 from the US National Cancer Institute, National Institutes of Health; US National Cancer Institute (R01CA72818); support from The National Health and Medical Research Council, Australia (126402, 209057, 251533, 396414, 450104, 504700, 504702, 504715, 623204, 940394 and 614296); NIH grants CA63464, CA54281 and CA098758; US National Cancer Institute (R01CA128813, PI: J.Y. Park); Bulgarian National Science Fund, Ministry of Education and Science (contract DOO-119/2009; DUNK01/2–2009; DFNI-B01/28/2012); Cancer Research UK grants [C8197/A10123] and [C8197/A10865]; grant code G0500966/75466; NIHR Health Technology Assessment Programme (projects 96/20/06 and 96/20/99); Cancer Research UK grant number C522/A8649, Medical Research Council of England grant number G0500966, ID 75466 and The NCRI, UK; The US Dept of Defense award W81XWH-04-1-0280; Australia Project Grant [390130, 1009458] and Enabling Grant [614296 to APCB]; the Prostate Cancer Foundation of Australia (Project Grant [PG7] and Research infrastructure grant [to APCB]); NIH grant R01 CA092447; Vanderbilt-Ingram Cancer Center (P30 CA68485); Cancer Research UK [C490/A10124] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge; Competitive Research Funding of the Tampere University Hospital (9N069 and X51003); Award Number P30CA042014 from the National Cancer Institute.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/0.1038/ncomms1097