Major milestones in translational oncology.

Translational oncology represents a bridge between basic research and clinical practice in cancer medicine. Today, translational research in oncology benefits from an abundance of knowledge resulting from genome-scale studies regarding the molecular pathways involved in tumorigenesis. In this Forum article, we highlight the state of the art of translational oncology in five major cancer types. We illustrate the use of molecular profiling to subtype colorectal cancer for both diagnosis and treatment, and summarize the results of a nationwide screening program for ovarian cancer based on detection of a tumor biomarker in serum. Additionally, we discuss how circulating tumor DNA can be assayed to safely monitor breast cancer over the course of treatment, and report on how therapy with immune checkpoint inhibitors is proving effective in advanced lung cancer. Finally, we summarize efforts to use molecular profiling of prostate cancer biopsy specimens to support treatment decisions. Despite encouraging early successes, we cannot disregard the complex genetics of individual susceptibility to cancer nor the enormous complexity of the somatic changes observed in tumors, which urge particular attention to the development of personalized therapies

Assessment of upper tropospheric and stratospheric water vapor and ozone in reanalyses as part of S-RIP

Reanalysis data sets are widely used to understand atmospheric processes and past variability, and are often used to stand in as “observations” for comparisons with climate model output. Because of the central role of water vapor (WV) and ozone (O3) in climate change, it is important to understand how accurately and consistently these species are represented in existing global reanalyses. In this paper, we present the results of WV and O3 intercomparisons that have been performed as part of the SPARC (Stratosphere–troposphere Processes and their Role in Climate) Reanalysis Intercomparison Project (S-RIP). The comparisons cover a range of timescales and evaluate both inter-reanalysis and observation-reanalysis differences. We also provide a systematic documentation of the treatment of WV and O3 in current reanalyses to aid future research and guide the interpretation of differences amongst reanalysis fields. The assimilation of total column ozone (TCO) observations in newer reanalyses results in realistic representations of TCO in reanalyses except when data coverage is lacking, such as during polar night. The vertical distribution of ozone is also relatively well represented in the stratosphere in reanalyses, particularly given the relatively weak constraints on ozone vertical structure provided by most assimilated observations and the simplistic representations of ozone photochemical processes in most of the reanalysis forecast models. However, significant biases in the vertical distribution of ozone are found in the upper troposphere and lower stratosphere in all reanalyses

Summary and Highlights of the SPARC-Reanalysis Intercomparison Project

The climate research community uses global atmospheric reanalysis data sets to understand a wide range of processes and variability in the atmosphere; they are a particularly powerful tool for studying phenomena that cannot be directly observed. Different reanalyses may give very different results for the same diagnostics. The Stratosphere troposphere Processes And their Role in Climate (SPARC) Reanalysis Intercomparison Project (S-RIP) is a coordinated activity to compare key diagnostics that are important for stratospheric processes and their tropospheric connections among available reanalyses. S-RIP has been identifying differences among reanalyses and their underlying causes, providing guidance on appropriate usage of reanalysis products in scientific studies (particularly those of relevance to SPARC), and contributing to future improvements in the reanalysis products by establishing collaborative links between reanalysis centres and data users. S-RIP emphasizes diagnostics of the upper troposphere, stratosphere, and lower mesosphere. The draft S-RIP final report is expected to be completed in 2018. This poster gives a summary of the S-RIP project and presents highlights including results on the Brewer-Dobson circulation, stratosphere/troposphere dynamical coupling, the extra-tropical upper troposphere / lower stratosphere, the tropical tropopause layer, the quasi-biennial oscillation, lower stratospheric polar processing, and the upper stratosphere/lower mesosphere

Numerical simulation of wind waves on the Río de la Plata: evaluation of four global atmospheric databases

The performance of NCEP/NCAR I, NCEP/DOE II, JRA-25 and ERA-Interim global databases, implemented as atmospheric forcings of the SWAN model in the Río de la Plata region, was quantitatively tested by calculating the bias, the mean square root error, the determination coefficient and the slope of the line fitted between observed and simulated wave parameters (significant wave height, mean period and direction). Even though statistical estimators showed no evident differences for wave periods and directions some noticeable differences were observed for simulated significant wave heights depending on the forcing used. The lowest bias (0.22 m) was obtained when the SWAN model was forced by ERA-Interim. With regard to the mean square root errors, the lowest values were obtained when NCEP/NCAR I (0.16 m) and NCEP/DOE II (0.19 m) were used as forcing. In addition, the best slope for simulated heights (0.79) was obtained using NCEP/DOE II. Computed determination coefficients for heights, periods and directions were very similar (0.89-0.93) for all the simulations carried out in this study. Energetic and severe wave events were given special consideration. The most energetic wave episode recorded in the Río de la Plata mouth (24 August, 2005) was analyzed and discussed in particular. It was concluded that during energetic atmospheric conditions the best agreement is achieved by implementing NCEP/DOE II as forcing. In the light of these results it is concluded that NCEP/DOE II is the most suitable atmospheric forcing to simulate wave heights with the SWAN model in the Río de la Plata region.Na região do Rio de la Plata, o desempenho das reanálises globais do NCEP/NCAR I, NCEP/DOE II, JRA-25 e ERAInterim implementadas como forçantes atmosféricas do modelo SWAN foram quantitativamente acessados através do viés, erro quadrático médio, coeficiente de determinação e inclinação da reta. Estes índices foram obtidos dos parâmetros de ondas observados e simulados (alturas significativas de ondas, período principal e direção). Embora as estimativas estatísticas não mostrem diferenças evidentes para períodos e direções, algumas diferenças notáveis foram obtidas para altura de ondas simuladas, dependendo do vento utilizado. O menor viés para altura significativa (0.22 m) foi obtido quando o SWAM foi forçado com a ERAInterim, enquanto o NCEP/NCAR I (0.16 m) e NCEP/DOE II (0.19 m) forneceram menor erro quadrático médio. A melhor inclinação da reta entre simulação e observação de altura significativa (0.79) foi obtida usando NCEP/DOE II. No período de estudo, o maior episódio de onda registrado na boca do Río de la Plata foi analisado e discutido. Neste evento de condições atmosféricas energéticas o melhor ajuste foi alcançado utilizando os ventos do NCEP/DOE II como forçante. Conclui-se que a base de dados NCEP/DOE II é forçante atmosférica mais adequada para simular alturas significativas de ondas com o modelo SWAN na região estudada

Identification of BC005512 as a DNA Damage Responsive Murine Endogenous Retrovirus of GLN Family Involved in Cell Growth Regulation

Genotoxicity assessment is of great significance in drug safety evaluation, and microarray is a useful tool widely used to identify genotoxic stress responsive genes. In the present work, by using oligonucleotide microarray in an in vivo model, we identified an unknown gene BC005512 (abbreviated as BC, official full name: cDNA sequence BC005512), whose expression in mouse liver was specifically induced by seven well-known genotoxins (GTXs), but not by non-genotoxins (NGTXs). Bioinformatics revealed that BC was a member of the GLN family of murine endogenous retrovirus (ERV). However, the relationship to genotoxicity and the cellular function of GLN are largely unknown. Using NIH/3T3 cells as an in vitro model system and quantitative real-time PCR, BC expression was specifically induced by another seven GTXs, covering diverse genotoxicity mechanisms. Additionally, dose-response and linear regression analysis showed that expression level of BC in NIH/3T3 cells strongly correlated with DNA damage, measured using the alkaline comet assay,. While in p53 deficient L5178Y cells, GTXs could not induce BC expression. Further functional studies using RNA interference revealed that down-regulation of BC expression induced G1/S phase arrest, inhibited cell proliferation and thus suppressed cell growth in NIH/3T3 cells. Together, our results provide the first evidence that BC005512, a member from GLN family of murine ERV, was responsive to DNA damage and involved in cell growth regulation. These findings could be of great value in genotoxicity predictions and contribute to a deeper understanding of GLN biological functions

Standing genetic variation and compensatory evolution in transgenic organisms: a growth-enhanced salmon simulation

Genetically modified strains usually are generated within defined genetic backgrounds to minimize variation for the engineered characteristic in order to facilitate basic research investigations or for commercial application. However, interactions between transgenes and genetic background have been documented in both model and commercial agricultural species, indicating that allelic variation at transgene-modifying loci are not uncommon in genomes. Engineered organisms that have the potential to allow entry of transgenes into natural populations may cause changes to ecosystems via the interaction of their specific phenotypes with ecosystem components and services. A transgene introgressing through natural populations is likely to encounter a range of natural genetic variation (among individuals or sub-populations) that could result in changes in phenotype, concomitant with effects on fitness and ecosystem consequences that differ from that seen in the progenitor transgenic strain. In the present study, using a growth hormone transgenic salmon example, we have modeled selection of modifier loci (single and multiple) in the presence of a transgene and have found that accounting for genetic background can significantly affect the persistence of transgenes in populations, potentially reducing or reversing a “Trojan gene” effect. Influences from altered life history characteristics (e.g., developmental timing, age of maturation) and compensatory demographic/ecosystem controls (e.g., density dependence) also were found to have a strong influence on transgene effects. Further, with the presence of a transgene in a population, genetic backgrounds were found to shift in non-transgenic individuals as well, an effect expected to direct phenotypes away from naturally selected optima. The present model has revealed the importance of understanding effects of selection for background genetics on the evolution of phenotypes in populations harbouring transgenes