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The developmental transcription factor SOX4 contributes to the metastatic spread of multiple solid cancer types, but its direct target genes that mediate cancer progression are not well defined. Using a systematic molecular and genomic approach, we identified the TMEM2 transmembrane protein gene as a direct transcriptional target of SOX4. TMEM2 was transcriptionally activated by SOX4 in breast cancer cells where, likeSOX4, TMEM2 was found to mediate proinvasive and promigratory effects. Similarly, TMEM2 was sufficient to promote metastatic colonization of breast cancer cells and its expression in primary breast tumors associated with a higher likelihood of metastatic relapse. Given earlier evidence that genetic inactivation of SOX4 or TMEM2 yield similar defects in cardiac development, our findings lead us to propose that TMEM2 may not only mediate the pathologic effects of SOX4 on cancer progression but also potentially its contributions to embryonic development. (C) 2016 AACR.

Taylor's law says that the variance of population density of a species is proportional to a power of mean population density. Density-mass allometry says that mean population density is proportional to a power of mean biomass per individual. These power laws predict a third, variance-mass allometry: the variance of population density of a species is proportional to a power of mean biomass per individual. We tested these laws using 10 censuses of New Zealand mountain beech trees in 250 plots over 30 years at spatial scales from 5 m to kilometers. We found that: 1) a single-species forest not disrupted by humans obeyed all three laws; 2) random sampling explained the parameters of Taylor's law at a large spatial scale in 8 of 10 censuses, but not at a fine spatial scale; 3) larger spatial scale increased the exponent of Taylor's law and decreased the exponent of variance-mass allometry (this is the first empirical demonstration that the latter exponent depends on spatial scale), but affected the exponent of density-mass allometry slightly; 4) despite varying natural disturbance, the three laws varied relatively little over the 30 years; 5) self-thinning and recruiting plots had significantly different intercepts and slopes of density-mass allometry and variance-mass allometry, but the parameters of Taylor's law were not usually significantly affected; and 6) higher soil calcium was associated with higher variance of population density in all censuses but not with a difference in the exponent of Taylor's law, while elevation above sea level and soil carbon-to-nitrogen ratios had little effect on the parameters of Taylor's law. In general, the three laws were remarkably robust. When their parameters were influenced by spatial scale and environmental factors, the parameters could not be species-specific indicators. We suggest biological mechanisms that may explain some of these findings.

DNA double-strand breaks (DSBs) are rare, but highly toxic, lesions requiring orchestrated and conserved machinery to prevent adverse consequences, such as cell death and cancer-causing genome structural mutations. DSBs trigger the DNA damage response (DDR) that directs a cell to repair the break, undergo apoptosis, or become senescent. There is increasing evidence that the various endpoints of DSB processing by different cells and tissues are part of the aging phenotype, with each stage of the DDR associated with specific aging pathologies. In this Perspective, we discuss the possibility that DSBs are major drivers of intrinsic aging, highlighting the dynamics of spontaneous DSBs in relation to aging, the distinct age-related pathologies induced by DSBs, and the segmental progeroid phenotypes in humans and mice with genetic defects in DSB repair. A model is presented as to how DSBs could drive some of the basic mechanisms underlying age-related functional decline and death.

Targeting the signaling pathway of the immunosuppressive metabolite adenosine is an emerging approach for cancer immunotherapy. In this issue of Cancer Cell, Young et al. describe that co-inhibition of the adenosingenic pathway through blockade of both CD73 and A2AR enhances antitumor efficacy through distinct mechanisms.

The level of activity of many animals including humans rises and falls with a period of similar to 24 hours. The intrinsic biological oscillator that gives rise to this circadian oscillation is driven by a molecular feedback loop with an approximately 24 hour cycle period and is influenced by the environment, most notably the light: dark cycle. In addition to the circadian oscillations, behavior of many animals is influenced by multiple oscillations occurring at fasterultradian-time scales. These ultradian oscillations are also thought to be driven by feedback loops. While many studies have focused on identifying such ultradian oscillations, less is known about how the ultradian behavioral oscillations interact with each other and with the circadian oscillation. Decoding the coupling among the various physiological oscillators may be important for understanding how they conspire together to regulate the normal activity levels, as well in disease states in which such rhythmic fluctuations in behavior may be disrupted. Here, we use a wavelet-based cross-frequency analysis to show that different oscillations identified in spontaneous mouse behavior are coupled such that the amplitude of oscillations occurring at higher frequencies are modulated by the phase of the slower oscillations. The patterns of these interactions are different among different individuals. Yet this variability is not random. Differences in the pattern of interactions are confined to a low dimensional subspace where different patterns of interactions formclusters. These clusters expose the differences among individuals-males and females are preferentially segregated into different clusters. These sex-specific features of spontaneous behavior were not apparent in the spectra. Thus, our methodology reveals novel aspects of the structure of spontaneous animal behavior that are not observable using conventional methodology.

Allostatic load (AL) is a complex clinical construct, providing a unique window into the cumulative impact of stress. However, due to its inherent complexity, AL presents two major measurement challenges to conventional statistical modeling (the field's dominant methodology): it is comprised of a complex causal network of bioallostatic systems, represented by an even larger set of dynamic biomarkers; and, it is situated within a web of antecedent socioecological systems, linking AL to differences in health outcomes and disparities. To address these challenges, we employed case-based computational modeling (CBM), which allowed us to make four advances: (1) we developed a multisystem, 7-factor (20 biomarker) model of AL's network of allostatic systems; (2) used it to create a catalog of nine different clinical AL profiles (causal pathways); (3) linked each clinical profile to a typology of 23 health outcomes; and (4) explored our results (post hoc) as a function of gender, a key socioecological factor. In terms of highlights, (a) the Healthy clinical profile had few health risks; (b) the pro-inflammatory profile linked to high blood pressure and diabetes; (c) Low Stress Hormones linked to heart disease, TIA/Stroke, diabetes, and circulation problems; and (d) high stress hormones linked to heart disease and high blood pressure. Post hoc analyses also found that males were overrepresented on the High Blood Pressure (61.2%), Metabolic Syndrome (63.2%), High Stress Hormones (66.4%), and High Blood Sugar (57.1%); while females were overrepresented on the Healthy (81.9%), Low Stress Hormones (66.3%), and Low Stress Antagonists (stress buffers) (95.4%) profiles. (C) 2015 Wiley Periodicals, Inc.

The intestinal microbiome modulates host susceptibility to enteric pathogens, but the specific protective factors and mechanisms of individual bacterial species are not fully characterized. We show that secreted antigen A (SagA) from Enterococcus faecium is sufficient to protect Caenorhabditis elegans against Salmonella pathogenesis by promoting pathogen tolerance. The NlpC/p60 peptidoglycan hydrolase activity of SagA is required and generates muramyl-peptide fragments that are sufficient to protect C. elegans against Salmonella pathogenesis in a tol-1-dependent manner. SagA can also be heterologously expressed and secreted to improve the protective activity of probiotics against Salmonella pathogenesis in C. elegans and mice. Our study highlights how protective intestinal bacteria can modify microbial-associated molecular patterns to enhance pathogen tolerance.

The unexpected emergence of Zika virus (ZIKV) in the Pacific Islands and Latin America and its association with congenital Zika virus syndrome (CZVS) (which includes microcephaly) and Guillain-Barre syndrome (GBS) have stimulated wide-ranging research. High densities of susceptible Aedes spp., immunologically naive human populations, global population growth with increased urbanization, and escalation of global transportation of humans and commercial goods carrying vectors and ZIKV undoubtedly enhanced the emergence of ZIKV. However, flavivirus mutations accumulate with time, increasing the likelihood that genetic viral differences are determinants of change in viral phenotype. Based on comparative ZIKV complete genome phylogenetic analyses and temporal estimates, we identify amino acid substitutions that may be associated with increased viral epidemicity, CZVS, and GBS. Reverse genetics, vector competence, and seroepidemiological studies will test our hypothesis that these amino acid substitutions are determinants of epidemic and neurotropic ZIKV emergence.