ER stress drives Lipocalin 2 upregulation in prostate cancer cells in an NF-κB-dependent manner

<p>Abstract</p> <p>Background</p> <p>Tumor cells adapt to endoplasmic reticulum (ER) stress through a set of conserved intracellular pathways, as part of a process termed the unfolded protein response (UPR). The expression of UPR genes/proteins correlates with increasing progression and poor clinical outcome of several tumor types, including prostate cancer. UPR signaling can activate NF-κB, a master regulator of transcription of pro-inflammatory, tumorigenic cytokines. Previous studies have shown that Lipocalin 2 (Lcn2) is upregulated in several epithelial cancers, including prostate cancer, and recently Lcn2 was implicated as a key mediator of breast cancer progression. Here, we hypothesize that the tumor cell UPR regulates Lcn2 production.</p> <p>Methods</p> <p>We interrogated Lcn2 regulation in murine and human prostate cancer cells undergoing pharmacological and physiological ER stress, and tested UPR and NF-κB dependence by using pharmacological inhibitors of these signaling pathways.</p> <p>Results</p> <p>Induction of ER stress using thapsigargin (Tg), a canonical pharmacologic ER stress inducer, or via glucose deprivation, a physiologic ER stressor present in the tumor microenvironment, upregulates LCN2 production in murine and human prostate cancer cells. Inhibition of the UPR using 4-phenylbutyric acid (PBA) dramatically decreases Lcn2 transcription and translation. Inhibition of NF-κB in prostate cancer cells undergoing Tg-mediated ER stress by BAY 11-7082 abrogates Lcn2 upregulation.</p> <p>Conclusions</p> <p>We conclude that the UPR activates Lcn2 production in prostate cancer cells in an NF-κB-dependent manner. Our results imply that the observed upregulation of Lipocalin 2 in various types of cancer cells may be the direct consequence of concomitant UPR activation, and that the ER stress/Lipocalin 2 axis is a potential new target for intervention in cancer progression.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

QCD and strongly coupled gauge theories : challenges and perspectives

We highlight the progress, current status, and open challenges of QCD-driven physics, in theory and in experiment. We discuss how the strong interaction is intimately connected to a broad sweep of physical problems, in settings ranging from astrophysics and cosmology to strongly coupled, complex systems in particle and condensed-matter physics, as well as to searches for physics beyond the Standard Model. We also discuss how success in describing the strong interaction impacts other fields, and, in turn, how such subjects can impact studies of the strong interaction. In the course of the work we offer a perspective on the many research streams which flow into and out of QCD, as well as a vision for future developments.Peer reviewe

TRY plant trait database - enhanced coverage and open access

Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

An enigma in the genetic responses of plants to salt stresses

Soil salinity is one of the main factors restricting crop production throughout the world. Various salt tolerance traits and the genes controlling these traits are responsible for coping with salinity stress in plants. These coping mechanisms include osmotic tolerance, ion exclusion, and tissue tolerance. Plants exposed to salinity stress sense the stress conditions, convey specific stimuli signals, and initiate responses against stress through the activation of tolerance mechanisms that include multiple genes and pathways. Advances in our understanding of the genetic responses of plants to salinity and their connections with yield improvement are essential for attaining sustainable agriculture. Although a wide range of studies have been conducted that demonstrate genetic variations in response to salinity stress, numerous questions need to be answered to fully understand plant tolerance to salt stress. This chapter provides an overview of previous studies on the genetic control of salinity stress in plants, including signaling, tolerance mechanisms, and the genes, pathways, and epigenetic regulators necessary for plant salinity tolerance