Early growth response-1 ( EGR1) is a transcription factor correlated with prostate cancer (PC) progression in a variety of contexts. For example, EGR1 levels increase in response to suppressed androgen receptor signaling or loss of the tumor suppressor, PTEN. EGR1 has been shown to regulate genes influencing proliferation, apoptosis, immune cell activation, and matrix degradation, among others. Despite this, the impact of EGR1 on PC metastatic colonization is unclear. We demonstrate using a PC model (DU145/RasB1) of bone and brain metastasis that EGR1 expression regulates angiogenic and osteoclastogenic properties of metastases. We have shown previously that FN14 (TNFRSF12A) and downstream NF-κB signaling is required for metastasis in this model. Here we demonstrate that FN14 ligation also leads to NF-κB-independent, MEK-dependent EGR1 expression. EGR1 -depletion in DU145/RasB1 cells reduced both the number and size of metastases but did not affect primary tumor growth. Decreased EGR1 expression led to reduced blood vessel density in brain and bone metastases as well as decreased osteolytic bone lesion area and reduced numbers of osteoclasts at the bone-tumor interface. TWEAK (TNFSF12) induced several EGR1 -dependent angiogenic and osteoclastogenic factors (e.g. PDGFA, TGFB1, SPP1, IL6, IL8, and TGFA, among others). Consistent with this, in clinical samples of PC, the level of several genes encoding angiogenic/osteoclastogenic pathway effectors correlated with EGR1 levels. Thus, we show here that EGR1 has a direct effect on prostate cancer metastases. EGR1 regulates angiogenic and osteoclastogenic factors, informing the underlying signaling networks that impact autonomous and microenvironmental mechanisms of cancer metastases.

Cotton is an important industrial crop worldwide and upland cotton (Gossypium hirsutum L.) is most widely cultivated in the world. Due to ever-increasing water deficit, drought stress brings a major threat to cotton production. Thus, it is important to reveal the genetic basis under drought stress and develop drought tolerant cotton cultivars. To address this issue, in present study, 319 upland cotton accessions were genotyped by 55,060 single nucleotide polymorphisms (SNPs) from high-density CottonSNP80K array and phenotyped nine drought tolerance related traits. The two datasets were used to identify quantitative trait nucleotides (QTNs) for the above nine traits using multi-locus random-SNP-effect mixed linear model method. As a result, a total of 20 QTNs distributed on 16 chromosomes were found to be significantly associated with six drought tolerance related traits. Of the 1,326 genes around the 20 QTNs, 205 were induced after drought stress treatment, and 46 were further mapped to Gene ontology (GO) term “response to stress.” Taken genome-wide association study (GWAS) analysis, RNA-seq data and qRT-PCR verification, four genes, RD2 encoding a response to desiccation 2 protein, HAT22 encoding a homeobox-leucine zipper protein, PIP2 encoding a plasma membrane intrinsic protein 2, and PP2C encoding a protein phosphatase 2C, were proposed to be potentially important for drought tolerance in cotton. These results will deepen our understanding of the genetic basis of drought stress tolerance in cotton and provide candidate markers to accelerate the development of drought-tolerant cotton cultivars.

We may want to keep sensitive information in a relational database hidden from a user or group thereof. We characterize sensitive data as the extensions of secrecy views. The database, before returning the answers to a query posed by a restricted user, is updated to make the secrecy views empty or a single tuple with null values. Then, a query about any of those views returns no meaningful information. Since the database is not supposed to be physically changed for this purpose, the updates are only virtual, and also minimal. Minimality makes sure that query answers, while being privacy preserving, are also maximally informative. The virtual updates are based on null values as used in the SQL standard. We provide the semantics of secrecy views, virtual updates, and secret answers to queries. The different instances resulting from the virtually updates are specified as the models of a logic program with stable model semantics, which becomes the basis for computation of the secret answers.Index Terms-Data privacy, views, query answering, null values, view updates, answer set programs, database repairs.

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