1617 Cells respond to external stimuli with transient gene expression changes in order to 18 adapt to environmental alterations. However, the dose response profile of gene 19 induction upon a given stress depends on many intrinsic and extrinsic factors. Here we 20show that the accurate quantification of dose dependent gene expression by live cell 21 luciferase reporters reveals fundamental insights into stress signaling. We make the 22 following discoveries applying this non-invasive reporter technology. (1) Signal 23 transduction sensitivities can be compared and we apply this here to salt, oxidative and 24 xenobiotic stress responsive transcription factors. (2) Stress signaling depends on where 25 and how the damage is generated within the cell. Specifically we show that two ROS-26 generating agents, menadione and hydrogen peroxide, differ in their dependence on 27 mitochondrial respiration. (3) Stress signaling is conditioned by the cells history. We 28 demonstrate here that positive memory or an acquired resistance towards oxidative 29 stress is induced dependent on the nature of the previous stress experience. (4) The 30 metabolic state of the cell impinges on the sensitivity of stress signaling. This is shown 31 here for the shift towards higher stress doses of the response profile for yeast cells 32 moved from complex to synthetic medium. (5) The age of the cell conditions its 33 transcriptional response capacity, which is demonstrated by the changes of the dose 34 response to oxidative stress during both replicative and chronological aging. We 35 conclude that capturing dose dependent gene expression in real time will be of 36 invaluable help to understand stress signaling and its dynamic modulation. 37 38 39 [16]. The yeast response to salt, nutrient or xenobiotic stress includes the simultaneous 57 activation of multiple, often structurally unrelated TFs [17,18,19]. Thus the use of 58 different transcriptional activators could create different gene expression patterns at 59 specific sets of target genes. Additionally, different TFs can form hierarchical networks 60 by regulatory connections between them [20,21,22], which makes it necessary to 61 determine the sensitivities of individual TFs. 62
Stress-activated TFs convert signals into a defined gene expression output by allowing 63RNAPII to engage in active transcription.Here, yet other regulatory mechanisms exist 64 to define the strength and timing of transcriptional activation. Active chromatin 65 remodeling is crucial for efficient stimulus-activated transcription. The nucleosome 66 structure of the inducible upstream region can determine the dynamics of the gene 67 expression at a given genomic locus, which has been reported for different stress and 68 developmental adaptations in yeast [23,24,25]. As a consequence, the response to 69 different stress doses might imply the contribution of distinct chromatin remodeling 70 complexes [26]. Finally the distribution of promoter binding sites and their affinity to 71 GRE2-luciferase reporter pAG413-pGRE...
IntroductionHigh-grade serous ovarian cancer (HGSOC) is the second most frequent gynecological malignancy but the most lethal, partially due to the spread of the disease through the peritoneal cavity. Recent evidence has shown that, apart from their role in immune defense through phagocytosis and degranulation, neutrophils are able to participate in cancer progression through the release of neutrophil extracellular traps (NETs) in a process called NETosis. NETs are composed of DNA, histones, calprotectin, myeloperoxidase (MPO) and elastase and the NETosis process has been proposed as a pre-requisite for the establishment of omental metastases in early stages of HGSOC. Nevertheless, its role in advanced stages remains to be elucidated. Therefore, our principal aim is to characterize a NETosis biomarker profile in biofluids from patients with advanced HGSOC and control women. MethodsSpecifically, five biomarkers of NETosis (cell-free DNA (cfDNA), nucleosomes, citrullinated histone 3 (citH3), calprotectin and MPO) were quantified in plasma and peritoneal fluid (PF) samples from patients (n=45) and control women (n=40).ResultsOur results showed that HGSOC patients presented a higher concentration of cfDNA, citH3 and calprotectin in plasma and of all five NETosis biomarkers in PF than control women. Moreover, these biomarkers showed a strong ability to differentiate the two clinical groups. Interestingly, neoadjuvant treatment (NT) seemed to reduce NETosis biomarkers mainly systemically (plasma) compared to the tumor environment (PF).DiscussionIn conclusion, NETosis biomarkers are present in the tumor environment of patients with advanced HGSOC, which might contribute to the progression of the disease. Besides, plasma cfDNA and calprotectin could represent minimally invasive surrogate biomarkers for HGSOC. Finally, NT modifies NETosis biomarkers levels mainly at the systemic level.
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