Replication Stress Drives Constitutive Activation of the DNA Damage Response and Radioresistance in Glioblastoma Stem-like Cells

Glioblastoma (GBM) is a lethal primary brain tumor characterized by treatment resistance and inevitable tumor recurrence, both of which are driven by a subpopulation of GBM cancer stem-like cells (GSC) with tumorigenic and self-renewal properties. Despite having broad implications for understanding GSC phenotype, the determinants of upregulated DNA damage response (DDR) and subsequent radiation resistance in GSC are unknown and represent a significant barrier to developing effective GBM treatments. In this study, we show that constitutive DDR activation and radiation resistance are driven by high levels of DNA replication stress (RS). CD133+ GSC exhibited reduced DNA replication velocity and a higher frequency of stalled replication forks than CD133- non-GSC in vitro; immunofluorescence studies confirmed these observations in a panel of orthotopic xenografts and human GBM specimens. Exposure of non-GSC to low-level exogenous RS generated radiation resistance in vitro, confirming RS as a novel determinant of radiation resistance in tumor cells. GSC exhibited DNA double strand breaks (DSB) which co-localized with 'replication factories' and RNA: DNA hybrids. GSC also demonstrated increased expression of long neural genes (>1Mbp) containing common fragile sites, supporting the hypothesis that replication/transcription collisions are the likely cause of RS in GSC. Targeting RS by combined inhibition of ATR and PARP (CAiPi) provided GSC-specific cytotoxicity and complete abrogation of GSC radiation resistance in vitro. These data identify RS as a cancer stem cell-specific target with significant clinical potential

Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorder

Funding Information: Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006] and is currently supported by the Wellcome Trust [216767/Z/19/Z]. Genotyping of the GS:SFHS samples was carried out by the Genetics Core Laboratory at the Edinburgh Clinical Research Facility, University of Edinburgh, Scotland and was funded by the Medical Research Council UK and the Wellcome Trust (Wellcome Trust Strategic Award “STratifying Resilience and Depression Longitudinally” (STRADL) Reference 104036/Z/14/Z). CG is supported by The Medical Research Council and The University of Edinburgh through the Precision Medicine Doctoral Training program. SRC is supported by the UK Medical Research Council [MR/R024065/1] and a National Institutes of Health (NIH) research grant R01AG054628. Acknowledgements The authors thank all of the STRADL and Generation Scotland participants for their time and effort taking part in this study. We would also like to thank all of the research assistants, clinicians and technicians for their help in the collecting this data.Peer reviewedPublisher PD

Multiomics Longitudinal Modeling of Preeclamptic Pregnancies

Preeclampsia is a complex disease of pregnancy whose physiopathology remains unclear and that poses a threat to both mothers and infants. Specific complex changes in women\u27s physiology precede a diagnosis of preeclampsia. Understanding multiple aspects of such a complex changes at different levels of biology, can be enabled by simultaneous application of multiple assays. We developed prediction models for preeclampsia risk by analyzing six omics datasets from a longitudinal cohort of pregnant women. A machine learning-based multiomics model had high accuracy (area under the receiver operating characteristics curve (AUC) of 0.94, 95% confidence intervals (CI):[0.90, 0.99]). A prediction model using only ten urine metabolites provided an accuracy of the whole metabolomic dataset and was validated using an independent cohort of 16 women (AUC= 0.87, 95% CI:[0.76, 0.99]). Integration with clinical variables further improved prediction accuracy of the urine metabolome model (AUC= 0.90, 95% CI:[0.80, 0.99], urine metabolome, validated). We identified several biological pathways to be associated with preeclampsia. The findings derived from models were integrated with immune system cytometry data, confirming known physiological alterations associated with preeclampsia and suggesting novel associations between the immune and proteomic dynamics. While further validation in larger populations is necessary, these encouraging results will serve as a basis for a simple, early diagnostic test for preeclampsia

Cumulative Prognostic Score Predicting Mortality in Patients Older Than 80 Years Admitted to the ICU.

OBJECTIVES: To develop a scoring system model that predicts mortality within 30 days of admission of patients older than 80 years admitted to intensive care units (ICUs). DESIGN: Prospective cohort study. SETTING: A total of 306 ICUs from 24 European countries. PARTICIPANTS: Older adults admitted to European ICUs (N = 3730; median age = 84 years [interquartile range = 81-87 y]; 51.8% male). MEASUREMENTS: Overall, 24 variables available during ICU admission were included as potential predictive variables. Multivariable logistic regression was used to identify independent predictors of 30-day mortality. Model sensitivity, specificity, and accuracy were evaluated with receiver operating characteristic curves. RESULTS: The 30-day-mortality was 1562 (41.9%). In multivariable analysis, these variables were selected as independent predictors of mortality: age, sex, ICU admission diagnosis, Clinical Frailty Scale, Sequential Organ Failure Score, invasive mechanical ventilation, and renal replacement therapy. The discrimination, accuracy, and calibration of the model were good: the area under the curve for a score of 10 or higher was .80, and the Brier score was .18. At a cut point of 10 or higher (75% of all patients), the model predicts 30-day mortality in 91.1% of all patients who die. CONCLUSION: A predictive model of cumulative events predicts 30-day mortality in patients older than 80 years admitted to ICUs. Future studies should include other potential predictor variables including functional status, presence of advance care plans, and assessment of each patient's decision-making capacity

Organization of multiprotein complexes at cell–cell junctions

The formation of stable cell–cell contacts is required for the generation of barrier-forming sheets of epithelial and endothelial cells. During various physiological processes like tissue development, wound healing or tumorigenesis, cellular junctions are reorganized to allow the release or the incorporation of individual cells. Cell–cell contact formation is regulated by multiprotein complexes which are localized at specific structures along the lateral cell junctions like the tight junctions and adherens junctions and which are targeted to these site through their association with cell adhesion molecules. Recent evidence indicates that several major protein complexes exist which have distinct functions during junction formation. However, this evidence also indicates that their composition is dynamic and subject to changes depending on the state of junction maturation. Thus, cell–cell contact formation and integrity is regulated by a complex network of protein complexes. Imbalancing this network by oncogenic proteins or pathogens results in barrier breakdown and eventually in cancer. Here, I will review the molecular organization of the major multiprotein complexes at junctions of epithelial cells and discuss their function in cell–cell contact formation and maintenance

Sepsis at ICU admission does not decrease 30-day survival in very old patients: a post-hoc analysis of the VIP1 multinational cohort study.

BACKGROUND: The number of intensive care patients aged ≥ 80 years (Very old Intensive Care Patients; VIPs) is growing. VIPs have high mortality and morbidity and the benefits of ICU admission are frequently questioned. Sepsis incidence has risen in recent years and identification of outcomes is of considerable public importance. We aimed to determine whether VIPs admitted for sepsis had different outcomes than those admitted for other acute reasons and identify potential prognostic factors for 30-day survival. RESULTS: This prospective study included VIPs with Sequential Organ Failure Assessment (SOFA) scores ≥ 2 acutely admitted to 307 ICUs in 21 European countries. Of 3869 acutely admitted VIPs, 493 (12.7%) [53.8% male, median age 83 (81-86) years] were admitted for sepsis. Sepsis was defined according to clinical criteria; suspected or demonstrated focus of infection and SOFA score ≥ 2 points. Compared to VIPs admitted for other acute reasons, VIPs admitted for sepsis were younger, had a higher SOFA score (9 vs. 7, p < 0.0001), required more vasoactive drugs [82.2% vs. 55.1%, p < 0.0001] and renal replacement therapies [17.4% vs. 9.9%; p < 0.0001], and had more life-sustaining treatment limitations [37.3% vs. 32.1%; p = 0.02]. Frailty was similar in both groups. Unadjusted 30-day survival was not significantly different between the two groups. After adjustment for age, gender, frailty, and SOFA score, sepsis had no impact on 30-day survival [HR 0.99 (95% CI 0.86-1.15), p = 0.917]. Inverse-probability weight (IPW)-adjusted survival curves for the first 30 days after ICU admission were similar for acute septic and non-septic patients [HR: 1.00 (95% CI 0.87-1.17), p = 0.95]. A matched-pair analysis in which patients with sepsis were matched with two control patients of the same gender with the same age, SOFA score, and level of frailty was also performed. A Cox proportional hazard regression model stratified on the matched pairs showed that 30-day survival was similar in both groups [57.2% (95% CI 52.7-60.7) vs. 57.1% (95% CI 53.7-60.1), p = 0.85]. CONCLUSIONS: After adjusting for organ dysfunction, sepsis at admission was not independently associated with decreased 30-day survival in this multinational study of 3869 VIPs. Age, frailty, and SOFA score were independently associated with survival