SWI/SNF regulates a transcriptional programme that induces senescence to prevent liver cancer

Oncogene-induced senescence (OIS) is a potent tumour suppressor mechanism. To identify senescence regulators relevant to cancer, we screened an shRNA library targeting genes deleted in hepatocellular carcinoma (HCC). Here, we describe how knockdown of the SWI/SNF component ARID1B prevents OIS and cooperates with RAS to induce liver tumours. ARID1B controls p16INK4a and p21CIP1a transcription but also regulates DNA damage, oxidative stress and p53 induction, suggesting that SWI/SNF uses additional mechanisms to regulate senescence. To systematically identify SWI/SNF targets regulating senescence, we carried out a focused shRNA screen. We discovered several new senescence regulators including ENTPD7, an enzyme that hydrolyses nucleotides. ENTPD7 affects oxidative stress, DNA damage and senescence. Importantly, expression of ENTPD7 or inhibition of nucleotide synthesis in ARID1B-depleted cells results in re-establishment of senescence. Our results identify novel mechanisms by which epigenetic regulators can affect tumor progression and suggest that pro-senescence therapies could be employed against SWI/SNF-mutated cancers

Correlation-Adjusted Regression Survival Scores for High-Dimensional Variable Selection

Background The development of classification methods for personalized medicine is highly dependent on the identification of predictive genetic markers. In survival analysis it is often necessary to discriminate between influential and non-influential markers. It is common to perform univariate screening using Cox scores, which quantify the associations between survival and each of the markers to provide a ranking. Since Cox scores do not account for dependencies between the markers, their use is suboptimal in the presence highly correlated markers. Methods As an alternative to the Cox score, we propose the correlation-adjusted regression survival (CARS) score for right-censored survival outcomes. By removing the correlations between the markers, the CARS score quantifies the associations between the outcome and the set of “de-correlated” marker values. Estimation of the scores is based on inverse probability weighting, which is applied to log-transformed event times. For high-dimensional data, estimation is based on shrinkage techniques. Results The consistency of the CARS score is proven under mild regularity conditions. In simulations with high correlations, survival models based on CARS score rankings achieved higher areas under the precision-recall curve than competing methods. Two example applications on prostate and breast cancer confirmed these results. CARS scores are implemented in the R package carSurv. Conclusions In research applications involving high-dimensional genetic data, the use of CARS scores for marker selection is a favorable alternative to Cox scores even when correlations between covariates are low. Having a straightforward interpretation and low computational requirements, CARS scores are an easy-to-use screening tool in personalized medicine research.This research was supported by the Deutsche Forschungsgemeinschaft (Project SCHM 2966/1-2), Wellcome Trust and the Royal Society (Grant Number 204623/Z/16/Z) and the UK Medical Research Council (Grant Number MC_UU_00002/7

Gd-149:What's confirmed? What's new?

A long run performed with EUROGAM II allowed remeasuring the Gd-149 superdeformed (SD) band 1. The Delta I = 4 bifurcation in band 1 is confirmed and two resolved gamma-ray transitions linking the SD band 1 and the normal deformed states have been observed

Gd-149:What's confirmed? What's new?

A long run performed with EUROGAM II allowed remeasuring the Gd-149 superdeformed (SD) band 1. The Delta I = 4 bifurcation in band 1 is confirmed and two resolved gamma-ray transitions linking the SD band 1 and the normal deformed states have been observed