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Background: Cirrhosis is known to have a high prevalence and mortality worldwide. However, in Europe, the epidemiology of cirrhosis is possibly undergoing demographic changes, and etiologies may have changed due to improvements in standard of care. The aim of this population-based study was to analyze the trends and the course of liver cirrhosis and its complications in recent years in Germany.
Methods: We analyzed the data of all hospital admissions in Germany within diagnosis-related groups from 2005 to 2018. The diagnostic records of cirrhosis and other categories of diseases were based on ICD-10-GM codes. The primary outcome measurement was in-hospital mortality. Trends were analyzed through Poisson regression of annual number of admissions. The impact of cirrhosis on overall in-hospital mortality were assessed through the multivariate multilevel logistic regression model adjusted for age, sex, and comorbidities.
Findings: Of the 248,085,936 admissions recorded between 2005 and 2018, a total of 2,302,171(0•94%) were admitted with the diagnosis of cirrhosis, mainly as a comorbidity. Compared with other chronic diseases, patients admitted with cirrhosis were younger, mainly male and had the highest in-hospital mortality rate. Diagnosis of cirrhosis was an independent risk factor of in-hospital mortality with the highest odds ratio (OR:6•2[95%CI:6.1-6•3]) among all diagnoses. The prevalence of non-alcoholic fatty liver disease has increased four times from 2005 to 2018, while alcoholic cirrhosis is 20 times than other etiologies. Bleeding was found to be decreasing over time, but ascites remained the most common complication and was increasing.
Interpretation: This nationwide study demonstrates that cirrhosis represents a considerable healthcare burden, as shown by the increasing in-hospital mortality, also in combination with other chronic diseases. Alcohol-related cirrhosis and complications are on the rise. More resources and better management strategies are warranted.
Genome-wide CRISPR screens are becoming more widespread and allow the simultaneous interrogation of thousands of genomic regions. Although recent progress has been made in the analysis of CRISPR screens, it is still an open problem how to interpret CRISPR mutations in non-coding regions of the genome. Most of the tools concentrate on the interpretation of mutations introduced in gene coding regions. We introduce a computational pipeline that uses epigenomic information about regulatory elements for the interpretation of CRISPR mutations in non-coding regions. We illustrate our approach on the analysis of a genome-wide CRISPR screen in hTERT-RPE-1 cells and reveal novel regulatory elements that mediate chemoresistance against doxorubicin in these cells. We infer links to established and to novel chemoresistance genes. Our approach is general and can be applied on any cell type and with different CRISPR enzymes.
Understanding the complexity of transcriptional regulation is a major goal of computational biology. Because experimental linkage of regulatory sites to genes is challenging, computational methods considering epigenomics data have been proposed to create tissue-specific regulatory maps. However, we showed that these approaches are not well suited to account for the variations of the regulatory landscape between cell-types. To overcome these drawbacks, we developed a new method called STITCHIT, that identifies and links putative regulatory sites to genes. Within STITCHIT, we consider the chromatin accessibility signal of all samples jointly to identify regions exhibiting a signal variation related to the expression of a distinct gene. STITCHIT outperforms previous approaches in various validation experiments and was used with a genome-wide CRISPR-Cas9 screen to prioritize novel doxorubicin-resistance genes and their associated non-coding regulatory regions. We believe that our work paves the way for a more refined understanding of transcriptional regulation at the gene-level.
Understanding how epigenetic variation in non-coding regions is involved in distal gene-expression regulation is an important problem. Regulatory regions can be associated to genes using large-scale datasets of epigenetic and expression data. However, for regions of complex epigenomic signals and enhancers that regulate many genes, it is difficult to understand these associations. We present StitchIt, an approach to dissect epigenetic variation in a gene-specific manner for the detection of regulatory elements (REMs) without relying on peak calls in individual samples. StitchIt segments epigenetic signal tracks over many samples to generate the location and the target genes of a REM simultaneously. We show that this approach leads to a more accurate and refined REM detection compared to standard methods even on heterogeneous datasets, which are challenging to model. Also, StitchIt REMs are highly enriched in experimentally determined chromatin interactions and expression quantitative trait loci. We validated several newly predicted REMs using CRISPR-Cas9 experiments, thereby demonstrating the reliability of StitchIt. StitchIt is able to dissect regulation in superenhancers and predicts thousands of putative REMs that go unnoticed using peak-based approaches suggesting that a large part of the regulome might be uncharted water.
Background and Aims: In patients with Rat sarcoma proto-oncogene (RAS) wild-type metastatic colorectal cancer (mCRC), anti-epidermal growth factor receptor (EGFR) antibodies have been established in first- and further therapy lines. Due to limited treatment options upon disease progression, anti-EGFR re-exposure is increasingly employed in real-world oncology. The aim of this study was to assess clinical implementation and utility of anti-EGFR retreatment strategies in real-world mCRC patients. Methods: In this monocentric retrospective study, we included 524 patients with CRC and identified patients who received an anti-EGFR-based treatment as well as anti-EGFR rechallenge (progression on first-line anti-EGFR therapy) or reintroduction (discontinuation due to intolerance/toxicity/other). Results: In total, 143 patients received an anti-EGFR-based first- or second-line treatment, showing a similar overall survival (OS) compared to the non-anti-EGFR treatment group (38.3 vs. 39.6 months, p = 0.88). Thirty-three patients met the inclusion criteria for anti-EGFR re-exposure and were either assigned to rechallenge (n = 21) or reintroduction (n = 12) subgroups. The median FU after re-exposure was 45.8 months. Cetuximab and Panitumumab were used in 21 and 12 patients, respectively, and the main chemotherapy at re-exposure was FOLFIRI in 39.4%. Anti-EGFR re-exposure was associated with a distinct trend towards a better outcome (median OS 56.0 vs. 35.4 months, p = 0.06). In a subgroup comparison, reintroduction was associated with a higher OS and PFS in trend compared to the rechallenge (mOS 66 vs. 52.4, n.s., mPFS 7.33 vs. 3.68 months, n.s.). Conclusions: This retrospective study provides real-world evidence underscoring that anti-EGFR re-exposure strategies might benefit patients independently of the reason for prior discontinuation.