DNA methylation dynamics during intestinal stem cell differentiation reveals enhancers driving gene expression in the villus

Background: DNA methylation is of pivotal importance during development. Previous genome-wide studies identified numerous differentially methylated regions upon differentiation of stem cells, many of them associated with transcriptional start sites. Results: We present the first genome-wide, single-base-resolution view into DNA methylation dynamics during differentiation of a mammalian epithelial stem cell: the mouse small intestinal Lgr5+ stem cell. Very little change was observed at transcriptional start sites and our data suggest that differentiation-related genes are already primed for expression in the stem cell. Genome-wide, only 50 differentially methylated regions were identified. Almost all of these loci represent enhancers driving gene expression in the differentiated part of the small intestine. Finally, we show that binding of the transcription factor Tcf4 correlates with hypo-methylation and demonstrate that Tcf4 is one of the factors contributing to formation of differentially methylated regions. Conclusions: Our results reveal limited DNA methylation dynamics during small intestine stem cell differentiation and an impact of transcription factor binding on shaping the DNA methylation landscape during differentiation of stem cells in vivo

Patient-Derived Xenografts and Organoids Recapitulate Castration-Resistant Prostate Cancer with Sustained Androgen Receptor Signaling

Castration-resistant prostate cancer (CRPC) remains an incurable and lethal malignancy. The development of new CRPC treatment strategies is strongly impeded by the scarcity of representative, scalable and transferable preclinical models of advanced, androgen receptor (AR)-driven CRPC. Here, we present contemporary patient-derived xenografts (PDXs) and matching PDX-derived organoids (PDXOs) from CRPC patients who had undergone multiple lines of treatment. These models were comprehensively profiled at the morphologic, genomic ( n = 8) and transcriptomic levels ( n = 81). All are high-grade adenocarcinomas that exhibit copy number alterations and transcriptomic features representative of CRPC patient cohorts. We identified losses of PTEN and RB1, MYC amplifications, as well as genomic alterations in TP53 and in members of clinically actionable pathways such as AR, PI3K and DNA repair pathways. Importantly, the clinically observed continued reliance of CRPC tumors on AR signaling is preserved across the entire set of models, with AR amplification identified in four PDXs. We demonstrate that PDXs and PDXOs faithfully reflect donor tumors and mimic matching patient drug responses. In particular, our models predicted patient responses to subsequent treatments and captured sensitivities to previously received therapies. Collectively, these PDX-PDXO pairs constitute a reliable new resource for in-depth studies of treatment-induced, AR-driven resistance mechanisms. Moreover, PDXOs can be leveraged for large-scale tumor-specific drug response profiling critical for accelerating therapeutic advances in CRPC. </p

The clonal relation of primary upper urinary tract urothelial carcinoma and paired urothelial carcinoma of the bladder

The risk of developing urothelial carcinoma of the bladder (UCB) in patients treated by radical nephroureterectomy (RNU) for an upper urinary tract urothelial carcinoma (UTUC) is 22% to 47% in the 2 years after surgery. Subject of debate remains whether UTUC and the subsequent UCB are clonally related or represent separate origins. To investigate the clonal relationship between both entities, we performed targeted DNA sequencing of a panel of 41 genes on matched normal and tumor tissue of 15 primary UTUC patients treated by RNU who later developed 19 UCBs. Based on the detected tumor-specific DNA aberrations, the paired UTUC and UCB(s) of 11 patients (73.3%) showed a clonal relation, whereas in four patients the molecular results did not indicate a clear clonal relationship. Our results support the hypothesis that UCBs following a primary surgically resected UTUC are predominantly clonally derived recurrences and not separate entities

The genomic and transcriptomic landscape of advanced renal cell cancer for individualized treatment strategies

Differences in the clinical course and treatment responses in individual patients with advanced renal cell carcinoma (RCC) can largely be explained by the different genomics of this disease. To improve the personalized treatment strategy and survival outcomes for patients with advanced RCC, the genomic make-up in patients with advanced RCC was investigated to identify putative actionable variants and signatures. In this prospective multicenter study (NCT01855477), whole-genome sequencing (WGS) data of locally advanced and metastatic tissue biopsies and matched whole-blood samples were collected from 91 patients with histopathologically confirmed RCC. WGS data were analyzed for small somatic variants, copy-number alterations and structural variants. For a subgroup of patients, RNA sequencing (RNA-Seq) data could be analyzed. RNA-Seq data were clustered on immunogenic and angiogenic gene expression patterns according to a previously developed angio-immunogenic gene signature. In all patients with papillary and clear cell RCC, putative actionable drug targets were detected by WGS, of which 94% were on-label available. RNA-Seq data of clear cell and papillary RCC were clustered using a previously developed angio-immunogenic gene signature. Analyses of driver mutations and RNA-Seq data revealed clear differences among different RCC subtypes, showing the added value of WGS and RNA-Seq over clinicopathological data. By improving both histological subtyping and the selection of treatment according to actionable targets and immune signatures, WGS and RNA-Seq may improve therapeutic decision making for most patients with advanced RCC, including patients with non-clear cell RCC for whom no standard treatment is available to data. Prospective clinical trials are needed to evaluate the impact of genomic and transcriptomic diagnostics on survival outcome for advanced RCC patients

Stratification of hospitalized COVID-19 patients into clinical severity progression groups by immuno-phenotyping and machine learning

Quantitative or qualitative differences in immunity may drive clinical severity in COVID-19. Although longitudinal studies to record the course of immunological changes are ample, they do not necessarily predict clinical progression at the time of hospital admission. Here we show, by a machine learning approach using serum pro-inflammatory, anti-inflammatory and anti-viral cytokine and anti-SARS-CoV-2 antibody measurements as input data, that COVID-19 patients cluster into three distinct immune phenotype groups. These immune-types, determined by unsupervised hierarchical clustering that is agnostic to severity, predict clinical course. The identified immune-types do not associate with disease duration at hospital admittance, but rather reflect variations in the nature and kinetics of individual patient's immune response. Thus, our work provides an immune-type based scheme to stratify COVID-19 patients at hospital admittance into high and low risk clinical categories with distinct cytokine and antibody profiles that may guide personalized therapy. Developing predictive methods to identify patients with high risk of severe COVID-19 disease is of crucial importance. Authors show here that by measuring anti-SARS-CoV-2 antibody and cytokine levels at the time of hospital admission and integrating the data by unsupervised hierarchical clustering/machine learning, it is possible to predict unfavourable outcome

Sleep, vigilance, and thermosensitivity

The regulation of sleep and wakefulness is well modeled with two underlying processes: a circadian and a homeostatic one. So far, the parameters and mechanisms of additional sleep-permissive and wake-promoting conditions have been largely overlooked. The present overview focuses on one of these conditions: the effect of skin temperature on the onset and maintenance of sleep, and alertness. Skin temperature is quite well suited to provide the brain with information on sleep-permissive and wake-promoting conditions because it changes with most if not all of them. Skin temperature changes with environmental heat and cold, but also with posture, environmental light, danger, nutritional status, pain, and stress. Its effect on the brain may thus moderate the efficacy by which the clock and homeostat manage to initiate or maintain sleep or wakefulness. The review provides a brief overview of the neuroanatomical pathways and physiological mechanisms by which skin temperature can affect the regulation of sleep and vigilance. In addition, current pitfalls and possibilities of practical applications for sleep enhancement are discussed, including the recent finding of impaired thermal comfort perception in insomniacs