FRAP Analysis Reveals Stabilization of Adhesion Structures in the Epidermis Compared to Cultured Keratinocytes

Proper development and tissue maintenance requires cell-cell adhesion structures, which serve diverse and crucial roles in tissue morphogenesis. Epithelial tissues have three main types of cell-cell junctions: tight junctions, which play a major role in barrier formation, and adherens junctions and desmosomes, which provide mechanical stability and organize the underlying cytoskeleton. Our current understanding of adhesion function is hindered by a lack of tools and methods to image junctions in mammals. To better understand the dynamics of adhesion in tissues we have created a knock-in ZO-1-GFP mouse and a BAC-transgenic mouse expressing desmoplakin I-GFP. We performed fluorescence recovery after photobleaching (FRAP) experiments to quantify the turnover rates of the tight junction protein ZO-1, the adherens junction protein E-cadherin, and the desmosomal protein desmoplakin in the epidermis. Proteins at each type of junction are remarkably stable in the epidermis, in contrast to the high observed mobility of E-cadherin and ZO-1 at adherens junctions and tight junctions, respectively, in cultured cells. Our data demonstrate that there are additional mechanisms for stabilizing junctions in tissues that are not modeled by cell culture

CRLX101, a Nanoparticle–Drug Conjugate Containing Camptothecin, Improves Rectal Cancer Chemoradiotherapy by Inhibiting DNA Repair and HIF1α

Novel agents are needed to improve chemoradiotherapy for locally advanced rectal cancer. In this study, we assessed the ability of CRLX101, an investigational nanoparticle-drug conjugate containing the payload camptothecin (CPT), to improve therapeutic responses as compared to standard chemotherapy. CRLX101 was evaluated as a radiosensitizer in colorectal cancer cell lines and murine xenograft models. CRLX101 was as potent as CPT in vitro in its ability to radiosensitize cancer cells. Evaluations in vivo demonstrated that the addition of CRLX101 to standard chemoradiotherapy significantly increased therapeutic efficacy by inhibiting DNA repair and HIF-1α pathway activation in tumor cells. Notably, CRLX101 was more effective than oxaliplatin at enhancing the efficacy of chemoradiotherapy, with CRLX101 and 5-fluorouracil (5-FU) producing the highest therapeutic efficacy. Gastrointestinal toxicity was also significantly lower for CRLX101 compared to CPT when combined with radiotherapy. Our results offer a preclinical proof of concept for CRLX101 as a modality to improve the outcome of neoadjuvant chemoradiotherapy for rectal cancer treatment, in support of ongoing clinical evaluation of this agent (LCC1315 {"type":"clinical-trial","attrs":{"text":"NCT02010567","term_id":"NCT02010567"}}NCT02010567)

Reviews and bibliographical notices

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Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease