Selective Autophagy Conceals the Enemy: Why Cytotoxic T Cells Don't (MH)C Pancreatic Cancer.

Cell surface MHC-I can present tumor antigens to CD8+ T cells. In pancreatic cancer, selective autophagy instead reroutes MHC-I to lysosomes, using the ubiquitin-binding receptor NBR1, precluding T cell recognition. Accordingly, immune clearance of tumors can be facilitated by blocking autophagy.

Bromodomain Protein BRD4 Is a Transcriptional Repressor of Autophagy and Lysosomal Function.

Autophagy is a membrane-trafficking process that directs degradation of cytoplasmic material in lysosomes. The process promotes cellular fidelity, and while the core machinery of autophagy is known, the mechanisms that promote and sustain autophagy are less well defined. Here we report that the epigenetic reader BRD4 and the methyltransferase G9a repress a TFEB/TFE3/MITF-independent transcriptional program that promotes autophagy and lysosome biogenesis. We show that BRD4 knockdown induces autophagy in vitro and in vivo in response to some, but not all, situations. In the case of starvation, a signaling cascade involving AMPK and histone deacetylase SIRT1 displaces chromatin-bound BRD4, instigating autophagy gene activation and cell survival. Importantly, this program is directed independently and also reciprocally to the growth-promoting properties of BRD4 and is potently repressed by BRD4-NUT, a driver of NUT midline carcinoma. These findings therefore identify a distinct and selective mechanism of autophagy regulation.

Picky Eating at the ER-phagy Buffet.

The degradation of the endoplasmic reticulum (ER) by autophagy (ER-phagy) regulates proteostasis. Two studies (An et al., Mol. Cell, 2019; Chino et al., Mol. Cell, 2019) have uncovered a new ER-phagy molecule, TEX264, yielding insight into how ER is packaged for degradation, and have illuminated the extent of redundancy between different ER-phagy 'pathways' in remodelling the ER proteome.

ACSL3 is a novel GABARAPL2 interactor that links ufmylation and lipid droplet biogenesis.

While studies of the autophagy-related (ATG) genes in knockout models have led to an explosion of knowledge about the functions of autophagy components, the exact roles of LC3 and GABARAP family proteins (human ATG8 equivalents) are still poorly understood. A major drawback in understanding their roles is that the available interactome data has largely been acquired using overexpression systems. To overcome these limitations, we employed CRISPR/Cas9-based genome-editing to generate a panel of cells in which human ATG8 genes were tagged at their natural chromosomal locations with an N-terminal affinity epitope. This cellular resource was employed to map endogenous GABARAPL2 protein complexes using interaction proteomics. This approach identified the ER-associated protein and lipid droplet (LD) biogenesis factor ACSL3 as a stabilizing GABARAPL2-binding partner. GABARAPL2 bound ACSL3 in a manner dependent on its LC3-interacting regions, whose binding site in GABARAPL2 was required to recruit the latter to the ER. Through this interaction, the UFM1-activating enzyme UBA5 became anchored at the ER. Furthermore, ACSL3 depletion and LD induction affected the abundance of several ufmylation components and ER-phagy. Together these data allow us to define ACSL3 as a novel regulator of the enigmatic UFM1 conjugation pathway.

The MDM2 ligand Nutlin-3 differentially alters expression of the immune blockade receptors PD-L1 and CD276.

BACKGROUND: The links between the p53/MDM2 pathway and the expression of pro-oncogenic immune inhibitory receptors in tumor cells are undefined. In this report, we evaluate whether there is p53 and/or MDM2 dependence in the expression of two key immune receptors, CD276 and PD-L1. METHODS: Proximity ligation assays were used to quantify protein-protein interactions in situ in response to Nutlin-3. A panel of p53-null melanoma cells was created using CRISPR-Cas9 guide RNA mediated genetic ablation. Flow cytometric analyses were used to assess the impact of TP53 or ATG5 gene ablation, as well as the effects of Nutlin-3 and an ATM inhibitor on cell surface PD-L1 and CD276. Targeted siRNA was used to deplete CD276 to assess changes in cell cycle parameters by flow cytometry. A T-cell proliferation assay was used to assess activity of CD4+ T-cells as a function of ATG5 genotype. RESULTS: CD276 forms protein-protein interactions with MDM2 in response to Nutlin-3, similar to the known MDM2 interactors p53 and HSP70. Isogenic HCT116 p53-wt/null cancer cells demonstrated that CD276 is induced on the cell surface by Nutlin-3 in a p53-dependent manner. PD-L1 was also unexpectedly induced by Nutlin-3, but PD-L1 does not bind MDM2. The ATM inhibitor KU55993 reduced the levels of PD-L1 under conditions where Nutlin-3 induces PD-L1, indicating that MDM2 and ATM have opposing effects on PD-L1 steady-state levels. PD-L1 is also up-regulated in response to genetic ablation of TP53 in A375 melanoma cell clones under conditions in which CD276 remains unaffected. A549 cells with a deletion in the ATG5 gene up-regulated only PD-L1, further indicating that PD-L1 and CD276 are under distinct genetic control. CONCLUSION: Genetic inactivation of TP53, or the use of the MDM2 ligand Nutlin-3, alters the expression of the immune blockade receptors PD-L1 and CD276. The biological function of elevated CD276 is to promote altered cell cycle progression in response to Nutlin-3, whilst the major effect of elevated PD-L1 is T-cell suppression. These data indicate that TP53 gene status, ATM and MDM2 influence PD-L1 and CD276 paralogs on the cell surface. These data have implications for the use of drugs that target the p53 pathway as modifiers of immune checkpoint receptor expression.

Bad air gets under your skin.

Air pollution is increasing beyond previous estimates and is viewed as the world's largest environmental health risk factor. Numerous clinical and epidemiological studies have highlighted the adverse effects of environmental pollutants on health. Although there is comparatively less research investigating the cutaneous effects of ambient pollution, there is growing recognition of the adverse effects on skin. In this article, we provide an overview of the nature of environmental pollution and highlight the current evidence detailing the effects on cutaneous health. There is convincing evidence demonstrating that air pollution has a detrimental impact on skin and can exacerbate skin disease. Further epidemiological and experimental studies are required to assess the short- and long-term deleterious effects of ambient pollutant exposure on skin. The future challenge would be to use this evidence to develop specific strategies to protect against pollution-induced damage and prevent the effects of "bad air getting under our skin."

Applicability of predictive toxicology methods for monoclonal antibody therapeutics: status Quo and scope.

Biopharmaceuticals, monoclonal antibody (mAb)-based therapeutics in particular, have positively impacted millions of lives. MAbs and related therapeutics are highly desirable from a biopharmaceutical perspective as they are highly target specific and well tolerated within the human system. Nevertheless, several mAbs have been discontinued or withdrawn based either on their inability to demonstrate efficacy and/or due to adverse effects. Approved monoclonal antibodies and derived therapeutics have been associated with adverse effects such as immunogenicity, cytokine release syndrome, progressive multifocal leukoencephalopathy, intravascular haemolysis, cardiac arrhythmias, abnormal liver function, gastrointestinal perforation, bronchospasm, intraocular inflammation, urticaria, nephritis, neuropathy, birth defects, fever and cough to name a few. The advances made in this field are also impeded by a lack of progress in bioprocess development strategies as well as increasing costs owing to attrition, wherein the lack of efficacy and safety accounts for nearly 60 % of all factors contributing to attrition. This reiterates the need for smarter preclinical development using quality by design-based approaches encompassing carefully designed predictive models during early stages of drug development. Different in vitro and in silico methods are extensively used for predicting biological activity as well as toxicity during small molecule drug development; however, their full potential has not been utilized for biological drug development. The scope of in vitro and in silico tools in early developmental stages of monoclonal antibody-based therapeutics production and how it contributes to lower attrition rates leading to faster development of potential drug candidates has been evaluated. The applicability of computational toxicology approaches in this context as well as the pitfalls and promises of extending such techniques to biopharmaceutical development has been highlighted.

Hypoxia-selective macroautophagy and cell survival signaled by autocrine PDGFR activity.

The selective regulation of macroautophagy remains poorly defined. Here we report that PDGFR signaling is an essential selective promoter of hypoxia-induced macroautophagy. Hypoxia-induced macroautophagy in tumor cells is also HIF1alpha-dependent, with HIF1alpha integrating signals from PDGFRs and oxygen tension. Inhibition of PDGFR signaling reduces HIF1alpha half-life, despite buffering of steady-state protein levels by a compensatory increase in HIF1alpha mRNA. This markedly changes HIF1alpha protein pool dynamics, and consequently reduces the HIF1alpha transcriptome. As autocrine growth factor signaling is a hallmark of many cancers, cell-autonomous enhancement of HIF1alpha-mediated macroautophagy may represent a mechanism for augmenting tumor cell survival under hypoxic conditions.

Practitioner Review: Involving young people with callous unemotional traits in treatment--does it work? A systematic review.

BACKGROUND: Children and adolescents with callous unemotional (CU) traits are at risk of severe and persistent antisocial behavior. It is commonly assumed that these children are difficult to treat but it has been proposed that they may benefit from being involved in interventions that go beyond typical parent training programs. This systematic review sought to answer two previously unanswered questions: do interventions involving young people reduce levels of CU traits? Do CU traits predict the effectiveness of interventions for antisocial behavior involving young people? METHOD: Studies were included that adopted an randomized controlled trial, controlled or open trial design and that had examined whether treatment was related to reductions in CU traits or whether CU traits predicted or moderated treatment effectiveness. RESULTS: Treatments used a range of approaches, including behavioral therapy, emotion recognition training, and multimodal interventions. 4/7 studies reported reductions in CU traits following treatment. There was a mixed pattern of findings in 15 studies that examined whether CU traits predicted treatment outcomes following interventions for antisocial behavior. In 7/15 studies, CU traits were associated with worse outcomes, although three of these studies did not provide data on baseline antisocial behavior, making it difficult to evaluate whether children with high CU traits had shown improvements relative to their own behavioral baseline, despite having the worst behavioral outcomes overall. CU traits did not predict outcomes in 7/15 studies. Finally, a single study reported that CU traits predicted an overall increased response to treatment. CONCLUSIONS: Overall, the evidence supports the idea that children with CU traits do show reductions in both their CU traits and their antisocial behavior, but typically begin treatment with poorer premorbid functioning and can still end with higher levels of antisocial behavior. However, there is considerable scope to build on the current evidence base.

Summary of the DREAM8 Parameter Estimation Challenge: Toward Parameter Identification for Whole-Cell Models.

Whole-cell models that explicitly represent all cellular components at the molecular level have the potential to predict phenotype from genotype. However, even for simple bacteria, whole-cell models will contain thousands of parameters, many of which are poorly characterized or unknown. New algorithms are needed to estimate these parameters and enable researchers to build increasingly comprehensive models. We organized the Dialogue for Reverse Engineering Assessments and Methods (DREAM) 8 Whole-Cell Parameter Estimation Challenge to develop new parameter estimation algorithms for whole-cell models. We asked participants to identify a subset of parameters of a whole-cell model given the model's structure and in silico "experimental" data. Here we describe the challenge, the best performing methods, and new insights into the identifiability of whole-cell models. We also describe several valuable lessons we learned toward improving future challenges. Going forward, we believe that collaborative efforts supported by inexpensive cloud computing have the potential to solve whole-cell model parameter estimation.