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BRAF plays an indispensable role in activating the MEK/ERK pathway to drive tumorigenesis. Receptor tyrosine kinase and RAS-mediated BRAF activation have been extensively characterized, however, it remains undefined how BRAF function is fine-tuned by stimuli other than growth factors. Here, we report that in response to proinflammatory cytokines, BRAF is subjected to lysine 27-linked poly-ubiquitination in melanoma cells by the ITCH ubiquitin E3 ligase. Lysine 27-linked ubiquitination of BRAF recruits PP2A to antagonize the S365 phosphorylation and disrupts the inhibitory interaction with 14–3–3, leading to sustained BRAF activation and subsequent elevation of the MEK/ERK signaling. Physiologically, proinflammatory cytokines activate ITCH to maintain BRAF activity and to promote proliferation and invasion of melanoma cells, whereas the ubiquitination-deficient BRAF mutant displays compromised kinase activity and reduced tumorigenicity. Collectively, our study reveals a pivotal role for ITCH-mediated BRAF ubiquitination in coordinating the signals between cytokines and the MAPK pathway activation in melanoma cells. BRAF drives MEK/ERK activation to facilitate tumorigenesis. Here, the authors show that in response to pro-inflammatory cytokines, ITCH mediates a non-proteolytic ubiquitination and activation of BRAF, which in turn sustains MEK/ERK signaling to facilitate melanoma cell growth.

•We propose a new generative model approach for unsupervised inference of dynamic brain networks, known as Dynamic Network Modes (DyNeMo).•DyNeMo avoids making the assumption of mutual exclusivity used in state-based models, such as the Hidden Markov Model (HMM).•DyNeMo reveals a plausible and physiologically meaningful description of resting-state and task MEG data.•DyNeMo is capable of learning longer range dependencies than the HMM, via a recurrent neural network.•We show DyNeMo provides a modest improvement in modelling dynamic spectral features compared to the HMM. Accurate temporal modelling of functional brain networks is essential in the quest for understanding how such networks facilitate cognition. Researchers are beginning to adopt time-varying analyses for electrophysiological data that capture highly dynamic processes on the order of milliseconds. Typically, these approaches, such as clustering of functional connectivity profiles and Hidden Markov Modelling (HMM), assume mutual exclusivity of networks over time. Whilst a powerful constraint, this assumption may be compromising the ability of these approaches to describe the data effectively. Here, we propose a new generative model for functional connectivity as a time-varying linear mixture of spatially distributed statistical “modes”. The temporal evolution of this mixture is governed by a recurrent neural network, which enables the model to generate data with a rich temporal structure. We use a Bayesian framework known as amortised variational inference to learn model parameters from observed data. We call the approach DyNeMo (for Dynamic Network Modes), and show using simulations it outperforms the HMM when the assumption of mutual exclusivity is violated. In resting-state MEG, DyNeMo reveals a mixture of modes that activate on fast time scales of 100–150 ms, which is similar to state lifetimes found using an HMM. In task MEG data, DyNeMo finds modes with plausible, task-dependent evoked responses without any knowledge of the task timings. Overall, DyNeMo provides decompositions that are an approximate remapping of the HMM’s while showing improvements in overall explanatory power. However, the magnitude of the improvements suggests that the HMM’s assumption of mutual exclusivity can be reasonable in practice. Nonetheless, DyNeMo provides a flexible framework for implementing and assessing future modelling developments.

BACKGROUNDMetastatic hormone-sensitive prostate cancer (mHSPC) is androgen dependent, and its treatment includes androgen deprivation therapy (ADT) with gonadal testosterone suppression. Since 2014, overall survival (OS) has been prolonged with addition of other systemic therapies, such as adrenal androgen synthesis blockers, potent androgen receptor blockers, or docetaxel, to ADT. HSD3B1 encodes the rate-limiting enzyme for nongonadal androgen synthesis, 3β-hydroxysteroid dehydrogenase-1, and has a common adrenal-permissive missense-encoding variant that confers increased synthesis of potent androgens from nongonadal precursor steroids and poorer prostate cancer outcomes.METHODSOur prespecified hypothesis was that poor outcome associated with inheritance of the adrenal-permissive HSD3B1 allele with ADT alone is reversed in patients with low-volume (LV) mHSPC with up-front ADT plus addition of androgen receptor (AR) antagonists to inhibit the effect of adrenal androgens. HSD3B1 genotype was obtained in 287 patients with LV disease treated with ADT + AR antagonist only in the phase III Enzalutamide in First Line Androgen Deprivation Therapy for Metastatic Prostate Cancer (ENZAMET) trial and was associated with clinical outcomes.RESULTSPatients who inherited the adrenal-permissive HSD3B1 allele had more favorable 5-year clinical progression-free survival and OS when treated with ADT plus enzalutamide or ADT plus nonsteroidal antiandrogen compared with their counterparts who did not have adrenal-permissive HSD3B1 inheritance. HSD3B1 was also associated with OS after accounting for known clinical variables. Patients with both genotypes benefited from early enzalutamide.CONCLUSIONThese data demonstrated an inherited physiologic driver of prostate cancer mortality is associated with clinical outcomes and is potentially pharmacologically reversible.FUNDINGNational Cancer Institute, NIH; Department of Defense; Prostate Cancer Foundation, Australian National Health and Medical Research Council.

Biosynthesis of all androgens and estrogens from cholesterol requires CYP11A1 and CYP17A1. There is no known pathway in humans or other vertebrates that circumvents CYP17A1 for androgen or estrogen biosynthesis in physiology or disease. However, CYP17A1 inhibition cannot completely inhibit androgen biosynthesis in prostate cancer. Here, we identify a surprising role for CYP51 in androgen biosynthesis that bypasses the requirement for CYP17A1. We find that an oxysterol is converted to androgens, which we confirmed with synthesis of a deuterium-labeled oxysterol precursor. Of 57 human cytochrome P450 enzymes tested, only CYP51A1 is capable of circumventing CYP17A1. Genetic studies using stable isotope tracing demonstrate that CYP51A1 is essential for biosynthesis of 13 C-testosterone from 13 C-cholesterol. Other vertebrate orthologs of human CYP51A1 also synthesize androgens. CYP51A1 knockout suppressed androgen-regulated genes in vitro and in vivo in prostate cancer xenografts. These findings have broad implications for sex steroid physiology and pharmacologic therapies for steroid-dependent diseases. Biosynthesis of all androgens from cholesterol first requires cytochrome P450 (CYP) 11A1 for generation of pregnanes and then CYP17A1 for biosynthesis of androgens, but CYP17A1 inhibition cannot completely inhibit androgen biosynthesis in prostate cancer. Here, the authors identify a role for CYP51A1 in the biosynthesis of androgens that completely bypasses the requirement for CYP17A1 and demonstrate that CYP51A1 is essential for the biosynthesis of 13 C-testosterone from 13 C-cholesterol in prostate cancer cells.

Neural activity contains rich spatiotemporal structure that corresponds to cognition. This includes oscillatory bursting and dynamic activity that span across networks of brain regions, all of which can occur on timescales of tens of milliseconds. While these processes can be accessed through brain recordings and imaging, modeling them presents methodological challenges due to their fast and transient nature. Furthermore, the exact timing and duration of interesting cognitive events are often a priori unknown. Here, we present the OHBA Software Library Dynamics Toolbox (osl-dynamics), a Python-based package that can identify and describe recurrent dynamics in functional neuroimaging data on timescales as fast as tens of milliseconds. At its core are machine learning generative models that are able to adapt to the data and learn the timing, as well as the spatial and spectral characteristics, of brain activity with few assumptions. osl-dynamics incorporates state-of-the-art approaches that can be, and have been, used to elucidate brain dynamics in a wide range of data types, including magneto/electroencephalography, functional magnetic resonance imaging, invasive local field potential recordings, and electrocorticography. It also provides novel summary measures of brain dynamics that can be used to inform our understanding of cognition, behavior, and disease. We hope osl-dynamics will further our understanding of brain function, through its ability to enhance the modeling of fast dynamic processes.

MicroRNAs (miRNA) and other components contained in extracellular vesicles may reflect the presence of a disease. Lung tissue, sputum, and sera of individuals with idiopathic pulmonary fibrosis (IPF) show alterations in miRNA expression. We designed this study to test whether urine and/or tissue derived exosomal miRNAs from individuals with IPF carry cargo that can promote fibrosis. Exosomes were isolated from urine (U-IPFexo), lung tissue myofibroblasts (MF-IPFexo), serum from individuals with IPF (n=16) and age/sex-matched controls without lung disease (n=10). We analyzed microRNA expression of isolated exosomes and their in vivo bio-distribution. We investigated the effect on ex vivo skin wound healing and in in vivo mouse lung models. U-IPFexo or MF-IPFexo expressed consistent with previous reports of miRNA expression obtained from lung tissue/sera from patients with IPF. In vivo bio-distribution experiments detected bioluminescent exosomes in the lung of normal C57Bl6 mice within 5 min after intravenous infusion, followed by distribution to other organs irrespective of exosome source. Exosomes labeled with gold nanoparticles and imaged by transmission electron microscopy were visualized in alveolar epithelial type I and type II cells. Treatment of human and mouse lung punches obtained from control, non-fibrotic lungs with either U-IPFexo or MF-IPFexo produced a fibrotic phenotype. A fibrotic phenotype was also induced in a human ex vivo skin model and in in vivo lung models. Our results provide evidence of a systemic feature of IPF whereby exosomes contain pro-fibrotic miRNAs when obtained from a fibrotic source and interfere with response to tissue injury as measured in skin and lung models. This work was supported in part by Lester and Sue Smith Foundation and The Samrick Family Foundation and NIH grants R21 AG060338 (SE and MKG), U01 DK119085 (IP, RS, MTC).

Metastatic outgrowth is supported by metabolic adaptations that may differ from the primary tumor of origin. However, it is unknown if such adaptations are therapeutically actionable. Here we report a novel aminopyridine compound that targets a unique Phosphogluconate Dehydrogenase (PGD)-dependent metabolic adaptation in distant metastases from pancreatic cancer patients. Compared to structurally similar analogs, 6-aminopicolamine (6AP) potently and selectively reversed PGD-dependent metastatic properties, including intrinsic tumorigenic capacity, excess glucose consumption, and global histone hyperacetylation. 6AP acted as a water-soluble prodrug that was converted into intracellular bioactive metabolites that inhibited PGD in vitro, and 6AP monotherapy demonstrated anti-metastatic efficacy with minimal toxicity in vivo. Collectively, these studies identify 6AP and possibly other 6-aminopyridines as well-tolerated prodrugs with selectivity for metastatic pancreatic cancers. If unique metabolic adaptations are a common feature of metastatic or otherwise aggressive human malignancies, then such dependencies could provide a largely untapped pool of druggable targets for patients with advanced cancers.

Most quantitative research on fertility decline in the United States ignores the potential impact of cultural and familial factors. We rely on new complete-count data from the 1880 U.S. census to construct couple-level measures of nativity/ethnicity, religiosity, and kin availability. We include these measures with a comprehensive set of demographic, economic, and contextual variables in Poisson regression models of net marital fertility to assess their relative importance. We construct models with and without area fixed effects to control for unobserved heterogeneity. All else being equal, we find a strong impact of nativity on recent net marital fertility. Fertility differentials among second generation couples relative to the native-born white population of native parentage were in most cases less than half of the differential observed among first generation immigrants, suggesting greater assimilation to native-born American childbearing norms. Our measures of parental religiosity and familial propinquity indicated a more modest impact on marital fertility. Couples who chose biblical names for their children had approximately 3% more children than couples relying on secular names while the presence of a potential mother-in-law in a nearby households was associated with 2% more children. Overall, our results demonstrate the need for more inclusive models of fertility behavior that include cultural and familial covariates.

Carboxysomes are bacterial microcompartments that enhance carbon fixation by concentrating ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO) and its substrate CO 2 within a proteinaceous shell. They are found in all cyanobacteria, some purple photoautotrophs and many chemoautotrophic bacteria. Carboxysomes consist of a protein shell that encapsulates several hundred molecules of RuBisCO and contain carbonic anhydrase and other accessory proteins. Genes coding for carboxysome shell components and the encapsulated proteins are typically found together in an operon. The α-carboxysome operon is embedded in a cluster of additional, conserved genes that are presumably related to its function. In many chemoautotrophs, products of the expanded carboxysome locus include CbbO and CbbQ, a member of the AAA+ domain superfamily. We bioinformatically identified subtypes of CbbQ proteins and show that their genes frequently co-occur with both Form IA and Form II RuBisCO. The α-carboxysome-associated ortholog, CsoCbbQ, from Halothiobacillus neapolitanus forms a hexamer in solution and hydrolyzes ATP. The crystal structure shows that CsoCbbQ is a hexamer of the typical AAA+ domain; the additional C-terminal domain, diagnostic of the CbbQ subfamily, structurally fills the inter-monomer gaps, resulting in a distinctly hexagonal shape. We show that CsoCbbQ interacts with CsoCbbO and is a component of the carboxysome shell, the first example of ATPase activity associated with a bacterial microcompartment.

Early-life conditions are associated with mortality in men, but not studied to the same extent in women. We add new evidence by studying a cohort of women born between 1916 and 1931 and followed for mortality between 1986 and 2013. Our sample from Iowa includes a significant number of rural women, from both farms and small towns. The long-term effects of growing up in a rural area were mixed: farmers’ daughters lived longer than women growing up off-farm in rural areas. Daughters of farm laborers and skilled or semiskilled trades workers fared worst, when considering early-life socioeconomic status. We also find evidence that migrating to small-town Iowa was associated with lower life expectancy after age fifty-five. Considering social class and farm-nonfarm status is important for understanding the health of rural America.