Explore the vast range of titles available.

Precision medicine starts with a precision diagnosis. Yet up to 80% of cases of monogenic diabetes, a form of diabetes characterized by mutations in a single gene, are either overlooked or misdiagnosed. A genetic test for monogenic diabetes does not always lead to a precise diagnosis, as novel variants are often classified as variants of unknown significance. Variant interpretation requires collation of a framework of evidence, including population, computational, and segregation data, and can be assisted by functional analysis. The inclusion of functional data can be challenging, depending on the number of benign and pathogenic variants available for benchmarking assays. Glucokinase is the rate-limiting step for glucose metabolism in the pancreatic beta-cell and governs the threshold for glucose-stimulated insulin release. Loss-of-function alleles in the glucokinase (GCK) gene are a cause of stable fasting hyperglycemia from birth and/or diabetes. In this study, we functionally characterized 25 variants identified during diagnostic testing or in exome sequencing studies. We assessed their kinetic characteristics, stability, and interaction with pharmacological and physiological regulators. We integrated our functional data with existing data from the ClinGen Monogenic Diabetes Variant Curation Expert Review panel using a gene-specific framework to assist variant classification. We show how functional evidence can aid variant classification, thus enabling diagnostic certainty.

Cancer-associated isocitrate dehydrogenase (IDH) mutations sensitize gliomas to replication stress, although the underlying mechanisms are unclear. IDH-mutant enzymes synthesize ( )-2-hydroxyglutarate (R2HG), which broadly inhibits 2-oxoglutarate-dependent enzymes. We performed forward genetic screens targeting all 2-oxoglutarate-dependent enzymes and discovered that KDM6 histone demethylases play a vital role in protecting cells from replication stress. Genetic or R2HG-mediated repression of KDM6 catalytic activity sensitized glioma cells to disparate replication stress-inducing drugs, including Ataxia-telangiectasia and Rad3-related (ATR) and dihydroorotate dehydrogenase (DHODH) inhibitors. This liability is generalizable because KDM6A loss-of-function mutations commonly observed in urothelial carcinomas sensitized bladder cancer cells to DHODH inhibition, thereby phenocopying IDH mutations in glioma. To exploit these oncogene-induced replication stress vulnerabilities, we developed an effective, on-target, and well-tolerated DHODH inhibitor, GLIO-1, that is poised for clinical translation. Collectively, we reveal KDM6 activity as a fundamental determinant of replication stress sensitivity and nominate pan-cancer, mechanism-based biomarkers of ATR and DHODH inhibitor efficacy. We discovered that the KDM6 enzymes are the mechanistic targets of R2HG that mediate mutant IDH-induced replication stress hypersensitivity. We report a promising new DHODH inhibitor, GLIO-1, and nominate KDM6 and IDH mutations as predictive biomarkers for the antitumor effects of GLIO-1 and other replication stress inducers.

The continued development of high-dimensional CRISPR screen readouts, such as single-cell RNA sequencing and high-content imaging, necessitates compact libraries to enable functional interrogation at genome scale. Improved genome annotations yield library deprecation over time, further motivating an updated genome-wide design effort. Recently, we have developed an enhanced model, Rule Set 3, which leveraged an expansive training set and feature space to predict guide efficacy. However, the benefit of such advances to library design is limited by current approaches to balance predictions of on-target activity with off-target considerations. Here we present a guide selection strategy that identifies guides with sufficient off-target activity to justify omission from the library, thus avoiding the unnecessary exclusion of active guides. We pair this model with strategic design choices to create Jacquere, an updated, optimized, and validated Cas9 CRISPR knockout (CRISPRko) genome-wide library for the human genome.

Base editing is a CRISPR-based technology that enables high-throughput, nucleotide-level functional interrogation of the genome, which is essential for understanding the genetic basis of human disease and informing therapeutic development. Base editing screens have emerged as a powerful experimental approach, yet significant cell-to-cell variability in editing efficiency introduces noise that may obscure meaningful results. Here, we develop a co-selection method that enriches for cells with high base editing activity, substantially increasing editing efficiency at a target locus. We evaluate this activity-based selection method against a traditional screening approach by tiling guide RNAs across TP53, demonstrating its enhanced capacity to pinpoint specific mutations and protein regions of functional importance. We anticipate that this modular selection method will enhance the resolution of base editing screens across many applications.Competing Interest StatementJGD consults for Microsoft Research, BioNTech, PhenomicAI, Servier, and Pfizer. JGD consults for and has equity in Tango Therapeutics. JGD serves as a paid scientific advisor to the Laboratory for Genomics Research, funded in part by GSK; and the Innovative Genomics Institute, funded in part by Apple Tree Partners. JGD receives funding support from the Functional Genomics Consortium: Abbvie, Bristol Myers Squibb, Janssen, and Merck. JGD interests are reviewed and managed by the Broad Institute in accordance with its conflict of interest policies. A patent application related to this work has been filed.

Sensitive biological compounds, such as vaccines and antibiotics, traditionally require a time-dependent “cold chain” to maximize therapeutic activity. This flawed process results in billions of dollars worth of viable drug loss during shipping and storage, and severely limits distribution to developing nations with limited infrastructure. To address these major limitations, we demonstrate self-standing silk protein biomaterial matrices capable of stabilizing labile vaccines and antibiotics, even at temperatures up to 60 °C over more than 6 months. Initial insight into the mechanistic basis for these findings is provided. Importantly, these findings suggest a transformative approach to the cold chain to revolutionize the way many labile therapeutic drugs are stored and utilized throughout the world.

Advances in personalized medicine are symbiotic with the development of novel technologies for biomedical devices. We present an approach that combines enhanced imaging of malignancies, therapeutics, and feedback about therapeutics in a single implantable, biocompatible, and resorbable device. This confluence of form and function is accomplished by capitalizing on the unique properties of silk proteins as a mechanically robust, biocompatible, optically clear biomaterial matrix that can house, stabilize, and retain the function of therapeutic components. By developing a form of high-quality microstructured optical elements, improved imaging of malignancies and of treatment monitoring can be achieved. The results demonstrate a unique family of devices for in vitro and in vivo use that provide functional biomaterials with built-in optical signal and contrast enhancement, demonstrated here with simultaneous drug delivery and feedback about drug delivery with no adverse biological effects, all while slowly degrading to regenerate native tissue.

PurposeStandard-of-care for HER2-positive metastatic breast cancer (HER2 + mBC) patients consists of trastuzumab ± pertuzumab with chemotherapy in first-line (1L), and ado-trastuzumab emtansine (T-DM1) or the more recently approved trastuzumab deruxtecan (T-DXd) in second-line (2L). Contemporary data on treatment sequencing and real-world effectiveness is limited. This study aims to report 2L treatments and outcomes among HER2 + mBC patients in the United States (US).MethodsHER2 + mBC patients initiating 2L treatment (index date) between January 2014 and February 2021 were identified from the Syapse Learning Health Network (LHN) database. Summary statistics for patient characteristics, treatment received, reasons for 2L discontinuation and time to 2L-clinical outcomes are reported.ResultsOf the 312 patients initiating 2L treatment, had a median age of 59 years (interquartile range [IQR], 50–66) at the start of 2L. The majority were white (69%) and had de novo mBC (62%). Top three 2L regimens included T-DM1 ± endocrine therapy (29%), trastuzumab/pertuzumab/taxane (10%) and T-DM1/trastuzumab (8%). Around 88% discontinued 2L and 63% received subsequent treatment. Median time-to-next-treatment was 10.6 months (95% CI, 8.8–13.3) and real-world progression-free-survival was 7.9 months (95% CI, 7.0–9.9). Among 274 patients who discontinued 2L, 47% discontinued due to progression and 17% because of intolerance/toxicity, respectively.ConclusionThis real-world US study showed that approximately two-thirds of 2L patients received subsequent therapy and disease progression was the most common reason for 2L discontinuation highlighting the need for timely 2L treatment with the most efficacious drug to allow patients to achieve longer treatment duration and delayed progression.

Though poorly defined, hypersomnia is associated with negative health outcomes and new-onset and recurrence of psychiatric illness. Lack of definition impedes generalizability across studies. The present research clarifies hypersomnia diagnoses in bipolar disorder by exploring possible subgroups and their relationship to prospective sleep data and relapse into mood episodes. A community sample of 159 adults (aged 18-70 years) with bipolar spectrum diagnoses, euthymic at study entry, was included. Self-report inventories and clinician-administered interviews determined features of hypersomnia. Participants completed sleep diaries and wore wrist actigraphs at home to obtain prospective sleep data. Approximately 7 months later, psychiatric status was reassessed. Factor analysis and latent profile analysis explored empirical groupings within hypersomnia diagnoses. Factor analyses confirmed two separate subtypes of hypersomnia ('long sleep' and 'excessive sleepiness') that were uncorrelated. Latent profile analyses suggested a four-class solution, with 'long sleep' and 'excessive sleepiness' again representing two separate classes. Prospective sleep data suggested that the sleep of 'long sleepers' is characterized by a long time in bed, not long sleep duration. Longitudinal assessment suggested that 'excessive sleepiness' at baseline predicted mania/hypomania relapse. This study is the largest of hypersomnia to include objective sleep measurement, and refines our understanding of classification, characterization and associated morbidity. Hypersomnia appears to be comprised of two separate subgroups: long sleep and excessive sleepiness. Long sleep is characterized primarily by long bedrest duration. Excessive sleepiness is not associated with longer sleep or bedrest, but predicts relapse to mania/hypomania. Understanding these entities has important research and treatment implications.

This paper describes the climate-related forcings (CRFs), i.e. change in climate comprising the atmosphere and the ocean, coastal water levels, and atmospheric composition (CO2 and methane concentrations), provided as input data within the “b” part of the third simulation round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b). While ISIMIP3a comprises historical impact models simulations forced by observational Direct Human Forcings (DHF), such as changes in population and asset distributions, land use, fishing efforts, agricultural and water management driven by socio-economic development or climate protection strategies, and observational CRF, the ISIMIP3b CRFs are based on climate model simulations generated within the sixth phase of the Coupled Model Intercomparison Project (CMIP6). In a first set of experiments covering the pre-industrial (1601–1849) and historical period (1850–2014) (ISIMIP3b, group I) the CMIP6-based CRFs for the historical period are combined with historical observation-based DHF also considered in ISIMIP3a. These group I simulations allow for the quantification of impacts of historical climate change by comparison to simulations where the observational DHF are combined with simulated pre-industrial CRFs. In addition, the impacts of observed changes in CRFs can be compared to the impacts of simulated changes in CRFs by comparing the ISIMIP3a simulations to the ISIMIP3b, group I simulations. The second group of experiments (ISIMIP3b, group II) comprises future projections assuming constant observational direct human forcings at 2015 levels to estimate the impact of climate change given today's DHF for the low emission scenario SSP1-2.6, the high and the very high emission scenarios SSP3-7.0, SSP5-8.5, and reference simulations based on pre-industrial CRF, respectively. The very high emissions scenarios and the assumption of fixed present day DHF particularly allow for testing the scalability of impacts in terms of global temperature change. The provided CRFs comprise atmospheric CO2 and CH4 concentrations, atmospheric and oceanic climate data, coastal water levels, tropical cyclone (TC) tracks and their associated wind speed and precipitation fields. In addition to the CRFs data, this paper describes the experiments belonging to group I and II and the rationale behind them. Another set of future projections accounting for changing DHFs (ISIMIP3b, group III) is in preparation and will be described in another paper.

A Correction to this paper has been published: https://doi.org/10.1038/s41586-020-03174-8.