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Lipid nanoparticles (LNPs) are the preeminent non-viral drug delivery vehicle for mRNA-based therapies. Immense effort has been placed on optimizing the ionizable lipid (IL) structure, which contains an amine core conjugated to lipid tails, as small molecular adjustments can result in substantial changes in the overall efficacy of the resulting LNPs. However, despite some advancements, a major barrier for LNP delivery is endosomal escape. Here, we develop a platform for synthesizing a class of branched ILs that improve endosomal escape. These compounds incorporate terminally branched groups that increase hepatic mRNA and ribonucleoprotein complex delivery and gene editing efficiency as well as T cell transfection compared to non-branched lipids. Through an array of complementary experiments, we determine that our lipid architecture induces greater endosomal penetration and disruption. This work provides a scheme to generate a class of ILs for both mRNA and protein delivery. Lipid nanoparticles (LNPs) are the preeminent drug delivery vehicle for mRNA therapies, partially due to the ionizable lipid (IL) components that facilitate endosomal escape. Here, authors devise terminally branched ILs that enhance endosome escape, resulting in increased liver and T cell delivery.

Pre-eclampsia is a placental disorder that affects 3–5% of all pregnancies and is a leading cause of maternal and fetal morbidity worldwide 1 , 2 . With no drug available to slow disease progression, engineering ionizable lipid nanoparticles (LNPs) for extrahepatic messenger RNA (mRNA) delivery to the placenta is an attractive therapeutic option for pre-eclampsia. Here we use high-throughput screening to evaluate a library of 98 LNP formulations in vivo and identify a placenta-tropic LNP (LNP 55) that mediates more than 100-fold greater mRNA delivery to the placenta in pregnant mice than a formulation based on the Food and Drug Administration-approved Onpattro LNP (DLin-MC3-DMA) 3 . We propose an endogenous targeting mechanism based on β 2 -glycoprotein I adsorption that enables LNP delivery to the placenta. In both inflammation- and hypoxia-induced models of pre-eclampsia, a single administration of LNP 55 encapsulating vascular endothelial growth factor (VEGF) mRNA resolves maternal hypertension until the end of gestation. In addition, with our VEGF mRNA LNP 55 therapeutic, we demonstrate improvements in fetal health and partially restore placental vasculature, the local and systemic immune landscape and serum levels of soluble Fms-like tyrosine kinase-1, a clinical biomarker of pre-eclampsia 1 . Together, these results demonstrate the potential of this mRNA LNP platform for treating placental disorders such as pre-eclampsia. A platform for mRNA lipid nanoparticle delivery to the placenta to treat pre-eclampsia is shown to improve fetal and maternal health in mice and has potential clinical applications in obstetric disorders and women’s health.

HIV-1 infection is incurable due to the persistence of the virus in a latent reservoir of resting memory CD4+ T cells. “Shock-and-kill” approaches that seek to induce HIV-1 gene expression, protein production, and subsequent targeting by the host immune system have been unsuccessful due to a lack of effective latency-reversing agents (LRAs) and kill strategies. In an effort to develop reagents that could be used to promote killing of infected cells, we constructed T cell receptor (TCR)-mimic antibodies to HIV-1 peptide- major histocompatibility complexes (pMHC). Using phage display, we panned for phages expressing antibody-like variable sequences that bound HIV-1 pMHC generated using the common HLA-A*02:01 allele. We targeted three epitopes in Gag and reverse transcriptase identified and quantified via Poisson detection mass spectrometry from cells infected in vitro with a pseudotyped HIV-1 reporter virus (NL4.3 dEnv). Sequences isolated from phages that bound these pMHC were cloned into a single-chain diabody backbone (scDb) sequence, such that one fragment is specific for an HIV-1 pMHC and the other fragment binds to CD3ε, an essential signal transduction subunit of the TCR. Thus, these antibodies utilize the sensitivity of T cell signaling as readouts for antigen processing and as agents to promote killing of infected cells. Notably, these scDbs are exquisitely sensitive and specific for the peptide portion of the pMHC. Most importantly, one scDb caused killing of infected cells presenting a naturally processed target pMHC. This work lays the foundation for a novel therapeutic killing strategy toward elimination of the HIV-1 reservoir.

A phase 2, multicenter study showed that four doses of neoadjuvant cemiplimab (anti–PD-1 antibody) led to a pathological complete response in 51% of patients with locally advanced cutaneous squamous-cell carcinoma.

Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse metabolomics as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for in public metabolomics datasets to uncover phenotypic associations. To demonstrate the concept, we broadly synthesized and explored multiple classes of metabolites in humans, including N -acyl amides, fatty acid esters of hydroxy fatty acids, bile acid esters and conjugated bile acids. Using repository-scale analysis 1 , 2 , we discovered that some conjugated bile acids are associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed that cholic acids conjugated to Glu, Ile/Leu, Phe, Thr, Trp or Tyr are increased in Crohn’s disease. Several of these compounds and related structures affected pathways associated with IBD, such as interferon-γ production in CD4 + T cells 3 and agonism of the pregnane X receptor 4 . Culture of bacteria belonging to the Bifidobacterium , Clostridium and Enterococcus genera produced these bile amidates. Because searching repositories with tandem mass spectrometry spectra has only recently become possible, this reverse metabolomics approach can now be used as a general strategy to discover other molecules from human and animal ecosystems. A new discovery strategy, ‘reverse metabolomics’, facilitates high-throughput matching of mass spectrometry spectra in public untargeted metabolomics datasets, and a proof-of-concept experiment identified an association between microbial bile amidates and inflammatory bowel disease.

Chemotherapy remains the standard of care for most cancers worldwide, however development of chemoresistance due to the presence of the drug-effluxing ATP binding cassette (ABC) transporters remains a significant problem. The development of safe and effective means to overcome chemoresistance is critical for achieving durable remissions in many cancer patients. We have investigated the energetic demands of ABC transporters in the context of the metabolic adaptations of chemoresistant cancer cells. Here we show that ABC transporters use mitochondrial-derived ATP as a source of energy to efflux drugs out of cancer cells. We further demonstrate that the loss of methylation-controlled J protein (MCJ) (also named DnaJC15), an endogenous negative regulator of mitochondrial respiration, in chemoresistant cancer cells boosts their ability to produce ATP from mitochondria and fuel ABC transporters. We have developed MCJ mimetics that can attenuate mitochondrial respiration and safely overcome chemoresistance in vitro and in vivo. Administration of MCJ mimetics in combination with standard chemotherapeutic drugs could therefore become an alternative strategy for treatment of multiple cancers. Drug efflux through ABC transporters is a common mechanism leading to chemoresistance in cancer. Here, the authors show that mitochondrial respiration provides ATP to allow ABC transporters activity so mitochondrial respiration inhibition overcomes chemoresistance in preclinical cancer models.

Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions. The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33–2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84–10·9) people and decline to 8·79 billion (6·83–11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion [0·72–1·71], Nigeria (791 million [594–1056]), China (732 million [456–1499]), the USA (336 million [248–456]), and Pakistan (248 million [151–427]). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91–2·87) individuals older than 65 years and 1·70 billion (1·11–2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (−6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82–8·73) in 2100 and a population of 6·88 billion (5·27–9·51) when assuming 99th percentile rates of change in these drivers. Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come. Bill & Melinda Gates Foundation.

Genomic studies have linked mTORC1 pathway-activating mutations with exceptional response to treatment with allosteric inhibitors of mTORC1 called rapalogs. Rapalogs are approved for selected cancer types, including kidney and breast cancers. Here, we used sequencing data from 22 human kidney cancer cases to identify the activating mechanisms conferred by mTOR mutations observed in human cancers and advance precision therapeutics. mTOR mutations that clustered in focal adhesion kinase targeting domain (FAT) and kinase domains enhanced mTORC1 kinase activity, decreased nutrient reliance, and increased cell size. We identified 3 distinct mechanisms of hyperactivation, including reduced binding to DEP domain-containing MTOR-interacting protein (DEPTOR), resistance to regulatory associated protein of mTOR-mediated (RAPTOR-mediated) suppression, and altered kinase kinetics. Of the 28 mTOR double mutants, activating mutations could be divided into 6 complementation groups, resulting in synergistic Rag- and Ras homolog enriched in brain-independent (RHEB-independent) mTORC1 activation. mTOR mutants were resistant to DNA damage-inducible transcript 1-mediated (REDD1-mediated) inhibition, confirming that activating mutations can bypass the negative feedback pathway formed between HIF1 and mTORC1 in the absence of von Hippel-Lindau (VHL) tumor suppressor expression. Moreover, VHL-deficient cells that expressed activating mTOR mutants grew tumors that were sensitive to rapamycin treatment. These data may explain the high incidence of mTOR mutations observed in clear cell kidney cancer, where VHL loss and HIF activation is pathognomonic. Our study provides mechanistic and therapeutic insights concerning mTOR mutations in human diseases.