T cell immunotherapies engage neutrophils to eliminate tumor antigen escape variants.

Cancer immunotherapies, including adoptive T cell transfer, can be ineffective because tumors evolve to display antigen-loss-variant clones. Therapies that activate multiple branches of the immune system may eliminate escape variants. Here, we show that melanoma-specific CD4+ T cell therapy in combination with OX40 co-stimulation or CTLA-4 blockade can eradicate melanomas containing antigen escape variants. As expected, early on-target recognition of melanoma antigens by tumor-specific CD4+ T cells was required. Surprisingly, complete tumor eradication was dependent on neutrophils and partly dependent on inducible nitric oxide synthase. In support of these findings, extensive neutrophil activation was observed in mouse tumors and in biopsies of melanoma patients treated with immune checkpoint blockade. Transcriptomic and flow cytometry analyses revealed a distinct anti-tumorigenic neutrophil subset present in treated mice. Our findings uncover an interplay between T cells mediating the initial anti-tumor immune response and neutrophils mediating the destruction of tumor antigen loss variants.

Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences.

The dichotomous model of "drivers" and "passengers" in cancer posits that only a few mutations in a tumor strongly affect its progression, with the remaining ones being inconsequential. Here, we leveraged the comprehensive variant dataset from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) project to demonstrate that-in addition to the dichotomy of high- and low-impact variants-there is a third group of medium-impact putative passengers. Moreover, we also found that molecular impact correlates with subclonal architecture (i.e., early versus late mutations), and different signatures encode for mutations with divergent impact. Furthermore, we adapted an additive-effects model from complex-trait studies to show that the aggregated effect of putative passengers, including undetected weak drivers, provides significant additional power (∼12% additive variance) for predicting cancerous phenotypes, beyond PCAWG-identified driver mutations. Finally, this framework allowed us to estimate the frequency of potential weak-driver mutations in PCAWG samples lacking any well-characterized driver alterations.

The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research.

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.

Reactive Oxygen Species and Neutrophil Function.

Neutrophils are essential for killing bacteria and other microorganisms, and they also have a significant role in regulating the inflammatory response. Stimulated neutrophils activate their NADPH oxidase (NOX2) to generate large amounts of superoxide, which acts as a precursor of hydrogen peroxide and other reactive oxygen species that are generated by their heme enzyme myeloperoxidase. When neutrophils engulf bacteria they enclose them in small vesicles (phagosomes) into which superoxide is released by activated NOX2 on the internalized neutrophil membrane. The superoxide dismutates to hydrogen peroxide, which is used by myeloperoxidase to generate other oxidants, including the highly microbicidal species hypochlorous acid. NOX activation occurs at other sites in the cell, where it is considered to have a regulatory function. Neutrophils also release oxidants, which can modify extracellular targets and affect the function of neighboring cells. We discuss the identity and chemical properties of the specific oxidants produced by neutrophils in different situations, and what is known about oxidative mechanisms of microbial killing, inflammatory tissue damage, and signaling.

Reservoir host immune responses to emerging zoonotic viruses.

Zoonotic viruses, such as HIV, Ebola virus, coronaviruses, influenza A viruses, hantaviruses, or henipaviruses, can result in profound pathology in humans. In contrast, populations of the reservoir hosts of zoonotic pathogens often appear to tolerate these infections with little evidence of disease. Why are viruses more dangerous in one species than another? Immunological studies investigating quantitative and qualitative differences in the host-virus equilibrium in animal reservoirs will be key to answering this question, informing new approaches for treating and preventing zoonotic diseases. Integrating an understanding of host immune responses with epidemiological, ecological, and evolutionary insights into viral emergence will shed light on mechanisms that minimize fitness costs associated with viral infection, facilitate transmission to other hosts, and underlie the association of specific reservoir hosts with multiple emerging viruses. Reservoir host studies provide a rich opportunity for elucidating fundamental immunological processes and their underlying genetic basis, in the context of distinct physiological and metabolic constraints that contribute to host resistance and disease tolerance.

Functional genomics data: privacy risk assessment and technological mitigation.

The generation of functional genomics data by next-generation sequencing has increased greatly in the past decade. Broad sharing of these data is essential for research advancement but poses notable privacy challenges, some of which are analogous to those that occur when sharing genetic variant data. However, there are also unique privacy challenges that arise from cryptic information leakage during the processing and summarization of functional genomics data from raw reads to derived quantities, such as gene expression values. Here, we review these challenges and present potential solutions for mitigating privacy risks while allowing broad data dissemination and analysis.

CAR T cell killing requires the IFNγR pathway in solid but not liquid tumours.

Chimeric antigen receptor (CAR) therapy has had a transformative effect on the treatment of haematologic malignancies1-6, but it has shown limited efficacy against solid tumours. Solid tumours may have cell-intrinsic resistance mechanisms to CAR T cell cytotoxicity. Here, to systematically identify potential resistance pathways in an unbiased manner, we conducted a genome-wide CRISPR knockout screen in glioblastoma, a disease in which CAR T cells have had limited efficacy7,8. We found that the loss of genes in the interferon-γ receptor (IFNγR) signalling pathway (IFNGR1, JAK1 or JAK2) rendered glioblastoma and other solid tumours more resistant to killing by CAR T cells both in vitro and in vivo. However, loss of this pathway did not render leukaemia or lymphoma cell lines insensitive to CAR T cells. Using transcriptional profiling, we determined that glioblastoma cells lacking IFNγR1 had lower upregulation of cell-adhesion pathways after exposure to CAR T cells. We found that loss of IFNγR1 in glioblastoma cells reduced overall CAR T cell binding duration and avidity. The critical role of IFNγR signalling in susceptibility of solid tumours to CAR T cells is surprising, given that CAR T cells do not require traditional antigen-presentation pathways. Instead, in glioblastoma tumours, IFNγR signalling was required for sufficient adhesion of CAR T cells to mediate productive cytotoxicity. Our work demonstrates that liquid and solid tumours differ in their interactions with CAR T cells and suggests that enhancing binding interactions between T cells and tumour cells may yield improved responses in solid tumours.

Intraventricular CARv3-TEAM-E T Cells in Recurrent Glioblastoma.

In this first-in-human, investigator-initiated, open-label study, three participants with recurrent glioblastoma were treated with CARv3-TEAM-E T cells, which are chimeric antigen receptor (CAR) T cells engineered to target the epidermal growth factor receptor (EGFR) variant III tumor-specific antigen, as well as the wild-type EGFR protein, through secretion of a T-cell-engaging antibody molecule (TEAM). Treatment with CARv3-TEAM-E T cells did not result in adverse events greater than grade 3 or dose-limiting toxic effects. Radiographic tumor regression was dramatic and rapid, occurring within days after receipt of a single intraventricular infusion, but the responses were transient in two of the three participants. (Funded by Gateway for Cancer Research and others; INCIPIENT ClinicalTrials.gov number, NCT05660369.).

Neoadjuvant Nivolumab and Ipilimumab in Resectable Stage III Melanoma.

BACKGROUND: Phase 1-2 trials involving patients with resectable, macroscopic stage III melanoma have shown that neoadjuvant immunotherapy is more efficacious than adjuvant immunotherapy. METHODS: In this phase 3 trial, we randomly assigned patients with resectable, macroscopic stage III melanoma, in a 1:1 ratio, to receive two cycles of neoadjuvant ipilimumab plus nivolumab and then undergo surgery or to undergo surgery and then receive 12 cycles of adjuvant nivolumab. Only the patients in the neoadjuvant group who had a partial response or nonresponse received subsequent adjuvant treatment. The primary end point was event-free survival. RESULTS: A total of 423 patients underwent randomization. At a median follow-up of 9.9 months, the estimated 12-month event-free survival was 83.7% (99.9% confidence interval [CI], 73.8 to 94.8) in the neoadjuvant group and 57.2% (99.9% CI, 45.1 to 72.7) in the adjuvant group. The difference in restricted mean survival time was 8.00 months (99.9% CI, 4.94 to 11.05; P<0.001; hazard ratio for progression, recurrence, or death, 0.32; 99.9% CI, 0.15 to 0.66). In the neoadjuvant group, 59.0% of the patients had a major pathological response, 8.0% had a partial response, 26.4% had a nonresponse (>50% residual viable tumor), and 2.4% had progression; in 4.2%, surgery had not yet been performed or was omitted. The estimated 12-month recurrence-free survival was 95.1% among patients in the neoadjuvant group who had a major pathological response, 76.1% among those who had a partial response, and 57.0% among those who had a nonresponse. Adverse events of grade 3 or higher that were related to systemic treatment occurred in 29.7% of the patients in the neoadjuvant group and in 14.7% in the adjuvant group. CONCLUSIONS: Among patients with resectable, macroscopic stage III melanoma, neoadjuvant ipilimumab plus nivolumab followed by surgery and response-driven adjuvant therapy resulted in longer event-free survival than surgery followed by adjuvant nivolumab. (Funded by Bristol Myers Squibb and others; NADINA ClinicalTrials.gov number, NCT04949113.).

How deregulation, drought and increasing fire impact Amazonian biodiversity.

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin1,2, but is increasingly threatened by deforestation and fire3,4. Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079-189,755 km2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3-85.2% of species that are listed as threatened in this region5. The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253-10,343 km2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon.

Inside the phagosome: A bacterial perspective.

The neutrophil phagosome is one of the most hostile environments that bacteria must face and overcome if they are to succeed as pathogens. Targeting bacterial defense mechanisms should lead to new therapies that assist neutrophils to kill pathogens, but this has not yet come to fruition. One of the limiting factors in this effort has been our incomplete knowledge of the complex biochemistry that occurs within the rapidly changing environment of the phagosome. The same compartmentalization that protects host tissue also limits our ability to measure events within the phagosome. In this review, we highlight the limitations in our knowledge, and how the contribution of bacteria to the phagosomal environment is often ignored. There appears to be significant heterogeneity among phagosomes, and it is important to determine whether survivors have more efficient defenses or whether they are ingested into less threatening environments than other bacteria. As part of these efforts, we discuss how monitoring or recovering bacteria from phagosomes can provide insight into the conditions they have faced. We also encourage the use of unbiased screening approaches to identify bacterial genes that are essential for survival inside neutrophil phagosomes.

Assessing and mitigating privacy risks of sparse, noisy genotypes by local alignment to haplotype databases.

Single nucleotide polymorphisms (SNPs) from omics data create a reidentification risk for individuals and their relatives. Although the ability of thousands of SNPs (especially rare ones) to identify individuals has been repeatedly shown, the availability of small sets of noisy genotypes, from environmental DNA samples or functional genomics data, motivated us to quantify their informativeness. We present a computational tool suite, termed Privacy Leakage by Inference across Genotypic HMM Trajectories (PLIGHT), using population-genetics-based hidden Markov models (HMMs) of recombination and mutation to find piecewise alignment of small, noisy SNP sets to reference haplotype databases. We explore cases in which query individuals are either known to be in the database, or not, and consider several genotype queries, including those from environmental sample swabs from known individuals and from simulated "mosaics" (two-individual composites). Using PLIGHT on a database with ∼5000 haplotypes, we find for common, noise-free SNPs that only ten are sufficient to identify individuals, ∼20 can identify both components in two-individual mosaics, and 20-30 can identify first-order relatives. Using noisy environmental-sample-derived SNPs, PLIGHT identifies individuals in a database using ∼30 SNPs. Even when the individuals are not in the database, local genotype matches allow for some phenotypic information leakage based on coarse-grained SNP imputation. Finally, by quantifying privacy leakage from sparse SNP sets, PLIGHT helps determine the value of selectively sanitizing released SNPs without explicit assumptions about population membership or allele frequency. To make this practical, we provide a sanitization tool to remove the most identifying SNPs from genomic data.

Phase 1 study of CAR-37 T cells in patients with relapsed or refractory CD37+ lymphoid malignancies.

We report on the first-in-human clinical trial using chimeric antigen receptor (CAR) T-cells targeting CD37, an antigen highly expressed in B- and T-cell malignancies (clinicaltrials.gov NCT04136275). Five patients with relapsed or refractory CD37+ lymphoid malignancies were enrolled and infused with autologous CAR-37 T-cells. CAR-37 T-cells expanded in the peripheral blood of all patients and, at peak, comprised >94% of the total lymphocytes in 4/5 patients. Tumor responses were observed in 4/5 patients, with 3 complete responses, 1 mixed response, and 1 patient whose disease progressed rapidly and with relative loss of CD37 expression. Three patients experienced prolonged and severe pancytopenia, and in two of these patients, efforts to ablate CAR-37 T-cells (which were engineered to co-express truncated EGFR) with cetuximab, were unsuccessful. Hematopoiesis was restored in these two patients following allogeneic hematopoietic stem cell transplantation. No other severe, non-hematopoietic toxicities occurred. We investigated the mechanisms of profound pancytopenia and did not observe activation of CAR-37 T-cells in response to hematopoietic stem cells in vitro or hematotoxicity in humanized models. Patients with pancytopenia had sustained high levels of IL-18, with low levels of IL-18 binding protein in their peripheral blood. IL-18 levels were significantly higher in CAR-37-treated patients relative to both cytopenic and non-cytopenic cohorts of CAR-19-treated cohorts of patients. In conclusion, CAR-37 T-cells exhibited anti-tumor activity, with significant CAR expansion and cytokine production. CAR-37 T-cells may be an effective therapy in hematologic malignancies as a bridge to hematopoietic stem cell transplant.

Ionic Liquids for the Separation of Fluorocarbon Refrigerant Mixtures.

This review discusses the research being performed on ionic liquids for the separation of fluorocarbon refrigerant mixtures. Fluorocarbon refrigerants, invented in 1928 by Thomas Midgley Jr., are a unique class of working fluids that are used in a variety of applications including refrigeration. Fluorocarbon refrigerants can be categorized into four generations: chlorofluorocarbons, hydrochlorofluorocarbons, hydrofluorocarbons, and hydrofluoroolefins. Each generation of refrigerants solved a key problem from the previous generation; however, each new generation has relied on more complex mixtures that are often zeotropic, near azeotropic, or azeotropic. The complexity of the refrigerants used and the fact that many refrigerants form azeotropes when mixed makes handling the refrigerants at end of life extremely difficult. Today, less than 3% of refrigerants that enter the market are recycled. This is due to a lack of technology in the refrigerant reclaim market that would allow for these complex, azeotropic refrigerant mixtures to be separated into their components in order to be effectively reused, recycled, and if needed repurposed. As the market for recovering and reclaiming refrigerants continues to grow, there is a strong need for separation technology. Ionic liquids show promise for separating azeotropic refrigerant mixtures as an entrainer in extractive distillation process. Ionic liquids have been investigated with refrigerants for this application since the early 2000s. This review will provide a comprehensive summary of the physical property measurements, equations of state modeling, molecular simulations, separation techniques, and unique materials unitizing ionic liquids for the development of an ionic-liquid-based separation process for azeotropic refrigerant mixtures.

Perspectives on ENCODE.

The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.

Clonally expanded CD8 T cells patrol the cerebrospinal fluid in Alzheimer's disease.

Alzheimer's disease is an incurable neurodegenerative disorder in which neuroinflammation has a critical function1. However, little is known about the contribution of the adaptive immune response in Alzheimer's disease2. Here, using integrated analyses of multiple cohorts, we identify peripheral and central adaptive immune changes in Alzheimer's disease. First, we performed mass cytometry of peripheral blood mononuclear cells and discovered an immune signature of Alzheimer's disease that consists of increased numbers of CD8+ T effector memory CD45RA+ (TEMRA) cells. In a second cohort, we found that CD8+ TEMRA cells were negatively associated with cognition. Furthermore, single-cell RNA sequencing revealed that T cell receptor (TCR) signalling was enhanced in these cells. Notably, by using several strategies of single-cell TCR sequencing in a third cohort, we discovered clonally expanded CD8+ TEMRA cells in the cerebrospinal fluid of patients with Alzheimer's disease. Finally, we used machine learning, cloning and peptide screens to demonstrate the specificity of clonally expanded TCRs in the cerebrospinal fluid of patients with Alzheimer's disease to two separate Epstein-Barr virus antigens. These results reveal an adaptive immune response in the blood and cerebrospinal fluid in Alzheimer's disease and provide evidence of clonal, antigen-experienced T cells patrolling the intrathecal space of brains affected by age-related neurodegeneration.

Space weather disrupts nocturnal bird migration.

Space weather, including solar storms, can impact Earth by disturbing the geomagnetic field. Despite the known dependence of birds and other animals on geomagnetic cues for successful seasonal migrations, the potential effects of space weather on organisms that use Earth's magnetic field for navigation have received little study. We tested whether space weather geomagnetic disturbances are associated with disruptions to bird migration at a macroecological scale. We leveraged long-term radar data to characterize the nightly migration dynamics of the nocturnally migrating North American avifauna over 22 y. We then used concurrent magnetometer data to develop a local magnetic disturbance index associated with each radar station (ΔBmax), facilitating spatiotemporally explicit analyses of the relationship between migration and geomagnetic disturbance. After controlling for effects of atmospheric weather and spatiotemporal patterns, we found a 9 to 17% decrease in migration intensity in both spring and fall during severe space weather events. During fall migration, we also found evidence for decreases in effort flying against the wind, which may represent a depression of active navigation such that birds drift more with the wind during geomagnetic disturbances. Effort flying against the wind in the fall was most reduced under both overcast conditions and high geomagnetic disturbance, suggesting that a combination of obscured celestial cues and magnetic disturbance may disrupt navigation. Collectively, our results provide evidence for community-wide avifaunal responses to geomagnetic disturbances driven by space weather during nocturnal migration.

Site-specific decreases in DNA methylation in replicating cells following exposure to oxidative stress.

Oxidative stress is a common feature of inflammation-driven cancers, and it promotes genomic instability and aggressive tumour phenotypes. It is known that oxidative stress transiently modulates gene expression through the oxidation of transcription factors and associated regulatory proteins. Neutrophils are our most abundant white blood cells and accumulate at sites of infection and inflammation. Activated neutrophils produce hypochlorous acid and chloramines, which can disrupt DNA methylation by oxidizing methionine. The goal of the current study was to determine whether chloramine exposure results in sequence-specific modifications in DNA methylation that enable long-term alterations in transcriptional output. Proliferating Jurkat T-lymphoma cells were exposed to sublethal doses of glycine chloramine and differential methylation patterns were compared using Illumina EPIC 850 K bead chip arrays. There was a substantial genome-wide decrease in methylation 4 h after exposure that correlated with altered RNA expression for 24 and 48 h, indicating sustained impacts on exposed cells. A large proportion of the most significant differentially methylated CpG sites were situated towards chromosomal ends, suggesting that these regions are most susceptible to inhibition of maintenance DNA methylation. This may contribute to epigenetic instability of chromosomal ends in rapidly dividing cells, with potential implications for the regulation of telomere length and cellular longevity.

MolLM: a unified language model for integrating biomedical text with 2D and 3D molecular representations.

MOTIVATION: The current paradigm of deep learning models for the joint representation of molecules and text primarily relies on 1D or 2D molecular formats, neglecting significant 3D structural information that offers valuable physical insight. This narrow focus inhibits the models' versatility and adaptability across a wide range of modalities. Conversely, the limited research focusing on explicit 3D representation tends to overlook textual data within the biomedical domain. RESULTS: We present a unified pre-trained language model, MolLM, that concurrently captures 2D and 3D molecular information alongside biomedical text. MolLM consists of a text Transformer encoder and a molecular Transformer encoder, designed to encode both 2D and 3D molecular structures. To support MolLM's self-supervised pre-training, we constructed 160K molecule-text pairings. Employing contrastive learning as a supervisory signal for learning, MolLM demonstrates robust molecular representation capabilities across four downstream tasks, including cross-modal molecule and text matching, property prediction, captioning, and text-prompted molecular editing. Through ablation, we demonstrate that the inclusion of explicit 3D representations improves performance in these downstream tasks. AVAILABILITY AND IMPLEMENTATION: Our code, data, pre-trained model weights, and examples of using our model are all available at https://github.com/gersteinlab/MolLM. In particular, we provide Jupyter Notebooks offering step-by-step guidance on how to use MolLM to extract embeddings for both molecules and text.

BioCoder: a benchmark for bioinformatics code generation with large language models.

SUMMARY: Pretrained large language models (LLMs) have significantly improved code generation. As these models scale up, there is an increasing need for the output to handle more intricate tasks and to be appropriately specialized to particular domains. Here, we target bioinformatics due to the amount of domain knowledge, algorithms, and data operations this discipline requires. We present BioCoder, a benchmark developed to evaluate LLMs in generating bioinformatics-specific code. BioCoder spans much of the field, covering cross-file dependencies, class declarations, and global variables. It incorporates 1026 Python functions and 1243 Java methods extracted from GitHub, along with 253 examples from the Rosalind Project, all pertaining to bioinformatics. Using topic modeling, we show that the overall coverage of the included code is representative of the full spectrum of bioinformatics calculations. BioCoder incorporates a fuzz-testing framework for evaluation. We have applied it to evaluate various models including InCoder, CodeGen, CodeGen2, SantaCoder, StarCoder, StarCoder+, InstructCodeT5+, GPT-3.5, and GPT-4. Furthermore, we fine-tuned one model (StarCoder), demonstrating that our training dataset can enhance the performance on our testing benchmark (by >15% in terms of Pass@K under certain prompt configurations and always >3%). The results highlight two key aspects of successful models: (i) Successful models accommodate a long prompt (>2600 tokens) with full context, including functional dependencies. (ii) They contain domain-specific knowledge of bioinformatics, beyond just general coding capability. This is evident from the performance gain of GPT-3.5/4 compared to the smaller models on our benchmark (50% versus up to 25%). AVAILABILITY AND IMPLEMENTATION: All datasets, benchmark, Docker images, and scripts required for testing are available at: https://github.com/gersteinlab/biocoder and https://biocoder-benchmark.github.io/.