Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning

Gait is impaired in musculoskeletal conditions, such as knee arthropathy. Gait analysis is used in clinical practice to inform diagnosis and to monitor disease progression or intervention response. However, clinical gait analysis relies on subjective visual observation of walking, as objective gait analysis has not been possible within clinical settings due to the expensive equipment, large-scale facilities, and highly trained staff required. Relatively low-cost wearable digital insoles may offer a solution to these challenges. In this work, we demonstrate how a digital insole measuring osteoarthritis-specific gait signatures yields similar results to the clinical gait-lab standard. To achieve this, we constructed a machine learning model, trained on force plate data collected in participants with knee arthropathy and controls. This model was highly predictive of force plate data from a validation set (area under the receiver operating characteristics curve [auROC] = 0.86; area under the precision-recall curve [auPR] = 0.90) and of a separate, independent digital insole dataset containing control and knee osteoarthritis subjects (auROC = 0.83; auPR = 0.86). After showing that digital insole derived gait characteristics are comparable to traditional gait measurements, we next showed that a single stride of raw sensor time series data could be accurately assigned to each subject, highlighting that individuals using digital insoles can be identified by their gait characteristics. This work provides a framework for a promising alternative to traditional clinical gait analysis methods, adds to the growing body of knowledge regarding wearable technology analytical pipelines, and supports clinical development of at-home gait assessments, with the potential to improve the ease, frequency, and depth of patient monitoring.

Identification of pan-cancer/testis genes and validation of therapeutic targeting in triple-negative breast cancer: Lin28a-based and Siglece-based vaccination induces antitumor immunity and inhibits metastasis

BACKGROUND

Cancer-testis (CT) genes are targets for tumor antigen-specific immunotherapy given that their expression is normally restricted to the immune-privileged testis in healthy individuals with aberrant expression in tumor tissues. While they represent targetable germ tissue antigens and play important functional roles in tumorigenesis, there is currently no standardized approach for identifying clinically relevant CT genes. Optimized algorithms and validated methods for accurate prediction of reliable CT antigens (CTAs) with high immunogenicity are also lacking.

METHODS

Sequencing data from the Genotype-Tissue Expression (GTEx) and The Genomic Data Commons (GDC) databases was used for the development of a bioinformatic pipeline to identify CT exclusive genes. A CT germness score was calculated based on the number of CT genes expressed within a tumor type and their degree of expression. The impact of tumor germness on clinical outcome was evaluated using healthy GTEx and GDC tumor samples. We then used a triple-negative breast cancer mouse model to develop and test an algorithm that predicts epitope immunogenicity based on the identification of germline sequences with strong major histocompatibility complex class I (MHCI) and MHCII binding affinities. Germline sequences for CT genes were synthesized as long synthetic peptide vaccines and tested in the 4T1 triple-negative model of invasive breast cancer with Poly(I:C) adjuvant. Vaccine immunogenicity was determined by flow cytometric analysis of in vitro and in vivo T-cell responses. Primary tumor growth and lung metastasis was evaluated by histopathology, flow cytometry and colony formation assay.

RESULTS

We developed a new bioinformatic pipeline to reliably identify CT exclusive genes as immunogenic targets for immunotherapy. We identified CT genes that are exclusively expressed within the testis, lack detectable thymic expression, and are significantly expressed in multiple tumor types. High tumor germness correlated with tumor progression but not with tumor mutation burden, supporting CTAs as appealing targets in low mutation burden tumors. Importantly, tumor germness also correlated with markers of antitumor immunity. Vaccination of 4T1 tumor-bearing mice with Siglece and Lin28a antigens resulted in increased T-cell antitumor immunity and reduced primary tumor growth and lung metastases.

CONCLUSION

Our results present a novel strategy for the identification of highly immunogenic CTAs for the development of targeted vaccines that induce antitumor immunity and inhibit metastasis.

Microenvironment-dependent growth of Sezary cells in humanized IL-15 mice

Sezary syndrome (SS) is a rare, aggressive leukemic variant of cutaneous T-cell lymphoma (CTCL) that lacks adequate therapeutic options and representative small-animal models. Here, we demonstrate that IL-15 is a critical CTCL growth factor. Importantly, an immunodeficient knock-in mouse model genetically engineered to express human IL-15 uniquely supported the growth of SS patient samples relative to conventional immunodeficient mouse strains. SS patient-derived xenograft (PDX) models recapacitated key pathological features of the human disease, including skin infiltration and spread of leukemic cells to the periphery, and maintained the dependence on human IL-15 upon serial in vivo passaging. Detailed molecular characterization of the engrafted cells by single-cell transcriptomic analysis revealed congruent neoplastic gene expression signatures but distinct clonal engraftment patterns. Overall, we document an important dependence of Sezary cell survival and proliferation on IL-15 signaling and the utility of immunodeficient humanized IL-15 mice as hosts for SS - and potentially other T and NK cell-derived hematologic malignancies - PDX model generation. Furthermore, these studies advocate the thorough molecular understanding of the resultant PDX models to maximize their translational impact.

Activin E-ACVR1C cross talk controls energy storage via suppression of adipose lipolysis in mice

Body fat distribution is a heritable risk factor for cardiovascular and metabolic disease. In humans, rare Inhibin beta E (INHBE, activin E) loss-of-function variants are associated with a lower waist-to-hip ratio and protection from type 2 diabetes. Hepatic fatty acid sensing promotes INHBE expression during fasting and in obese individuals, yet it is unclear how the hepatokine activin E governs body shape and energy metabolism. Here, we uncover activin E as a regulator of adipose energy storage. By suppressing β-agonist-induced lipolysis, activin E promotes fat accumulation and adipocyte hypertrophy and contributes to adipose dysfunction in mice. Mechanistically, we demonstrate that activin E elicits its effect on adipose tissue through ACVR1C, activating SMAD2/3 signaling and suppressing PPARG target genes. Conversely, loss of activin E or ACVR1C in mice increases fat utilization, lowers adiposity, and drives PPARG-regulated gene signatures indicative of healthy adipose function. Our studies identify activin E-ACVR1C as a metabolic rheostat promoting liver-adipose cross talk to restrain excessive fat breakdown and preserve fat mass during prolonged fasting, a mechanism that is maladaptive in obese individuals.

TRAPnSeq allows high-throughput profiling of antigen-specific antibody-secreting cells

Following activation by cognate antigen, B cells undergo fine-tuning of their antigen receptors and may ultimately differentiate into antibody-secreting cells (ASCs). While antigen-specific B cells that express surface receptors (B cell receptors [BCRs]) can be readily cloned and sequenced following flow sorting, antigen-specific ASCs that lack surface BCRs cannot be easily profiled. Here, we report an approach, TRAPnSeq (antigen specificity mapping through immunoglobulin [Ig] secretion TRAP and Sequencing), that allows capture of secreted antibodies on the surface of ASCs, which in turn enables high-throughput screening of single ASCs against large antigen panels. This approach incorporates flow cytometry, standard microfluidic platforms, and DNA-barcoding technologies to characterize antigen-specific ASCs through single-cell V(D)J, RNA, and antigen barcode sequencing. We show the utility of TRAPnSeq by profiling antigen-specific IgG and IgE ASCs from both mice and humans and highlight its capacity to accelerate therapeutic antibody discovery from ASCs.

A cellular and molecular spatial atlas of dystrophic muscle

Asynchronous skeletal muscle degeneration/regeneration is a hallmark feature of Duchenne muscular dystrophy (DMD); however, traditional -omics technologies that lack spatial context make it difficult to study the biological mechanisms of how asynchronous regeneration contributes to disease progression. Here, using the severely dystrophic D2-mdx mouse model, we generated a high-resolution cellular and molecular spatial atlas of dystrophic muscle by integrating spatial transcriptomics and single-cell RNAseq datasets. Unbiased clustering revealed nonuniform distribution of unique cell populations throughout D2-mdx muscle that were associated with multiple regenerative timepoints, demonstrating that this model faithfully recapitulates the asynchronous regeneration observed in human DMD muscle. By probing spatiotemporal gene expression signatures, we found that propagation of inflammatory and fibrotic signals from locally damaged areas contributes to widespread pathology and that querying expression signatures within discrete microenvironments can identify targetable pathways for DMD therapy. Overall, this spatial atlas of dystrophic muscle provides a valuable resource for studying DMD disease biology and therapeutic target discovery.

Age-related gene expression signatures from limb skeletal muscles and the diaphragm in mice and rats reveal common and species-specific changes

BACKGROUND

As a result of aging, skeletal muscle undergoes atrophy and a decrease in function. This age-related skeletal muscle weakness is known as "sarcopenia". Sarcopenia is part of the frailty observed in humans. In order to discover treatments for sarcopenia, it is necessary to determine appropriate preclinical models and the genes and signaling pathways that change with age in these models.

METHODS AND RESULTS

To understand the changes in gene expression that occur as a result of aging in skeletal muscles, we generated a multi-time-point gene expression signature throughout the lifespan of mice and rats, as these are the most commonly used species in preclinical research and intervention testing. Gastrocnemius, tibialis anterior, soleus, and diaphragm muscles from male and female C57Bl/6J mice and male Sprague Dawley rats were analyzed at ages 6, 12, 18, 21, 24, and 27 months, plus an additional 9-month group was used for rats. More age-related genes were identified in rat skeletal muscles compared with mice; this was consistent with the finding that rat muscles undergo more robust age-related decline in mass. In both species, pathways associated with innate immunity and inflammation linearly increased with age. Pathways linked with extracellular matrix remodeling were also universally downregulated. Interestingly, late downregulated pathways were exclusively found in the rat limb muscles and these were linked to metabolism and mitochondrial respiration; this was not seen in the mouse.

CONCLUSIONS

This extensive, side-by-side transcriptomic profiling shows that the skeletal muscle in rats is impacted more by aging compared with mice, and the pattern of decline in the rat may be more representative of the human. The observed changes point to potential therapeutic interventions to avoid age-related decline in skeletal muscle function.

Intratumoral dendritic cell-CD4+ T helper cell niches enable CD8+ T cell differentiation following PD-1 blockade in hepatocellular carcinoma

Despite no apparent defects in T cell priming and recruitment to tumors, a large subset of T cell rich tumors fail to respond to immune checkpoint blockade (ICB). We leveraged a neoadjuvant anti-PD-1 trial in patients with hepatocellular carcinoma (HCC), as well as additional samples collected from patients treated off-label, to explore correlates of response to ICB within T cell-rich tumors. We show that ICB response correlated with the clonal expansion of intratumoral CXCL13+CH25H+IL-21+PD-1+CD4+ T helper cells ("CXCL13+ TH") and Granzyme K+ PD-1+ effector-like CD8+ T cells, whereas terminally exhausted CD39hiTOXhiPD-1hiCD8+ T cells dominated in nonresponders. CD4+ and CD8+ T cell clones that expanded post-treatment were found in pretreatment biopsies. Notably, PD-1+TCF-1+ (Progenitor-exhausted) CD8+ T cells shared clones mainly with effector-like cells in responders or terminally exhausted cells in nonresponders, suggesting that local CD8+ T cell differentiation occurs upon ICB. We found that these Progenitor CD8+ T cells interact with CXCL13+ TH within cellular triads around dendritic cells enriched in maturation and regulatory molecules, or "mregDC". These results suggest that discrete intratumoral niches that include mregDC and CXCL13+ TH control the differentiation of tumor-specific Progenitor exhasuted CD8+ T cells following ICB.

Identification of pan-cancer/testis genes and validation of therapeutic targeting in triple-negative breast cancer: Lin28a- and Siglece-based vaccination induces anti-tumor immunity and inhibits metastasis

Background

Cancer-testis (CT) genes are targets for tumor antigen-specific immunotherapy given that their expression is normally restricted to the immune-privileged testis in healthy individuals with aberrant expression in tumor tissues. While they represent targetable germ-tissue antigens and play important functional roles in tumorigenesis, there is currently no standardized approach for identifying clinically relevant CT genes. Optimized algorithms and validated methods for accurate prediction of reliable CT antigens with high immunogenicity are also lacking.

Methods

Sequencing data from the Genotype-Tissue Expression (GTEx) and The Genomic Data Commons (GDC) databases was utilized for the development of a bioinformatic pipeline to identify CT exclusive genes. A CT germness score was calculated based on the number of CT genes expressed within a tumor type and their degree of expression. The impact of tumor germness with clinical outcome was evaluated using healthy GTEx and GDC tumor samples. We then used a triple-negative breast cancer mouse model to develop and test an algorithm that predicts epitope immunogenicity based on the identification of germline sequences with strong MHCI and MHCII binding affinities. Germline sequences for CT genes were synthesized as long synthetic peptide vaccines and tested in the 4T1 triple-negative model of invasive breast cancer with Poly(I:C) adjuvant. Vaccine immunogenicity was determined by flow cytometric analysis of in vitro and in vivo T cell responses. Primary tumor growth and lung metastasis was evaluated by histopathology, flow cytometry and colony formation assay.

Results

We developed a new bioinformatic pipeline to reliably identify CT exclusive genes as immunogenic targets for immunotherapy. We identified CT genes that are exclusively expressed within the testis, lack detectable thymic expression, and are significantly expressed in multiple tumor types. High tumor germness correlated with tumor progression but not with tumor mutation burden, supporting CT antigens as appealing targets in low mutation burden tumors. Importantly, tumor germness also correlated with markers of anti-tumor immunity. Vaccination of 4T1 tumor bearing mice with Siglece and Lin28a antigens resulted in increased T cell anti-tumor immunity and reduced primary tumor growth and lung metastases.

Conclusion

Our results present a novel strategy for the identification of highly immunogenic CT antigens for the development of targeted vaccines that induce anti-tumor immunity and inhibit metastasis.

Structure of the Inmazeb cocktail and resistance to Ebola virus escape

Monoclonal antibodies can provide important pre- or post-exposure protection against infectious disease for those not yet vaccinated or in individuals that fail to mount a protective immune response after vaccination. Inmazeb (REGN-EB3), a three-antibody cocktail against Ebola virus, lessened disease and improved survival in a controlled trial. Here, we present the cryo-EM structure at 3.1 Å of the Ebola virus glycoprotein, determined without symmetry averaging, in a simultaneous complex with the antibodies in the Inmazeb cocktail. This structure allows the modeling of previously disordered portions of the glycoprotein glycan cap, maps the non-overlapping epitopes of Inmazeb, and illuminates the basis for complementary activities and residues critical for resistance to escape by these and other clinically relevant antibodies. We further provide direct evidence that Inmazeb protects against the rapid emergence of escape mutants, whereas monotherapies even against conserved epitopes do not, supporting the benefit of a cocktail versus a monotherapy approach.

Proteogenomic identification of Hepatitis B virus (HBV) genotype-specific HLA-I restricted peptides from HBV-positive patient liver tissues

The presentation of virus-derived peptides by HLA class I molecules on the surface of an infected cell and the recognition of these HLA-peptide complexes by, and subsequent activation of, CD8⁺ cytotoxic T cells provides an important mechanism for immune protection against viruses. Recent advances in proteogenomics have allowed researchers to discover a growing number of unique HLA-restricted viral peptides, resulting in a rapidly expanding repertoire of targets for immunotherapeutics (i.e. bispecific antibodies, engineered T-cell receptors (TCRs), chimeric antigen receptor T-cells (CAR-Ts)) to infected tissues. However, genomic variability between viral strains, such as Hepatitis-B virus (HBV), in combination with differences in patient HLA alleles, make it difficult to develop therapeutics against these targets. To address this challenge, we developed a novel proteogenomics approach for generating patient-specific databases that enable the identification of viral peptides based on the viral transcriptomes sequenced from individual patient liver samples. We also utilized DNA sequencing of patient samples to identify HLA genotypes and assist in target selection. Liver samples from 48 HBV infected patients, primarily from Asia, were examined to reconstruct patient-specific HBV genomes, identify regions within the human chromosomes targeted by HBV integrations and obtain a comprehensive view of HBV peptide epitopes using our HLA class-I (HLA-I) immunopeptidomics discovery platform. Two previously reported HLA associated HBV-derived peptides, HLA-A02 binder FLLTRILTI (S_194-202) from the large surface antigen and HLA-A11 binder STLPETTVVRR (C_141-151) from the capsid protein were validated by our discovery platform, but both were detected at very low frequencies. In addition, we identified and validated, using heavy peptide analogues, novel strain-specific HBV-HLA associated peptides, such as GSLPQEHIVQK (P_606-616) and variants. Overall, our novel approach can guide the development of bispecific antibody, TCR-T, or CAR-T based therapeutics for the treatment of HBV-related HCC and inform vaccine development.

Cancer cell-derived type I interferons instruct tumor monocyte polarization

Monocytes are highly plastic immune cells that modulate antitumor immunity. Therefore, identifying factors that regulate tumor monocyte functions is critical for developing effective immunotherapies. Here, we determine that endogenous cancer cell-derived type I interferons (IFNs) control monocyte functional polarization. Guided by single-cell transcriptomic profiling of human and mouse tumors, we devise a strategy to distinguish and separate immunostimulatory from immunosuppressive tumor monocytes by surface CD88 and Sca-1 expression. Leveraging this approach, we show that cGAS-STING-regulated cancer cell-derived IFNs polarize immunostimulatory monocytes associated with anti-PD-1 immunotherapy response in mice. We also demonstrate that immunosuppressive monocytes convert into immunostimulatory monocytes upon cancer cell-intrinsic cGAS-STING activation. Consistently, we find that human cancer cells can produce type I IFNs that polarize monocytes, and our immunostimulatory monocyte gene signature is enriched in patient tumors that respond to anti-PD-1 immunotherapy. Our work exposes a role for cancer cell-derived IFNs in licensing monocyte functions that influence immunotherapy outcomes.

Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes

Body fat distribution is a major, heritable risk factor for cardiometabolic disease, independent of overall adiposity. Using exome-sequencing in 618,375 individuals (including 160,058 non-Europeans) from the UK, Sweden and Mexico, we identify 16 genes associated with fat distribution at exome-wide significance. We show 6-fold larger effect for fat-distribution associated rare coding variants compared with fine-mapped common alleles, enrichment for genes expressed in adipose tissue and causal genes for partial lipodystrophies, and evidence of sex-dimorphism. We describe an association with favorable fat distribution (p = 1.8 × 10^-09), favorable metabolic profile and protection from type 2 diabetes (~28% lower odds; p = 0.004) for heterozygous protein-truncating mutations in INHBE, which encodes a circulating growth factor of the activin family, highly and specifically expressed in hepatocytes. Our results suggest that inhibin βE is a liver-expressed negative regulator of adipose storage whose blockade may be beneficial in fat distribution-associated metabolic disease.

Single-cell RNA transcriptome landscape of hepatocytes and non-parenchymal cells in healthy and NAFLD mouse liver

Nonalcoholic fatty liver disease (NAFLD) is a global health-care problem with limited therapeutic options. To obtain a cellular resolution of pathogenesis, 82,168 single-cell transcriptomes (scRNA-seq) across different NAFLD stages were profiled, identifying hepatocytes and 12 other non-parenchymal cell (NPC) types. scRNA-seq revealed insights into the cellular and molecular mechanisms of the disease. We discovered a dual role for hepatic stellate cells in gene expression regulation and in the potential to trans-differentiate into myofibroblasts. We uncovered distinct expression profiles of Kupffer cells versus monocyte-derived macrophages during NAFLD progression. Kupffer cells showed stronger immune responses, while monocyte-derived macrophages demonstrated a capability for differentiation. Three chimeric NPCs were identified including endothelial-chimeric stellate cells, hepatocyte-chimeric endothelial cells, and endothelial-chimeric Kupffer cells. Our work identified unanticipated aspects of mouse with NAFLD at the single-cell level and advanced the understanding of cellular heterogeneity in NAFLD livers.

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Of all, 82,168 single-cell transcriptomes across different NAFLD stages were profiled

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Hepatocytes and 12 non-parenchymal cell types were identified in mouse liver

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Three chimeric NPCs were identified in mouse liver

AdRoit is an accurate and robust method to infer complex transcriptome composition

Bulk RNA sequencing provides the opportunity to understand biology at the whole transcriptome level without the prohibitive cost of single cell profiling. Advances in spatial transcriptomics enable to dissect tissue organization and function by genome-wide gene expressions. However, the readout of both technologies is the overall gene expression across potentially many cell types without directly providing the information of cell type constitution. Although several in-silico approaches have been proposed to deconvolute RNA-Seq data composed of multiple cell types, many suffer a deterioration of performance in complex tissues. Here we present AdRoit, an accurate and robust method to infer the cell composition from transcriptome data of mixed cell types. AdRoit uses gene expression profiles obtained from single cell RNA sequencing as a reference. It employs an adaptive learning approach to alleviate the sequencing technique difference between the single cell and the bulk (or spatial) transcriptome data, enhancing cross-platform readout comparability. Our systematic benchmarking and applications, which include deconvoluting complex mixtures that encompass 30 cell types, demonstrate its preferable sensitivity and specificity compared to many existing methods as well as its utilities. In addition, AdRoit is computationally efficient and runs orders of magnitude faster than most methods.

Butyrophilin-like 2 regulates site-specific adaptations of intestinal γδ intraepithelial lymphocytes

Tissue-resident γδ intraepithelial lymphocytes (IELs) orchestrate innate and adaptive immune responses to maintain intestinal epithelial barrier integrity. Epithelia-specific butyrophilin-like (Btnl) molecules induce perinatal development of distinct Vγ TCR⁺ IELs, however, the mechanisms that control γδ IEL maintenance within discrete intestinal segments are unclear. Here, we show that Btnl2 suppressed homeostatic proliferation of γδ IELs preferentially in the ileum. High throughput transcriptomic characterization of site-specific Btnl2-KO γδ IELs reveals that Btnl2 regulated the antimicrobial response module of ileal γδ IELs. Btnl2 deficiency shapes the TCR specificities and TCRγ/δ repertoire diversity of ileal γδ IELs. During DSS-induced colitis, Btnl2-KO mice exhibit increased inflammation and delayed mucosal repair in the colon. Collectively, these data suggest that Btnl2 fine-tunes γδ IEL frequencies and TCR specificities in response to site-specific homeostatic and inflammatory cues. Hence, Btnl-mediated targeting of γδ IEL development and maintenance may help dissect their immunological functions in intestinal diseases with segment-specific manifestations.

Panea et al showed that epithelia-specific butyrophilinlike 2 (Btnl2) suppressed homeostatic proliferation of γδ intraepithelial lymphocytes (IELs) preferentially in the ileum and used high throughput transcriptomic characterization of Btnl2-deficient γδ IELs to demonstrate that Btnl2 impacts γδ TCR specificities and repertoire diversity of ileal γδ IELs. In addition, they showed that Btnl2-deficient mice exhibited increased inflammation and delayed mucosal repair in the colon, suggesting that it plays a key immunological function in intestinal diseases.

The monoclonal antibody combination REGEN-COV protects against SARS-CoV-2 mutational escape in preclinical and human studies

Monoclonal antibodies against SARS-CoV-2 are a clinically validated therapeutic option against COVID-19. Because rapidly emerging virus mutants are becoming the next major concern in the fight against the global pandemic, it is imperative that these therapeutic treatments provide coverage against circulating variants and do not contribute to development of treatment-induced emergent resistance. To this end, we investigated the sequence diversity of the spike protein and monitored emergence of virus variants in SARS-COV-2 isolates found in COVID-19 patients treated with the two-antibody combination REGEN-COV, as well as in preclinical in vitro studies using single, dual, or triple antibody combinations, and in hamster in vivo studies using REGEN-COV or single monoclonal antibody treatments. Our study demonstrates that the combination of non-competing antibodies in REGEN-COV provides protection against all current SARS-CoV-2 variants of concern/interest and also protects against emergence of new variants and their potential seeding into the population in a clinical setting.

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring.

Noise regularization removes correlation artifacts in single-cell RNA-seq data preprocessing

With the rapid advancement of single-cell RNA-sequencing (scRNA-seq) technology, many data-preprocessing methods have been proposed to address numerous systematic errors and technical variabilities inherent in this technology. While these methods have been demonstrated to be effective in recovering individual gene expression, the suitability to the inference of gene-gene associations and subsequent gene network reconstruction have not been systemically investigated. In this study, we benchmarked five representative scRNA-seq normalization/imputation methods on Human Cell Atlas bone marrow data with respect to their impacts on inferred gene-gene associations. Our results suggested that a considerable amount of spurious correlations was introduced during the data-preprocessing steps due to oversmoothing of the raw data. We proposed a model-agnostic noise-regularization method that can effectively eliminate the correlation artifacts. The noise-regularized gene-gene correlations were further used to reconstruct a gene co-expression network and successfully revealed several known immune cell modules.

REGN-COV2 antibodies prevent and treat SARS-CoV-2 infection in rhesus macaques and hamsters

An urgent global quest for effective therapies to prevent and treat coronavirus disease 2019 (COVID-19) is ongoing. We previously described REGN-COV2, a cocktail of two potent neutralizing antibodies (REGN10987 and REGN10933) that targets nonoverlapping epitopes on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein. In this report, we evaluate the in vivo efficacy of this antibody cocktail in both rhesus macaques, which may model mild disease, and golden hamsters, which may model more severe disease. We demonstrate that REGN-COV-2 can greatly reduce virus load in the lower and upper airways and decrease virus-induced pathological sequelae when administered prophylactically or therapeutically in rhesus macaques. Similarly, administration in hamsters limits weight loss and decreases lung titers and evidence of pneumonia in the lungs. Our results provide evidence of the therapeutic potential of this antibody cocktail.

Antibody cocktail to SARS-CoV-2 spike protein prevents rapid mutational escape seen with individual antibodies

Antibodies targeting the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) present a promising approach to combat the coronavirus disease 2019 (COVID-19) pandemic; however, concerns remain that mutations can yield antibody resistance. We investigated the development of resistance against four antibodies to the spike protein that potently neutralize SARS-CoV-2, individually as well as when combined into cocktails. These antibodies remain effective against spike variants that have arisen in the human population. However, novel spike mutants rapidly appeared after in vitro passaging in the presence of individual antibodies, resulting in loss of neutralization; such escape also occurred with combinations of antibodies binding diverse but overlapping regions of the spike protein. Escape mutants were not generated after treatment with a noncompeting antibody cocktail.

Absence of central tolerance in Aire-deficient mice synergizes with immune-checkpoint inhibition to enhance antitumor responses

The endogenous anti-tumor responses are limited in part by the absence of tumor-reactive T cells, an inevitable consequence of thymic central tolerance mechanisms ensuring prevention of autoimmunity. Here we show that tumor rejection induced by immune checkpoint blockade is significantly enhanced in Aire-deficient mice, the epitome of central tolerance breakdown. The observed synergy in tumor rejection extended to different tumor models, was accompanied by increased numbers of activated T cells expressing high levels of Gzma, Gzmb, Perforin, Cxcr3, and increased intratumoural levels of Cxcl9 and Cxcl10 compared to wild-type mice. Consistent with Aire's central role in T cell repertoire selection, single cell TCR sequencing unveiled expansion of several clones with high tumor reactivity. The data suggest that breakdown in central tolerance synergizes with immune checkpoint blockade in enhancing anti-tumor immunity and may serve as a model to unmask novel anti-tumor therapies including anti-tumor TCRs, normally purged during central tolerance.

Abstract A41: Absence of central tolerance as a sculpting mechanism of immune-checkpoint therapy

Therapeutic targeting of immune checkpoint pathways, which are exploited by tumors to evade the immune system, can result in increased overall survival for some patients with specific types of cancers. The endogenous antitumor response is limited in part by the absence of tumor-reactive T cells, an inevitable consequence of thymic central tolerance mechanisms ensuring their deletion to protect against autoimmunity. In this study, we show that compared to wild-type mice, tumor rejection induced by immune checkpoint blockade is significantly enhanced in Aire-deficient mice, the epitome of central tolerance breakdown. The observed synergy in tumor rejection extended to different tumor models and was accompanied by increased numbers of activated T cells expressing high levels of genes such as Gzma, Gzmb, Perforin, and Cxcr3, and tumors contained high levels of the chemokines Cxcl9 and Cxcl10 compared to wild-type mice. Furthermore, there was an enrichment of T cells expressing markers associated with the potent antitumor tissue-resident memory T cells expressing Cd103. Consistent with Aire’s central role in T cells’ repertoire selection, single-cell TCR sequencing unveiled the expansion of several clones with high tumor reactivity. Together, these results show that a break in central tolerance in combination with immune checkpoint blockade can potently enhance antitumor immunity and serve as a model system to unmask novel antitumor therapies.

Citation Format: Asiel A. Benitez, Sara Khalil-Aguero, Anjali Nandakumar, Namita Gupta, Wendy Zhang, Gurinder S. Atwal, Andrew J. Murphy, Matthew A. Sleeman, Sokol Haxhinasto. Absence of central tolerance as a sculpting mechanism of immune-checkpoint therapy [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2019 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(3 Suppl):Abstract nr A41.

Bayesian Inference of Allelic Inclusion Rates in the Human T Cell Receptor Repertoire

A small population of αβ T cells is characterized by the expression of more than one unique T cell receptor (TCR); this outcome is the result of "allelic inclusion," that is, inclusion of both α- or β-chain alleles during V(D)J recombination. Limitations in single-cell sequencing technology, however, have precluded comprehensive enumeration of these dual receptor T cells. Here, we develop and experimentally validate a fully Bayesian inference model capable of reliably estimating the true rate of α and β TCR allelic inclusion across two different emulsion-barcoding single-cell sequencing platforms. We provide a database composed of over 51,000 previously unpublished allelic inclusion TCR sequence sets drawn from eight healthy individuals and show that allelic inclusion contributes a distinct and functionally important set of sequences to the human TCR repertoire. This database and a Python implementation of our statistical inference model are freely available at our Github repository (https://github.com/JasonACarter/Allelic_inclusion).

Single T Cell Sequencing Demonstrates the Functional Role of αβ TCR Pairing in Cell Lineage and Antigen Specificity

Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antigen recognition, repertoire-level immunogenomic analyses have historically examined the β chain alone. To determine the amount of useful information about TCR repertoire function encoded within αβ pairings, we analyzed paired TCR sequences from nearly 100,000 unique CD4+ and CD8+ T cells captured using two different high-throughput, single-cell sequencing approaches. Our results demonstrate little overlap in the healthy CD4+ and CD8+ repertoires, with shared TCR sequences possessing significantly shorter CDR3 sequences corresponding to higher generation probabilities. We further utilized tools from information theory and machine learning to show that while α and β chains are only weakly associated with lineage, αβ pairings appear to synergistically drive TCR-MHC interactions. Vαβ gene pairings were found to be the TCR feature most informative of T cell lineage, supporting the existence of germline-encoded paired αβ TCR-MHC interaction motifs. Finally, annotating our TCR pairs using a database of sequences with known antigen specificities, we demonstrate that approximately a third of the T cells possess α and β chains that each recognize different known antigens, suggesting that αβ pairing is critical for the accurate inference of repertoire functionality. Together, these findings provide biological insight into the functional implications of αβ pairing and highlight the utility of single-cell sequencing in immunogenomics.

Ostium Ratio and Neck Ratio Could Predict the Outcome of Sidewall Intracranial Aneurysms Treated with Flow Diverters

BACKGROUND AND PURPOSE

Incompletely occluded flow diverter treated aneurysms remain at risk of rupture and thromboembolic complications. Our aim was to identify the potential for incomplete occlusion of intracranial aneurysms treated by flow diverters. We investigated whether aneurysm ostium size in relation to parent artery size affects angiographic outcomes of flow diverter-treated sidewall aneurysms.

MATERIALS AND METHODS

Flow diverter-treated sidewall aneurysms were divided into "occluded" and "residual" (incomplete occlusion) groups based on 6-month angiographic follow-up. We calculated the ostium ratio, a new parameter defined as the aneurysm ostium surface area versus the circumferential surface area of the parent artery. We also calculated the neck ratio, defined as clinical aneurysm neck diameter versus parent artery diameter from pretreatment 2D DSA, as a 2D surrogate. We compared the performance of these ratios with existing aneurysm morphometrics (size, neck diameter, volume, aspect ratio, size ratio, undulation index, nonsphericity index, ellipticity index, bottleneck factor, aneurysm angle, and parent vessel angle) and flow diverter-related parameters (metal coverage rate and pore density). Statistical tests and receiver operating characteristic analyses were performed to identify significantly different parameters between the 2 groups and test their predictive performances.

RESULTS

We included 63 flow diverter-treated aneurysms, 46 occluded and 17 residual. The ostium ratio and neck ratio were significantly higher in the residual group than in the occluded group (P < .001 and P = .02, respectively), whereas all other parameters showed no statistical difference. As discriminating parameters for occlusion, ostium ratio and neck ratio achieved areas under the curve of 0.912 (95% CI, 0.838-0.985) and 0.707 (95% CI, 0.558-0.856), respectively.

CONCLUSIONS

High ostium ratios and neck ratios could predict incomplete occlusion of flow diverter-treated sidewall aneurysms. Neck ratio can be easily calculated by interventionists to predict flow-diverter treatment outcomes.

Ancient trans-Acting siRNAs Confer Robustness and Sensitivity onto the Auxin Response

Novel developmental programs often evolve via cooption of existing genetic networks. To understand this process, we explored cooption of the TAS3 tasiRNA pathway in the moss Physcomitrella patens. We find an ancestral function for this repeatedly redeployed pathway in the spatial regulation of a conserved set of Auxin Response Factors. In moss, this results in stochastic patterning of the filamentous protonemal tissue. Through modeling and experimentation, we demonstrate that tasiRNA regulation confers sensitivity and robustness onto the auxin response. Increased auxin sensitivity parallels increased developmental sensitivity to nitrogen, a key environmental signal. We propose that the properties lent to the auxin response network, along with the ability to stochastically modulate development in response to environmental cues, have contributed to repeated cooption of the tasiRNA-ARF module during evolution. The signaling properties of a genetic network, and not just its developmental output, are thus critical to understanding evolution of multicellular forms.

Interactive analysis and assessment of single-cell copy-number variations

We present Ginkgo (http://qb.cshl.edu/ginkgo), a user-friendly, open-source web platform for the analysis of single-cell copy-number variations (CNVs). Ginkgo automatically constructs copy-number profiles of cells from mapped reads and constructs phylogenetic trees of related cells. We validated Ginkgo by reproducing the results of five major studies. After comparing three commonly used single-cell amplification techniques, we concluded that degenerate oligonucleotide-primed PCR is the most consistent for CNV analysis.

Equitability, mutual information, and the maximal information coefficient

How should one quantify the strength of association between two random variables without bias for relationships of a specific form? Despite its conceptual simplicity, this notion of statistical "equitability" has yet to receive a definitive mathematical formalization. Here we argue that equitability is properly formalized by a self-consistency condition closely related to Data Processing Inequality. Mutual information, a fundamental quantity in information theory, is shown to satisfy this equitability criterion. These findings are at odds with the recent work of Reshef et al. [Reshef DN, et al. (2011) Science 334(6062):1518-1524], which proposed an alternative definition of equitability and introduced a new statistic, the "maximal information coefficient" (MIC), said to satisfy equitability in contradistinction to mutual information. These conclusions, however, were supported only with limited simulation evidence, not with mathematical arguments. Upon revisiting these claims, we prove that the mathematical definition of equitability proposed by Reshef et al. cannot be satisfied by any (nontrivial) dependence measure. We also identify artifacts in the reported simulation evidence. When these artifacts are removed, estimates of mutual information are found to be more equitable than estimates of MIC. Mutual information is also observed to have consistently higher statistical power than MIC. We conclude that estimating mutual information provides a natural (and often practical) way to equitably quantify statistical associations in large datasets.

Parametric inference in the large data limit using maximally informative models

Motivated by data-rich experiments in transcriptional regulation and sensory neuroscience, we consider the following general problem in statistical inference: when exposed to a high-dimensional signal S, a system of interest computes a representation R of that signal, which is then observed through a noisy measurement M. From a large number of signals and measurements, we wish to infer the "filter" that maps S to R. However, the standard method for solving such problems, likelihood-based inference, requires perfect a priori knowledge of the "noise function" mapping R to M. In practice such noise functions are usually known only approximately, if at all, and using an incorrect noise function will typically bias the inferred filter. Here we show that in the large data limit, this need for a precharacterized noise function can be circumvented by searching for filters that instead maximize the mutual information I[M; R] between observed measurements and predicted representations. Moreover, if the correct filter lies within the space of filters being explored, maximizing mutual information becomes equivalent to simultaneously maximizing every dependence measure that satisfies the data processing inequality. It is important to note that maximizing mutual information will typically leave a small number of directions in parameter space unconstrained. We term these directions diffeomorphic modes and present an equation that allows these modes to be derived systematically. The presence of diffeomorphic modes reflects a fundamental and nontrivial substructure within parameter space, one that is obscured by standard likelihood-based inference.

Kerfuffle: a web tool for multi-species gene colocalization analysis

BACKGROUND

The evolutionary pressures that underlie the large-scale functional organization of the genome are not well understood in eukaryotes. Recent evidence suggests that functionally similar genes may colocalize (cluster) in the eukaryotic genome, suggesting the role of chromatin-level gene regulation in shaping the physical distribution of coordinated genes. However, few of the bioinformatic tools currently available allow for a systematic study of gene colocalization across several, evolutionarily distant species. Furthermore, most tools require the user to input manually curated lists of gene position information, DNA sequence or gene homology relations between species. With the growing number of sequenced genomes, there is a need to provide new comparative genomics tools that can address the analysis of multi-species gene colocalization.

RESULTS

Kerfuffle is a web tool designed to help discover, visualize, and quantify the physical organization of genomes by identifying significant gene colocalization and conservation across the assembled genomes of available species (currently up to 47, from humans to worms). Kerfuffle only requires the user to specify a list of human genes and the names of other species of interest. Without further input from the user, the software queries the e!Ensembl BioMart server to obtain positional information and discovers homology relations in all genes and species specified. Using this information, Kerfuffle performs a multi-species clustering analysis, presents downloadable lists of clustered genes, performs Monte Carlo statistical significance calculations, estimates how conserved gene clusters are across species, plots histograms and interactive graphs, allows users to save their queries, and generates a downloadable visualization of the clusters using the Circos software. These analyses may be used to further explore the functional roles of gene clusters by interrogating the enriched molecular pathways associated with each cluster.

CONCLUSIONS

Kerfuffle is a new, easy-to-use and publicly available tool to aid our understanding of functional genomics and comparative genomics. This software allows for flexibility and quick investigations of a user-defined set of genes, and the results may be saved online for further analysis. Kerfuffle is freely available at http://atwallab.org/kerfuffle, is implemented in JavaScript (using jQuery and jsCharts libraries) and PHP 5.2, runs on an Apache server, and stores data in flat files and an SQLite database.

Developmental Coordination of Gene Expression between Synaptic Partners During GABAergic Circuit Assembly in Cerebellar Cortex

The assembly of neural circuits involves multiple sequential steps such as the specification of cell-types, their migration to proper brain locations, morphological and physiological differentiation, and the formation and maturation of synaptic connections. This intricate and often prolonged process is guided by elaborate genetic mechanisms that regulate each step. Evidence from numerous systems suggests that each cell-type, once specified, is endowed with a genetic program that unfolds in response to, and is regulated by, extrinsic signals, including cell–cell and synaptic interactions. To a large extent, the execution of this intrinsic program is achieved by the expression of specific sets of genes that support distinct developmental processes. Therefore, a comprehensive analysis of the developmental progression of gene expression in synaptic partners of neurons may provide a basis for exploring the genetic mechanisms regulating circuit assembly. Here we examined the developmental gene expression profiles of well-defined cell-types in a stereotyped microcircuit of the cerebellar cortex. We found that the transcriptomes of Purkinje cell and stellate/basket cells are highly dynamic throughout postnatal development. We revealed “phasic expression” of transcription factors, ion channels, receptors, cell adhesion molecules, gap junction proteins, and identified distinct molecular pathways that might contribute to sequential steps of cerebellar inhibitory circuit formation. We further revealed a correlation between genomic clustering and developmental co-expression of hundreds of transcripts, suggesting the involvement of chromatin level gene regulation during circuit formation.

Identification of PHLPP1 as a tumor suppressor reveals the role of feedback activation in PTEN-mutant prostate cancer progression

Hyperactivation of the PI 3-kinase/AKT pathway is a driving force of many cancers. Here we identify the AKT-inactivating phosphatase PHLPP1 as a prostate tumor suppressor. We show that Phlpp1-loss causes neoplasia and, on partial Pten-loss, carcinoma in mouse prostate. This genetic setting initially triggers a growth suppressive response via p53 and the Phlpp2 ortholog, and reveals spontaneous Trp53 inactivation as a condition for full-blown disease. Surprisingly, the codeletion of PTEN and PHLPP1 in patient samples is highly restricted to metastatic disease and tightly correlated to deletion of TP53 and PHLPP2. These data establish a conceptual framework for progression of PTEN mutant prostate cancer to life-threatening disease.

p53: a new player in reproduction

The roles of the p53 protein in tumor suppression have been firmly established. However, the functions of this protein under normal conditions or in the absence of stress, if any, have remained a mystery. In humans, some alleles containing a functional single nucleotide polymorphism in the p53 gene and its negative regulator, the Mdm2 gene, are under positive selection over evolutionary time frames, suggesting that the p53 pathway might have important functions that are optimized and selected for by evolutionary or reproductive pressures. Indeed, a recent study demonstrated a new function for the p53 protein in the regulation of maternal reproduction in mice, through transcriptional regulation of leukemia inhibitory factor (LIF), a novel p53 target gene. Sufficient uterine LIF levels are essential for the implantation of blastocysts or early embryos into the uterus. p53 deficient (p53(-/-)) female mice have a reduced pregnancy rate and litter size, due to impaired implantation resulting from decreased uterine LIF levels. Administration of LIF to pregnant p53(-/-) mice restored maternal reproduction by improving implantation. An association has been reported between women carrying the p53 codon 72 polymorphism (a proline to arginine change) with recurrent implantation failure, suggesting a similar function for p53 in humans. These findings of a new function for the p53 protein in reproduction may help to explain the observed evolutionary selection of some alleles of the p53 and Mdm2 genes. This may also be an excellent example of antagonistic pleiotrophy.

Grandmultiparae in a modern setting

OBJECTIVE

To compare the incidence of antenatal and intrapartum complications and neonatal outcomes among women who had previously delivered five or more times (grandmultiparous) with that of age-matched control women who had previously delivered two or three times (multiparous).

DESIGN

A matched cohort study.

SETTING

An inner city university maternity hospital in the United Kingdom.

SAMPLE

Three hundred and ninety-seven grandmultiparous women were compared with three hundred and ninety-seven age-matched multiparous women.

METHODS

Data on the subjects were obtained from a computerised maternity information system (SMMIS). Characteristics and complications occurring in the two groups were compared. Data validation was performed with a 10% randomised sample of the casenotes in both groups. Nineteen relevant data fields were abstracted and compared with the matched SMMIS record. Results The overall incidence of intrapartum complications for grandmultiparous women was 16% compared with 18% in the control multiparous women (odds ratio 0.9, 95% CI 0.6-1.3). Grand multiparity was associated with a significantly higher body mass index at booking (P < 0.01) and the last antenatal clinic (P < 0.05), an increased incidence of antenatal anaemia (22% vs 16%, odds ratio 1.8, 95% CI 1.2-2.8) and a decreased incidence of elective caesarean section (6% vs 11%, odds ratio 0.5, 95% CI 0.3-0.9). Agreement was greater than 95% in all the data fields reviewed except three. In the 14 categorical variables reviewed the Cohen's kappa results were in excess of 0.6.

CONCLUSION

This study suggests that in a developed country with satisfactory health care conditions, grandmultiparity should not be considered dangerous,and risk assessment should be based on past and present history and not simply on the basis of parity.

Bruising in non-accidental head injured children; a retrospective study of the prevalence, distribution and pathological associations in 24 cases

Non-accidental head injury, be it shaking, impact(s) or a combination of the two, is characterised by subdural and/or subarachnoid haemorrhages with retinal haemorrhages, but minimal or absent external cranio-facial trauma. The classical assault scenario depicts the infant being gripped around the head, face, chest and abdomen and shaken or being gripped by a limb and swung. This gripping might be expected to leave physical evidence in the form of bruising. A study was undertaken to establish the prevalence, distribution and pathological association of external bruising in 24 cases of fatal non-accidental head injury in children. At autopsy, 17 cases had new external bruises, 15 old external bruises and 13, a combination of both. However, seven (29%) cases showed no fresh external bruising and five (21%) showed no external bruising at all. Thus, external bruising may be absent in children with fatal intracranial injury. The face was shown to be the commonest site of bruising followed by the forehead and buttocks. Limb, chest and abdominal bruising were found to be uncommon. Retinal haemorrhages were confirmed in 23 (96%) cases. It is hypothesised that bruising, when present, may be a result of abuse in the form of punches and slaps rather than due to gripping during the assault. We discuss why gripping does not necessarily result in external bruising.