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Mouse syngeneic tumor models are widely used tools to demonstrate activity of novel anti-cancer immunotherapies. Despite their widespread use, a comprehensive view of their tumor-immune compositions and their relevance to human tumors has only begun to emerge. We propose each model possesses a unique tumor-immune infiltrate profile that can be probed with immunotherapies to inform on anti-tumor mechanisms and treatment strategies in human tumors with similar profiles. In support of this endeavor, we characterized the tumor microenvironment of four commonly used models and demonstrate they encompass a range of immunogenicities, from highly immune infiltrated RENCA tumors to poorly infiltrated B16F10 tumors. Tumor cell lines for each model exhibit different intrinsic factors in vitro that likely influence immune infiltration upon subcutaneous implantation. Similarly, solid tumors in vivo for each model are unique, each enriched in distinct features ranging from pathogen response elements to antigen presentation machinery. As RENCA tumors progress in size, all major T cell populations diminish while myeloid-derived suppressor cells become more enriched, possibly driving immune suppression and tumor progression. In CT26 tumors, CD8 T cells paradoxically increase in density yet are restrained as tumor volume increases. Finally, immunotherapy treatment across these different tumor-immune landscapes segregate into responders and non-responders based on features partially dependent on pre-existing immune infiltrates. Overall, these studies provide an important resource to enhance our translation of syngeneic models to human tumors. Future mechanistic studies paired with this resource will help identify responsive patient populations and improve strategies where immunotherapies are predicted to be ineffective.

Background Little is known about the interactions between the lung microbiome and host response in chronic obstructive pulmonary disease (COPD). Methods We performed a longitudinal 16S ribosomal RNA gene-based microbiome survey on 101 sputum samples from 16 healthy subjects and 43 COPD patients, along with characterization of host sputum transcriptome and proteome in COPD patients. Results Dysbiosis of sputum microbiome was observed with significantly increased relative abundance of Moraxella in COPD versus healthy subjects and during COPD exacerbations, and Haemophilus in COPD ex-smokers versus current smokers. Multivariate modeling on sputum microbiome, host transcriptome and proteome profiles revealed that significant associations between Moraxella and Haemophilus , host interferon and pro-inflammatory signaling pathways and neutrophilic inflammation predominated among airway host-microbiome interactions in COPD. While neutrophilia was positively correlated with Haemophilus , interferon signaling was more strongly linked to Moraxella. Moreover, while Haemophilus was significantly associated with host factors both in stable state and during exacerbations, Moraxella -associated host responses were primarily related to exacerbations. Conclusions Our study highlights a significant airway host-microbiome interplay associated with COPD inflammation and exacerbations. These findings indicate that Haemophilus and Moraxella influence different components of host immune response in COPD, and that novel therapeutic strategies should consider targeting these bacteria and their associated host pathways in COPD.

Hidradenitis suppurativa (HS) is a common, debilitating inflammatory skin disease linked to immune dysregulation and abnormalities in follicular structure and function. Several studies have characterized the transcriptomic profile of affected and unaffected skin in small populations. In this study of 20 patients, RNA from lesional and matching non-lesional skin biopsies in 20 subjects were used to identify an expression-based HS disease signature. This was followed by differential expression and pathway enrichment analyses, as well as jointly reanalyzing our findings with previously published transcriptomic profiles. We establish an RNA-Seq based HS expression disease signature that is mostly consistent with previous reports. Bulk-RNA profiles from 104 subjects in 7 previously reported data sets identified a disease signature of 118 differentially regulated genes compared to three control data sets from non-lesional skin. We confirmed previously reported expression profiles and further characterized dysregulation in complement activation and host response to bacteria in disease pathogenesis. Changes in the transcriptome of lesional skin in this cohort of HS patients is consistent with smaller previously reported populations. The findings further support the significance of immune dysregulation, in particular with regard to bacterial response mechanisms. Joint analysis of this and previously reported cohorts indicate a remarkably consistent expression profile.

Background With increasing concerns about the impact of frequent antibiotic usage on the human microbiome, it is important to characterize the potential for such effects in early antibiotic drug development clinical trials. In a randomised Phase 2a clinical trial study that evaluated the pharmacokinetics of repeated oral doses of gepotidacin, a first-in-chemical-class triazaacenaphthylene antibiotic with a distinct mechanism of action, in adult females with uncomplicated urinary tract infections for gepotidacin (GSK2140944) we evaluated the potential changes in microbiome composition across multiple time points and body-sites ( ClinicalTrials.gov : NCT03568942). Results Samples of gastrointestinal tract (GIT), pharyngeal cavity and vaginal microbiota were collected with consent from 22 patients at three time points relative to the gepotidacin dosing regimen; Day 1 (pre-dose), Day 5 (end of dosing) and Follow-up (Day 28 ± 3 days). Microbiota composition was determined by DNA sequencing of 16S rRNA gene variable region 4 amplicons. By Day 5, significant changes were observed in the microbiome diversity relative to pre-dose across the tested body-sites. However, by the Follow-up visit, microbiome diversity changes were reverted to compositions comparable to Day 1. The greatest range of microbiome changes by body-site were GIT followed by the pharyngeal cavity then vagina. In Follow-up visit samples we found no statistically significant occurrences of pathogenic taxa. Conclusion Our findings suggest that gepotidacin alteration of the human microbiome after 5 days of dosing is temporary and rebound to pre-dosing states is evident within the first month post-treatment. We recommend that future antibiotic drug trials include similar exploratory investigations into the duration and context of microbiome modification and recovery. Trial registration NCT03568942 . Registered 26 June 2018.

An amendment to this paper has been published and can be accessed via the original article.

Background Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. Methods We performed comprehensive RNA sequencing of skin and blood (n = 718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe chronic plaque psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. Results Here we show, using two complementary dimensionality reduction methods, that co-expressed gene modules and factors within skin and blood are significantly associated with psoriasis phenotypes and disease severity. We identify a 14-gene signature negatively associated with BMI in nonlesional skin and with disease severity in lesional skin. Genotype integration reveals that HLA-DQA1*01 and HLA-DRB1*15 genotypes are positively associated with baseline psoriasis severity. Using explainable machine learning models, we define two disease severity-associated gene modules in lesional skin - one positive, one negatively-associated - and a 9-gene signature in lesional skin predictive of disease severity. Disease severity signatures in blood are only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status is independent of disease severity or drug. Conclusions These findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity. Plain language summary Psoriasis is a common and debilitating skin disease, linked to other inflammatory conditions. A lot is known about what causes psoriasis and the factors that influence it, but doctors still cannot offer personalised treatments. This is because it has been difficult to understand what makes psoriasis more or less severe, why people respond differently to treatment, or why some people develop related diseases. To help address this, we collected skin and blood samples and personal information from people with severe psoriasis across the United Kingdom. Using computer-based methods, we found shared biological processes that link the disease with obesity and help predict its severity. Rider, Grantham, Smith, Watson et al. integrate multiomic data from patients with psoriasis using dimensionality reduction and machine learning techniques. This approach identifies biological relationships between genetic background, clinical features and disease severity, providing insight into disease variability across individuals.

Introduction Metformin and glucagon‐like peptide‐1 (GLP‐1) agonists are widely used for treating type two diabetes mellitus (T2DM). While recent studies suggest these drugs might modify the gastrointestinal tract (GIT) microbiome, further confirmation is required from human clinical trials. Materials and methods Here, we compare, in patients with T2DM, the effects of metformin (n = 18 subjects) and liraglutide (n = 19), a GLP‐1 agonist, on their GIT microbiomes over a 42 day period (n = 74 samples) using 16S ribosomal RNA (rRNA) sequencing. Results We found that these drugs had markedly different effects on the microbiome composition. At both baseline and Day 42, subjects taking metformin had a significant increase (Baseline adj. P = .038, Day 42 adj. P = .041) in the relative abundance of the bacterial genus Sutterella, whereas liraglutide dosing is associated with a significant increase (Baseline adj. P = .048, Day 42 adj. P = .003) in the genus Akkermansia, a GIT bacteria positively associated with gut barrier homoeostasis. Bacteroides and Akkermansia relative abundances were also significantly associated with duration of subject diabetes (adj P < .05). Specifically, there was a significantly higher abundance of Akkermansia in subjects with short and medium durations than those with long duration of diabetes. Discussion To our knowledge, this is the first report of GLP‐1 agonist‐associated changes in the human microbiome and its differentiating effects to metformin. Our study suggests that modulation of the GIT microbiome is a potentially important component in the mechanism of action of these drugs. Although metformin and liraglutide, a glucagon‐like peptide‐1 agonist, are the most widely used drugs for the treatment of type 2 diabetes mellitus (T2DM), their mechanisms of action are still being uncovered. In this study, we show that these drugs are associated with different changes in the gut microbiome in T2DM subjects. In particular, liraglutide appears to promote colonization by the genus Akkermansia, which has been previously implicated in having a key role in maintaining a healthy epithelial mucosal interface and the integrity of gut barrier function.

Hidradenitis suppurativa (HS) is a common, debilitating inflammatory skin disease linked to immune dysregulation and abnormalities in follicular structure and function. Several studies have characterized the transcriptomic profile of affected and unaffected skin in small populations. In this study of 20 patients, RNA from lesional and matching non-lesional skin biopsies in 20 subjects were used to identify an expression-based HS disease signature. This was followed by differential expression and pathway enrichment analyses, as well as jointly reanalyzing our findings with previously published transcriptomic profiles. We establish an RNA-Seq based HS expression disease signature that is mostly consistent with previous reports. Bulk-RNA profiles from 104 subjects in 7 previously reported data sets identified a disease signature of 118 differentially regulated genes compared to three control data sets from non-lesional skin. We confirmed previously reported expression profiles and further characterized dysregulation in complement activation and host response to bacteria in disease pathogenesis. Changes in the transcriptome of lesional skin in this cohort of HS patients is consistent with smaller previously reported populations. The findings further support the significance of immune dysregulation, in particular with regard to bacterial response mechanisms. Joint analysis of this and previously reported cohorts indicate a remarkably consistent expression profile.

IntroductionMetformin and glucagon‐like peptide‐1 (GLP‐1) agonists are widely used for treating type two diabetes mellitus (T2DM). While recent studies suggest these drugs might modify the gastrointestinal tract (GIT) microbiome, further confirmation is required from human clinical trials.Materials and methodsHere, we compare, in patients with T2DM, the effects of metformin (n = 18 subjects) and liraglutide (n = 19), a GLP‐1 agonist, on their GIT microbiomes over a 42 day period (n = 74 samples) using 16S ribosomal RNA (rRNA) sequencing.ResultsWe found that these drugs had markedly different effects on the microbiome composition. At both baseline and Day 42, subjects taking metformin had a significant increase (Baseline adj. P = .038, Day 42 adj. P = .041) in the relative abundance of the bacterial genus Sutterella, whereas liraglutide dosing is associated with a significant increase (Baseline adj. P = .048, Day 42 adj. P = .003) in the genus Akkermansia, a GIT bacteria positively associated with gut barrier homoeostasis. Bacteroides and Akkermansia relative abundances were also significantly associated with duration of subject diabetes (adj P < .05). Specifically, there was a significantly higher abundance of Akkermansia in subjects with short and medium durations than those with long duration of diabetes.DiscussionTo our knowledge, this is the first report of GLP‐1 agonist‐associated changes in the human microbiome and its differentiating effects to metformin. Our study suggests that modulation of the GIT microbiome is a potentially important component in the mechanism of action of these drugs.