Immune response in silico (IRIS): immune-specific genes identified from a compendium of microarray expression data

Early life adversity is associated with differential gene expression in immune cells: A cluster-based analysis across an acute psychosocial stressor

Elucidating mechanisms by which early-life adversity (ELA) contributes to increased disease risk is important for mitigating adverse health outcomes. Prior work has found differences in immune cell gene expression related to inflammation and mitochondrial activity. Using a within-person between-group experimental design, we investigated differences in gene expression clusters across acute psychosocial stress and no-stress conditions. Participants were young adults (N = 29, aged 18 - 25 years, 62 % female, 47 % with a history of ELA). Gene expression was assessed in peripheral blood mononuclear cells collected at 8 blood draws spanning two 5-hour sessions (stress vs. no-stress) separated by a week, 4 across each session (number of observations = 221). We applied two unsupervised gene clustering methods - latent profile analysis (LPA) and weighted gene co-expression analysis (WGCNA) - to cluster genes with similar expression patterns across participants. LPA identified 11 clusters, 7 of which were significantly associated with ELA-status. WGCNA identified 5 clusters, 3 of which were significantly associated with ELA-status. LPA- and WGCNA-identified clusters were correlated, and all clusters were highly preserved across sessions and time. There was no significant effect of acute stress on cluster gene expression, but there was a significant effect of time, and significant differences by ELA-status. ELA-associated clusters related to RNA splicing/processing, inflammation, leukocyte differentiation and division, and mitochondrial activity were differentially expressed across time: ELA-exposed individuals showed decreased expression of these clusters at 90-minutes while controls showed increased expression. Our findings replicate previous work in this area and highlight additional mechanisms by which ELA may contribute to disease risk.

CAPN2-responsive mesoporous silica nanoparticles: A promising nanocarrier for targeted therapy of pancreatic cancer

Pancreatic adenocarcinoma (PDAC) is highly resistant to conventional chemotherapeutic interventions, resulting in exceptionally low survival rates. The limited efficacy can in part be attributed to dose limitations and treatment cessation urged by toxicity of currently used chemotherapy. The advent of targeted delivery strategies has kindled hope for circumventing off-target toxicity. We have previously reported a PDAC-specific mesoporous silica nanoparticle (MSN) containing a protease linker responsive to ADAM9, a PDAC-enriched extracellularly deposited protease. Upon loading with paclitaxel these ADAM9-MSNs reduced side effects both in vitro and in vivo, however, disappointing antitumor efficacy was observed in vivo. Here, we propose that an efficient uptake of MSNs by tumor cells might underlie the lack of antitumor efficacy of MSNs functionalized with linker responsive to extracellular proteases. Harnessing this premise to improve antitumor efficacy, we performed an in silico analysis to identify PDAC-enriched intracellular proteases. We report the identification of BACE2, CAPN2 and DPP3 as PDAC enriched intracellular proteases, and report the synthesis of BACE2-, CAPN2- and DPP3-responsive MSNs. Extensive preclinical assessments revealed that paclitaxel-loaded CAPN2- and DPP3-MSNs exhibit high PDAC specificity in vitro as opposed to free paclitaxel. The administration of paclitaxel-loaded CAPN2- and DPP3-MSNs in vivo confirmed the reduction of leukopenia and induced no organ damage. Promisingly, in two mouse models CAPN2-MSNs reduced tumor growth at least as efficiently as free paclitaxel. Taken together, our results pose CAPN2-MSNs as a promising nanocarrier for the targeted delivery of chemotherapeutics in PDAC.

Skeletal muscle of young females under resistance exercise exhibits a unique innate immune cell infiltration profile compared to males and elderly individuals

Muscle damage resulting from physical activities such as exercise triggers an immune response crucial for tissue repair and recovery. This study investigates the immune cell profiles in muscle biopsies of individuals engaged in resistance exercise (RE) and explores the impact of age and sex on the immune response following exercise-induced muscle damage. Microarray datasets from muscle biopsies of young and old subjects were analyzed, focusing on the gene expression patterns associated with immune cell activation. Genes were compared with immune cell signatures to reveal the cellular landscape during exercise. Results show that the most significant modulated gene after RE was Folliculin Interacting Protein 2 (FNIP2) a crucial regulator in cellular homeostasis. Moreover, the transcriptome was stratified based on the expression of FNIP2 and the 203 genes common to the groups obtained based on sex and age. Gene ontology analysis highlighted the FLCN-FNIP1-FNIP2 complex, which exerts as a negative feedback loop to Pi3k-Akt-mTORC1 pathway. Furthermore, we highlighted that the young females exhibit a distinct innate immune cell activation signature compared to males after a RE session. Specifically, young females demonstrate a notable overlap with dendritic cells (DCs), M1 macrophages, M2 macrophages, and neutrophils, while young males overlap with M1 macrophages, M2 macrophages, and motor neurons. Interestingly, in elderly subjects, both sexes display M1 macrophage activation signatures. Comparison of young and elderly signatures reveals an increased M1 macrophage percentage in young subjects. Additionally, common genes were identified in both sexes across different age groups, elucidating biological functions related to cell remodeling and immune activation. This study underscores the intricate interplay between sex, age, and the immune response in muscle tissue following RE, offering potential directions for future research. Nevertheless, there is a need for further studies to delve deeper and confirm the dynamics of immune cells in response to exercise-induced muscle damage.

Regulation of Zbp1 by miR-99b-5p in microglia controls the development of schizophrenia-like symptoms in mice

Current approaches to the treatment of schizophrenia have mainly focused on the protein-coding part of the genome; in this context, the roles of microRNAs have received less attention. In the present study, we analyze the microRNAome in the blood and postmortem brains of schizophrenia patients, showing that the expression of miR-99b-5p is downregulated in both the prefrontal cortex and blood of patients. Lowering the amount of miR-99b-5p in mice leads to both schizophrenia-like phenotypes and inflammatory processes that are linked to synaptic pruning in microglia. The microglial miR-99b-5p-supressed inflammatory response requires Z-DNA binding protein 1 (Zbp1), which we identify as a novel miR-99b-5p target. Antisense oligonucleotides against Zbp1 ameliorate the pathological effects of miR-99b-5p inhibition. Our findings indicate that a novel miR-99b-5p-Zbp1 pathway in microglia might contribute to the pathogenesis of schizophrenia.

Antiviral memory B cells exhibit enhanced innate immune response facilitated by epigenetic memory

The long-lasting humoral immunity induced by viral infections or vaccinations depends on memory B cells with greatly increased affinity to viral antigens, which are evolved from germinal center (GC) responses. However, it is unclear whether antiviral memory B cells represent a distinct subset among the highly heterogeneous memory B cell population. Here, we examined memory B cells induced by a virus-mimicking antigen at both transcriptome and epigenetic levels and found unexpectedly that antiviral memory B cells exhibit an enhanced innate immune response, which appeared to be facilitated by the epigenetic memory that is established through the memory B cell development. In addition, T-bet is associated with the altered chromatin architecture and is required for the formation of the antiviral memory B cells. Thus, antiviral memory B cells are distinct from other GC-derived memory B cells in both physiological functions and epigenetic landmarks.

Genome-wide classification of epigenetic activity reveals regions of enriched heritability in immune-related traits

Epigenetics underpins the regulation of genes known to play a key role in the adaptive and innate immune system (AIIS). We developed a method, EpiNN, that leverages epigenetic data to detect AIIS-relevant genomic regions and used it to detect 2,765 putative AIIS loci. Experimental validation of one of these loci, DNMT1, provided evidence for a novel AIIS-specific transcription start site. We built a genome-wide AIIS annotation and used linkage disequilibrium (LD) score regression to test whether it predicts regional heritability using association statistics for 176 traits. We detected significant heritability effects (average |τ∗|=1.65) for 20 out of 26 immune-relevant traits. In a meta-analysis, immune-relevant traits and diseases were 4.45× more enriched for heritability than other traits. The EpiNN annotation was also depleted of trans-ancestry genetic correlation, indicating ancestry-specific effects. These results underscore the effectiveness of leveraging supervised learning algorithms and epigenetic data to detect loci implicated in specific classes of traits and diseases.

TIGIT may Serve as a Potential Target for the Immunotherapy of Renal Cell Carcinoma

This study aims to explore whether TIGIT is an effective target for the immunotherapy of renal cell cancer (RCC) with PD-1 as a positive control. The expression of TIGIT and PD-1 in RCC and peripheral blood mononuclear cells (PBMC) and the correlation between TIGIT and PD-1 are evaluated. The expression of TIGIT and PD-1 is inhibited, and then the proliferation, apoptosis, and migration are assessed. TIGIT expression is positively related to the expression of PDCD1, BTLA, ICOS, and FOXP3 (p < 0.05). TIGIT expression in the PBMC, TIL, RCC, and adjacent normal tissues is higher than PD-1 expression. Blocking the TIGIT and PD-1 signaling pathways significantly inhibits the proliferation, migration, and invasion of RCC cells and promotes their apoptosis. These effects are more evident in TIGIT inhibitors than in PD-1 inhibitors. TIGIT inhibitor mainly regulates the expression of differential genes to achieve the reconstruction of immune killing and restore the killing effect on the RCC, and its mechanism by which TIGIT functions overlap that of PD-1 inhibitor. TIGIT may become a target for the immunotherapy of RCC, and there is a theoretical basis for the combination of TIGIT inhibitors and PD-1 inhibitors for the treatment of RCC.

A modified immune cell infiltration score achieves ideal stratification for CD8+ T cell efficacy and immunotherapy benefit in hepatocellular carcinoma

Immunotherapy, which aims to enhance the function of T cells, has emerged as a novel therapeutic approach for hepatocellular carcinoma (HCC). Nevertheless, the clinical utility of using flow cytometry to assess immune cell infiltration (ICI) is hindered by its cumbersome procedures, prompting the need for more accessible methods. Here, we acquired gene expression profiles and survival data of HCC from TCGA and GSE10186 datasets. The patients were categorized into two clusters of ICI, and a set of 11 characteristic genes responsible for the differentiation performance of these ICI clusters were identified. Subsequently, we successfully developed a modified ICI score (mICIS) by utilizing the expression levels of these genes. The efficacy of our mICIS was confirmed via mass cytometry, flow cytometry, and immunohistochemistry. Our research indicated that the favorable overall survival (OS) rate could be attributed to the improved function of anti-tumor leukocytes rather than their infiltration. Furthermore, we observed that the low score group exhibited lower expression levels of T-cell exhaustion-associated genes, which was confirmed in both HCC tissues from patients and mice, which demonstrated that the benefits of the low scores were due to enhanced active/cytotoxic CD8+ T cells and reduced exhausted CD8+ T cells. Additionally, our mICIS stratified the benefits derived from immunotherapies. Lastly, we observed a misalignment between CD8+ T-cell infiltration and function in HCC. In summary, our mICIS demonstrated proficiency in assessing the OS rate of HCC and offering significant stratified data pertaining to distinct responses to immunotherapy.

Soluble PD-L1 as a diagnostic and prognostic biomarker in resectable gastric cancer patients

BACKGROUND

In this study, we compared programmed death-ligand 1 (PD-L1) expression in primary tissue samples and its soluble form (sPD-L1) concentration in matched preoperative plasma samples from gastric cancer patients to understand the relationship between tissue and plasma PD-L1 expression and to determine its diagnostic and prognostic value.

METHODS

PD-L1 expression in tissue was assessed by immunohistochemistry and enzyme-linked immunosorbent assay (ELISA), and sPD-L1 concentration in plasma was quantified by ELISA. The levels of the CD274 gene, which encodes for PD-L1 protein, were examined as part of bulk tissue RNA-sequencing analyses. Additionally, we evaluated the association between sPD-L1 levels and various laboratory parameters, disease characteristics, and patient outcomes.

RESULTS

GC patients had significantly higher levels of sPD-L1 in their plasma (71.69 pg/mL) compared to healthy controls (35.34 pg/mL) (p < 0.0001). Moreover, sPD-L1 levels were significantly correlated with tissue PD-L1 protein, CD274 mRNA expression, larger tumor size, advanced tumor stage, and lymph node metastasis. Elevated sPD-L1 levels (> 103.5 ng/mL) were associated with poor overall survival (HR = 2.16, 95%CI 1.15-4.08, p = 0.017). Furthermore, intratumoral neutrophil and dendritic cell levels were directly correlated with plasma sPD-L1 concentration in the GC patients.

CONCLUSIONS

sPD-L1 was readily measurable in GC patients, and its level was associated with GC tissue PD-L1 expression, greater inflammatory cell infiltration, disease progression, and survival. Thus, sPD-L1 may be a useful minimally invasive diagnostic and prognostic biomarker in GC patients.

Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures

The advent of single-cell multi-omics sequencing technology makes it possible for researchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high-dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Here, we propose an interpretable deep learning method called moETM to perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder and employs multiple linear decoders to learn the multi-omics signatures. moETM demonstrates superior performance compared with six state-of-the-art methods on seven publicly available datasets. By applying moETM to the scRNA + scATAC data, we identified sequence motifs corresponding to the transcription factors regulating immune gene signatures. Applying moETM to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omics biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

Immune cell type signature discovery and random forest classification for analysis of single cell gene expression datasets

Background

Robust immune cell gene expression signatures are central to the analysis of single cell studies. Nearly all known sets of immune cell signatures have been derived by making use of only single gene expression datasets. Utilizing the power of multiple integrated datasets could lead to high-quality immune cell signatures which could be used as superior inputs to machine learning-based cell type classification approaches.

Results

We established a novel workflow for the discovery of immune cell type signatures based primarily on gene-versus-gene expression similarity. It leverages multiple datasets, here seven single cell expression datasets from six different cancer types and resulted in eleven immune cell type-specific gene expression signatures. We used these to train random forest classifiers for immune cell type assignment for single-cell RNA-seq datasets. We obtained similar or better prediction results compared to commonly used methods for cell type assignment in independent benchmarking datasets. Our gene signature set yields higher prediction scores than other published immune cell type gene sets in random forest-based cell type classification. We further demonstrate how our approach helps to avoid bias in downstream statistical analyses by re-analysis of a published IFN stimulation experiment.

Discussion and conclusion

We demonstrated the quality of our immune cell signatures and their strong performance in a random forest-based cell typing approach. We argue that classifying cells based on our comparably slim sets of genes accompanied by a random forest-based approach not only matches or outperforms widely used published approaches. It also facilitates unbiased downstream statistical analyses of differential gene expression between cell types for significantly more genes compared to previous cell classification algorithms.

Heterogeneity of the tumor immune microenvironment and clinical interventions

The tumor immune microenvironment (TIME) is broadly composed of various immune cells, and its heterogeneity is characterized by both immune cells and stromal cells. During the course of tumor formation and progression and anti-tumor treatment, the composition of the TIME becomes heterogeneous. Such immunological heterogeneity is not only present between populations but also exists on temporal and spatial scales. Owing to the existence of TIME, clinical outcomes can differ when a similar treatment strategy is provided to patients. Therefore, a comprehensive assessment of TIME heterogeneity is essential for developing precise and effective therapies. Facilitated by advanced technologies, it is possible to understand the complexity and diversity of the TIME and its influence on therapy responses. In this review, we discuss the potential reasons for TIME heterogeneity and the current approaches used to explore it. We also summarize clinical intervention strategies based on associated mechanisms or targets to control immunological heterogeneity.

Extracellular matrix educates an immunoregulatory tumor macrophage phenotype found in ovarian cancer metastasis

Recent studies have shown that the tumor extracellular matrix (ECM) associates with immunosuppression, and that targeting the ECM can improve immune infiltration and responsiveness to immunotherapy. A question that remains unresolved is whether the ECM directly educates the immune phenotypes seen in tumors. Here, we identify a tumor-associated macrophage (TAM) population associated with poor prognosis, interruption of the cancer immunity cycle, and tumor ECM composition. To investigate whether the ECM was capable of generating this TAM phenotype, we developed a decellularized tissue model that retains the native ECM architecture and composition. Macrophages cultured on decellularized ovarian metastasis shared transcriptional profiles with the TAMs found in human tissue. ECM-educated macrophages have a tissue-remodeling and immunoregulatory phenotype, inducing altered T cell marker expression and proliferation. We conclude that the tumor ECM directly educates this macrophage population found in cancer tissues. Therefore, current and emerging cancer therapies that target the tumor ECM may be tailored to improve macrophage phenotype and their downstream regulation of immunity.

DectiSomes: C-type lectin receptor-targeted liposomes as pan-antifungal drugs

Combatting the ever-increasing threat from invasive fungal pathogens faces numerous fundamental challenges, including constant human exposure to large reservoirs of species in the environment, the increasing population of immunocompromised or immunosuppressed individuals, the unsatisfactory efficacy of current antifungal drugs and their associated toxicity, and the scientific and economic barriers limiting a new antifungal pipeline. DectiSomes represent a new drug delivery platform that enhances antifungal efficacy for diverse fungal pathogens and reduces host toxicity for current and future antifungals. DectiSomes employ pathogen receptor proteins - C-type lectins - to target drug-loaded liposomes to conserved fungal cognate ligands and away from host cells. DectiSomes represent one leap forward for urgently needed effective pan-antifungal therapy. Herein, we discuss the problems of battling fungal diseases and the state of DectiSome development.

Integrated bioinformatic analysis and cell line experiments reveal the significant role of the novel immune checkpoint TIGIT in kidney renal clear cell carcinoma

Background

T cell immunoglobulin and ITIM domain (TIGIT) is a widely concerned immune checkpoint, which plays an essential role in immunosuppression and immune evasion. However, the role of TIGIT in normal organ tissues and renal clear cell carcinoma is unclear. We aim to identify the critical role of TIGIT in renal clear cell carcinoma and find potential targeted TIGIT drugs.

Materials and methods

Data retrieved from the GTEX database and TCGA database was used to investigate the expression of TIGIT in normal whole-body tissues and abnormal pan-cancer, then the transcriptome atlas of patients with kidney renal clear cell carcinoma (KIRC) in the TCGA database were applied to distinguish the TIGIT related features, including differential expression status, prognostic value, immune infiltration, co-expression, and drug response of sunitinib an anti-PD1/CTLA4 immunotherapy in KIRC. Furthermore, we constructed a gene-drug network to discover a potential drug targeting TIGIT and verified it by performing molecular docking. Finally, we conducted real-time polymerase chain reaction (PCR) and assays for Transwell migration and CCK-8 to explore the potential roles of TIGIT.

Results

TIGIT showed a moderate expression in normal kidney tissues and was confirmed as an essential prognostic factor that was significantly higher expressed in KIRC tissues, and high expression of TIGIT is associated with poor OS, PFS, and DSS in KIRC. Also, the expression of TIGIT was closely associated with the pathological characteristics of the tumor, high expression of TIGIT in KIRC was observed with several critical functions or pathways such as apoptosis, BCR signaling, TCR signaling et al. Moreover, the expression of TIGIT showed a strong positive correlation with infiltration of CD8+ T cells and Tregs and a positive correlation with the drug sensitivity of sunitinib simultaneously. Further Tide ips score analysis and submap analysis reveal that patients with high TIGIT expression significantly show a better response to anti-PD1 immunotherapy. Following this, we discovered Selumetinib and PD0325901 as potential drugs targeting TIGIT and verified the interaction between these two drugs and TIGIT protein by molecular docking. Finally, we verified the essential role of TIGIT in the proliferation and migration functions by using KIRC cell lines.

Conclusions

TIGIT plays an essential role in tumorigenesis and progression in KIRC. High expression of TIGIT results in poor survival of KIRC and high drug sensitivity to sunitinib. Besides, Selumetinib and PD0325901 may be potential drugs targeting TIGIT, and combined therapy of anti-TIGIT and other treatments show great potential in treating KIRC.

Neuro-immune deconvolution analysis of OAS3 as a transcriptomic central node in HIV-associated neurocognitive disorders

Neurological complications of AIDS (NeuroAIDS) include primary HIV-associated neurocognitive disorder (HAND). OAS3 is an enzyme belonging to the 2', 5' oligoadenylate synthase family induced by type I interferons and involved in the degradation of both viral and endogenous RNA. Here, we used microarray datasets from NCBI of brain samples of non-demented HIV-negative controls (NDC), HIV, deceased patients with HAND and encephalitis (HIVE) (treated and untreated with antiretroviral therapy, ART), and with HAND without HIVE. The HAND/HIVE patients were stratified according to the OAS3 gene expression. The genes positively and negatively correlated to the OAS3 gene expression were used to perform a genomic deconvolution analysis using neuroimmune signatures (NIS) belonging to sixteen signatures. Expression analysis revealed significantly higher OAS3 expression in HAND/HIVE and HAND/HIVE/ART compared with NDC. OAS3 expressed an excellent diagnostic ability to discriminate NDC from HAND/HIVE, HAND from HAND/HIVE, HAND from HAND/HIVE/ART, and HIV from HAND/HIVE. Noteworthy, OAS3 expression levels in the brains of HAND/HIVE patients were positively correlated with viral load in both peripheral blood and cerebrospinal fluid (CSF). Furthermore, deconvolution analysis revealed that the genes positively correlated to OAS3 expression were associated with inflammatory signatures. Neuronal activation profiles were significantly activated by the genes negatively correlated to OAS3 expression levels. Moreover, gene ontology analysis performed on genes characterizing the microglia signature highlighted an immune response as a main biological process. According to our results, genes positively correlated to OAS3 gene expression in the brains of HAND/HIVE patients are associated with inflammatory transcriptomic signatures and likely worse cognitive impairment.

Zetomipzomib (KZR-616) attenuates lupus in mice via modulation of innate and adaptive immune responses

Zetomipzomib (KZR-616) is a selective inhibitor of the immunoproteasome currently undergoing clinical investigation in autoimmune disorders. Here, we characterized KZR-616 in vitro and in vivo using multiplexed cytokine analysis, lymphocyte activation and differentiation, and differential gene expression analysis. KZR-616 blocked production of &gt;30 pro-inflammatory cytokines in human peripheral blood mononuclear cells (PBMCs), polarization of T helper (Th) cells, and formation of plasmablasts. In the NZB/W F1 mouse model of lupus nephritis (LN), KZR-616 treatment resulted in complete resolution of proteinuria that was maintained at least 8 weeks after the cessation of dosing and was mediated in part by alterations in T and B cell activation, including reduced numbers of short and long-lived plasma cells. Gene expression analysis of human PBMCs and tissues from diseased mice revealed a consistent and broad response focused on inhibition of T, B, and plasma cell function and the Type I interferon pathway and promotion of hematopoietic cell lineages and tissue remodeling. In healthy volunteers, KZR-616 administration resulted in selective inhibition of the immunoproteasome and blockade of cytokine production following ex vivo stimulation. These data support the ongoing development of KZR-616 in autoimmune disorders such as systemic lupus erythematosus (SLE)/LN.

CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data

Bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell type-specific inferences from bulk data. Our real data exploration suggests that differential expression or methylation status is often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell type-specific differential analyses of bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell type-specific differential signals compared with existing methods, especially in low-abundance cell types.

A new natural killer cell-specific gene signature predicting recurrence in colorectal cancer patients

The protective role of Natural Killer (NK) cell tumour immunosurveillance has long been recognised in colorectal cancer (CRC). However, as most patients show limited intra-tumoral NK cell infiltration, improving our ability to identify those with high NK cell activity might aid in dissecting the molecular features which underlie NK cell sensitivity. Here, a novel CRC-specific NK cell gene signature that infers NK cell load in primary tissue samples was derived and validated in multiple patient CRC cohorts. In contrast with other NK cell gene signatures that have several overlapping genes across different immune cell types, our NK cell signature has been extensively refined to be specific for CRC-infiltrating NK cells. The specificity of the signature is substantiated in tumour-infiltrating NK cells from primary CRC tumours at the single cell level, and the signature includes genes representative of NK cells of different maturation states, activation status and anatomical origin. Our signature also accurately discriminates murine NK cells, demonstrating the applicability of this geneset when mining datasets generated from preclinical studies. Differential gene expression analysis revealed tumour-intrinsic features associated with NK cell inclusion versus exclusion in CRC patients, with those tumours with predicted high NK activity showing strong evidence of enhanced chemotactic and cytotoxic transcriptional programs. Furthermore, survival modelling indicated that NK signature expression is associated with improved survival outcomes in CRC patients. Thus, scoring CRC samples with this refined NK cell signature might aid in identifying patients with high NK cell activity who could be prime candidates for NK cell directed immunotherapies.

Aging-associated HELIOS deficiency in naive CD4+ T cells alters chromatin remodeling and promotes effector cell responses

Immune aging combines cellular defects in adaptive immunity with the activation of pathways causing a low-inflammatory state. Here we examined the influence of age on the kinetic changes in the epigenomic and transcriptional landscape induced by T cell receptor (TCR) stimulation in naive CD4+ T cells. Despite attenuated TCR signaling in older adults, TCR activation accelerated remodeling of the epigenome and induced transcription factor networks favoring effector cell differentiation. We identified increased phosphorylation of STAT5, at least in part due to aberrant IL-2 receptor and lower HELIOS expression, as upstream regulators. Human HELIOS-deficient, naive CD4+ T cells, when transferred into human-synovium-mouse chimeras, infiltrated tissues more efficiently. Inhibition of IL-2 or STAT5 activity in T cell responses of older adults restored the epigenetic response pattern to the one seen in young adults. In summary, reduced HELIOS expression in non-regulatory naive CD4+ T cells in older adults directs T cell fate decisions toward inflammatory effector cells that infiltrate tissue.

IL1RAP expression and the enrichment of IL-33 activation signatures in severe neutrophilic asthma

BACKGROUND

Interleukin (IL)-33 is an upstream regulator of type 2 (T2) eosinophilic inflammation and has been proposed as a key driver of some asthma phenotypes.

OBJECTIVE

To derive gene signatures from in vitro studies of IL-33-stimulated cells and use these to determine IL-33-associated enrichment patterns in asthma.

METHODS

Signatures downstream of IL-33 stimulation were derived from our in vitro study of human mast cells and from public datasets of in vitro stimulated human basophils, type 2 innate lymphoid cells (ILC2), regulatory T cells (Treg) and endothelial cells. Gene Set Variation Analysis (GSVA) was used to probe U-BIOPRED and ADEPT sputum transcriptomics to determine enrichment scores (ES) for each signature according to asthma severity, sputum granulocyte status and previously defined molecular phenotypes.

RESULTS

IL-33-activated gene signatures were cell-specific with little gene overlap. Individual signatures, however, were associated with similar signalling pathways (TNF, NF-κB, IL-17 and JAK/STAT signalling) and immune cell differentiation pathways (Th17, Th1 and Th2 differentiation). ES for IL-33-activated gene signatures were significantly enriched in asthmatic sputum, particularly in patients with neutrophilic and mixed granulocytic phenotypes. IL-33 mRNA expression was not elevated in asthma whereas the expression of mRNA for IL1RL1, the IL-33 receptor, was up-regulated in the sputum of severe eosinophilic asthma. The mRNA expression for IL1RAP, the IL1RL1 co-receptor, was greatest in severe neutrophilic and mixed granulocytic asthma.

CONCLUSIONS

IL-33-activated gene signatures are elevated in neutrophilic and mixed granulocytic asthma corresponding with IL1RAP co-receptor expression. This suggests incorporating T2-low asthma in anti-IL-33 trials.

Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature

The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.

TIGIT-expressing zoledronate-specific γδ T cells display enhanced antitumor activity

Human γδ T cells hold a pivotal role in tumor immunosurveillance through their prompt activation and cytokine secretion and have received much attention in adoptive immunotherapy of clear cell renal cell carcinoma (ccRCC). However, the therapeutic effects are limited in ccRCC. Therefore, it is now critical to improve therapeutic strategies based on γδ T cells, especially identification of functional γδ T cell subsets. In this study, we aimed to identify γδ T cells that might have enhanced responses against ccRCC. Bioinformatic analysis showed that ccRCC patients with high T cell immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domain (TIGIT) expression had higher levels of effector molecules. Then, we examined the changes in the TIGIT⁺ γδ T cell percentages of 6 ccRCC patients and 14 healthy subjects through zoledronate (ZOL) stimulation. Results indicated that percentages of TIGIT⁺ γδ T cells were positively correlated with activated γδ T cells in early activation stage. Further study demonstrated that TIGIT⁺ γδ T cells exhibited enhanced activation, contained more terminally differentiated effector γδ T cells and produced higher cytokine compared with TIGIT^- γδ T cells. Finally, we investigated the functions and found that TIGIT⁺ γδ T cells exhibited stronger tumor reactivities and higher cytotoxicity when challenged by tumor cells. Above results imply that TIGIT⁺ γδ T cells are the main effectors in ZOL recognition and tumor cells challenging. The results of the present study serve as basis for future functional studies on TIGIT⁺ γδ T cells and provide a promising approach of immunotherapy in ccRCC.

Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses' health study

BACKGROUND

Breast tumor immune infiltration is clearly associated with improved treatment response and outcomes in breast cancer. However, modifiable patient factors associated with breast cancer immune infiltrates are poorly understood. The Nurses' Health Study (NHS) offers a unique cohort to study immune gene expression in tumor and adjacent normal breast tissue, immune cell-specific immunohistochemistry (IHC), and patient exposures. We evaluated the association of body mass index (BMI) change since age 18, physical activity, and the empirical dietary inflammatory pattern (EDIP) score, all implicated in systemic inflammation, with immune cell-specific expression scores.

METHODS

This population-based, prospective observational study evaluated 882 NHS and NHSII participants diagnosed with invasive breast cancer with detailed exposure and gene expression data. Of these, 262 women (training cohort) had breast tumor IHC for four classic immune cell markers (CD8, CD4, CD20, and CD163). Four immune cell-specific scores were derived via lasso regression using 105 published immune expression signatures' association with IHC. In the remaining 620 patient evaluation cohort, we evaluated association of each immune cell-specific score as outcomes, with BMI change since age 18, physical activity, and EDIP score as predictors, using multivariable-adjusted linear regression.

RESULTS

Among women with paired expression/IHC data from breast tumor tissue, we identified robust correlation between novel immune cell-specific expression scores and IHC. BMI change since age 18 was positively associated with CD4+ (β = 0.16; p = 0.009), and CD163 novel immune scores (β = 0.14; p = 0.04) in multivariable analyses. In other words, for each 10 unit (kg/m2) increase in BMI, the percentage of cells positive for CD4 and CD163 increased 1.6% and 1.4%, respectively. Neither physical activity nor EDIP was significantly associated with any immune cell-specific expression score in multivariable analyses.

CONCLUSIONS

BMI change since age 18 was positively associated with novel CD4+ and CD163+ cell scores in breast cancer, supporting further study of the effect of modifiable factors like weight gain on the immune microenvironment.

Internal checkpoint regulates T cell neoantigen reactivity and susceptibility to PD1 blockade

BACKGROUND

Adoptive transfer of tumor-infiltrating lymphocytes (TIL) fails to consistently elicit tumor rejection. Manipulation of intrinsic factors that inhibit T cell effector function and neoantigen recognition may therefore improve TIL therapy outcomes. We previously identified the cytokine-induced SH2 protein (CISH) as a key regulator of T cell functional avidity in mice. Here, we investigate the mechanistic role of CISH in regulating human T cell effector function in solid tumors and demonstrate that CRISPR/Cas9 disruption of CISH enhances TIL neoantigen recognition and response to checkpoint blockade.

METHODS

Single-cell gene expression profiling was used to identify a negative correlation between high CISH expression and TIL activation in patient-derived TIL. A GMP-compliant CRISPR/Cas9 gene editing process was developed to assess the impact of CISH disruption on the molecular and functional phenotype of human peripheral blood T cells and TIL. Tumor-specific T cells with disrupted Cish function were adoptively transferred into tumor-bearing mice and evaluated for efficacy with or without checkpoint blockade.

FINDINGS

CISH expression was associated with T cell dysfunction. CISH deletion using CRISPR/Cas9 resulted in hyper-activation and improved functional avidity against tumor-derived neoantigens without perturbing T cell maturation. Cish knockout resulted in increased susceptibility to checkpoint blockade in vivo.

CONCLUSIONS

CISH negatively regulates human T cell effector function, and its genetic disruption offers a novel avenue to improve the therapeutic efficacy of adoptive TIL therapy.

FUNDING

This study was funded by Intima Bioscience, U.S. and in part through the Intramural program CCR at the National Cancer Institute.

Distinct roles of ORAI1 in T cell-mediated allergic airway inflammation and immunity to influenza A virus infection

T cell activation and function depend on Ca2+ signals mediated by store-operated Ca2+ entry (SOCE) through Ca2+ release-activated Ca2+ (CRAC) channels formed by ORAI1 proteins. We here investigated how SOCE controls T cell function in pulmonary inflammation during a T helper 1 (TH1) cell-mediated response to influenza A virus (IAV) infection and TH2 cell-mediated allergic airway inflammation. T cell-specific deletion of Orai1 did not exacerbate pulmonary inflammation and viral burdens following IAV infection but protected mice from house dust mite-induced allergic airway inflammation. ORAI1 controlled the expression of genes including p53 and E2F transcription factors that regulate the cell cycle in TH2 cells in response to allergen stimulation and the expression of transcription factors and cytokines that regulate TH2 cell function. Systemic application of a CRAC channel blocker suppressed allergic airway inflammation without compromising immunity to IAV infection, suggesting that inhibition of SOCE is a potential treatment for allergic airway disease.

Severe, but not moderate asthmatics share blood transcriptomic changes with post-traumatic stress disorder and depression

Asthma, an inflammatory disorder of the airways, is one of the most common chronic illnesses worldwide and is associated with significant morbidity. There is growing recognition of an association between asthma and mood disorders including post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). Although there are several hypotheses regarding the relationship between asthma and mental health, there is little understanding of underlying mechanisms and causality. In the current study we utilized publicly available datasets of human blood mRNA collected from patients with severe and moderate asthma, MDD, and PTSD. We performed differential expression (DE) analysis and Gene Set Enrichment Analysis (GSEA) on diseased subjects against the healthy subjects from their respective datasets, compared the results between diseases, and validated DE genes and gene sets with 4 more independent datasets. Our analysis revealed that commonalities in blood transcriptomic changes were only found between the severe form of asthma and mood disorders. Gene expression commonly regulated in PTSD and severe asthma, included ORMDL3 a gene known to be associated with asthma risk and STX8, which is involved in TrkA signaling. We also identified several pathways commonly regulated to both MDD and severe asthma. This study reveals gene and pathway regulation that potentially drives the comorbidity between severe asthma, PTSD, and MDD and may serve as foci for future research aimed at gaining a better understanding of both the relationship between asthma and PTSD, and the pathophysiology of the individual disorders.

A sex-stratified analysis of neuroimmune gene expression signatures in Alzheimer's disease brains

Alzheimer's disease (AD) is the most common form of progressively disabling dementia. The chitinases CHI3L1 and CHI3L2 have long been known as biomarkers for microglial and astrocytic activation in neurodegeneration. Here, we collected microarray datasets from the National Center for Biotechnology Information (NCBI) brain samples of non-demented controls (NDC) (n = 460), and of deceased patients with AD (n = 697). The AD patients were stratified according to sex. Comparing the high CHI3L1 and CHI3L2 expression group (75^th percentile), and low CHI3L1 and CHI3L2 expression group (25^th percentile), we obtained eight signatures according to the sex of patients and performed a genomic deconvolution analysis using neuroimmune signatures (NIS) belonging to twelve cell populations. Expression analysis revealed significantly higher CHI3L1 and CHI3L2 expression in AD compared with NDC, and positive correlations of these genes with GFAP and TMEM119. Furthermore, deconvolution analysis revealed that CHI3L1 and CHI3L2 high expression was associated with inflammatory signatures in both sexes. Neuronal activation profiles were significantly activated in AD patients with low CHI3L1 and CHI3L2 expression levels. Furthermore, gene ontology analysis of common genes regulated by the two chitinases unveiled immune response as a main biological process. Finally, microglia NIS significantly correlated with CHI3L2 expression levels and were more than 98% similar to microglia NIS determined by CHI3L1. According to our results, high levels of CHI3L1 and CHI3L2 in the brains of AD patients are associated with inflammatory transcriptomic signatures. The high correlation between CHI3L1 and CHI3L2 suggests strong co-regulation.

GJA1/CX43 High Expression Levels in the Cervical Spinal Cord of ALS Patients Correlate to Microglia-Mediated Neuroinflammatory Profile

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder affecting motoneurons (MNs) with a fatal outcome. The typical degeneration of cortico-spinal, spinal, and bulbar MNs, observed in post-mortem biopsies, is associated with the activation of neuroimmune cells. GJA1, a member of the connexins (Cxs) gene family, encodes for connexin 43 (Cx43), a core gap junctions (GJs)- and hemichannels (HCs)-forming protein, involved in cell death, proliferation, and differentiation. Recently, Cx43 expression was found to play a role in ALS pathogenesis. Here, we used microarray and RNA-seq datasets from the NCBI of the spinal cord of control (NDC) and ALS patients, which were stratified according to the GJA1 gene expression. Genes that positively or negatively correlated to GJA1 expression were used to perform a genomic deconvolution analysis (GDA) using neuroimmune signatures. Expression analysis revealed a significantly higher GJA1 expression in the MNs of ALS patients as compared to NDC. Gene deconvolution analysis revealed that positively correlated genes were associated with microglia activation, whereas negatively correlated genes were associated with neuronal activation profiles. Moreover, gene ontology analysis, performed on genes characterizing either microglia or neuronal signature, indicated immune activation or neurogenesis as main biological processes. Finally, using a synthetic analysis of drugs able to revert the GJA1 transcriptomic signatures, we found a specific drug profile for ALS patients with high GJA1 expression levels, composed of amlodipine, sertraline, and prednisolone. In conclusion, our exploratory study suggests GJA1 as a new neuro-immunological gene correlated to microglial cellular profile in the spinal cord of ALS patients. Further studies are warranted to confirm these results and to evaluate the therapeutic potential of drugs able to revert typical GJA1/CX43 signature in ALS patients

NKG7 Enhances CD8+ T Cell Synapse Efficiency to Limit Inflammation

Cytotoxic lymphocytes are essential for anti-tumor immunity, and for effective responses to cancer immunotherapy. Natural killer cell granule protein 7 (NKG7) is expressed at high levels in cytotoxic lymphocytes infiltrating tumors from patients treated with immunotherapy, but until recently, the role of this protein in cytotoxic lymphocyte function was largely unknown. Unexpectedly, we found that highly CD8+ T cell-immunogenic murine colon carcinoma (MC38-OVA) tumors grew at an equal rate in Nkg7^+/+ and Nkg7^-/- littermate mice, suggesting NKG7 may not be necessary for effective CD8+ T cell anti-tumor activity. Mechanistically, we found that deletion of NKG7 reduces the ability of CD8+ T cells to degranulate and kill target cells in vitro. However, as a result of inefficient cytotoxic activity, NKG7 deficient T cells form a prolonged immune synapse with tumor cells, resulting in increased secretion of inflammatory cytokines, including tumor necrosis factor alpha (TNF). By deleting the TNF receptor, TNFR1, from MC38-OVA tumors, we demonstrate that this hyper-secretion of TNF compensates for reduced synapse-mediated cytotoxic activity against MC38-OVA tumors in vivo, via increased TNF-mediated tumor cell death. Taken together, our results demonstrate that NKG7 enhances CD8+ T cell immune synapse efficiency, which may serve as a mechanism to accelerate direct cytotoxicity and limit potentially harmful inflammatory responses.

EARLY DIFFERENTIATION BETWEEN SEPSIS AND STERILE INFLAMMATION VIA URINARY GENE SIGNATURES OF METABOLIC DYSREGULATION

ABSTRACT

Objective: The aim of this study was to characterize early urinary gene expression differences between patients with sepsis and patients with sterile inflammation and summarize in terms of a reproducible sepsis probability score. Design: This was a prospective observational cohort study. Setting: The study was conducted in a quaternary care academic hospital. Patients: One hundred eighty-six sepsis patients and 78 systemic inflammatory response syndrome (SIRS) patients enrolled between January 2015 and February 2018. Interventions: Whole-genome transcriptomic analysis of RNA was extracted from urine obtained from sepsis patients within 12 hours of sepsis onset and from patients with surgery-acquired SIRS within 4 hours after major inpatient surgery. Measurements and Main Results: We identified 422 of 23,956 genes (1.7%) that were differentially expressed between sepsis and SIRS patients. Differentially expressed probes were provided to a collection of machine learning feature selection models to identify focused probe sets that differentiate between sepsis and SIRS. These probe sets were combined to find an optimal probe set (UrSepsisModel) and calculate a urinary sepsis score (UrSepsisScore), which is the geometric mean of downregulated genes subtracted from the geometric mean of upregulated genes. This approach summarizes the expression values of all decisive genes as a single sepsis score. The UrSepsisModel and UrSepsisScore achieved area under the receiver operating characteristic curves 0.91 (95% confidence interval, 0.86-0.96) and 0.80 (95% confidence interval, 0.70-0.88) on the validation cohort, respectively. Functional analyses of probes associated with sepsis demonstrated metabolic dysregulation manifest as reduced oxidative phosphorylation, decreased amino acid metabolism, and decreased oxidation of lipids and fatty acids. Conclusions: Whole-genome transcriptomic profiling of urinary cells revealed focused probe panels that can function as an early diagnostic tool for differentiating sepsis from sterile SIRS. Functional analysis of differentially expressed genes demonstrated a distinct metabolic dysregulation signature in sepsis.

Signal pathways and precision therapy of small-cell lung cancer

Small-cell lung cancer (SCLC) encounters up 15% of all lung cancers, and is characterized by a high rate of proliferation, a tendency for early metastasis and generally poor prognosis. Most of the patients present with distant metastatic disease at the time of clinical diagnosis, and only one-third are eligible for potentially curative treatment. Recently, investigations into the genomic make-up of SCLC show extensive chromosomal rearrangements, high mutational burden and loss-of-function mutations of several tumor suppressor genes. Although the clinical development of new treatments for SCLC has been limited in recent years, a better understanding of oncogenic driver alterations has found potential novel targets that might be suitable for therapeutic approaches. Currently, there are six types of potential treatable signaling pathways in SCLC, including signaling pathways targeting the cell cycle and DNA repair, tumor development, cell metabolism, epigenetic regulation, tumor immunity and angiogenesis. At this point, however, there is still a lack of understanding of their role in SCLC tumor biology and the promotion of cancer growth. Importantly optimizing drug targets, improving drug pharmacology, and identifying potential biomarkers are the main focus and further efforts are required to recognize patients who benefit most from novel therapies in development. This review will focus on the current learning on the signaling pathways, the status of immunotherapy, and targeted therapy in SCLC.

Tumor-induced erythroid precursor-differentiated myeloid cells mediate immunosuppression and curtail anti-PD-1/PD-L1 treatment efficacy

Despite the unprecedented success of immune checkpoint inhibitors (ICIs) as anti-cancer therapy, it remains a prevailing clinical need to identify additional mechanisms underlying ICI therapeutic efficacy and potential drug resistance. Here, using lineage tracking in cancer patients and tumor-bearing mice, we demonstrate that erythroid progenitor cells lose their developmental potential and switch to the myeloid lineage. Single-cell transcriptome analyses reveal that, notwithstanding quantitative differences in erythroid gene expression, erythroid differentiated myeloid cells (EDMCs) are transcriptionally indistinguishable from their myeloid-originated counterparts. EDMCs possess multifaceted machinery to curtail T cell-mediated anti-tumor responses. Consequently, EDMC content within tumor tissues is negatively associated with T cell inflammation for the majority of solid cancers; moreover, EDMC enrichment, in accordance with anemia manifestation, is predictive of poor prognosis in various cohorts of patients undergoing ICI therapy. Together, our findings reveal a feedforward mechanism by which tumors exploit anemia-triggered erythropoiesis for myeloid transdifferentiation and immunosuppression.

Immune Cell Networks Uncover Candidate Biomarkers of Melanoma Immunotherapy Response

The therapeutic activation of antitumour immunity by immune checkpoint inhibitors (ICIs) is a significant advance in cancer medicine, not least due to the prospect of long-term remission. However, many patients are unresponsive to ICI therapy and may experience serious side effects; companion biomarkers are urgently needed to help inform ICI prescribing decisions. We present the IMMUNETS networks of gene coregulation in five key immune cell types and their application to interrogate control of nivolumab response in advanced melanoma cohorts. The results evidence a role for each of the IMMUNETS cell types in ICI response and in driving tumour clearance with independent cohorts from TCGA. As expected, ‘immune hot’ status, including T cell proliferation, correlates with response to first-line ICI therapy. Genes regulated in NK, dendritic, and B cells are the most prominent discriminators of nivolumab response in patients that had previously progressed on another ICI. Multivariate analysis controlling for tumour stage and age highlights CIITA and IKZF3 as candidate prognostic biomarkers. IMMUNETS provide a resource for network biology, enabling context-specific analysis of immune components in orthogonal datasets. Overall, our results illuminate the relationship between the tumour microenvironment and clinical trajectories, with potential implications for precision medicine.

The 'Alu-ome' shapes the epigenetic environment of regulatory elements controlling cellular defense

Promoters and enhancers are sites of transcription initiation (TSSs) and carry specific histone modifications, including H3K4me1, H3K4me3, and H3K27ac. Yet, the principles governing the boundaries of such regulatory elements are still poorly characterized. Alu elements are good candidates for a boundary function, being highly abundant in gene-rich regions, while essentially excluded from regulatory elements. Here, we show that the interval ranging from TSS to first upstream Alu, accommodates all H3K4me3 and most H3K27ac marks, while excluding DNA methylation. Remarkably, the average length of these intervals greatly varies in-between tissues, being longer in stem- and shorter in immune-cells. The very shortest TSS-to-first-Alu intervals were observed at promoters active in T-cells, particularly at immune genes, where first-Alus were traversed by RNA polymerase II transcription, while accumulating H3K4me1 signal. Finally, DNA methylation at first-Alus was found to evolve with age, regressing from young to middle-aged, then recovering later in life. Thus, the first-Alus upstream of TSSs appear as dynamic boundaries marking the transition from DNA methylation to active histone modifications at regulatory elements, while also participating in the recording of immune gene transcriptional events by positioning H3K4me1-modified nucleosomes.

Molecular characterization, expression, and functional analysis of cystatin B in the big-belly seahorse (Hippocampus abdominalis)

Cystatins are a diverse group of cysteine protease inhibitors widely present among various organisms. Beyond their protease inhibitor function, cystatins play a crucial role in diverse pathophysiological conditions in animals, including neurodegenerative disorders, tumor progression, inflammatory diseases, and immune response. However, the role of cystatins in immunity against viral and bacterial infections in fish remains to be elucidated. In this study, the cystatin B from big-belly seahorse, Hippocampus abdominalis, designated as HaCSTB, was identified and characterized. HaCSTB shared the highest homology with type 1 cystatin family members of teleosts and had three cystatin catalytic domains with no signal peptides or disulfide bonds. HaCSTB transcripts were mainly expressed in peripheral blood cells (PBCs), followed by the testis and pouch of healthy big-belly seahorses. Immune challenge with lipopolysaccharides (LPS), polyinosinic:polycytidylic acid (Poly I:C), and Streptococcus iniae induced upregulation of relative HaCSTB mRNA expression in PBCs. Subcellular localization analysis revealed the distribution of HaCSTB in the cytosol, mitochondria, and nuclei of fathead minnow cells (FHM). Recombinant HaCSTB (rHaCSTB) exhibited potent in vitro inhibitory activity against papain, a cysteine protease, in a concentration-, pH-, and temperature-dependent manner. Overexpression of HaCSTB in viral hemorrhagic septicemia virus (VHSV)-susceptible FHM cells increased cell viability and reduced VHSV-induced apoptosis. Collectively, these results suggest that HaCSTB might engage in the teleostean immune protection against bacteria and viruses.

The Effect of Hypoxia and Hypoxia-Associated Pathways in the Regulation of Antitumor Response: Friends or Foes?

Hypoxia is an environmental stressor that is instigated by low oxygen availability. It fuels the progression of solid tumors by driving tumor plasticity, heterogeneity, stemness and genomic instability. Hypoxia metabolically reprograms the tumor microenvironment (TME), adding insult to injury to the acidic, nutrient deprived and poorly vascularized conditions that act to dampen immune cell function. Through its impact on key cancer hallmarks and by creating a physical barrier conducive to tumor survival, hypoxia modulates tumor cell escape from the mounted immune response. The tumor cell-immune cell crosstalk in the context of a hypoxic TME tips the balance towards a cold and immunosuppressed microenvironment that is resistant to immune checkpoint inhibitors (ICI). Nonetheless, evidence is emerging that could make hypoxia an asset for improving response to ICI. Tackling the tumor immune contexture has taken on an in silico, digitalized approach with an increasing number of studies applying bioinformatics to deconvolute the cellular and non-cellular elements of the TME. Such approaches have additionally been combined with signature-based proxies of hypoxia to further dissect the turbulent hypoxia-immune relationship. In this review we will be highlighting the mechanisms by which hypoxia impacts immune cell functions and how that could translate to predicting response to immunotherapy in an era of machine learning and computational biology.

DAISM-DNNXMBD: Highly accurate cell type proportion estimation with in silico data augmentation and deep neural networks

Understanding the immune cell abundance of cancer and other disease-related tissues has an important role in guiding disease treatments. Computational cell type proportion estimation methods have been previously developed to derive such information from bulk RNA sequencing data. Unfortunately, our results show that the performance of these methods can be seriously plagued by the mismatch between training data and real-world data. To tackle this issue, we propose the DAISM-DNN^XMBD (XMBD: Xiamen Big Data, a biomedical open software initiative in the National Institute for Data Science in Health and Medicine, Xiamen University, China.) (denoted as DAISM-DNN) pipeline that trains a deep neural network (DNN) with dataset-specific training data populated from a certain amount of calibrated samples using DAISM, a novel data augmentation method with an in silico mixing strategy. The evaluation results demonstrate that the DAISM-DNN pipeline outperforms other existing methods consistently and substantially for all the cell types under evaluation in real-world datasets.

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We propose a data augmentation method (DAISM) for DNN-based cell type deconvolution

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DAISM-DNN enables accurate cell type deconvolution with dataset-specific training data

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DAISM-DNN is robust to random errors in calibration samples

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Trained DAISM-DNN model is reusable across biomedical experiments following same SOP

Computational cell type deconvolution methods were developed to understand the cellular heterogeneity in disease-related tissues from bulk RNA-seq data. Due to the presence of strong batch effects, the performance of existing methods could fluctuate greatly when applied to different datasets even with the latest development in batch normalization or platform-agnostic signature designs. To tackle this issue, we proposed a DNN-based cell abundance estimation method with dataset-specific training data populated from a certain number of calibrated samples from a target dataset using DAISM, a data augmentation method using an in silico mixing strategy. DAISM-DNN enables accurate cell type proportions prediction and is robust to random errors in the ground truth cell type proportions of calibration samples. Importantly, we showed that with strict SOPs, it is possible to create a “train once, reuse many times” DAISM-DNN model for multiple biomedical experiments without the need for retraining.

Diurnal and circadian rhythmicity of the human blood transcriptome overlaps with organ- and tissue-specific expression of a non-human primate

Background

Twenty-four-hour rhythmicity in mammalian tissues and organs is driven by local circadian oscillators, systemic factors, the central circadian pacemaker and light-dark cycles. At the physiological level, the neural and endocrine systems synchronise gene expression in peripheral tissues and organs to the 24-h-day cycle, and disruption of such regulation has been shown to lead to pathological conditions. Thus, monitoring rhythmicity in tissues/organs holds promise for circadian medicine; however, most tissues and organs are not easily accessible in humans and alternative approaches to quantify circadian rhythmicity are needed. We investigated the overlap between rhythmic transcripts in human blood and transcripts shown to be rhythmic in 64 tissues/organs of the baboon, how these rhythms are aligned with light-dark cycles and each other, and whether timing of tissue-specific rhythmicity can be predicted from a blood sample.

Results

We compared rhythmicity in transcriptomic time series collected from humans and baboons using set logic, circular cross-correlation, circular clustering, functional enrichment analyses, and least squares regression. Of the 759 orthologous genes that were rhythmic in human blood, 652 (86%) were also rhythmic in at least one baboon tissue and most of these genes were associated with basic processes such as transcription and protein homeostasis. In total, 109 (17%) of the 652 overlapping rhythmic genes were reported as rhythmic in only one baboon tissue or organ and several of these genes have tissue/organ-specific functions. The timing of human and baboon rhythmic transcripts displayed prominent ‘night’ and ‘day’ clusters, with genes in the dark cluster associated with translation. Alignment between baboon rhythmic transcriptomes and the overlapping human blood transcriptome was significantly closer when light onset, rather than midpoint of light, or end of light period, was used as phase reference point. The timing of overlapping human and baboon rhythmic transcriptomes was significantly correlated in 25 tissue/organs with an average earlier timing of 3.21 h (SD 2.47 h) in human blood.

Conclusions

The human blood transcriptome contains sets of rhythmic genes that overlap with rhythmic genes of tissues/organs in baboon. The rhythmic sets vary across tissues/organs, but the timing of most rhythmic genes is similar in human blood and baboon tissues/organs. These results have implications for development of blood transcriptome-based biomarkers for circadian rhythmicity in tissues and organs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-022-01258-7.

Multidimensional analysis of the host response reveals prognostic and pathogen-driven immune subtypes among adults with sepsis in Uganda

Background

The global burden of sepsis is concentrated in sub-Saharan Africa, where severe infections disproportionately affect young, HIV-infected adults and high-burden pathogens are unique. In this context, poor understanding of sepsis immunopathology represents a crucial barrier to development of locally-effective treatment strategies. We sought to determine inter-individual immunologic heterogeneity among adults hospitalized with sepsis in a sub-Saharan African setting, and characterize associations between immune subtypes, infecting pathogens, and clinical outcomes.

Methods

Among a prospective observational cohort of 288 adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to 14 soluble host immune mediators, reflective of key domains of sepsis immunopathology (innate and adaptive immune activation, endothelial dysfunction, fibrinolysis), to identify immune subtypes in randomly-split discovery (N = 201) and internal validation (N = 87) sub-cohorts. In parallel, we applied similar methods to whole-blood RNA-sequencing data from a consecutive subset of patients (N = 128) to identify transcriptional subtypes, which we characterized using biological pathway and immune cell-type deconvolution analyses.

Results

Unsupervised clustering consistently identified two immune subtypes defined by differential activation of pro-inflammatory innate and adaptive immune pathways, with transcriptional evidence of concomitant CD56(-)/CD16( +) NK-cell expansion, T-cell exhaustion, and oxidative-stress and hypoxia-induced metabolic and cell-cycle reprogramming in the hyperinflammatory subtype. Immune subtypes defined by greater pro-inflammatory immune activation, T-cell exhaustion, and metabolic reprogramming were consistently associated with a high-prevalence of severe and often disseminated HIV-associated tuberculosis, as well as more extensive organ dysfunction, worse functional outcomes, and higher 30-day mortality.

Conclusions

Our results highlight unique host- and pathogen-driven features of sepsis immunopathology in sub-Saharan Africa, including the importance of severe HIV-associated tuberculosis, and reinforce the need to develop more biologically-informed treatment strategies in the region, particularly those incorporating immunomodulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-03907-3.

Project-based learning course on metabolic network modelling in computational systems biology

Project-based learning (PBL) is a dynamic student-centred teaching method that encourages students to solve real-life problems while fostering engagement and critical thinking. Here, we report on a PBL course on metabolic network modelling that has been running for several years within the Master in Integrated Systems Biology (MISB) at the University of Luxembourg. This 2-week full-time block course comprises an introduction into the core concepts and methods of constraint-based modelling (CBM), applied to toy models and large-scale networks alongside the preparation of individual student projects in week 1 and, in week 2, the presentation and execution of these projects. We describe in detail the schedule and content of the course, exemplary student projects, and reflect on outcomes and lessons learned. PBL requires the full engagement of students and teachers and gives a rewarding teaching experience. The presented course can serve as a role model and inspiration for other similar courses.

A novel PDK1 inhibitor, JX06, inhibits glycolysis and induces apoptosis in multiple myeloma cells

Pyruvate dehydrogenase kinase 1 (PDK1) is a Ser/Thr kinase that inactivates mitochondrial pyruvate dehydrogenase (PDH), leading to switch of glucose metabolism from mitochondrial oxidation to aerobic glycolysis. We previously reported that PDK1 inhibition is a potent therapeutic strategy in multiple myeloma (MM). However, availability of PDK1 inhibitors, which are effective at low concentrations, are limited at present, making PDK1 inhibition difficult to apply in the clinic. In the present study, we examined the efficacy and mechanism of action of JX06, a novel PDK1 inhibitor, against MM cells. We confirmed that PDK1 is highly expressed in normal plasma cells and MM cells using publicly available gene expression datasets. JX06 suppressed cell growth and induced apoptosis against MM cells from approximately 0.5 μM JX06 treatment reduced PDH phosphorylation, suggesting that JX06 is indeed inhibiting PDK1. Intracellular metabolite analysis revealed that JX06 treatment reduced metabolites associated with glucose metabolism of MM cells. Additionally, JX06 in combination with a well-known proteasome inhibitor, bortezomib, significantly increased MM cell death, which raises the possibility of combination use of JX06 with proteasome inhibitors in the clinic. These findings demonstrate that PDK1 can be potentially targeted by JX06 in MM through glycolysis inhibition, leading to a novel therapeutic strategy in MM.

Mapping atopic dermatitis and anti-IL-22 response signatures to type 2-low severe neutrophilic asthma

BACKGROUND

Transcriptomic changes in patients who respond clinically to biological therapies may identify responses in other tissues or diseases.

OBJECTIVE

We sought to determine whether a disease signature identified in atopic dermatitis (AD) is seen in adults with severe asthma and whether a transcriptomic signature for patients with AD who respond clinically to anti-IL-22 (fezakinumab [FZ]) is enriched in severe asthma.

METHODS

An AD disease signature was obtained from analysis of differentially expressed genes between AD lesional and nonlesional skin biopsies. Differentially expressed genes from lesional skin from therapeutic superresponders before and after 12 weeks of FZ treatment defined the FZ-response signature. Gene set variation analysis was used to produce enrichment scores of AD and FZ-response signatures in the Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes asthma cohort.

RESULTS

The AD disease signature (112 upregulated genes) encompassing inflammatory, T-cell, TH2, and TH17/TH22 pathways was enriched in the blood and sputum of patients with asthma with increasing severity. Patients with asthma with sputum neutrophilia and mixed granulocyte phenotypes were the most enriched (P < .05). The FZ-response signature (296 downregulated genes) was enriched in asthmatic blood (P < .05) and particularly in neutrophilic and mixed granulocytic sputum (P < .05). These data were confirmed in sputum of the Airway Disease Endotyping for Personalized Therapeutics cohort. IL-22 mRNA across tissues did not correlate with FZ-response enrichment scores, but this response signature correlated with TH22/IL-22 pathways.

CONCLUSIONS

The FZ-response signature in AD identifies severe neutrophilic asthmatic patients as potential responders to FZ therapy. This approach will help identify patients for future asthma clinical trials of drugs used successfully in other chronic diseases.

Association of Differential Mast Cell Activation to Granulocytic Inflammation in Severe Asthma

BACKGROUND

Mast cells (MC) play a role in inflammation and both innate and adaptive immunity but their involvement in severe asthma (SA) remains undefined.

OBJECTIVE

We investigated the phenotypic characteristics of the U-BIOPRED asthma cohort by applying published MC activation signatures to the sputum cell transcriptome.

METHODS

84 SA, 20 mild/moderate (MMA) asthma, and 16 non-asthmatic healthy participants were studied. We calculated enrichment scores (ES) for nine MC activation signatures by asthma severity, sputum granulocyte status and three previously-defined sputum molecular phenotypes or transcriptome-associated clusters (TAC1, 2, 3) using gene-set variation analysis.

RESULTS

MC signatures except unstimulated, repeated FcεR1-stimulated and IFNγ-stimulated were enriched in SA. A FcεR1-IgE-stimulated and a single cell signature from asthmatic bronchial biopsies were highly enriched in eosinophilic asthma and in the TAC1 molecular phenotype. Subjects with a high ES for these signatures had elevated sputum levels of similar genes and pathways. IL-33- and LPS-stimulated MC signatures had greater ES in neutrophilic and mixed granulocytic asthma and in the TAC2 molecular phenotype. These subjects exhibited neutrophil, NF-κB, and IL-1β/TNFα pathway activation. The IFNγ-stimulated signature had the greatest ES in TAC2 and TAC3 that was associated with responses to viral infection. Similar results were obtained in an independent ADEPT asthma cohort.

CONCLUSIONS

Gene signatures of MC activation allow the detection of SA phenotypes and indicate that MC can be induced to take on distinct transcriptional phenotypes associated with specific clinical phenotypes. IL-33-stimulated MCs signature was associated with severe neutrophilic asthma while IgE-activated MC with an eosinophilic phenotype.

Immunomagnetic B cell isolation as a tool to study blood cell subsets and enrich B cell transcripts

OBJECTIVE

Transcriptional profiling of immune cells is an indispensable tool in biomedical research; however, heterogenous sample types routinely used in transcriptomic studies may mask important cell type-specific transcriptional differences. Techniques to isolate desired cell types are used to overcome this limitation. We sought to evaluate the use of immunomagnetic B cell isolation on RNA quality and transcriptional output. Additionally, we aimed to develop a B cell gene signature representative of a freshly isolated B cell population to be used as a tool to verify isolation efficacy and to provide a transcriptional standard for evaluating maintenance or deviation from traditional B cell identity.

RESULTS

We found RNA quality and RNA-sequencing output to be comparable between donor-matched PBMC, whole blood, and B cells following negative selection by immunomagnetic B cell isolation. Transcriptional analysis enabled the development of an 85 gene B cell signature. This signature effectively clustered isolated B cells from heterogeneous sample types in our study and naïve and memory B cells when applied to transcriptional data from a published source. Additionally, by identifying B cell signature genes whose functional role in B cells is currently unknown, our gene signature has uncovered areas for future investigation.

Categorizing sequences of concern by function to better assess mechanisms of microbial pathogenesis

To identify sequences with a role in microbial pathogenesis, we assessed the adequacy of their annotation by existing controlled vocabularies and sequence databases. Our goal was to regularize descriptions of microbial pathogenesis for improved integration with bioinformatic applications. Here, we review the challenges of annotating sequences for pathogenic activity. We relate the categorization of more than 2,750 sequences of pathogenic microbes through a controlled vocabulary called Functions of Sequences of Concern (FunSoCs). These allow for an ease of description by both humans and machines. We provide a subset of 220 fully annotated sequences in the supplemental material as examples. The use of this compact (∼30 terms), controlled vocabulary has potential benefits for research in microbial genomics, public health, biosecurity, biosurveillance, and the characterization of new and emerging pathogens.

Matched cohort study of germline BRCA mutation carriers with triple negative breast cancer in brightness

In the BrighTNess trial, carboplatin added to neoadjuvant chemotherapy (NAC) was associated with increased pathologic complete response (pCR) rates in patients with stage II/III triple-negative breast cancer (TNBC). In this matched cohort study, cases with a germline BRCA1/2 mutation (gBRCA; n = 75) were matched 1:2 with non-gBRCA controls (n = 150) by treatment arm, lymph node status, and age to evaluate pCR rates and association of benefit from platinum/PARP inhibitors with validated RNA expression-based immune, proliferation, and genomic instability scores among gBRCA with the addition of carboplatin ± veliparib to NAC. Among the well-matched cohorts, odds of pCR were not higher in gBRCA cancers who received standard NAC with carboplatin (OR 0.24, 95% CI [0.04-1.24], p = 0.09) or with carboplatin/veliparib (OR 0.44, 95% CI [0.10-1.84], p = 0.26) compared to non-gBRCA cancers. Higher PAM50 proliferation, GeparSixto immune, and CIN70 genomic instability scores were each associated with higher pCR rate in the overall cohort, but not specifically in gBRCA cases. In this study, gBRCA carriers did not have higher odds of pCR than non-gBRCA controls when carboplatin ± veliparib was added to NAC, and showed no significant differences in molecular, immune, chromosomal instability, or proliferation gene expression metrics.