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

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.

Pathogenic and transcriptomic differences of emerging SARS-CoV-2 variants in the Syrian golden hamster model

Background

Following the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread throughout the world, new viral variants of concern (VOC) have emerged. There is a critical need to understand the impact of the emerging variants on host response and disease dynamics to facilitate the development of vaccines and therapeutics.

Methods

Syrian golden hamsters are the leading small animal model that recapitulates key aspects of severe coronavirus disease 2019 (COVID-19). We performed intranasal inoculation of SARS-CoV-2 into hamsters with the ancestral virus (nCoV-WA1-2020) or VOC first identified in the United Kingdom (B.1.1.7, alpha) and South Africa (B.1.351, beta) and analyzed viral loads and host responses.

Findings

Similar gross and histopathologic pulmonary lesions were observed after infection with all three variants. Although differences in viral genomic copy numbers were noted in the lungs and oral swabs of challenged animals, infectious titers in the lungs were comparable between the variants. Antibody neutralization capacities varied, dependent on the original challenge virus and cross-variant protective capacity. Transcriptional profiling of lung samples 4 days post-challenge (DPC) indicated significant induction of antiviral pathways in response to all three challenges with a more robust inflammatory signature in response to B.1.1.7 infection. Furthermore, no additional mutations in the spike protein were detected at 4 DPC.

Interpretations

Although disease severity and viral shedding were not significantly different, the emerging VOC induced distinct humoral responses and transcriptional profiles compared to the ancestral virus. These observations suggest potential differences in acute early responses or alterations in immune modulation by VOC.

Funding

Intramural Research Program, NIAID, NIH; National Center for Research Resources, NIH; National Center for Advancing Translational Sciences, NIH.

Venetoclax imparts distinct cell death sensitivity and adaptivity patterns in T cells

BH3 mimetics are increasingly used as anti-cancer therapeutics either alone or in conjunction with other chemotherapies. However, mounting evidence has also demonstrated that BH3 mimetics modulate varied amounts of apoptotic signaling in healthy immune populations. In order to maximize their clinical potential, it will be essential to understand how BH3 mimetics affect discrete immune populations and to determine how BH3 mimetic pressure causes immune system adaptation. Here we focus on the BCL-2 specific inhibitor venetoclax (ABT-199) and its effects following short-term and long-term BCL-2 blockade on T cell subsets. Seven day "short-term" ex vivo and in vivo BCL-2 inhibition led to divergent cell death sensitivity patterns in CD8⁺ T cells, CD4⁺ T cells, and Tregs resulting in shifting of global T cell populations towards a more memory T cell state with increased expression of BCL-2, BCL-X_L, and MCL-1. However, twenty-eight day "long-term" BCL-2 blockade following T cell-depleted bone marrow transplantation did not lead to changes in the global T cell landscape. Despite the lack of changes in T cell proportions, animals treated with venetoclax developed CD8⁺ and CD4⁺ T cells with high levels of BCL-2 and were more resistant to apoptotic stimuli following expansion post-transplant. Further, we demonstrate through RNA profiling that T cells adapt while under BCL-2 blockade post-transplant and develop a more activated genotype. Taken together, these data emphasize the importance of evaluating how BH3 mimetics affect the immune system in different treatment modalities and disease contexts and suggest that venetoclax should be further explored as an immunomodulatory compound.

The GPR171 pathway suppresses T cell activation and limits antitumor immunity

The recently identified G-protein-coupled receptor GPR171 and its ligand BigLEN are thought to regulate food uptake and anxiety. Though GPR171 is commonly used as a T cell signature gene in transcriptomic studies, its potential role in T cell immunity has not been explored. Here we show that GPR171 is transcribed in T cells and its protein expression is induced upon antigen stimulation. The neuropeptide ligand BigLEN interacts with GPR171 to suppress T cell receptor-mediated signalling pathways and to inhibit T cell proliferation. Loss of GPR171 in T cells leads to hyperactivity to antigen stimulation and GPR171 knockout mice exhibit enhanced antitumor immunity. Blockade of GPR171 signalling by an antagonist promotes antitumor T cell immunity and improves immune checkpoint blockade therapies. Together, our study identifies the GPR171/BigLEN axis as a T cell checkpoint pathway that can be modulated for cancer immunotherapy.

Follicular Helper-like T Cells in the Lung Highlight a Novel Role of B Cells in Sarcoidosis

Rationale

Pulmonary sarcoidosis is generally presumed to be a T-helper cell type 1– and macrophage-driven disease. However, mouse models have recently revealed that chronically inflamed lung tissue can also comprise T follicular helper (Tfh)-like cells and represents a site of active T-cell/B-cell cooperation.

Objectives

To assess the role of pulmonary Tfh- and germinal center–like lymphocytes in sarcoidosis.

Methods

BAL fluid, lung tissue, and peripheral blood samples from patients with sarcoidosis were analyzed by flow cytometry, immunohistology, RNA sequencing, and in vitro T-cell/B-cell cooperation assays for phenotypic and functional characterization of germinal center–like reactions in inflamed tissue.

Measurements and Main Results

We identified a novel population of Tfh-like cells characterized by high expression of the B helper molecules CD40L and IL-21 in BAL of patients with sarcoidosis. Transcriptome analysis further confirmed a phenotype that was both Tfh-like and tissue resident. BAL T cells provided potent help for B cells to differentiate into antibody-producing cells. In lung tissue, we observed large peribronchial infiltrates with T and B cells in close contact, and many IgA⁺ plasmablasts. Most clusters were nonectopic; that is, they did not contain follicular dendritic cells. Patients with sarcoidosis also showed elevated levels of PD-1^high CXCR5⁻ CD40L^high ICOS^high Tfh-like cells, but not classical CXCR5⁺ Tfh cells, in the blood.

Conclusions

Active T-cell/B-cell cooperation and local production of potentially pathogenic antibodies in the inflamed lung represents a novel pathomechanism in sarcoidosis and should be considered from both diagnostic and therapeutic perspectives.

Transcriptional Analysis of Infection With Early or Late Isolates From the 2013-2016 West Africa Ebola Virus Epidemic Does Not Suggest Attenuated Pathogenicity as a Result of Genetic Variation

The 2013-2016 West Africa Ebola virus (EBOV) epidemic caused by the EBOV-Makona isolate is the largest and longest recorded to date. It incurred over 28,000 infections and ∼11,000 deaths. Early in this epidemic, several mutations in viral glycoprotein (A82V), nucleoprotein (R111C), and polymerase L (D759G) emerged and stabilized. In vitro studies of these new EBOV-Makona isolates showed enhanced fitness and viral replication capacity. However, in vivo studies in mice and rhesus macaques did not provide any evidence of enhanced viral fitness or shedding. Infection with late isolates carrying or early isolates lacking (early) these mutations resulted in uniformly lethal disease in nonhuman primates (NHPs), albeit with slightly delayed kinetics with late isolates. The recent report of a possible reemergence of EBOV from a persistent infection in a survivor of the epidemic highlights the urgency for understanding the impact of genetic variation on EBOV pathogenesis. However, potential molecular differences in host responses remain unknown. To address this gap in knowledge, we conducted the first comparative analysis of the host responses to lethal infection with EBOV-Mayinga and EBOV-Makona isolates using bivariate, longitudinal, regression, and discrimination transcriptomic analyses. Our analysis shows a conserved core of differentially expressed genes (DEGs) involved in antiviral defense, immune cell activation, and inflammatory processes in response to EBOV-Makona and EBOV-Mayinga infections. Additionally, EBOV-Makona and EBOV-Mayinga infections could be discriminated based on the expression pattern of a small subset of genes. Transcriptional responses to EBOV-Makona isolates that emerged later during the epidemic, specifically those from Mali and Liberia, lacked signatures of profound lymphopenia and excessive inflammation seen following infection with EBOV-Mayinga and early EBOV-Makona isolate C07. Overall, these findings provide novel insight into the mechanisms underlying the lower case fatality rate (CFR) observed with EBOV-Makona compared to EBOV-Mayinga.

Cellular senescence in lymphoid organs and immunosenescence

Immunosenescence is a multi-faceted phenomenon at the root of age-associated immune dysfunction. It can lead to an array of pathological conditions, including but not limited to a decreased capability to surveil and clear senescent cells (SnCs) and cancerous cells, an increased autoimmune responses leading to tissue damage, a reduced ability to tackle pathogens, and a decreased competence to illicit a robust response to vaccination. Cellular senescence is a phenomenon by which oncogene-activated, stressed or damaged cells undergo a stable cell cycle arrest. Failure to efficiently clear SnCs results in their accumulation in an organism as it ages. SnCs actively secrete a myriad of molecules, collectively called senescence-associated secretory phenotype (SASP), which are factors that cause dysfunction in the neighboring tissue. Though both cellular senescence and immunosenescence have been studied extensively and implicated in various pathologies, their relationship has not been greatly explored. In the wake of an ongoing pandemic (COVID-19) that disproportionately affects the elderly, immunosenescence as a function of age has become a topic of great importance. The goal of this review is to explore the role of cellular senescence in age-associated lymphoid organ dysfunction and immunosenescence, and provide a framework to explore therapies to rejuvenate the aged immune system.

SSMD: a semi-supervised approach for a robust cell type identification and deconvolution of mouse transcriptomics data

Deconvolution of mouse transcriptomic data is challenged by the fact that mouse models carry various genetic and physiological perturbations, making it questionable to assume fixed cell types and cell type marker genes for different data set scenarios. We developed a Semi-Supervised Mouse data Deconvolution (SSMD) method to study the mouse tissue microenvironment. SSMD is featured by (i) a novel nonparametric method to discover data set-specific cell type signature genes; (ii) a community detection approach for fixing cell types and their marker genes; (iii) a constrained matrix decomposition method to solve cell type relative proportions that is robust to diverse experimental platforms. In summary, SSMD addressed several key challenges in the deconvolution of mouse tissue data, including: (i) varied cell types and marker genes caused by highly divergent genotypic and phenotypic conditions of mouse experiment; (ii) diverse experimental platforms of mouse transcriptomics data; (iii) small sample size and limited training data source and (iv) capable to estimate the proportion of 35 cell types in blood, inflammatory, central nervous or hematopoietic systems. In silico and experimental validation of SSMD demonstrated its high sensitivity and accuracy in identifying (sub) cell types and predicting cell proportions comparing with state-of-the-arts methods. A user-friendly R package and a web server of SSMD are released via https://github.com/xiaoyulu95/SSMD.

Pathogenic and transcriptomic differences of emerging SARS-CoV-2 variants in the Syrian golden hamster model.. [PMID: 34268506 PMCID: PMC8282094 DOI: 10.1101/2021.07.11.451964]

Following the discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid spread throughout the world, new viral variants of concern (VOC) have emerged. There is a critical need to understand the impact of the emerging variants on host response and disease dynamics to facilitate the development of vaccines and therapeutics. Syrian golden hamsters are the leading small animal model that recapitulates key aspects of severe coronavirus disease 2019 (COVID-19). In this study, we show that intranasal inoculation of SARS-CoV-2 into hamsters with the ancestral virus (nCoV-WA1–2020) or VOC first identified in the United Kingdom (B.1.1.7) and South Africa (B.1.351) led to similar gross and histopathologic pulmonary lesions. Although differences in viral genomic copy numbers were noted in the lungs and oral swabs of challenged animals, infectious titers in the lungs were comparable. Antibody neutralization capacities varied, dependent on the original challenge virus and cross-variant protective capacity. Transcriptional profiling indicated significant induction of antiviral pathways in response to all three challenges with a more robust inflammatory signature in response to B.1.1.7. Furthermore, no additional mutations in the spike protein were detected at peak disease. In conclusion, the emerging VOC showed distinct humoral responses and transcriptional profiles in the hamster model compared to the ancestral virus.

Establishment of an Immune Cell Infiltration Score to Help Predict the Prognosis and Chemotherapy Responsiveness of Gastric Cancer Patients

The immune microenvironment plays a critical role in tumor biology. The molecular profiles of immune components and related genes are of tremendous value for the study of primary resistance to immune checkpoint blockers (ICBs) for gastric cancer (GC) and serve as prognostic biomarkers to predict GC survival. Recent studies have revealed that tumor immune cell infiltration (ICI) is an indicator of the survival and responsiveness to chemotherapy in GC patients. Here, we describe the immune cell landscape based on the ESTIMATE and CIBERSORT algorithms to help separate GC into 3 ICI clusters using the unsupervised clustering method. Further in-depth analyses, such as differential expression gene (DEG) analysis and principal component analysis (PCA), help to establish an ICI scoring system. A low ICI score is characterized by an increased tumor mutation burden (TMB). The combination of the ICI score and TMB score better predicts the survival of GC patients. Analyses based on public and our own database revealed that the ICI scoring system could also help predict the survival and chemotherapy responsiveness of GC patients. The present study demonstrated that the ICI score may be an effective prognostic biomarker and predictive indicator for chemotherapy and immunotherapy.

ADAM9-Responsive Mesoporous Silica Nanoparticles for Targeted Drug Delivery in Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) has the worst survival rate of all cancers. This poor prognosis results from the lack of efficient systemic treatment regimens, demanding high-dose chemotherapy that causes severe side effects. To overcome dose-dependent toxicities, we explored the efficacy of targeted drug delivery using a protease-dependent drug-release system. To this end, we developed a PDAC-specific drug delivery system based on mesoporous silica nanoparticles (MSN) functionalized with an avidin-biotin gatekeeper system containing a protease linker that is specifically cleaved by tumor cells. Bioinformatic analysis identified ADAM9 as a PDAC-enriched protease, and PDAC cell-derived conditioned medium efficiently cleaved protease linkers containing ADAM9 substrates. Cleavage was PDAC specific as conditioned medium from leukocytes was unable to cleave the ADAM9 substrate. Protease linker-functionalized MSNs were efficiently capped with avidin, and cap removal was confirmed to occur in the presence of PDAC cell-derived ADAM9. Subsequent treatment of PDAC cells in vitro with paclitaxel-loaded MSNs indeed showed high cytotoxicity, whereas no cell death was observed in white blood cell-derived cell lines, confirming efficacy of the nanoparticle-mediated drug delivery system. Taken together, this research introduces a novel ADAM9-responsive, protease-dependent, drug delivery system for PDAC as a promising tool to reduce the cytotoxicity of systemic chemotherapy.

Genomic features of rapid versus late relapse in triple negative breast cancer

Background

Triple-negative breast cancer (TNBC) is a heterogeneous disease and we have previously shown that rapid relapse of TNBC is associated with distinct sociodemographic features. We hypothesized that rapid versus late relapse in TNBC is also defined by distinct clinical and genomic features of primary tumors.

Methods

Using three publicly-available datasets, we identified 453 patients diagnosed with primary TNBC with adequate follow-up to be characterized as ‘rapid relapse’ (rrTNBC; distant relapse or death ≤2 years of diagnosis), ‘late relapse’ (lrTNBC; > 2 years) or ‘no relapse’ (nrTNBC: > 5 years no relapse/death). We explored basic clinical and primary tumor multi-omic data, including whole transcriptome (n = 453), and whole genome copy number and mutation data for 171 cancer-related genes (n = 317). Association of rapid relapse with clinical and genomic features were assessed using Pearson chi-squared tests, t-tests, ANOVA, and Fisher exact tests. We evaluated logistic regression models of clinical features with subtype versus two models that integrated significant genomic features.

Results

Relative to nrTNBC, both rrTNBC and lrTNBC had significantly lower immune signatures and immune signatures were highly correlated to anti-tumor CD8 T-cell, M1 macrophage, and gamma-delta T-cell CIBERSORT inferred immune subsets. Intriguingly, lrTNBCs were enriched for luminal signatures. There was no difference in tumor mutation burden or percent genome altered across groups. Logistic regression mModels that incorporate genomic features significantly outperformed standard clinical/subtype models in training (n = 63 patients), testing (n = 63) and independent validation (n = 34) cohorts, although performance of all models were overall modest.

Conclusions

We identify clinical and genomic features associated with rapid relapse TNBC for further study of this aggressive TNBC subset.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08320-7.

Molecular correlates of response to nivolumab at baseline and on treatment in patients with RCC

BACKGROUND

Nivolumab is an immune checkpoint inhibitor targeting the programmed death-1 receptor that improves survival in a subset of patients with clear cell renal cell carcinoma (ccRCC). In contrast to other tumor types that respond to immunotherapy, factors such as programmed death ligand-1 (PD-L1) status and tumor mutational burden show limited predictive utility in ccRCC. To address this gap, we report here the first molecular characterization of nivolumab response using paired index lesions, before and during treatment of metastatic ccRCC.

METHODS

We analyzed gene expression and T-cell receptor (TCR) clonality using lesion-paired biopsies provided in the CheckMate 009 trial and integrated the results with their PD-L1/CD4/CD8 status, genomic mutation status and serum cytokine assays. Statistical tests included linear mixed models, logistic regression models, Fisher's exact test, and Kruskal-Wallis rank-sum test.

RESULTS

We identified transcripts related to response, both at baseline and on therapy, including several that are amenable to peripheral bioassays or to therapeutic intervention. At both timepoints, response was positively associated with T-cell infiltration but not associated with TCR clonality, and some non-Responders were highly infiltrated. Lower baseline T-cell infiltration correlated with elevated transcription of Wnt/β-catenin signaling components and hypoxia-regulated genes, including the Treg chemoattractant CCL28. On treatment, analysis of the non-responding patients whose tumors were highly T-cell infiltrated suggests association of the RIG-I-MDA5 pathway in their nivolumab resistance. We also analyzed our data using previous transcriptional classifications of ccRCC and found they concordantly identified a molecular subtype that has enhanced nivolumab response but is sunitinib-resistant.

CONCLUSION

Our study describes molecular characteristics of response and resistance to nivolumab in patients with metastatic ccRCC, potentially impacting patient selection and first-line treatment decisions.

TRIAL REGISTRATION NUMBER

NCT01358721.

Tumor-associated neutrophils (TANs) in human carcinoma-draining lymph nodes: a novel TAN compartment

Objectives

The role of tumor‐associated neutrophils (TANs) in the nodal spread of cancer cells remains unexplored. The present study evaluates the occurrence and clinical significance of human nodal TANs.

Methods

The relevance, derivation, phenotype and interactions of nodal TANs were explored via a large immunohistochemical analysis of carcinoma‐draining lymph nodes, and their clinical significance was evaluated on a retrospective cohort of oral squamous cell carcinomas (OSCC). The tumor‐promoting function of nodal TAN was probed in the OSCC TCGA dataset combining TAN and epithelial‐to‐mesenchymal transition (EMT) signatures.

Results

The pan‐carcinoma screening identified a consistent infiltration (59%) of CD66b⁺  TANs in tumor‐draining lymph nodes (TDLNs). Microscopic findings, including the occurrence of intra‐lymphatic conjugates of TANs and cancer cells, indicate that TANs migrate through lymphatic vessels. In vitro experiments revealed that OSCC cell lines sustain neutrophil viability and activation via release of GM‐CSF. Moreover, by retrospective analysis, a high CD66b⁺ TAN density in M‐TDLNs of OSCC (n = 182 patients) predicted a worse prognosis. The analysis of the OSCC‐TCGA dataset unveiled that the expression of a set of neutrophil‐specific genes in the primary tumor (PT) is highly associated with an EMT signature, which predicts nodal spread. Accordingly, in the PT of OSCC cases, CD66b⁺TANs co‐localised with PDPN⁺S100A9⁻ EMT‐switched tumor cells in areas of lymphangiogenesis. The pro‐EMT signature is lacking in peripheral blood neutrophils from OSCC patients, suggesting tissue skewing of TANs.

Conclusion

Our findings are consistent with a novel pro‐tumoral TAN compartment that may promote nodal spread via EMT, through the lymphatics.

Instability of sputum molecular phenotypes in U-BIOPRED severe asthma

The Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) project has described phenotypic differences of severe asthma using a systems biology approach. We obtained three molecular phenotypes termed transcription-associated clusters (TACs) using hierarchical clustering of differentially expressed transcripts between T2-high and T2-low [1]. TAC1 was characterised by receptors IL33R, CCR3 and TSLPR, with the highest enrichment of gene signatures for IL-13/type-2 (T2) inflammation with sputum eosinophilia; TAC2 by inflammasome-associated genes, interferon-α (IFN-α) and tumour necrosis factor-α (TNF-α)-associated genes with sputum neutrophilia; and TAC3 by metabolic and mitochondrial function genes with pauci-granulocytic inflammation. Given that sputum eosinophilia may vary with time in many asthmatic subjects [2, 3], we hypothesised that TAC status may also change with time.

At 1 year, 45% of severe asthma change molecular phenotype as determined by sputum transcriptomic analysis. Together with concomitant shift in sputum granulocytic markers, this may indicate variability of driving mechanisms in this unstable group.https://bit.ly/35aj489

A CD8+ NK cell transcriptomic signature associated with clinical outcome in relapsing remitting multiple sclerosis

Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS) with the majority of cases characterised by relapsing/remitting (RRMS) attacks of neurologic dysfunction followed by variable resolution. Improving clinical outcomes in RRMS requires both a better understanding of the immunological mechanisms driving recurrent demyelination and better means of predicting future disease course to facilitate early targeted therapy. Here, we apply hypothesis-generating network transcriptomics to CD8⁺ cells isolated from patients in RRMS, identifying a signature reflecting expansion of a subset of CD8⁺ natural killer cells (NK8⁺) associated with favourable outcome. NK8⁺ are capable of regulating CD4⁺ T cell activation and proliferation in vitro, with reduced expression of HLA-G binding inhibitory receptors and consequent reduced sensitivity to HLA-G-mediated suppression. We identify surrogate markers of the NK8⁺ signature in peripheral blood leucocytes and validate their association with clinical outcome in an independent cohort, suggesting their measurement may facilitate early, targeted therapy in RRMS.

Integrative computational approach identifies drug targets in CD4+ T-cell-mediated immune disorders

CD4⁺ T cells provide adaptive immunity against pathogens and abnormal cells, and they are also associated with various immune-related diseases. CD4⁺ T cells’ metabolism is dysregulated in these pathologies and represents an opportunity for drug discovery and development. Genome-scale metabolic modeling offers an opportunity to accelerate drug discovery by providing high-quality information about possible target space in the context of a modeled disease. Here, we develop genome-scale models of naïve, Th1, Th2, and Th17 CD4⁺ T-cell subtypes to map metabolic perturbations in rheumatoid arthritis, multiple sclerosis, and primary biliary cholangitis. We subjected these models to in silico simulations for drug response analysis of existing FDA-approved drugs and compounds. Integration of disease-specific differentially expressed genes with altered reactions in response to metabolic perturbations identified 68 drug targets for the three autoimmune diseases. In vitro experimental validation, together with literature-based evidence, showed that modulation of fifty percent of identified drug targets suppressed CD4⁺ T cells, further increasing their potential impact as therapeutic interventions. Our approach can be generalized in the context of other diseases, and the metabolic models can be further used to dissect CD4⁺ T-cell metabolism.

Relevance of Immune Infiltration and Clinical Outcomes in Pancreatic Ductal Adenocarcinoma Subtypes

Purpose

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with high heterogeneity and dismal survival rates. Tumor immune microenvironment plays a critical role in sensitive to chemotherapy and prognosis. Herein, we determined the relevance of the composition of tumor-infiltrating immune cells to clinical outcomes in PDACs, and we evaluated these effects by molecular subtype.

Experimental Design

Data of 1,274 samples from publically available datasets were collected. Molecular subtypes were predicted with support vector machine. Twenty-two subsets of immune cells were estimated with CIBERSORTx. The associations between each cell subset and overall survival (OS), relapse free survival (RFS), and complete response (CR) to chemotherapy were evaluated, modelling cellular proportions as quartiles.

Results

An immune-related cluster was identified with unsupervised hierarchical clustering of hallmark pathways. Of the immune cells investigated, M0 macrophages emerged as closely associated with worse OS (HR =1.23, 95% CI = 1.15–1.31, p=1.57×10^-9) and RFS (HR = 1.14, 95% CI =1.04–1.25, p=2.93×10^-3), regardless of molecular subtypes. The CD8+ T cells conferred favorable survival. The neutrophils conferred poor OS overall (HR=1.17, 95% CI=1.10–1.23, p=1.74×10^-7) and within the classical subtype. In the basal-like subtype, activated mast cells were associated with worse OS. Consensus clustering revealed six immune subgroups with distinct survival patterns and CR rates. The higher expression of PD1 was associated with better OS.

Conclusions

The immune cellular composition infiltrate in PDAC are likely to have effects on prognosis. Further exploration of the cellular immune response has the potential to identify candidates for immunotherapy.

Lipopolysaccharide-Mediated Chronic Inflammation Promotes Tobacco Carcinogen-Induced Lung Cancer and Determines the Efficacy of Immunotherapy

Chronic obstructive pulmonary disease (COPD) is an inflammatory disease that is associated with increased risk of lung cancer. Pseudomonas aeruginosa (PA) infections are frequent in patients with COPD, which increase lung inflammation and acute exacerbations. However, the influences of PA-induced inflammation on lung tumorigenesis and the efficacy of immune checkpoint blockade remain unknown. In this study, we initiated a murine model of lung cancer by treating FVB/NJ female mice with tobacco carcinogen nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) alone or in combination with PA-lipopolysaccharide (LPS). LPS-mediated chronic inflammation induced T-cell exhaustion, increased the programmed cell death-1 (PD-1)/programmed cell death ligand-1 (PD-L1) axis, and enhanced NNK-induced lung tumorigenesis through an immunosuppressive microenvironment characterized by accumulation of myeloid-derived suppressive cells (MDSC) and regulatory T cells. Anti-PD-1 antibody treatment reduced tumors in NNK/LPS-treated mice with a 10-week LPS treatment but failed to inhibit tumor growth when LPS exposure was prolonged to 16 weeks. Anti-Ly6G antibody treatment coupled with depletion of MDSC alone reduced tumor growth; when combined with anti-PD-1 antibody, this treatment further enhanced antitumor activity in 16-week NNK/LPS-treated mice. Immune gene signatures from a human lung cancer dataset of PD-1 blockade were identified, which predicted treatment responses and survival outcome and overlapped with those from the mouse model. This study demonstrated that LPS-mediated chronic inflammation creates a favorable immunosuppressive microenvironment for tumor progression and correlates with the efficacy of anti-PD-1 treatment in mice. Immune gene signatures overlap with human and mouse lung tumors, providing potentially predictive markers for patients undergoing immunotherapy. SIGNIFICANCE: This study identifies an immune gene signature that predicts treatment responses and survival in patients with tobacco carcinogen-induced lung cancer receiving immune checkpoint blockade therapy.

Transcriptional Signatures That Define Ulcerative Colitis in Remission

BACKGROUND

This study addresses whether existing specific transcriptional profiles can improve and support the current status of the definition of ulcerative colitis (UC) remission apart from the existing endoscopic, histologic, and laboratory scoring systems. For that purpose, a well-stratified UC patient population in remission was compared to active UC and control patients and was investigated by applying the next-generation technology RNA-Seq.

METHODS

Mucosal biopsies from patients in remission (n = 14), patients with active UC (n = 14), and healthy control patientss (n = 16) underwent whole-transcriptome RNA-Seq. Principal component analysis, cell deconvolution methods, gene profile enrichment, and pathway enrichment methods were applied to define a specific transcriptional signature of UC in remission.

RESULTS

Analyses revealed specific transcriptional signatures for UC in remission with increased expression of genes involved in O-glycosylation (MUC17, MUC3A, MUC5AC, MUC12, SPON1, B3GNT3), ephrin-mediated repulsion of cells (EFNB2E, EFNA3, EPHA10, EPHA1), GAP junction trafficking (TUBA1C, TUBA4A, TUBB4B, GJB3, CLTB), and decreased expression of several toll-like receptors (TLR1, TLR3, TLR5, TLR6).

CONCLUSIONS

This study reveals specific transcriptional signatures for remission. Partial restoration and improvement of homeostasis in the epithelial mucus layer and revival of immunological functions were observed. A clear role for bacterial gut flora composition can be implied. The results can be useful for the development of treatment strategies for UC in remission and may be useful targets for further investigations aiming to predict the outcome of UC in the future.

A newly discovered teleost disulfide isomerase, thioredoxin domain containing 5 (TXNDC5), from big-belly seahorse (Hippocampus abdominalis): Insights into its molecular and functional properties and immune regulatory functions

The thioredoxin domain containing 5 (TXNDC5) is a recently discovered member of the protein disulfide isomerase family (PDI), which is mainly involved in the proper folding of and the correct formation of disulfide bonds in newly synthesized proteins via its disulfide isomerase and chaperone activities. Although the structural and functional features of mammalian TXNDC5 have been explored in previous studies, no studies have reported the functional characteristics of TXNDC5 in teleost fish. In this study, we report the identification and characterization of TXNDC5 from big-belly seahorse (Hippocampus abdominalis) (ShTXNDC5) accompanied by functional studies. The in-silico analysis revealed that the gene encodes a 433 amino acid (aa) long polypeptide chain with a predicted molecular weight of 49.3 kDa. According to homology analysis, ShTXNDC5 shares more than 55% sequence similarity with other teleost TXNDC5 proteins, and the alignment of the gene sequence convincingly reflects the accepted phylogeny of teleost. Analysis of the spatial distribution of ShTXNDC5 expression showed that its highest expression was observed in the ovary, gill, and pouch of seahorses. Moreover, significant upregulation of ShTXNDC5 transcription was noted in seahorse blood and kidney tissues in a time-dependent manner upon viral and bacterial immune challenges. Furthermore, considerable NADPH turnover, insulin reduction ability and significant cell survival effects of ShTXNDC5 were determined by the functional assay, revealing its capability to overcome cellular oxidative stress. Altogether, these findings expand our understanding of TXNDC5 at the molecular and functional levels, and its putative role in seahorse immunity.

Deconvolution of heterogeneous tumor samples using partial reference signals

Deconvolution of heterogeneous bulk tumor samples into distinct cellular populations is an important yet challenging problem, particularly when only partial references are available. A common approach to dealing with this problem is to deconvolve the mixed signals using available references and leverage the remaining signal as a new cell component. However, as indicated in our simulation, such an approach tends to over-estimate the proportions of known cell types and fails to detect novel cell types. Here, we propose PREDE, a partial reference-based deconvolution method using an iterative non-negative matrix factorization algorithm. Our method is verified to be effective in estimating cell proportions and expression profiles of unknown cell types based on simulated datasets at a variety of parameter settings. Applying our method to TCGA tumor samples, we found that proportions of pure cancer cells better indicate different subtypes of tumor samples. We also detected several cell types for each cancer type whose proportions successfully predicted patient survival. Our method makes a significant contribution to deconvolution of heterogeneous tumor samples and could be widely applied to varieties of high throughput bulk data. PREDE is implemented in R and is freely available from GitHub (https://xiaoqizheng.github.io/PREDE).

Tumor tissues are mixtures of different cell types. Identification and quantification of constitutional cell types within tumor tissues are important tasks in cancer research. The problem can be readily solved using regression-based methods if reference signals are available. But in most clinical applications, only partial references are available, which significantly reduces the deconvolution accuracy of the existing regression-based methods. In this paper, we propose a partial-reference based deconvolution model, PREDE, integrating the non-negative matrix factorization framework with an iterative optimization strategy. We conducted comprehensive evaluations for PREDE using both simulation and real data analyses, demonstrating better performance of our method than other existing methods.

Computational deconvolution of transcriptomic data for the study of tumor-infiltrating immune cells

Cancer is a complex disease characterized by a wide array of mutually interacting components constituting the tumor microenvironment (connective tissue, vascular system, immune cells), many of which are targeted therapeutically. In particular, immune checkpoint inhibitors have recently become an established part of the treatment of cancer. Despite great promise, only a portion of the patients display durable response. Current research efforts are concentrated on the determination of tumor-specific biomarkers predictive of response, such as tumor mutational burden, microsatellite instability, and neo-antigen presentation. However, it is clear that several additional characteristics pertaining to the tumor microenvironment play a critical role in the effectiveness of immunotherapy. Here we comment on the computational methods that are used for the analysis of the tumor microenvironment components from transcriptomic data, discuss the critical needs, and foresee potential evolutions in the field.

Discovery and Validation of Urinary Molecular Signature of Early Sepsis

Supplemental Digital Content is available in the text.

Objectives:

Identify alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients.

Design:

Prospective cohort study.

Setting:

Quaternary care academic hospital.

Patients:

A total of 266 sepsis and 82 control patients enrolled between January 2015 and February 2018.

Interventions:

Whole-genome transcriptomic analysis of messenger RNA isolated from the urinary cells of sepsis patients within 12 hours of sepsis onset and from control subjects.

Measurements and Main Results:

The differentially expressed probes that map to known genes were subjected to feature selection using multiple machine learning techniques to find the best subset of probes that differentiates sepsis from control subjects. Using differential expression augmented with machine learning ensembles, we identified a set of 239 genes in urine, which show excellent effectiveness in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes disrupted biological pathways in early sepsis and reveal key molecular networks driving its pathogenesis.

Conclusions:

We identified unique urinary gene expression profile in early sepsis. Future studies need to confirm whether this approach can complement blood transcriptomic approaches for sepsis diagnosis and prognostication.

Sources of variation in cell-type RNA-Seq profiles

Cell-type specific gene expression profiles are needed for many computational methods operating on bulk RNA-Seq samples, such as deconvolution of cell-type fractions and digital cytometry. However, the gene expression profile of a cell type can vary substantially due to both technical factors and biological differences in cell state and surroundings, reducing the efficacy of such methods. Here, we investigated which factors contribute most to this variation. We evaluated different normalization methods, quantified the variance explained by different factors, evaluated the effect on deconvolution of cell type fractions, and examined the differences between UMI-based single-cell RNA-Seq and bulk RNA-Seq. We investigated a collection of publicly available bulk and single-cell RNA-Seq datasets containing B and T cells, and found that the technical variation across laboratories is substantial, even for genes specifically selected for deconvolution, and this variation has a confounding effect on deconvolution. Tissue of origin is also a substantial factor, highlighting the challenge of using cell type profiles derived from blood with mixtures from other tissues. We also show that much of the differences between UMI-based single-cell and bulk RNA-Seq methods can be explained by the number of read duplicates per mRNA molecule in the single-cell sample. Our work shows the importance of either matching or correcting for technical factors when creating cell-type specific gene expression profiles that are to be used together with bulk samples.

A novel scoring method based on RNA-Seq immunograms describing individual cancer-immunity interactions

Because of the complexity of cancer‐immune system interactions, combinations of biomarkers will be required for predicting individual patient responses to treatment and for monitoring combination strategies to overcome treatment resistance. To this end, the “immunogram” has been proposed as a comprehensive framework to capture all relevant immunological variables. Here, we developed a method to convert transcriptomic data into immunogram scores (IGS). This immunogram includes 10 molecular profiles, consisting of innate immunity, priming and activation, T cell response, interferon γ (IFNG) response, inhibitory molecules, regulatory T cells, myeloid‐derived suppressor cells (MDSCs), recognition of tumor cells, proliferation, and glycolysis. Using genes related to these 10 parameters, we applied single‐sample gene set enrichment analysis (ssGSEA) to 9417 bulk RNA‐Seq data from 9362 cancer patients with 29 different solid cancers in The Cancer Genome Atlas (TCGA). Enrichment scores were z‐score normalized (Z) for each cancer type or the entire TCGA cohort. The IGS was defined by the formula IGS = 3 + 1.5 × Z so that patients would be well distributed over a range of scores from 1 to 5. The immunograms constructed in this way for all individual patients in the entire TCGA cohort can be accessed at “The RNA‐Seq based Cancer Immunogram Web” (https://yamashige33.shinyapps.io/immunogram/).

Identification of non-cancer cells from cancer transcriptomic data

Interactions between cancer cells and non-cancer cells composing the tumour microenvironment play a primary role in determining cancer progression and shaping the response to therapy. The qualitative and quantitative characterisation of the different cell populations in the tumour microenvironment is therefore crucial to understand its role in cancer. In recent years, many experimental and computational approaches have been developed to identify the cell populations composing heterogeneous tissue samples, such as cancer. In this review, we describe the state-of-the-art approaches for the quantification of non-cancer cells from bulk and single-cell cancer transcriptomic data, with a focus on immune cells. We illustrate the main features of these approaches and highlight their applications for the analysis of the tumour microenvironment in solid cancers. We also discuss techniques that are complementary and alternative to RNA sequencing, particularly focusing on approaches that can provide spatial information on the distribution of the cells within the tumour in addition to their qualitative and quantitative measurements. This article is part of a Special Issue entitled: Transcriptional Profiles and Regulatory Gene Networks edited by Dr. Federico Manuel Giorgi and Dr. Shaun Mahony.

The relationship between TIGIT+ regulatory T cells and autoimmune disease

The role of regulatory T cells (Treg cell) in controlling autoimmune disease is an area of intense study. As such, the characterization and understanding the function of Treg markers has the potential to provide a considerable impact in developing treatments and understanding the pathogenesis of autoimmune diseases. One such inhibitory Treg cell marker that has been recently discovered is T cell immunoglobulin and ITIM domain (TIGIT). In this review, we discuss what is known about the expression and function of TIGIT on Treg cells, and we discuss the relationship between TIGIT expressing Treg cells and different autoimmune diseases such as atopic dermatitis, autoimmune thyroiditis, type 1 diabetes, autoimmune uveitis, aplastic anemia, multiple sclerosis, systemic lupus erythematosus, arthritis, and colitis.

Untangling the effects of cellular composition on coexpression analysis

Coexpression analysis is widely used for inferring regulatory networks, predicting gene function, and interpretation of transcriptome profiling studies, based on methods such as clustering. The majority of such studies use data collected from bulk tissue, where the effects of cellular composition present a potential confound. However, the impact of composition on coexpression analysis has not been studied in detail. Here, we examine this issue for the case of human RNA analysis. Focusing on brain tissue, we found that, for most genes, differences in expression levels across cell types account for a large fraction of the variance of their measured RNA levels (median R 2 = 0.68). We then show that genes that have similar expression patterns across cell types will have correlated RNA levels in bulk tissue, due to the effect of variation in cellular composition. We demonstrate that much of the coexpression and the formation of coexpression clusters can be attributed to this effect for both brain and blood transcriptomes. For brain, we further show how this composition-induced coexpression masks underlying intra-cell-type coexpression observed in single-cell data. An attempt to correct for composition yielded mixed results. Our conclusion is that the dominant coexpression signal in brain, blood, and, likely, other complex tissues can be attributed to cellular compositional effects, rather than intra-cell-type regulatory relationships. These results have implications for the relevance and interpretation of coexpression analysis.

Early Transcriptional Changes within Liver, Adrenal Gland, and Lymphoid Tissues Significantly Contribute to Ebola Virus Pathogenesis in Cynomolgus Macaques

Ebola virus (EBOV) continues to pose a significant threat to human health, as evidenced by the 2013-2016 epidemic in West Africa and the ongoing outbreak in the Democratic Republic of the Congo. EBOV causes hemorrhagic fever, organ damage, and shock culminating in death, with case fatality rates as high as 90%. This high lethality combined with the paucity of licensed medical countermeasures makes EBOV a critical human pathogen. Although EBOV infection results in significant damage to the liver and the adrenal glands, little is known about the molecular signatures of injury in these organs. Moreover, while changes in peripheral blood cells are becoming increasingly understood, the host responses within organs and lymphoid tissues remain poorly characterized. To address this knowledge gap, we tracked longitudinal transcriptional changes in tissues collected from EBOV-Makona-infected cynomolgus macaques. Following infection, both liver and adrenal glands exhibited significant and early downregulation of genes involved in metabolism, coagulation, hormone synthesis, and angiogenesis; upregulated genes were associated with inflammation. Analysis of lymphoid tissues showed early upregulation of genes that play a role in innate immunity and inflammation and downregulation of genes associated with cell cycle and adaptive immunity. Moreover, transient activation of innate immune responses and downregulation of humoral immune responses in lymphoid tissues were confirmed with flow cytometry. Together, these data suggest that the liver, adrenal gland, and lymphatic organs are important sites of EBOV infection and that dysregulating the function of these vital organs contributes to the development of Ebola virus disease.IMPORTANCE Ebola virus (EBOV) remains a high-priority pathogen since it continues to cause outbreaks with high case fatality rates. Although it is well established that EBOV results in severe organ damage, our understanding of tissue injury in the liver, adrenal glands, and lymphoid tissues remains limited. We begin to address this knowledge gap by conducting longitudinal gene expression studies in these tissues, which were collected from EBOV-infected cynomolgus macaques. We report robust and early gene expression changes within these tissues, indicating they are primary sites of EBOV infection. Furthermore, genes involved in metabolism, coagulation, and adaptive immunity were downregulated, while inflammation-related genes were upregulated. These results indicate significant tissue damage consistent with the development of hemorrhagic fever and lymphopenia. Our study provides novel insight into EBOV-host interactions and elucidates how host responses within the liver, adrenal glands, and lymphoid tissues contribute to EBOV pathogenesis.

High Expression of microRNA-143 is Associated with Favorable Tumor Immune Microenvironment and Better Survival in Estrogen Receptor Positive Breast Cancer

microRNA-143 (miR-143) is a well-known tumor suppressive microRNA that exhibits anti-tumoral function by targeting KRAS signaling pathways in various malignancies. We hypothesized that miR-143 suppresses breast cancer progression by targeting KRAS and its effector molecules. We further hypothesized that high expression of miR-143 is associated with a favorable tumor immune microenvironment of estrogen receptor (ER)-positive breast cancer patients which result in improved survival. Two major publicly available breast cancer cohorts; The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) were used. The miR-143 high expression group was associated with increased infiltration of anti-cancer immune cells and decreased pro-cancer immune cells, as well as enrichment of the genes relating to T helper (Th1) cells resulting in improved overall survival (OS) in ER-positive breast cancer patients. To the best of our knowledge, this is the first study to demonstrate that high expression of miR-143 in cancer cells associates with a favorable tumor immune microenvironment, upregulation of anti-cancer immune cells, and suppression of the pro-cancer immune cells, associating with better survival of the breast cancer patients.

The Immune Landscape of Prostate Cancer and Nomination of PD-L2 as a Potential Therapeutic Target

BACKGROUND

Immunotherapy has been less successful in treating prostate cancer than other solid tumors. We sought to better understand the immune landscape in prostate cancer and identify immune-related biomarkers and potential therapeutic targets.

METHODS

We analyzed gene expression data from 7826 prospectively collected prostatectomy samples (2013-2016), and 1567 retrospective samples with long-term clinical outcomes, for a total of 9393 samples, all profiled on the same commercial clinical platform in a CLIA-certified lab. The primary outcome was distant metastasis-free survival (DMFS). Secondary outcomes included biochemical recurrence-free survival (bRFS), prostate cancer-specific survival (PCSS), and overall survival (OS). All statistical tests were two-sided.

RESULTS

Unsupervised hierarchical clustering of hallmark pathways demonstrated an immune-related tumor cluster. Increased estimated immune content scores based on immune-specific genes from the literature were associated with worse bRFS (hazard ratio [HR] = 1.26 [95% confidence interval [CI] = 1.12 to 1.42]; P < .001), DMFS (HR = 1.34 [95% CI = 1.13 to 1.58]; P < .001), PCSS (HR = 1.53 [95% CI = 1.21 to 1.92]; P < .001), and OS (HR = 1.27 [95% CI = 1.07 to 1.50]; P = .006). Deconvolution using Cibersort revealed that mast cells, natural killer cells, and dendritic cells conferred improved DMFS, whereas macrophages and T-cells conferred worse DMFS. Interestingly, while PD-L1 was not prognostic, consistent with its low expression in prostate cancer, PD-L2 was expressed at statistically significantly higher levels (P < .001) and was associated with worse bRFS (HR = 1.17 [95% CI = 1.03 to 1.33]; P = .01), DMFS (HR = 1.25 [95% CI = 1.05 to 1.49]; P = .01), and PCSS (HR = 1.45 [95% CI = 1.13 to 1.86]; P = .003). PD-L2 was strongly associated with immune-related pathways on gene set enrichment analysis suggesting that it is playing an important role in immune modulation in clinical prostate cancer samples. Furthermore, PD-L2 was correlated with radiation response pathways, and also predicted response to postoperative radiation therapy (PORT) on multivariable interaction analysis (P = .03).

CONCLUSION

In the largest study of its kind to date, these results illustrate the complex relationship between the tumor-immune interaction, prognosis, and response to radiotherapy, and nominate PD-L2 as a potential novel therapeutic target in prostate cancer, potentially in combination with radiotherapy.

PD-L1 and tumor-associated macrophages in de novo DLBCL

Programmed death-ligand 1 (PD-L1) and its receptor, programmed cell death-1 (PD-1), are important negative regulators of immune cell activation. Therapeutically targeting PD-1/PD-L1 in diffuse large B-cell lymphoma (DLBCL) patients with a single agent has limited activity, meriting a deeper understanding of this complex biology and of available PD-L1 clinical assays. In this study, we leveraged 2 large de novo DLBCL phase 3 trials (GOYA and MAIN) to better understand the biologic and clinical relevance of PD-L1 in de novo DLBCL. PD-L1 was expressed on myeloid cells in 85% to 95% of DLBCL patients (depending on staining procedure), compared with 10% on tumor cells, and correlated with macrophage gene expression. PD-L1 did not identify high-risk patients in de novo DLBCL; it correlated with STAT3, macrophage gene expression, and improved outcomes among a subset of patients. These results may help identify immunologically distinct DLBCL subsets relevant for checkpoint blockade. GOYA and MAIN trials were registered at www.clinicaltrials.gov as #NCT01287741 and #NCT00486759, respectively.

Immune correlates of postexposure vaccine protection against Marburg virus

Postexposure immunization can prevent disease and reduce transmission following pathogen exposure. The rapid immunostimulatory properties of recombinant vesicular stomatitis virus (rVSV)-based vaccines make them suitable postexposure treatments against the filoviruses Ebola virus and Marburg virus (MARV); however, the mechanisms that drive this protection are undefined. Previously, we reported 60–75% survival of rhesus macaques treated with rVSV vectors expressing MARV glycoprotein (GP) 20–30 minutes after a low dose exposure to the most pathogenic variant of MARV, Angola. Survival in this model was linked to production of GP-specific antibodies and lower viral load. To confirm these results and potentially identify novel correlates of postexposure protection, we performed a similar experiment, but analyzed plasma cytokine levels, frequencies of immune cell subsets, and the transcriptional response to infection in peripheral blood. In surviving macaques (80–89%), we observed induction of genes mapping to antiviral and interferon-related pathways early after treatment and a higher percentage of T helper 1 (Th1) and NK cells. In contrast, the response of non-surviving macaques was characterized by hypercytokinemia; a T helper 2 signature; recruitment of low HLA-DR expressing monocytes and regulatory T-cells; and transcription of immune checkpoint (e.g., PD-1, LAG3) genes. These results suggest dysregulated immunoregulation is associated with poor prognosis, whereas early innate signaling and Th1-skewed immunity are important for survival.

Seasonal Variability and Shared Molecular Signatures of Inactivated Influenza Vaccination in Young and Older Adults

The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of human influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. In this study we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days postvaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced Ab responses were distinct in young and older adults; for example, increased expression of killer cell lectin-like receptor B1 (KLRB1; CD161) 28 days postvaccination positively and negatively predicted vaccine-induced Ab responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.

Regenerative lineages and immune-mediated pruning in lung cancer metastasis

Developmental processes underlying normal tissue regeneration have been implicated in cancer, but the degree of their enactment during tumor progression and under the selective pressures of immune surveillance, remain unknown. Here, we show that human primary lung adenocarcinomas are characterized by the emergence of regenerative cell types typically seen in response to lung injury, and by striking infidelity amongst transcription factors specifying most alveolar and bronchial epithelial lineages. In contrast, metastases are enriched for key endoderm and lung-specifying transcription factors, SOX2 and SOX9, and recapitulate more primitive transcriptional programs spanning stem-like to regenerative pulmonary epithelial progenitor states. This developmental continuum mirrors the progressive stages of spontaneous outbreak from metastatic dormancy in a mouse model and exhibits SOX9-dependent resistance to Natural Killer (NK) cells. Loss of developmental stage-specific constraint in macrometastases triggered by NK cell depletion suggests a dynamic interplay between developmental plasticity and immune-mediated pruning during metastasis.

Porcine models for studying complications and organ crosstalk in diabetes mellitus

The worldwide prevalence of diabetes mellitus and obesity is rapidly increasing not only in adults but also in children and adolescents. Diabetes is associated with macrovascular complications increasing the risk for cardiovascular disease and stroke, as well as microvascular complications leading to diabetic nephropathy, retinopathy and neuropathy. Animal models are essential for studying disease mechanisms and for developing and testing diagnostic procedures and therapeutic strategies. Rodent models are most widely used but have limitations in translational research. Porcine models have the potential to bridge the gap between basic studies and clinical trials in human patients. This article provides an overview of concepts for the development of porcine models for diabetes and obesity research, with a focus on genetically engineered models. Diabetes-associated ocular, cardiovascular and renal alterations observed in diabetic pig models are summarized and their similarities with complications in diabetic patients are discussed. Systematic multi-organ biobanking of porcine models of diabetes and obesity and molecular profiling of representative tissue samples on different levels, e.g., on the transcriptome, proteome, or metabolome level, is proposed as a strategy for discovering tissue-specific pathomechanisms and their molecular key drivers using systems biology tools. This is exemplified by a recent study providing multi-omics insights into functional changes of the liver in a transgenic pig model for insulin-deficient diabetes mellitus. Collectively, these approaches will provide a better understanding of organ crosstalk in diabetes mellitus and eventually reveal new molecular targets for the prevention, early diagnosis and treatment of diabetes mellitus and its associated complications.

In Silico Cell-Type Deconvolution Methods in Cancer Immunotherapy

Several computational methods have been proposed to infer the cellular composition from bulk RNA-seq data of a tumor biopsy sample. Elucidating interactions in the tumor microenvironment can yield unique insights into the status of the immune system. In immuno-oncology, this information can be crucial for deciding whether the immune system of a patient can be stimulated to target the tumor. Here, we shed a light on the working principles, capabilities, and limitations of the most commonly used methods for cell-type deconvolution in immuno-oncology and offer guidelines for method selection.

Computational Deconvolution of Tumor-Infiltrating Immune Components with Bulk Tumor Gene Expression Data

Tumor-infiltrating immune cells play critical roles in immune-mediated tumor rejection and/or progression, and are key targets of immunotherapies. Estimation of different immune subsets becomes increasingly important with the decreased cost of high-throughput molecular profiling and the rapidly growing amount of cancer genomics data. Here, we present Tumor IMmune Estimation Resource (TIMER), an in silico deconvolution method for inference of tumor-infiltrating immune components. TIMER takes bulk tissue gene expression profiles measured with RNA-seq or microarray to evaluate the abundance of six immune cell types in the tumor microenvironment: B cell, CD4+ T cell, CD8+ T cell, neutrophil, macrophage, and dendritic cell. We further introduce its associated webserver for convenient, user-friendly analysis of tumor immune infiltrates across multiple cancer types.

Decoding the complexities of human malaria through systems immunology

The complexity of the Plasmodium parasite and its life cycle poses a challenge to our understanding of the host immune response against malaria. Studying human immune responses during natural and experimental Plasmodium infections can enhance our understanding of malaria-protective immunity and inform the design of disease-modifying adjunctive therapies and next-generation malaria vaccines. Systems immunology can complement conventional approaches to facilitate our understanding of the complex immune response to the highly dynamic malaria parasite. In this review, recent studies that used systems-based approaches to evaluate human immune responses during natural and experimental Plasmodium falciparum and Plasmodium vivax infections as well as during immunization with candidate malaria vaccines are summarized and related to each other. The potential for next-generation technologies to address the current limitations of systems-based studies of human malaria are discussed.

PHF6 and DNMT3A mutations are enriched in distinct subgroups of mixed phenotype acute leukemia with T-lineage differentiation

The genetic aberrations that drive mixed phenotype acute leukemia (MPAL) remain largely unknown, with the exception of a small subset of MPALs harboring BCR -ABL1 and MLL translocations. We performed clinicopathologic and genetic evaluation of 52 presumptive MPAL cases at Memorial Sloan Kettering Cancer Center. Only 29 out of 52 (56%) cases were confirmed to be bona fide MPAL according to the 2016 World Heath Organization classification. We identified PHF6 and DNMT3A mutations as the most common recurrent mutations in MPAL, each occurring in 6 out of 26 (23%) cases. These mutations are mutually exclusive of each other and BCR-ABL1/MLL translocations. PHF6- and DNMT3A-mutated MPAL showed marked predilection for T-lineage differentiation (5/6 PHF6 mutated, 6/6 DNMT3A mutated). PHF6-mutated MPAL occurred in a younger patient cohort compared with DNMT3A-mutated cases (median age, 27 years vs 61 years, P < .01). All 3 MPAL cases with both T- and B-lineage differentiation harbored PHF6 mutations. MPAL with T-lineage differentiation was associated with nodal or extramedullary involvement (9/15 [60%] vs 0, P = .001) and a higher relapse incidence (78% vs 22%, P = .017) compared with those without T-lineage differentiation. Sequencing studies on flow-cytometry-sorted populations demonstrated that PHF6 mutations are present in all blast compartments regardless of lineage differentiation with high variant allele frequency, implicating PHF6 as an early mutation in MPAL pathogenesis. In conclusion, PHF6 and DNMT3A mutations are the most common somatic alterations identified in MPAL and appear to define 2 distinct subgroups of MPAL with T-lineage differentiation with inferior outcomes.