Democratizing systems immunology with modular transcriptional repertoire analyses

Chemotherapy-induced high expression of IL23A enhances efficacy of anti-PD-1 therapy in TNBC by co-activating the PI3K-AKT signaling pathway of CTLs

Treatment of advanced triple-negative breast cancer (TNBC) is a great challenge in clinical practice. The immune checkpoints are a category of immunosuppressive molecules that cancer could hijack and impede anti-tumor immunity. Targeting immune checkpoints, such as anti-programmed cell death 1 (PD-1) therapy, is a promising therapeutic strategy in TNBC. The efficacy and safety of PD-1 monoclonal antibody (mAb) with chemotherapy have been validated in TNBC patients. However, the precise mechanisms underlying the synergistic effect of chemotherapy and anti-PD-1 therapy have not been elucidated, causing the TNBC patients that might benefit from this combination regimen not to be well selected. In the present work, we found that IL-23, an immunological cytokine, is significantly upregulated after chemotherapy in TNBC cells and plays a vital role in enhancing the anti-tumor immune response of cytotoxic T cells (CTLs), especially in combination with PD-1 mAb. In addition, the combination of IL-23 and PD-1 mAb could synergistically inhibit the expression of Phosphoinositide-3-Kinase Regulatory Subunit 1 (PIK3R1), which is a regulatory subunit of PI3K and inhibit p110 activity, and promote phosphorylation of AKT in TNBC-specific CTLs. Our findings might provide a molecular marker that could be used to predict the effects of combination chemotherapy therapy and PD-1 mAb in TNBC.

Multi-cohort comprehensive analysis unveiling the clinical value and therapeutic effect of GNAL in glioma

Clinical data indicates that glioma patients have poor treatment outcomes and clinical prognosis. The role of olfactory signaling pathway-related genes (OSPRGs) in glioma has not been fully elucidated. In this study, we aimed to investigate the role and relationship between OSPRGs and glioma. Univariate and multivariate Cox regression analyses were performed to assess the relationship between OSPRGs and the overall survival of glioma based on public cohorts, and the target gene (G Protein Subunit Alpha L, GNAL) was screened. The association of GNAL expression with clinicopathological characteristics, gene mutation landscape, tumor immune microenvironment (TIME), deoxyribonucleic acid (DNA) methylation, and naris-occlusion controlled genes (NOCGs) was performed. Immunohistochemistry was used to evaluate GNAL level in glioma. Further analysis was conducted to evaluate the drug sensitivity, immunotherapy response, and functional enrichment of GNAL. GNAL was an independent prognostic factor, and patients with low GNAL expression have a poor prognosis. Expression of GNAL was closely associated with clinicopathological characteristics, DNA methylation, and several immune-related pathways. Immune infiltration analysis indicated that GNAL levels were negatively correlated with immune scores. GNAL low-expression group showed efficacy with anti-PD-1 therapy. Ten compounds with significantly different half-maximal inhibitory concentration (IC50) values between the GNAL high and low-expression groups were identified. Furthermore, its expression was associated with several immune cells, immune-related genes, and NOCGs. The expression of GNAL is closely associated with clinicopathological characteristics, TIME, and the response to therapeutic interventions, highlighting its potential as a prognostic biomarker for glioma.

Myeloablation Followed by Hematopoietic Stem Cell Transplantation and Long-Term Normalization of Systemic Sclerosis Molecular Signatures

OBJECTIVE

In the randomized Scleroderma: Cyclophosphamide or Transplantation (SCOT) trial, myeloablation, followed by hematopoietic stem cell transplantation (HSCT), led to the normalization of systemic sclerosis (SSc) peripheral blood cell (PBC) gene expression signature at the 26-month visit. Herein, we examined long-term molecular changes ensuing 54 months after randomization for individuals receiving an HSCT or 12 months of intravenous cyclophosphamide (CYC).

METHODS

Global PBC transcript studies were performed in study participants at pretreatment baseline and at 38 months and 54 months after randomization, as well as in healthy controls using Illumina HT-12 arrays.

RESULTS

Thirty (HSCT = 19 and CYC = 11) participants had 38-month samples available, and 26 (HSCT = 16 and CYC = 11) had 54-month samples available. In the paired comparison to baseline, a significant down-regulation of interferon modules and an up-regulation of cytotoxic/natural killer module were observed at the 38-month and 54-month visits in the HSCT arm, indicating a long-term normalization of baseline SSc gene expression signature. No differentially expressed modules were detected in the CYC arm. In comparison to samples from healthy controls, 38-month visit samples in the HSCT arm showed an up-regulation of B cell and plasmablast modules and a down-regulation of myeloid and inflammation modules. Importantly, 54-month HSCT samples did not show any differentially expressed modules compared to healthy control samples, suggesting completion of immune reconstitution. Participants in the CYC arm continued to show an SSc transcript signature in comparison to controls at both time points.

CONCLUSION

Paralleling the observed clinical benefit, HSCT leads to durable long-term normalization of the molecular signature in SSc, with completion of immune resetting to 54 months after HSCT.

Preparation of hepatocellular carcinoma mRNA vaccines based on potential tumor targets and immunophenotypes

Background

With the development of messenger RNA (mRNA)-based therapeutics for malignant tumor, mRNA vaccines have shown considerable promise for tumor immunotherapy. Immunophenotypes can reflect the tumor microenvironment, which might have a significant influence on the effect of immunotherapy. This study seeks to discover and validate effective antigens that can be employed to develop mRNA vaccines for hepatocellular carcinoma (HCC) and to construct immunophenotypes and immune landscapes to identify potential beneficiaries.

Methods

RNA sequencing (RNASeq) data, mutation information, and clinical information were obtained from HCC patients and control cases from The Cancer Genome Atlas - Liver Hepatocellular Carcinoma (TCGA-LIHC), International Cancer Genome Consortium - Liver Cancer (ICGC-LIRI) and Gene Expression Omnibus (GEO) cohorts. Gene Expression Profiling Interactive Analysis (GEPIA2.0), cBioPortal for Cancer Genomics (cBioPortal), Tumor IMmune Estimation Resource (TIMER2.0), and immunohistochemistry (IHC) were employed to discover tumor antigens. ConsensusClusterPlus was employed to perform consistency matrix building and immunophenotypic clustering. Single sample gene set enrichment analysis (ssGSEA), ESTIMATE and monocle2 were employed to map immune cell distribution. Weighted correlation network analysis (WGCNA) was employed to identify potential gene modules that influence the efficacy of mRNA vaccines.

Results

Six antigen targets were discovered in the TCGA cohort, including AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1, which were associated with antigen-presenting cell infiltration and poor prognosis. IHC scores of AURKA, CDC25C and MCM3 were higher in tumor tissues, and high scores of AURKA and CDC25C indicated poor prognosis in the validation cohort. Five immunophenotypes derived from TCGA-LIHC and ICGC-LIRI cohorts were consistent. Furthermore, increased expression of blue and black modules may reduce vaccine responsiveness.

Conclusions

AURKA, CDC25C, KPNA2, MCM3, NEK2 and TUBG1 may be potential targets for mRNA vaccine development for HCC, especially AURKA and CDC25C. HCC patients with IS1 and IS5 subtypes perhaps present an autoimmunosuppressed state, then IS2 and IS3 subtypes perhaps the potential beneficiaries.

Design of a targeted blood transcriptional panel for monitoring immunological changes accompanying pregnancy

Background

Immunomodulatory processes exert steering functions throughout pregnancy. Detecting diversions from this physiologic immune clock may help identify pregnant women at risk for pregnancy-associated complications. We present results from a data-driven selection process to develop a targeted panel of mRNAs that may prove effective in detecting pregnancies diverting from the norm.

Methods

Based on a de novo dataset from a resource-constrained setting and a dataset from a resource-rich area readily available in the public domain, whole blood gene expression profiles of uneventful pregnancies were captured at multiple time points during pregnancy. BloodGen3, a fixed blood transcriptional module repertoire, was employed to analyze and visualize gene expression patterns in the two datasets. Differentially expressed genes were identified by comparing their abundance to non-pregnant postpartum controls. The selection process for a targeted gene panel considered (i) transcript abundance in whole blood; (ii) degree of correlation with the BloodGen3 module; and (iii) pregnancy biology.

Results

We identified 176 transcripts that were complemented with eight housekeeping genes. Changes in transcript abundance were seen in the early stages of pregnancy and similar patterns were observed in both datasets. Functional gene annotation suggested significant changes in the lymphoid, prostaglandin and inflammation-associated compartments, when compared to the postpartum controls.

Conclusion

The gene panel presented here holds promise for the development of predictive, targeted, transcriptional profiling assays. Such assays might become useful for monitoring of pregnant women, specifically to detect potential adverse events early. Prospective validation of this targeted assay, in-depth investigation of functional annotations of differentially expressed genes, and assessment of common pregnancy-associated complications with the aim to identify these early in pregnancy to improve pregnancy outcomes are the next steps.

Mapping inherited genetic variation with opposite effects on autoimmune disease and cancer identifies candidate drug targets associated with the anti-tumor immune response

Background

Germline alleles near genes that encode certain immune checkpoints (CTLA4, CD200) are associated with autoimmune/autoinflammatory disease and cancer but in opposite directions. This motivates a systematic search for additional germline alleles which demonstrate this pattern with the aim of identifying potential cancer immunotherapeutic targets using human genetic evidence.

Methods

Pairwise fixed effect cross-disorder meta-analyses combining genome-wide association studies (GWAS) for breast, prostate, ovarian and endometrial cancers (240,540 cases/317,000 controls) and seven autoimmune/autoinflammatory diseases (112,631 cases/895,386 controls) coupled with in silico follow-up. To ensure detection of alleles with opposite effects on cancer and autoimmune/autoinflammatory disease, the signs on the beta coefficients in the autoimmune/autoinflammatory GWAS were reversed prior to meta-analyses.

Results

Meta-analyses followed by linkage disequilibrium clumping identified 312 unique, independent lead variants with Pmeta<5x10-8 associated with at least one of the cancer types at Pcancer<10-3 and one of the autoimmune/autoinflammatory diseases at Pauto<10-3. At each lead variant, the allele that conferred autoimmune/autoinflammatory disease risk was protective for cancer. Mapping each lead variant to its nearest gene as its putative functional target and focusing on genes with established immunological effects implicated 32 of the nearest genes. Tumor bulk RNA-Seq data highlighted that the tumor expression of 5/32 genes (IRF1, IKZF1, SPI1, SH2B3, LAT) were each strongly correlated (Spearman's ρ>0.5) with at least one intra-tumor T/myeloid cell infiltration marker (CD4, CD8A, CD11B, CD45) in every one of the cancer types. Tumor single-cell RNA-Seq data from all cancer types showed that the five genes were more likely to be expressed in intra-tumor immune versus malignant cells. The five lead SNPs corresponding to these genes were linked to them via expression quantitative trait locus mechanisms and at least one additional line of functional evidence. Proteins encoded by the genes were predicted to be druggable.

Conclusion

We provide population-scale germline genetic and functional genomic evidence to support further evaluation of the proteins encoded by IRF1, IKZF1, SPI1, SH2B3, and LAT as possible targets for cancer immunotherapy.

Young infants display heterogeneous serological responses and extensive but reversible transcriptional changes following initial immunizations

Infants necessitate vaccinations to prevent life-threatening infections. Our understanding of the infant immune responses to routine vaccines remains limited. We analyzed two cohorts of 2-month-old infants before vaccination, one week, and one-month post-vaccination. We report remarkable heterogeneity but limited antibody responses to the different antigens. Whole-blood transcriptome analysis in an initial cohort showed marked overexpression of interferon-stimulated genes (ISGs) and to a lesser extent of inflammation-genes at day 7, which normalized one month post-vaccination. Single-cell RNA sequencing in peripheral blood mononuclear cells from a second cohort identified at baseline a predominantly naive immune landscape including ISGhi cells. On day 7, increased expression of interferon-, inflammation-, and cytotoxicity-related genes were observed in most immune cells, that reverted one month post-vaccination, when a CD8+ ISGhi and cytotoxic cluster and B cells expanded. Antibody responses were associated with baseline frequencies of plasma cells, B-cells, and monocytes, and induction of ISGs at day 7.

Harnessing large language models (LLMs) for candidate gene prioritization and selection

BACKGROUND

Feature selection is a critical step for translating advances afforded by systems-scale molecular profiling into actionable clinical insights. While data-driven methods are commonly utilized for selecting candidate genes, knowledge-driven methods must contend with the challenge of efficiently sifting through extensive volumes of biomedical information. This work aimed to assess the utility of large language models (LLMs) for knowledge-driven gene prioritization and selection.

METHODS

In this proof of concept, we focused on 11 blood transcriptional modules associated with an Erythroid cells signature. We evaluated four leading LLMs across multiple tasks. Next, we established a workflow leveraging LLMs. The steps consisted of: (1) Selecting one of the 11 modules; (2) Identifying functional convergences among constituent genes using the LLMs; (3) Scoring candidate genes across six criteria capturing the gene's biological and clinical relevance; (4) Prioritizing candidate genes and summarizing justifications; (5) Fact-checking justifications and identifying supporting references; (6) Selecting a top candidate gene based on validated scoring justifications; and (7) Factoring in transcriptome profiling data to finalize the selection of the top candidate gene.

RESULTS

Of the four LLMs evaluated, OpenAI's GPT-4 and Anthropic's Claude demonstrated the best performance and were chosen for the implementation of the candidate gene prioritization and selection workflow. This workflow was run in parallel for each of the 11 erythroid cell modules by participants in a data mining workshop. Module M9.2 served as an illustrative use case. The 30 candidate genes forming this module were assessed, and the top five scoring genes were identified as BCL2L1, ALAS2, SLC4A1, CA1, and FECH. Researchers carefully fact-checked the summarized scoring justifications, after which the LLMs were prompted to select a top candidate based on this information. GPT-4 initially chose BCL2L1, while Claude selected ALAS2. When transcriptional profiling data from three reference datasets were provided for additional context, GPT-4 revised its initial choice to ALAS2, whereas Claude reaffirmed its original selection for this module.

CONCLUSIONS

Taken together, our findings highlight the ability of LLMs to prioritize candidate genes with minimal human intervention. This suggests the potential of this technology to boost productivity, especially for tasks that require leveraging extensive biomedical knowledge.

Comprehensive Analysis of Tumor Microenvironment Reveals Prognostic ceRNA Network Related to Immune Infiltration in Sarcoma

PURPOSE

Sarcoma is the second most common solid tumor type in children and adolescents. The high level of tumor heterogeneity as well as aggressive behavior of sarcomas brings serious difficulties to developing effective therapeutic strategies for clinical application. Therefore, it is of great importance to identify accurate biomarkers for early detection and prognostic prediction of sarcomas.

EXPERIMENTAL DESIGN

In this study, we characterized three subtypes of sarcomas based on tumor immune infiltration levels (TIIL), and constructed a prognosis-related competing endogenous RNA (ceRNA) network to investigate molecular regulations in the sarcoma tumor microenvironment (TME). We further built a subnetwork consisting of mRNAs and lncRNAs that are targets of key miRNAs and strongly correlated with each other in the ceRNA network. After validation using public data and experiments in vivo and in vitro, we deeply dug the biological role of the miRNAs and lncRNAs in a subnetwork and their impact on TME.

RESULTS

Altogether, 5 miRNAs (hsa-mir-125b-2, hsa-mir-135a-1, hsa-mir92a-2, hsa-mir-181a-2, and hsa-mir-214), 3 lncRNAs (LINC00641, LINC01146, and LINC00892), and 10 mRNAs (AGO2, CXCL10, CD86, CASP1, IKZF1, CD27, CD247, CD69, CCR2, and CSF2RB) in the subnetwork were identified as vital regulators to shape the TME. On the basis of the systematic network, we identified that trichostatin A, a pan-HDAC inhibitor, could potentially regulate the TME of sarcoma, thereby inhibiting the tumor growth.

CONCLUSIONS

Our study identifies a ceRNA network as a promising biomarker for sarcoma. This system provides a more comprehensive understanding and a novel perspective of how ceRNAs are involved in shaping sarcoma TME.

Projecting genetic associations through gene expression patterns highlights disease etiology and drug mechanisms

Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.

Ancestry-based differences in the immune phenotype are associated with lupus activity

Systemic lupus erythematosus (SLE) affects 1 in 537 Black women, which is >2-fold more than White women. Black patients develop the disease at a younger age, have more severe symptoms, and have a greater chance of early mortality. We used a multiomics approach to uncover ancestry-associated immune alterations in patients with SLE and healthy controls that may contribute biologically to disease disparities. Cell composition, signaling, epigenetics, and proteomics were evaluated by mass cytometry; droplet-based single-cell transcriptomics and proteomics; and bead-based multiplex soluble mediator levels in plasma. We observed altered whole blood frequencies and enhanced activity in CD8+ T cells, B cells, monocytes, and DCs in Black patients with more active disease. Epigenetic modifications in CD8+ T cells (H3K27ac) could distinguish disease activity level in Black patients and differentiate Black from White patient samples. TLR3/4/7/8/9-related gene expression was elevated in immune cells from Black patients with SLE, and TLR7/8/9 and IFN-α phospho-signaling and cytokine responses were heightened even in immune cells from healthy Black control patients compared with White individuals. TLR stimulation of healthy immune cells recapitulated the ancestry-associated SLE immunophenotypes. This multiomic resource defines ancestry-associated immune phenotypes that differ between Black and White patients with SLE, which may influence the course and severity of SLE and other diseases.

Construction of a fecal immune-related protein-based biomarker panel for colorectal cancer diagnosis: a multicenter study

Purpose

To explore fecal immune-related proteins that can be used for colorectal cancer (CRC) diagnosis.

Patients and methods

Three independent cohorts were used in present study. In the discovery cohort, which included 14 CRC patients and 6 healthy controls (HCs), label-free proteomics was applied to identify immune-related proteins in stool that could be used for CRC diagnosis. Exploring potential links between gut microbes and immune-related proteins by 16S rRNA sequencing. The abundance of fecal immune-associated proteins was verified by ELISA in two independent validation cohorts and a biomarker panel was constructed that could be used for CRC diagnosis. The validation cohort I included 192 CRC patients and 151 HCs from 6 different hospitals. The validation cohort II included 141 CRC patients, 82 colorectal adenoma (CRA) patients, and 87 HCs from another hospital. Finally, the expression of biomarkers in cancer tissues was verified by immunohistochemistry (IHC).

Results

In the discovery study, 436 plausible fecal proteins were identified. And among 67 differential fecal proteins (|log2 fold change| > 1, P< 0.01) that could be used for CRC diagnosis, 16 immune-related proteins with diagnostic value were identified. The 16S rRNA sequencing results showed a positive correlation between immune-related proteins and the abundance of oncogenic bacteria. In the validation cohort I, a biomarker panel consisting of five fecal immune-related proteins (CAT, LTF, MMP9, RBP4, and SERPINA3) was constructed based on the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. The biomarker panel was found to be superior to hemoglobin in the diagnosis of CRC in both validation cohort I and validation cohort II. The IHC result showed that protein expression levels of these five immune-related proteins were significantly higher in CRC tissue than in normal colorectal tissue.

Conclusion

A novel biomarker panel consisting of fecal immune-related proteins can be used for the diagnosis of CRC.

Inflammatory and interferon gene expression signatures in patients with mitochondrial disease

BACKGROUND

People with mitochondrial disease (MtD) are susceptible to metabolic decompensation and neurological symptom progression in response to an infection. Increasing evidence suggests that mitochondrial dysfunction may cause chronic inflammation, which may promote hyper-responsiveness to pathogens and neurodegeneration. We sought to examine transcriptional changes between MtD patients and healthy controls to identify common gene signatures of immune dysregulation in MtD.

METHODS

We collected whole blood from a cohort of MtD patients and healthy controls and performed RNAseq to examine transcriptomic differences. We performed GSEA analyses to compare our findings against existing studies to identify commonly dysregulated pathways.

RESULTS

Gene sets involved in inflammatory signaling, including type I interferons, interleukin-1β and antiviral responses, are enriched in MtD patients compared to controls. Monocyte and dendritic cell gene clusters are also enriched in MtD patients, while T cell and B cell gene sets are negatively enriched. The enrichment of antiviral response corresponds with an independent set of MELAS patients, and two mouse models of mtDNA dysfunction.

CONCLUSIONS

Through the convergence of our results, we demonstrate translational evidence of systemic peripheral inflammation arising from MtD, predominantly through antiviral response gene sets. This provides key evidence linking mitochondrial dysfunction to inflammation, which may contribute to the pathogenesis of primary MtD and other chronic inflammatory disorders associated with mitochondrial dysfunction.

Longitudinal global transcriptomic profiling of preclinical systemic sclerosis reveals molecular changes associated with disease progression

OBJECTIVE

To investigate peripheral blood cell (PBCs) global gene expression profile of SSc at its preclinical stage (PreSSc) and to characterize the molecular changes associated with progression to a definite disease over time.

MATERIAL AND METHODS

Clinical data and PBCs of 33 participants with PreSSc and 16 healthy controls (HCs) were collected at baseline and follow-up (mean 4.2 years). Global gene expression profiling was conducted by RNA sequencing and a modular analysis was performed.

RESULTS

Comparison of baseline PreSSc to HCs revealed 2889 differentially expressed genes. Interferon signalling was the only activated pathway among top over-represented pathways. Moreover, 10 modules were significantly decreased in PreSSc samples (related to lymphoid lineage, cytotoxic/NK cell, and erythropoiesis) in comparison to HCs. At follow-up, 14 subjects (42.4%) presented signs of progression (evolving PreSSc) and 19 remained in stable preclinical stage (stable PreSSc). Progression was not associated with baseline clinical features or baseline PBC transcript modules. At follow-up stable PreSSc normalized their down-regulated cytotoxic/NK cell and protein synthesis modules while evolving PreSSc kept a down-regulation of cytotoxic/NK cell and protein synthesis modules. Transcript level changes of follow-up vs baseline in stable PreSSc vs evolving PreSSc showed 549 differentially expressed transcripts (336 up and 213 down) with upregulation of the EIF2 Signalling pathway.

CONCLUSIONS

Participants with PreSSc had a distinct gene expression profile indicating that molecular differences at a transcriptomic level are already present in the preclinical stages of SSc. Furthermore, a reduced NK signature in PBCs was related to SSc progression over time.

Inflammatory and interferon gene expression signatures in patients with mitochondrial disease

Background: People with mitochondrial disease (MtD) are susceptible to metabolic decompensation and neurological symptom progression in response to an infection. Increasing evidence suggests that mitochondrial dysfunction may cause chronic inflammation, which may promote hyperresponsiveness to pathogens and neurodegeneration. Methods: We collected whole blood from a cohort of MtD patients and healthy controls and performed RNAseq to examine transcriptomic differences. We performed GSEA analyses to compare our findings against existing studies to identify commonly dysregulated pathways. Results: Gene sets involved in inflammatory signaling, including type I interferons, interleukin-1β and antiviral responses, are enriched in MtD patients compared to controls. Monocyte and dendritic cell gene clusters are also enriched in MtD patients, while T cell and B cell gene sets are negatively enriched. The enrichment of antiviral response corresponds with an independent set of MELAS patients, and two mouse models of mtDNA dysfunction. Conclusions: Through the convergence of our results, we demonstrate translational evidence of systemic peripheral inflammation arising from MtD, predominantly through antiviral response gene sets. This provides key evidence linking mitochondrial dysfunction to inflammation, which may contribute to the pathogenesis of primary MtD and other chronic inflammatory disorders associated with mitochondrial dysfunction.

The Dynamic Linkage between Provirus Integration Sites and the Host Functional Genome Property Alongside HIV-1 Infections Associated with Antiretroviral Therapy

(1) Background: The HIV-1 latent reservoir harboring replication-competent proviruses is the major barrier in the quest for an HIV-1 infection cure. HIV-1 infection at all stages of disease progression is associated with immune activation and dysfunctional production of proinflammatory soluble factors (cytokines and chemokines), and it is expected that during HIV-1 infection, different immune components and immune cells, in turn, participate in immune responses, subsequently activating downstream biological pathways. However, the functional interaction between HIV-1 integration and the activation of host biological pathways is presently not fully understood. (2) Methods: In this work, I used genes targeted by proviruses from published datasets to seek enriched immunologic signatures and host biological pathways alongside HIV-1 infections based on MSigDb and KEGG over-representation analysis. (3) Results: I observed that different combinations of immunologic signatures of immune cell types and proinflammatory soluble factors appeared alongside HIV-1 infections associated with antiretroviral therapy. Moreover, enriched KEGG pathways were often related to "cancer specific types", "immune system", "infectious disease viral", and "signal transduction". (4) Conclusions: The observations in this work suggest that the gene sets harboring provirus integration sites may define specific immune cells and proinflammatory soluble factors during HIV-1 infections associated with antiretroviral therapy.

Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers

Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.

Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine

Background

Both sex and prior exposure to pathogens are known to influence responses to immune challenges, but their combined effects are not well established in humans, particularly in early innate responses critical for shaping subsequent outcomes.

Methods

We employed systems immunology approaches to study responses to a replication-defective, herpes simplex virus (HSV) 2 vaccine in men and women either naive or previously exposed to HSV.

Results

Blood transcriptomic and cell population profiling showed substantial changes on day 1 after vaccination, but the responses depended on sex and whether the vaccinee was naive or previously exposed to HSV. The magnitude of early transcriptional responses was greatest in HSV naive women where type I interferon (IFN) signatures were prominent and associated negatively with vaccine-induced neutralizing antibody titers, suggesting that a strong early antiviral response reduced the uptake of this replication-defective virus vaccine. While HSV seronegative vaccine recipients had upregulation of gene sets in type I IFN (IFN-α/β) responses, HSV2 seropositive vaccine recipients tended to have responses focused more on type II IFN (IFN-γ) genes.

Conclusions

These results together show that prior exposure and sex interact to shape early innate responses that then impact subsequent adaptive immune phenotypes.

Funding

Intramural Research Program of the NIH, the National Institute of Allergy and Infectious Diseases, and other institutes supporting the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation. The vaccine trial was supported through a clinical trial agreement between the National Institute of Allergy and Infectious Diseases and Sanofi Pasteur. Clinical trial number: NCT01915212.

Proteomic characteristics of saliva in patients with different subgroups of IgG4-RD

Background

Immunoglobulin G4-related disease (IgG4-RD) is a newly defined disease entity, with great heterogeneity among IgG4-RD subgroups with different organ involvement patterns. Identification of the proteomic characteristics of IgG4-RD subgroups will be critical for the understanding of the pathogenic mechanisms of IgG4-RD.

Method

In this study, we performed proteomic analysis using Tandem Mass Tags (TMT) technology with "high field" mass analyzer with improved resolution and sequencing speed to investigate the proteomic profile of saliva and plasma samples from ten untreated IgG4-RD patients and five healthy controls (HCs). Differentially expressed proteins (DEPs) were identified by "t test" function in R package. Functional enrichment analysis was used to investigate pathways enriched in IgG4-RD samples.

Results

Most salivary DEPs identified in IgG4-RD patients compared with HCs were mainly enriched in neutrophil mediated GO bioprocess. Within the comparisons between four IgG4-RD subgroups, more DEPs were identified in the comparison of Mikulicz group and Head and neck group. Among four subgroups of IgG4-RD, Head and neck group showed the most distinctive proteomic expression pattern when compared with HCs. Moreover, "Neutrophil mediated process" related GO bioprocess was commonly identified between comparisons of Mikulicz group and Head and neck group, Head and neck group and Retroperitoneal aorta group, Head and neck group and HCs, IgG4-RD patients with saliva gland involvement and those without saliva gland involvement. Key DEPs that involved in this GO bioprocess were identified. Besides, we performed proteomic analysis for plasma samples between ten IgG4-RD and five HCs and there were several DEPs identified overlapped in saliva and plasma.

Conclusion

We identified multiple processes/factors and several signaling pathways in saliva that may be involved in the IgG4-RD pathogenesis.

OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data

OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-seq datasets, compendia sharing, RESTful API support, and an additional meta-analysis method based on random effects. Here, we provide a step-by-step guide for using OMiCC.

For complete details on the use and execution of this protocol, please refer to Shah et al. (2016).

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OMiCC (OMics Compendia Commons) is a free web-based tool for gene expression data reuse

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Search publicly available studies to perform sample group comparisons to explore a disease

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In meta-analysis, multiple studies are combined to identify coherent signals

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OMiCC supports crowd-sharing and users can share their own analyses with the community

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Transcriptome-module phenotype association study implicates extracellular vesicles biogenesis in Plasmodium falciparum artemisinin resistance

Plasmodium falciparum malaria is still an important disease in sub-Saharan Africa (sSA). Great strides have been made in its control spear-headed by artemisinin (ART)-based combination therapies (ACTs). However, concerns about the imminent spread of ART-resistant (ARTr) malaria parasites to sSA threaten gains already made. Attempts to mitigate this risk have highlighted the need to discover novel P. falciparum drug targets. Therefore, studies to deepen our understanding of the biology of P. falciparum are needed. The role of extracellular vesicles (EVs) in the biology of malaria parasites is not fully understood. Recently, the ART resistance-associated transcriptional profile has been reported to involve several biological processes connected to vesicular trafficking, proteotoxic stress, erythrocyte remodelling, and mitochondrial metabolism. We explored a role for EVs in developing the P. falciparum ARTr phenotype using bulk RNA sequencing of unsynchronized parasite cultures under untreated, 0.1% dimethyl sulfoxide and 700nM dihydroartemisinin treated conditions for six hours. As pathway and gene ontology analysis is limited in its curated knowledge repertoire on EVs biogenesis in P. falciparum, we used a modular (gene set) analysis approach to explore whether an EVs biogenesis module is associated with the ARTr phenotype in P. falciparum. We first generated well-defined EVs modules of interest and used statistical tools to determine differences in their expression among the parasite and treatment conditions. Then we used gene set enrichment analysis to determine the strength of the association between each EVs module of interest and the ARTr phenotype. This transcriptome-module phenotype association study (TMPAS) represents a well-powered approach to making meaningful discoveries out of bulk gene expression data. We identified four EVs module of interest and report that one module representing gene sets with correlated expression to PF3D7_1441800 – involved with EVs biogenesis in P. falciparum - is associated with the ARTr phenotype (R539T_DHA_treated versus R539T_untreated: normalized enrichment score (NES) = 1.1830174, FDR q-value < 0.25; C580R_DHA_treated versus C580R_untreated: NES = 1.2457103, FDR q-value < 0.25). PF3D7_1441800 has been reported to reduce EVs production when knocked out in P. falciparum. Altogether, our findings suggest a role for EVs in developing ART resistance and warrant further studies interrogating this association.

DDOST Correlated with Malignancies and Immune Microenvironment in Gliomas

Among the most common types of brain tumor, gliomas are the most aggressive and have the poorest prognosis. Dolichyl-diphosphooligosaccharide protein glycosyltransferase non-catalytic subunit (DDOST) encodes a component of the oligosaccharide transferase complex and is related to the N-glycosylation of proteins. The role of DDOST in gliomas, however, is not yet known. First, we performed a pan cancer analysis of DDOST in the TCGA cohort. The expression of DDOST was compared between glioma and normal brain tissues in the GEO and Chinese Glioma Genome Atlas (CGGA) databases. In order to explore the role of DDOST in glioma, we analyze the impact of DDOST on the prognosis of glioma patients, with the CGGA 325 dataset as a test set and the CGGA 693 dataset as a validation set. Immunohistochemistry was performed on tissue microarrays to examine whether DDOST has an impact on glioma patient survival. Next, using single-cell sequencing analysis, GSEA, immune infiltration analysis, and mutation analysis, we explored how DDOST affected the glioma tumor microenvironment. Finally, we evaluated the clinical significance of DDOST for glioma treatment by constructing nomograms and decision curve analysis (DCA) curves. We found that DDOST was overexpressed in patients with high grade, IDH wild type, 1p19q non-codel and MGMT un-methylated, which was associated with poor prognosis. Patients with high levels of DDOST, regardless of their clinical characteristics, had a worse prognosis. Immunohistochemical analysis confirmed the results of the above bioinformatics analysis. Mechanistic analysis revealed that DDOST was closely associated with the glioma microenvironment and negatively related to tumor-infiltrating B cells and CD4+ T cells and positively related to CAFs and tumor-associated macrophages. In conclusion, these findings suggested that DDOST mediated the immunosuppressive microenvironment of gliomas and could be an important biomarker in diagnosing and treating gliomas.

Peripheral blood gene expression profiling shows predictive significance for response to mycophenolate in systemic sclerosis-related interstitial lung disease

OBJECTIVES

To characterise the peripheral blood cell (PBC) gene expression changes ensuing from mycophenolate mofetil (MMF) or cyclophosphamide (CYC) treatment and to determine the predictive significance of baseline PBC transcript scores for response to immunosuppression in systemic sclerosis (SSc)-related interstitial lung disease (ILD).

METHODS

PBC RNA samples from baseline and 12-month visits, corresponding to the active treatment period of both arms in Scleroderma Lung Study II, were investigated by global RNA sequencing. Joint models were created to examine the predictive significance of baseline composite modular scores for the course of forced vital capacity (FVC) per cent predicted measurements from 3 to 12 months.

RESULTS

134 patients with SSc-ILD (CYC=69 and MMF=65) were investigated. CYC led to an upregulation of erythropoiesis, inflammation and myeloid lineage-related modules and a downregulation of lymphoid lineage-related modules. The modular changes resulting from MMF treatment were more modest and included a downregulation of plasmablast module. In the longitudinal analysis, none of the baseline transcript module scores showed predictive significance for FVC% course in the CYC arm. In contrast, in the MMF arm, higher baseline lymphoid lineage modules predicted better subsequent FVC% course, while higher baseline myeloid lineage and inflammation modules predicted worse subsequent FVC% course.

CONCLUSION

Consistent with the primary mechanism of action of MMF on lymphocytes, patients with SSc-ILD with higher baseline lymphoid module scores had better FVC% course, while those with higher myeloid cell lineage activation score had poorer FVC% course on MMF.

Development and Validation of Novel Prognostic Models for Immune-Related Genes in Osteosarcoma

Immunotherapy has shown excellent therapeutic effects on various malignant tumors; however, to date, immunotherapy for osteosarcoma is still suboptimal. In this study, we performed comprehensive bioinformatic analysis of immune-related genes (IRGs) and tumor-infiltrating immune cells (TIICs). Datasets of differentially expressed IRGs were extracted from the GEO database (GSE16088). The functions and prognostic values of these differentially expressed IRGs were systematically investigated using a series of bioinformatics methods. In addition, CCK8 and plate clone formation assays were used to explore the effect of PGF on osteosarcoma cells, and twenty-nine differentially expressed IRGs were identified, of which 95 were upregulated and 34 were downregulated. Next, PPI was established for Identifying Hub genes and biology networks by Cytoscape. Six IRGs (APLNR, TPM2, PGF, CD86, PROCR, and SEMA4D) were used to develop an overall survival (OS) prediction model, and two IRGs (HLA-B and PGF) were used to develop a relapse-free survival (RFS) prediction model. Compared with the low-risk patients in the training cohort (GSE39058) and TARGET validation cohorts, high-risk patients had poorer OS and RFS. Using these identified IRGs, we used OS and RFS prediction nomograms to generate a clinical utility model. The risk scores of the two prediction models were associated with the infiltration proportions of some TIICs, and the activation of memory CD4 T-cells was associated with OS and RFS. CD86 was associated with CTLA4 and CD28 and influenced the infiltration of different TIICs. In vitro experiments showed that the knockdown of PGF inhibited the proliferation and viability of osteosarcoma cells. In conclusion, these findings help us better understand the prognostic roles of IRGs and TIICs in osteosarcoma, and CD86 and PGF may serve as specific immune targets.

Weighted Gene Coexpression Network Analysis Identifies TBC1D10C as a New Prognostic Biomarker for Breast Cancer

Background

Immune checkpoint inhibitors are a promising therapeutic strategy for breast cancer (BRCA) patients. The tumor microenvironment (TME) can downregulate the immune response to cancer therapy. Our study is aimed at finding a TME-related biomarker to identify patients who might respond to immunotherapy.

Method

We downloaded raw data from several databases including TCGA and MDACC to identify TME hub genes associated with overall survival (OS) and the progression-free interval (PFI) by WGCNA. Correlations between hub genes and either tumor-infiltrating immune cells or immune checkpoints were conducted by ssGSEA.

Result

TME-related green and black modules were selected by WGCNA to further screen hub genes. Random forest and univariate and multivariate Cox regressions were applied to screen hub genes (MYO1G, TBC1D10C, SELPLG, and LRRC15) and construct a nomogram to predict the survival of BRCA patients. The C-index for the nomogram was 0.713. A DCA of the predictive model revealed that the net benefit of the nomogram was significantly higher than others and the calibration curve demonstrated a good performance by the nomogram. Only TBC1D10C was correlated with both OS and the PFI (both p values < 0.05). TBC1D10C also had a high positive association with tumor-infiltrating immune cells and common immune checkpoints (PD-1, CTLA-4, and TIGIT).

Conclusion

We constructed a TME-related gene signature model to predict the survival probability of BRCA patients. We also identified a hub gene, TBC1D10C, which was correlated with both OS and the PFI and had a high positive association with tumor-infiltrating immune cells and common immune checkpoints. TBC1D10C may be a new biomarker to select patients who may benefit from immunotherapy.

Progress towards the Elusive Mastitis Vaccines

Mastitis is a major problem in dairy farming. Vaccine prevention of mammary bacterial infections is of particular interest in helping to deal with this issue, all the more so as antibacterial drug inputs in dairy farms must be reduced. Unfortunately, the effectiveness of current vaccines is not satisfactory. In this review, we examine the possible reasons for the current shortcomings of mastitis vaccines. Some reasons stem from the peculiarities of the mammary gland immunobiology, others from the pathogens adapted to the mammary gland niche. Infection does not induce sterilizing protection, and recurrence is common. Efficacious vaccines will have to elicit immune mechanisms different from and more effective than those induced by infection. We propose focusing our research on a few points pertaining to either the current immune knowledge or vaccinology approaches to get out of the current deadlock. A possible solution is to focus on the contribution of cell-mediated immunity to udder protection based on the interactions of T cells with the mammary epithelium. On the vaccinology side, studies on the orientation of the immune response by adjuvants, the route of vaccine administration and the delivery systems are among the keys to success.

Bet v 1 triggers antiviral-type immune signaling in birch pollen allergic individuals

Background

In allergic patients, clinical symptoms caused by pollen remind of symptoms triggered by viral respiratory infections, which are also the main cause of asthmatic exacerbations. In patients sensitized to birch pollen, Bet v 1 is the major symptom‐causing allergen. Immune mechanisms driving Bet v 1‐related responses of human blood cells have not been fully characterized.

Objective

To characterize the immune response to Bet v 1 in peripheral blood in patients allergic to birch pollen.

Methods

The peripheral blood mononuclear cells of birch‐allergic (n = 24) and non‐allergic (n = 47) adolescents were stimulated ex‐vivo followed by transcriptomic profiling. Systems‐biology approaches were employed to decipher disease‐relevant gene networks and deconvolution of associated cell populations.

Results

Solely in birch‐allergic patients, co‐expression analysis revealed activation of networks of innate immunity and antiviral signalling as the immediate response to Bet v 1 stimulation. Toll‐like receptors and signal transducer transcription were the main drivers of gene expression patterns. Macrophages and dendritic cells were the main cell subsets responding to Bet v 1.

Conclusions and clinical relevance

In birch‐pollen‐allergic patients, the activated innate immune networks seem to be, in part, the same as those activated during viral infections. This tendency of the immune system to read pollens as viruses may provide new insight to allergy prevention and treatment.

Transcriptome-wide changes in gene expression, splicing, and lncRNAs in response to a live attenuated dengue virus vaccine

The tetravalent dengue vaccine candidate, TAK-003, induces a functional antibody response, but the titers of antibodies against the four serotypes of the dengue virus (DENV) can vary. Here, through a transcriptomic analysis on whole blood collected from recipients of a two-dose schedule of TAK-003, we examine gene expression, splicing, and transcript isoform-level changes for both protein-coding and noncoding genes to broaden our understanding of the immune response. Our analysis reveals a dynamic pattern of vaccine-associated regulation of long noncoding RNAs (lncRNAs), differential splicing of interferon-stimulated gene exons, and gene expression changes related to multiple signaling pathways that detect viral infection. Co-expression networks isolate immune cell-type-related and interferon-response modules that represent specific biological processes that correlate with more robust antibody responses. These data provide insights into the early determinants of the variable immune response to the vaccine, highlighting the significance of splicing and isoform-level gene regulatory mechanisms in defining vaccine immunogenicity.

oCEM: Automatic detection and analysis of overlapping co-expressed gene modules

Background

When it comes to the co-expressed gene module detection, its typical challenges consist of overlap between identified modules and local co-expression in a subset of biological samples. The nature of module detection is the use of unsupervised clustering approaches and algorithms. Those methods are advanced undoubtedly, but the selection of a certain clustering method for sample- and gene-clustering tasks is separate, in which the latter task is often more complicated.

Results

This study presented an R-package, Overlapping CoExpressed gene Module (oCEM), armed with the decomposition methods to solve the challenges above. We also developed a novel auxiliary statistical approach to select the optimal number of principal components using a permutation procedure. We showed that oCEM outperformed state-of-the-art techniques in the ability to detect biologically relevant modules additionally.

Conclusions

oCEM helped non-technical users easily perform complicated statistical analyses and then gain robust results. oCEM and its applications, along with example data, were freely provided at https://github.com/huynguyen250896/oCEM.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-08072-5.

The potential of using blood circular RNA as liquid biopsy biomarker for human diseases

Circular RNA (circRNA) is a novel class of single-stranded RNAs with a closed loop structure. The majority of circRNAs are formed by a back-splicing process in pre-mRNA splicing. Their expression is dynamically regulated and shows spatiotemporal patterns among cell types, tissues and developmental stages. CircRNAs have important biological functions in many physiological processes, and their aberrant expression is implicated in many human diseases. Due to their high stability, circRNAs are becoming promising biomarkers in many human diseases, such as cardiovascular diseases, autoimmune diseases and human cancers. In this review, we focus on the translational potential of using human blood circRNAs as liquid biopsy biomarkers for human diseases. We highlight their abundant expression, essential biological functions and significant correlations to human diseases in various components of peripheral blood, including whole blood, blood cells and extracellular vesicles. In addition, we summarize the current knowledge of blood circRNA biomarkers for disease diagnosis or prognosis.

The network interplay of interferon and Toll-like receptor signaling pathways in the anti-Candida immune response

Fungal infections represent a major global health problem affecting over a billion people that kills more than 1.5 million annually. In this study, we employed an integrative approach to reveal the landscape of the human immune responses to Candida spp. through meta-analysis of microarray, bulk, and single-cell RNA sequencing (scRNA-seq) data for the blood transcriptome. We identified across these different studies a consistent interconnected network interplay of signaling molecules involved in both Toll-like receptor (TLR) and interferon (IFN) signaling cascades that is activated in response to different Candida species (C. albicans, C. auris, C. glabrata, C. parapsilosis, and C. tropicalis). Among these molecules are several types I IFN, indicating an overlap with antiviral immune responses. scRNA-seq data confirmed that genes commonly identified by the three transcriptomic methods show cell type-specific expression patterns in various innate and adaptive immune cells. These findings shed new light on the anti-Candida immune response, providing putative molecular pathways for therapeutic intervention.

Dramatic transcriptomic differences in Macaca mulatta and Macaca fascicularis with Plasmodium knowlesi infections

Plasmodium knowlesi, a model malaria parasite, is responsible for a significant portion of zoonotic malaria cases in Southeast Asia and must be controlled to avoid disease severity and fatalities. However, little is known about the host-parasite interactions and molecular mechanisms in play during the course of P. knowlesi malaria infections, which also may be relevant across Plasmodium species. Here we contrast P. knowlesi sporozoite-initiated infections in Macaca mulatta and Macaca fascicularis using whole blood RNA-sequencing and transcriptomic analysis. These macaque hosts are evolutionarily close, yet malaria-naïve M. mulatta will succumb to blood-stage infection without treatment, whereas malaria-naïve M. fascicularis controls parasitemia without treatment. This comparative analysis reveals transcriptomic differences as early as the liver phase of infection, in the form of signaling pathways that are activated in M. fascicularis, but not M. mulatta. Additionally, while most immune responses are initially similar during the acute stage of the blood infection, significant differences arise subsequently. The observed differences point to prolonged inflammation and anti-inflammatory effects of IL10 in M. mulatta, while M. fascicularis undergoes a transcriptional makeover towards cell proliferation, consistent with its recovery. Together, these findings suggest that timely detection of P. knowlesi in M. fascicularis, coupled with control of inflammation while initiating the replenishment of key cell populations, helps contain the infection. Overall, this study points to specific genes and pathways that could be investigated as a basis for new drug targets that support recovery from acute malaria.

Condition-Specific Molecular Network Analysis Revealed That Flagellar Proteins Are Involved in Electron Transfer Processes of Shewanella piezotolerans WP3

Because of the ability to metabolize a large number of electron acceptors such as nitrate, nitrite, fumarate, and metal oxides, Shewanella species have attracted much attention in recent years. Generally, the use of these electron acceptors is mainly achieved through electron transfer proteins and their interactions which will dynamically change across different environmental conditions in cells. Therefore, functional analysis of condition-specific molecular networks can reveal biological information on electron transfer processes. By integrating expression data and molecular networks, we constructed condition-specific molecular networks for Shewanella piezotolerans WP3. We then identified condition-specific key genes and studied their potential functions with an emphasis on their roles in electron transfer processes. Functional module analysis showed that different flagellar assembly modules appeared under these conditions and suggested that flagellar proteins are important for these conditions. We also identified the electron transfer modules underlying these various environmental conditions. The present results could help with screening electron transfer genes and understanding electron transfer processes under various environmental conditions for the Shewanella species.

Immunophenotyping assessment in a COVID-19 cohort (IMPACC): A prospective longitudinal study

The Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective longitudinal study designed to enroll 1000 hospitalized patients with COVID-19 (NCT04378777). IMPACC collects detailed clinical, laboratory, and radiographic data along with longitudinal biologic sampling of blood and respiratory secretions for in-depth testing. Clinical and laboratory data are integrated to identify immunologic, virologic, proteomic, metabolomic, and genomic features of COVID-19–related susceptibility, severity, and disease progression. The goals of IMPACC are to better understand the contributions of pathogen dynamics and host immune responses to the severity and course of COVID-19 and to generate hypotheses for identification of biomarkers and effective therapeutics, including optimal timing of such interventions. In this report, we summarize the IMPACC study design and protocols including clinical criteria and recruitment, multisite standardized sample collection and processing, virologic and immunologic assays, harmonization of assay protocols, high-level analyses, and the data sharing plans.

Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data

As the capacity for generating large-scale molecular profiling data continues to grow, the ability to extract meaningful biological knowledge from it remains a limitation. Here, we describe the development of a new fixed repertoire of transcriptional modules, BloodGen3, that is designed to serve as a stable reusable framework for the analysis and interpretation of blood transcriptome data. The construction of this repertoire is based on co-clustering patterns observed across sixteen immunological and physiological states encompassing 985 blood transcriptome profiles. Interpretation is supported by customized resources, including module-level analysis workflows, fingerprint grid plot visualizations, interactive web applications and an extensive annotation framework comprising functional profiling reports and reference transcriptional profiles. Taken together, this well-characterized and well-supported transcriptional module repertoire can be employed for the interpretation and benchmarking of blood transcriptome profiles within and across patient cohorts. Blood transcriptome fingerprints for the 16 reference cohorts can be accessed interactively via:  https://drinchai.shinyapps.io/BloodGen3Module/ .

Early changes in interferon gene expression and antibody responses following influenza vaccination in pregnant women

BACKGROUND

Influenza immunization during pregnancy provides protection to the mother and the infant. Studies in adults and children with inactivated influenza vaccine (IIV) have identified changes in immune gene expression that correlated with antibody responses.

OBJECTIVE

To define baseline blood transcriptional profiles and changes induced by IIV in pregnant women and to identify correlates with antibody responses.

METHODS

Pregnant women were immunized with IIV during the 2013-14 and 2014-15 seasons. Blood samples were collected on day (d) 0 (pre-vaccination), d1 and d7 post-vaccination for transcriptional profile analyses; and d0, d30, delivery and cord blood to measure antibody titers.

RESULTS

Transcriptional analysis demonstrated overexpression of interferon-stimulated genes (ISGs) on d1 and of plasma cell genes on d7. Pre-vaccination ISGs expression and ISGs over-expressed on d1 significantly correlated with increased H3N2, B Yamagata and B Victoria antibody titers. Plasma-cell gene expression on d7 correlated with increased B Yamagata and B Victoria antibody titers. Compared with women vaccinated during the previous influenza season, women who were not vaccinated the prior year showed more frequent significant correlations between ISGs and antibody titers.

CONCLUSIONS

Influenza vaccination in pregnant women resulted in enhanced expression of ISGs and plasma cell genes that correlated with antibody responses.

Immune profiles provide insights into respiratory syncytial virus disease severity in young children

Respiratory syncytial virus (RSV) is associated with major morbidity in infants, although most cases result in mild disease. The pathogenesis of the disease is incompletely understood, especially the determining factors of disease severity. A better characterization of these factors may help with development of RSV vaccines and antivirals. Hence, identification of a "safe and protective" immunoprofile induced by natural RSV infection could be used as a as a surrogate of ideal vaccine-elicited responses in future clinical trials. In this study, we integrated blood transcriptional and cell immune profiling, RSV loads, and clinical data to identify factors associated with a mild disease phenotype in a cohort of 190 children <2 years of age. Children with mild disease (outpatients) showed higher RSV loads, greater induction of interferon (IFN) and plasma cell genes, and decreased expression of inflammation and neutrophil genes versus children with severe disease (inpatients). Additionally, only infants with severe disease had increased numbers of HLA-DR^low monocytes, not present in outpatients. Multivariable analyses confirmed that IFN overexpression was associated with decreased odds of hospitalization, whereas increased numbers of HLA-DR^low monocytes were associated with increased risk of hospitalization. These findings suggest that robust innate immune responses are associated with mild RSV infection in infants.

Reference Transcriptomes of Porcine Peripheral Immune Cells Created Through Bulk and Single-Cell RNA Sequencing

Pigs are a valuable human biomedical model and an important protein source supporting global food security. The transcriptomes of peripheral blood immune cells in pigs were defined at the bulk cell-type and single cell levels. First, eight cell types were isolated in bulk from peripheral blood mononuclear cells (PBMCs) by cell sorting, representing Myeloid, NK cells and specific populations of T and B-cells. Transcriptomes for each bulk population of cells were generated by RNA-seq with 10,974 expressed genes detected. Pairwise comparisons between cell types revealed specific expression, while enrichment analysis identified 1,885 to 3,591 significantly enriched genes across all 8 cell types. Gene Ontology analysis for the top 25% of significantly enriched genes (SEG) showed high enrichment of biological processes related to the nature of each cell type. Comparison of gene expression indicated highly significant correlations between pig cells and corresponding human PBMC bulk RNA-seq data available in Haemopedia. Second, higher resolution of distinct cell populations was obtained by single-cell RNA-sequencing (scRNA-seq) of PBMC. Seven PBMC samples were partitioned and sequenced that produced 28,810 single cell transcriptomes distributed across 36 clusters and classified into 13 general cell types including plasmacytoid dendritic cells (DC), conventional DCs, monocytes, B-cell, conventional CD4 and CD8 αβ T-cells, NK cells, and γδ T-cells. Signature gene sets from the human Haemopedia data were assessed for relative enrichment in genes expressed in pig cells and integration of pig scRNA-seq with a public human scRNA-seq dataset provided further validation for similarity between human and pig data. The sorted porcine bulk RNAseq dataset informed classification of scRNA-seq PBMC populations; specifically, an integration of the datasets showed that the pig bulk RNAseq data helped define the CD4CD8 double-positive T-cell populations in the scRNA-seq data. Overall, the data provides deep and well-validated transcriptomic data from sorted PBMC populations and the first single-cell transcriptomic data for porcine PBMCs. This resource will be invaluable for annotation of pig genes controlling immunogenetic traits as part of the porcine Functional Annotation of Animal Genomes (FAANG) project, as well as further study of, and development of new reagents for, porcine immunology.

Transfer transcriptomic signatures for infectious diseases

Human responses to infection include transcriptional changes shared across diverse pathogens. To capture these common patterns, we establish the concept of, and the method for, the identification of “transfer signatures”: sets of genes defining human immunophenotypes. We demonstrate the usefulness of transfer signatures in two use cases: the progression of latent to active tuberculosis and the severity of viral respiratory infections.

The modulation of the transcriptome is among the earliest responses to infection. However, defining the transcriptomic signatures of disease is challenging because logistic, technical, and cost factors limit the size and representativeness of samples in clinical studies. These limitations lead to a poor performance of signatures when applied to new datasets. Although the study focuses on infection, the central hypothesis of the work is the generalization of sets of signatures across diseases. We use a machine learning approach to identify common elements in datasets and then test empirically whether they are informative about a second dataset from a disease or process distinct from the original dataset. We identify sets of genes, which we name transfer signatures, that are predictive across diverse datasets and/or species (e.g., rhesus to humans). We demonstrate the usefulness of transfer signatures in two use cases: the progression of latent to active tuberculosis and the severity of COVID-19 and influenza A H1N1 infection. This indicates that transfer signatures can be deployed in settings that lack disease-specific biomarkers. The broad significance of our work lies in the concept that a small set of archetypal human immunophenotypes, captured by transfer signatures, can explain a larger set of responses to diverse diseases.

Integrated transcriptional-phenotypic analysis captures systemic immunomodulation following antiangiogenic therapy in renal cell carcinoma patients

BACKGROUND

The combination of immune checkpoint blockade (ICB) with standard therapies is becoming a common approach for overcoming resistance to cancer immunotherapy in most human malignancies including metastatic renal cell carcinoma (mRCC). In this regard, insights into the immunomodulatory properties of antiangiogenic agents may help designing multidrug schedules based on specific immune synergisms.

METHODS

We used orthogonal transcriptomic and phenotyping platforms combined with functional analytic pipelines to elucidate the immunomodulatory effect of the antiangiogenic agent pazopanib in mRCC patients. Nine patients were studied longitudinally over a period of 6 months. We also analyzed transcriptional data from The Cancer Genome Atlas (TCGA) RCC cohort (N = 571) to assess the prognostic implications of our findings. The effect of pazopanib was assessed in vitro on NK cells and T cells. Additionally, myeloid-derived suppressor (MDSC)-like cells were generated from CD14+ monocytes transfected with mimics of miRNAs associated with MDSC function in the presence or absence of pazopanib.

RESULTS

Pazopanib administration caused a rapid and dramatic reshaping in terms of frequency and transcriptional activity of multiple blood immune cell subsets, with a downsizing of MDSC and regulatory T cells in favor of a strong enhancement in PD-1 expressing cytotoxic T and Natural Killer effectors. These changes were paired with an increase of the expression of transcripts reflecting activation of immune-effector functions. This immunomodulation was marked but transient, peaking at the third month of treatment. Moreover, the intratumoral expression level of a MDSC signature (MDSC INT) was strongly associated with poor prognosis in RCC patients. In vitro experiments indicate that the observed immunomodulation might be due to an inhibitory effect on MDSC-mediated suppression, rather than a direct effect on NK and T cells.

CONCLUSIONS

The marked but transient nature of this immunomodulation, peaking at the third month of treatment, provides the rationale for the use of antiangiogenics as a preconditioning strategy to improve the efficacy of ICB.

RAMRSGL: A Robust Adaptive Multinomial Regression Model for Multicancer Classification

In view of the challenges of the group Lasso penalty methods for multicancer microarray data analysis, e.g., dividing genes into groups in advance and biological interpretability, we propose a robust adaptive multinomial regression with sparse group Lasso penalty (RAMRSGL) model. By adopting the overlapping clustering strategy, affinity propagation clustering is employed to obtain each cancer gene subtype, which explores the group structure of each cancer subtype and merges the groups of all subtypes. In addition, the data-driven weights based on noise are added to the sparse group Lasso penalty, combining with the multinomial log-likelihood function to perform multiclassification and adaptive group gene selection simultaneously. The experimental results on acute leukemia data verify the effectiveness of the proposed method.

Immunomodulatory Effects of Vitamin D Supplementation in a Deficient Population

In addition to its canonical functions, vitamin D has been proposed to be an important mediator of the immune system. Despite ample sunshine, vitamin D deficiency is prevalent (>80%) in the Middle East, resulting in a high rate of supplementation. However, the underlying molecular mechanisms of the specific regimen prescribed and the potential factors affecting an individual's response to vitamin D supplementation are not well characterized. Our objective is to describe the changes in the blood transcriptome and explore the potential mechanisms associated with vitamin D3 supplementation in one hundred vitamin D-deficient women who were given a weekly oral dose (50,000 IU) of vitamin D3 for three months. A high-throughput targeted PCR, composed of 264 genes representing the important blood transcriptomic fingerprints of health and disease states, was performed on pre and post-supplementation blood samples to profile the molecular response to vitamin D3. We identified 54 differentially expressed genes that were strongly modulated by vitamin D3 supplementation. Network analyses showed significant changes in the immune-related pathways such as TLR4/CD14 and IFN receptors, and catabolic processes related to NF-kB, which were subsequently confirmed by gene ontology enrichment analyses. We proposed a model for vitamin D3 response based on the expression changes of molecules involved in the receptor-mediated intra-cellular signaling pathways and the ensuing predicted effects on cytokine production. Overall, vitamin D3 has a strong effect on the immune system, G-coupled protein receptor signaling, and the ubiquitin system. We highlighted the major molecular changes and biological processes induced by vitamin D3, which will help to further investigate the effectiveness of vitamin D3 supplementation among individuals in the Middle East as well as other regions.

Rapid Multicomponent Bioluminescence Imaging via Substrate Unmixing

Studies of biological function demand probes that can report on processes in real time and in physiological environments. Bioluminescent tools are uniquely suited for this purpose, as they enable sensitive imaging in cells and tissues. Bioluminescent reporters can also be monitored continuously over time without detriment, as excitation light is not required. Rather, light emission derives from luciferase-luciferin reactions. Several engineered luciferases and luciferins have expanded the scope of bioluminescence imaging in recent years. Multicomponent tracking remains challenging, though, due to a lack of streamlined methods to visualize combinations of bioluminescent reporters. Conventional approaches image one luciferase at a time. Consequently, short-term changes in cell growth or gene expression cannot be easily captured. Here, we report a strategy for rapid, multiplexed imaging with a wide range of luciferases and luciferins. Sequential addition of orthogonal luciferins, followed by substrate unmixing, enabled facile detection of multiple luciferases in vitro and in vivo. Multicomponent imaging in mice was also achieved on the minutes-to-hours time scale.

ModularBoost: an efficient network inference algorithm based on module decomposition

Background

Given expression data, gene regulatory network(GRN) inference approaches try to determine regulatory relations. However, current inference methods ignore the inherent topological characters of GRN to some extent, leading to structures that lack clear biological explanation. To increase the biophysical meanings of inferred networks, this study performed data-driven module detection before network inference. Gene modules were identified by decomposition-based methods.

Results

ICA-decomposition based module detection methods have been used to detect functional modules directly from transcriptomic data. Experiments about time-series expression, curated and scRNA-seq datasets suggested that the advantages of the proposed ModularBoost method over established methods, especially in the efficiency and accuracy. For scRNA-seq datasets, the ModularBoost method outperformed other candidate inference algorithms.

Conclusions

As a complicated task, GRN inference can be decomposed into several tasks of reduced complexity. Using identified gene modules as topological constraints, the initial inference problem can be accomplished by inferring intra-modular and inter-modular interactions respectively. Experimental outcomes suggest that the proposed ModularBoost method can improve the accuracy and efficiency of inference algorithms by introducing topological constraints.

Single-cell transcriptomic analysis reveals key immune cell phenotypes in the lungs of patients with asthma exacerbation

BACKGROUND

Asthma exacerbations are associated with heightened asthma symptoms, which can result in hospitalization in severe cases. However, the molecular immunologic processes that determine the course of an exacerbation remain poorly understood, impeding the progression of development of effective therapies.

OBJECTIVE

Our aim was to identify candidate genes that are strongly associated with asthma exacerbation at a cellular level.

METHODS

Subjects with asthma exacerbation and healthy control subjects were recruited, and bronchoalveolar lavage fluid was isolated from these subjects via bronchoscopy. Cells were isolated through fluorescence-activated cell sorting, and single-cell RNA sequencing was performed on enriched cell populations.

RESULTS

We showed that the levels of monocytes, CD8+ T cells, and macrophages are significantly elevated in the bronchoalveolar lavage fluid of patients. A set of cytokines and intracellular transduction regulators are associated with asthma exacerbations and are shared across multiple cell clusters, forming a complicated molecular framework. An additional group of core exacerbation-associated modules is activated, including eukaryotic initiation factor 2 signaling, ephrin receptor signaling, and C-X-C chemokine receptor type 4 signaling in the subpopulations of CD8+ T cells (C1-a) and monocyte clusters (C7 clusters), which are associated with infection.

CONCLUSION

Our study identified a significant number of severe asthma-associated genes that are differentially expressed by multiple cell clusters.

BloodGen3Module: Blood transcriptional module repertoire analysis and visualization using R

Motivation

We previously described the construction and characterization of fixed reusable blood transcriptional module repertoires. More recently we released a third iteration (‘BloodGen3’ module repertoire) that comprises 382 functionally annotated modules and encompasses 14 168 transcripts. Custom bioinformatic tools are needed to support downstream analysis, visualization and interpretation relying on such fixed module repertoires.

Results

We have developed and describe here an R package, BloodGen3Module. The functions of our package permit group comparison analyses to be performed at the module-level, and to display the results as annotated fingerprint grid plots. A parallel workflow for computing module repertoire changes for individual samples rather than groups of samples is also available; these results are displayed as fingerprint heatmaps. An illustrative case is used to demonstrate the steps involved in generating blood transcriptome repertoire fingerprints of septic patients. Taken together, this resource could facilitate the analysis and interpretation of changes in blood transcript abundance observed across a wide range of pathological and physiological states.

Availability and implementation

The BloodGen3Module package and documentation are freely available from Github: https://github.com/Drinchai/BloodGen3Module.

Supplementary information

Supplementary data are available at Bioinformatics online.

Emerging dynamics pathways of response and resistance to PD-1 and CTLA-4 blockade: tackling uncertainty by confronting complexity

Immune checkpoint inhibitors provide considerable therapeutic benefit in a range of solid cancers as well as in a subgroup of hematological malignancies. Response rates are however suboptimal, and despite considerable efforts, predicting response to immune checkpoint inhibitors ahead of their administration in a given patient remains elusive. The study of the dynamics of the immune system and of the tumor under immune checkpoint blockade brought insight into the mechanisms of action of these therapeutic agents. Equally relevant are the mechanisms of adaptive resistance to immune checkpoint inhibitors that have been uncovered through this approach. In this review, we discuss the dynamics of the immune system and of the tumor under immune checkpoint blockade emanating from recent studies on animal models and humans. We will focus on mechanisms of action and of resistance conveying information predictive of therapeutic response.

Navigating the murky waters of maternal fetal tolerance: Put big data at the helm

The last 20 years have seen significant progress in our understanding of the maternal T cell response to the fetus. However, major questions still remain. In this review, we discuss the contribution of Big Data approaches to our evolving understanding of maternal fetal tolerance. This includes investigations which have employed systems immunology, high dimensional mass spectrometry, whole genome transcriptomics, as well as single-cell RNA-sequencing. These studies reveal "new" mechanisms of T cell dysfunction that are conserved across immune responses and highlight the breadth and magnitude of the systemic maternal response to the fetus during pregnancy.

Proceedings From the First International Workshop at Sidra Medicine: "Engineered Immune Cells in Cancer Immunotherapy (EICCI): From Discovery to Off-the-Shelf Development", 15th-16th February 2019, Doha, Qatar

The progress in the isolation and characterization of tumor antigen (TA)-specific T lymphocytes and in the genetic modification of immune cells allowed the clinical development of adoptive cell therapy (ACT). Several clinical studies highlighted the striking clinical activity of T cells engineered to express either Chimeric Antigen (CAR) or T Cell (TCR) Receptors to target molecularly defined antigens expressed on tumor cells. The breakthrough of immunotherapy is represented by the approval of CAR-T cells specific for advanced or refractory CD19⁺ B cell malignancies by both the Food and Drug Administration (FDA) and the European Medicinal Agency (EMA). Moreover, advances in the manufacturing and gene editing of engineered immune cells contributed to the selection of drug products with desired phenotype, refined specificity and decreased toxicity. An important step toward the optimization of CAR-T cell therapy is the development of "off-the shelf" T cell products that allow to reduce the complexity and the costs of the manufacturing and to render these drugs available for a broad number of cancer patients. The Engineered Immune Cells in Cancer Immunotherapy (EICCI) workshop hosted in Doha, Qatar, renowned experts, from both academia and industry, to present and discuss the progress on both pre-clinical and clinical development of genetically modified immune cells, including advances in the "off-the-shelf" manufacturing. These experts have addressed also organizational needs and hurdles for the clinical grade production and application of these biological drugs.

Definition of erythroid cell-positive blood transcriptome phenotypes associated with severe respiratory syncytial virus infection

Biomarkers to assess the risk of developing severe respiratory syncytial virus (RSV) infection are needed. We conducted a meta-analysis of 490 unique profiles from six public RSV blood transcriptome datasets. A repertoire of 382 well-characterized transcriptional modules was used to define dominant host responses to RSV infection. The consolidated RSV cohort was stratified according to four traits: "interferon response" (IFN), "neutrophil-driven inflammation" (Infl), "cell cycle" (CC), and "erythrocytes" (Ery). We identified eight prevalent blood transcriptome phenotypes, of which three Ery+ phenotypes comprised higher proportions of patients requiring intensive care. This finding confirms on a larger scale data from one of our earlier reports describing an association between an erythrocyte signature and RSV disease severity. Further contextual interpretation made it possible to associate this signature with immunosuppressive states (late stage cancer, pharmacological immunosuppression), and with a population of fetal glycophorin A+ erythroid precursors. Furthermore, we posit that this erythrocyte cell signature may be linked to a population of immunosuppressive erythroid cells previously described in the literature, and that overabundance of this cell population in RSV patients may underlie progression to severe disease. These findings outline potential priority areas for biomarker development and investigations into the immune biology of RSV infection. The approach that we developed and employed here should also permit to delineate prevalent blood transcriptome phenotypes in other settings.