IL4I1 Accelerates the Expansion of Effector CD8+ T Cells at the Expense of Memory Precursors by Increasing the Threshold of T-Cell Activation

Immunometabolism: signaling pathways, homeostasis, and therapeutic targets

Immunometabolism plays a central role in sustaining immune system functionality and preserving physiological homeostasis within the organism. During the differentiation and activation, immune cells undergo metabolic reprogramming mediated by complex signaling pathways. Immune cells maintain homeostasis and are influenced by metabolic microenvironmental cues. A series of immunometabolic enzymes modulate immune cell function by metabolizing nutrients and accumulating metabolic products. These enzymes reverse immune cells' differentiation, disrupt intracellular signaling pathways, and regulate immune responses, thereby influencing disease progression. The huge population of immune metabolic enzymes, the ubiquity, and the complexity of metabolic regulation have kept the immune metabolic mechanisms related to many diseases from being discovered, and what has been revealed so far is only the tip of the iceberg. This review comprehensively summarized the immune metabolic enzymes' role in multiple immune cells such as T cells, macrophages, natural killer cells, and dendritic cells. By classifying and dissecting the immunometabolism mechanisms and the implications in diseases, summarizing and analyzing advancements in research and clinical applications of the inhibitors targeting these enzymes, this review is intended to provide a new perspective concerning immune metabolic enzymes for understanding the immune system, and offer novel insight into future therapeutic interventions.

IL-4-Induced Gene 1: A Potential Player in Myocardial Infarction

Myocardial infarction (MI), a severe outcome of cardiovascular disease, poses a serious threat to human health. Uncontrolled inflammation and excessive cardiomyocyte death, following an infarction event, significantly contribute to both the mortality rate and complications associated with MI. The protein IL-4-induced gene 1 (IL4I1 or FIG1) serves as a natural inhibitor of innate and adaptive immunity, playing a crucial role in CD4+ T cell differentiation, macrophage polarization, and ferroptosis inhibition. Previous studies have linked IL4I1 to acute MI. This review summarizes evidence from both basic and clinical research, highlighting IL4I1 as a critical immunoregulatory enzyme that not only regulates inflammatory responses, but also potentially mitigates MI-induced damage.

Targeting amino acid-metabolizing enzymes for cancer immunotherapy

Despite the immune system's role in the detection and eradication of abnormal cells, cancer cells often evade elimination by exploitation of various immune escape mechanisms. Among these mechanisms is the ability of cancer cells to upregulate amino acid-metabolizing enzymes, or to induce these enzymes in tumor-infiltrating immunosuppressive cells. Amino acids are fundamental cellular nutrients required for a variety of physiological processes, and their inadequacy can severely impact immune cell function. Amino acid-derived metabolites can additionally dampen the anti-tumor immune response by means of their immunosuppressive activities, whilst some can also promote tumor growth directly. Based on their evident role in tumor immune escape, the amino acid-metabolizing enzymes glutaminase 1 (GLS1), arginase 1 (ARG1), inducible nitric oxide synthase (iNOS), indoleamine 2,3-dioxygenase 1 (IDO1), tryptophan 2,3-dioxygenase (TDO) and interleukin 4 induced 1 (IL4I1) each serve as a promising target for immunotherapeutic intervention. This review summarizes and discusses the involvement of these enzymes in cancer, their effect on the anti-tumor immune response and the recent progress made in the preclinical and clinical evaluation of inhibitors targeting these enzymes.

Pan-cancer analysis of prognostic and immunological role of IL4I1 in human tumors: a bulk omics research and single cell sequencing validation

BACKGROUND

Interleukin-4 inducible gene 1 (IL4I1) regulates tumor progression in numerous tumor types. However, its correlation with immune infiltration and prognosis of patients in a pan-cancer setting remains unclear.

METHODS

Data from the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), UALCAN, Clinical Proteomic Tumor Analysis Consortium (CPTAC), Gene Expression Omnibus (GEO), cBioPortal, Cancer Single-cell State Atlas (CancerSEA), and Tumor IMmune Estimation Resource(TIMER) databases were used to evaluate IL4I1 expression, clinical features and prognostic effects, gene set enrichment, and correlation with immune cell infiltration, as well as the relationship between IL4I1 methylation and expression and survival prognosis. Correlations with 192 anticancer drugs were also analyzed.

RESULTS

IL4I1 was significantly overexpressed in the majority of tumors, and the imbalance of IL4I1 was significantly correlated with overall survival and pathological stage. Moreover, total IL4I1 protein was increased in cancer. Therefore, IL4I1 may be used as a prognostic biomarker or protective factor in numerous types of cancer. The methylation level of IL4I1 may also be used as a prognostic marker. The functional enrichment of IL4I1 was closely related to the immunomodulatory pathway. In addition, the level of tumor-associated macrophage infiltration was positively correlated with the expression of IL4I1 in pan-cancerous tissues. scRNA-seq analysis suggested that IL4I1 differ significantly among different cells in the tumor microenvironment and was most enriched in macrophages. Various immune checkpoint genes were positively correlated with IL4I1 expression in most tumors. In addition, patients with high IL4I1 expression may be resistant to BMS-754807 and docetaxel, but sensitive to temozolomide.

CONCLUSION

IL4I1 may play a role as promoter of cancer and prognostic indicator in patients. High expression of IL4I1 is associated with the state of tumor immunosuppression and may contribute to tumor-associated macrophage invasion. Therefore, IL4I1 may be a new therapeutic target for the treatment and prognosis of patients with cancer.

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

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

IL4I1-catalyzed tryptophan metabolites mediate the anti-inflammatory function of cytokine-primed human muscle stem cells

Muscle stem cells (MuSCs) have been demonstrated to exert impressive therapeutic efficacy in disease settings through orchestrating inflammatory microenvironments. Nevertheless, the mechanisms underlying the immunoregulatory property of MuSCs remain largely uncharacterized. Here, we showed that interleukin-4-induced-1 (IL4I1), an essential enzyme that catalyzes indole metabolism in humans, was highly expressed in human MuSCs exposed to IFN-γ and TNF-α. Functionally, the MuSCs were found to inhibit the infiltration of neutrophils into sites of inflammation in a IL4I1-dependent manner and thus ameliorate acute lung injury in mice. Mechanistically, the indole metabolites, including indole-3-pyruvic acid (I3P) and indole-3-aldehyde (I3A), produced by IL4I1, acted as ligands to activate aryl hydrocarbon receptor (AHR), leading to augmented expression of TNF-stimulated gene 6 (TSG-6) in inflammatory cytokine-primed MuSCs. Furthermore, I3P administration alone suppressed neutrophil infiltration into damaged lungs. I3P could also reduce the level of reactive oxygen species in neutrophils. Therefore, our study has uncovered a novel mechanism by which MuSCs acquire their immunoregulatory property and may help to develop or optimize MuSC-based therapies for inflammatory diseases.

Group A Streptococcus induces CD1a-autoreactive T cells and promotes psoriatic inflammation

Group A Streptococcus (GAS) infection is associated with multiple clinical sequelae, including different subtypes of psoriasis. Such post-streptococcal disorders have been long known but are largely unexplained. CD1a is expressed at constitutively high levels by Langerhans cells and presents lipid antigens to T cells, but the potential relevance to GAS infection has not been studied. Here, we investigated whether GAS-responsive CD1a-restricted T cells contribute to the pathogenesis of psoriasis. Healthy individuals had high frequencies of circulating and cutaneous GAS-responsive CD4+ and CD8+ T cells with rapid effector functions, including the production of interleukin-22 (IL-22). Human skin and blood single-cell CITE-seq analyses of IL-22-producing T cells showed a type 17 signature with proliferative potential, whereas IFN-γ-producing T cells displayed cytotoxic T lymphocyte characteristics. Furthermore, individuals with psoriasis had significantly higher frequencies of circulating GAS-reactive T cells, enriched for markers of activation, cytolytic potential, and tissue association. In addition to responding to GAS, subsets of expanded GAS-reactive T cell clones/lines were found to be autoreactive, which included the recognition of the self-lipid antigen lysophosphatidylcholine. CD8+ T cell clones/lines produced cytolytic mediators and lysed infected CD1a-expressing cells. Furthermore, we established cutaneous models of GAS infection in a humanized CD1a transgenic mouse model and identified enhanced and prolonged local and systemic inflammation, with resolution through a psoriasis-like phenotype. Together, these findings link GAS infection to the CD1a pathway and show that GAS infection promotes the proliferation and activation of CD1a-autoreactive T cells, with relevance to post-streptococcal disease, including the pathogenesis and treatment of psoriasis.

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

The advent of single-cell multi-omics sequencing technology makes it possible for re-searchers to leverage multiple modalities for individual cells and explore cell heterogeneity. However, the high dimensional, discrete, and sparse nature of the data make the downstream analysis particularly challenging. Most of the existing computational methods for single-cell data analysis are either limited to single modality or lack flexibility and interpretability. In this study, we propose an interpretable deep learning method called multi-omic embedded topic model (moETM) to effectively perform integrative analysis of high-dimensional single-cell multimodal data. moETM integrates multiple omics data via a product-of-experts in the encoder for efficient variational inference and then employs multiple linear decoders to learn the multi-omic signatures of the gene regulatory programs. Through comprehensive experiments on public single-cell transcriptome and chromatin accessibility data (i.e., scRNA+scATAC), as well as scRNA and proteomic data (i.e., CITE-seq), moETM demonstrates superior performance compared with six state-of-the-art single-cell data analysis methods on seven publicly available datasets. By applying moETM to the scRNA+scATAC data in human bone marrow mononuclear cells (BMMCs), we identified sequence motifs corresponding to the transcription factors that regulate immune gene signatures. Applying moETM analysis to CITE-seq data from the COVID-19 patients revealed not only known immune cell-type-specific signatures but also composite multi-omic biomarkers of critical conditions due to COVID-19, thus providing insights from both biological and clinical perspectives.

The single cell transcriptional landscape of esophageal adenocarcinoma and its modulation by neoadjuvant chemotherapy

Immune checkpoint blockade has recently proven effective in subsets of patients with esophageal adenocarcinoma (EAC) but little is known regarding the EAC immune microenvironment. We determined the single cell transcriptional profile of EAC in 8 patients who were treatment-naive (n = 4) or had received neoadjuvant chemotherapy (n = 4). Analysis of 52,387 cells revealed 10 major cell subsets of tumor, immune and stromal cells. Prior to chemotherapy tumors were heavy infiltrated by T regulatory cells and exhausted effector T cells whilst plasmacytoid dendritic cells were markedly expanded. Two dominant cancer-associated fibroblast populations were also observed whilst endothelial populations were suppressed. Pathological remission following chemotherapy associated with broad reversal of immune abnormalities together with fibroblast transition and an increase in endothelial cells whilst a chemoresistant epithelial stem cell population correlated with poor response. These findings reveal features that underlie and limit the response to current immunotherapy and identify a range of novel opportunities for targeted therapy.

Single-cell analysis revealed that IL4I1 promoted ovarian cancer progression

Background

Ovarian cancer was one of the leading causes of female deaths. Patients with OC were essentially incurable and portends a poor prognosis, presumably because of profound genetic heterogeneity limiting reproducible prognostic classifications.

Methods

We comprehensively analyzed an ovarian cancer single-cell RNA sequencing dataset, GSE118828, and identified nine major cell types. Relationship between the clusters was explored with CellPhoneDB. A malignant epithelial cluster was confirmed using pseudotime analysis, CNV and GSVA. Furthermore, we constructed the prediction model (i.e., RiskScore) consisted of 10 prognosis-specific genes from 2397 malignant epithelial genes using the LASSO Cox regression algorithm based on public datasets. Then, the prognostic value of Riskscore was assessed with Kaplan–Meier survival analysis and time-dependent ROC curves. At last, a series of in-vitro assays were conducted to explore the roles of IL4I1, an important gene in Riskscore, in OC progression.

Results

We found that macrophages possessed the most interaction pairs with other clusters, and M2-like TAMs were the dominant type of macrophages. C0 was identified as the malignant epithelial cluster. Patients with a lower RiskScore had a greater OS (log-rank P < 0.01). In training set, the AUC of RiskScore was 0.666, 0.743 and 0.809 in 1-year, 3-year and 5-year survival, respectively. This was also validated in another two cohorts. Moreover, downregulation of IL4I1 inhibited OC cells proliferation, migration and invasion.

Conclusions

Our work provide novel insights into our understanding of the heterogeneity among OCs, and would help elucidate the biology of OC and provide clinical guidance in prognosis for OC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03123-7.

What role for AHR activation in IL4I1-mediated immunosuppression ?

The amino-acid catabolizing enzyme Interleukin-4 induced gene 1 (IL4I1) remains poorly characterized despite it is emerging as a pertinent therapeutic target for cancer. IL4I1 is secreted in the synaptic cleft by antigen-presenting cells. It inhibits TCR signaling, modulates naïve T cell differentiation and limits effector T cell proliferation. IL4I1 expression in tumors shapes the tumor microenvironment and impairs the antitumor cytotoxic T cell response, thereby facilitating cancer immune escape. Several mechanisms participate in these effects. Recent data suggest a role of new IL4I1 metabolites in activation of the aryl-hydrocarbon receptor (AHR). Here, we observe that expression of IL4I1 is poorly correlated with that of validated targets of AHR in human cancers. Moreover, dendritic cells do not upregulate AHR target genes in relation with IL4I1 expression in vivo. Finally, IL4I1 activity toward tryptophan leading to production of AHR-activating products is very low, and should be negligible when tryptophan-degrading enzymes of higher affinity compete for the substrate. We recently showed that IL4I1 expression by dendritic cells directly regulates immune synapse formation and modulates the repertoire and memory differentiation of responding CD8 T cells after viral infection. Thus, IL4I1 may restrain tumor control through regulating the priming of tumor-specific CD8 T cells, independently of AHR activation.

Control of T-Cell Activation and Signaling by Amino-Acid Catabolizing Enzymes

Amino acids are essential for protein synthesis, epigenetic modification through the methylation of histones, and the maintenance of a controlled balance of oxidoreduction via the production of glutathione and are precursors of certain neurotransmitters. T lymphocytes are particularly sensitive to fluctuations in amino acid levels. During evolution, the production of amino-acid catabolizing enzymes by mainly antigen-presenting cells has become a physiological mechanism to control T-cell activation and polarization. The action of these enzymes interferes with TCR and co-stimulation signaling, allowing tuning of the T-cell response. These capacities can be altered in certain pathological conditions, with relevant consequences for the development of disease.