Cytokine-receptor interactions as drug targets

Unveiling the molecular mechanisms of Dendrobium officinale polysaccharides on intestinal immunity: An integrated study of network pharmacology, molecular dynamics and in vivo experiments

Intestinal immunity plays a pivotal role in overall immunological defenses, constructing mechanisms against pathogens while maintaining balance with commensal microbial communities. Existing therapeutic interventions may lead to drug resistance and potential toxicity when immune capacity is compromised. Dendrobium officinale, a traditional Chinese medicine, contains components identified to bolster immunity. Employing network pharmacology strategies, this study identified constituents of Dendrobium officinale and their action targets in the TCMSP and Swiss Target Prediction databases, and compared them with intestinal immunity-related targets. Protein-protein interaction networks revealed the core targets of Dendrobium officinale polysaccharides, encompassing key pathways such as cell proliferation, inflammatory response, and immune reactions, particularly in association with the Toll-like receptor 4. Molecular docking and molecular dynamics simulation further confirmed the high affinity and stability between Dendrobium officinale polysaccharides and Toll-like receptor 4. In vivo experiments demonstrated that Dendrobium officinale polysaccharides modulates the expression of Toll-like receptor 4 and its downstream key proteins in the colonic mucosa of mice. Consequently, these findings suggest that Dendrobium officinale polysaccharides may serve as a potential modulator for intestinal immune functions, with its mechanism potentially related to the Toll-like receptor 4.

The JAK-STAT pathway: from structural biology to cytokine engineering

The Janus kinase-signal transducer and activator of transcription (JAK-STAT) pathway serves as a paradigm for signal transduction from the extracellular environment to the nucleus. It plays a pivotal role in physiological functions, such as hematopoiesis, immune balance, tissue homeostasis, and surveillance against tumors. Dysregulation of this pathway may lead to various disease conditions such as immune deficiencies, autoimmune diseases, hematologic disorders, and cancer. Due to its critical role in maintaining human health and involvement in disease, extensive studies have been conducted on this pathway, ranging from basic research to medical applications. Advances in the structural biology of this pathway have enabled us to gain insights into how the signaling cascade operates at the molecular level, laying the groundwork for therapeutic development targeting this pathway. Various strategies have been developed to restore its normal function, with promising therapeutic potential. Enhanced comprehension of these molecular mechanisms, combined with advances in protein engineering methodologies, has allowed us to engineer cytokines with tailored properties for targeted therapeutic applications, thereby enhancing their efficiency and safety. In this review, we outline the structural basis that governs key nodes in this pathway, offering a comprehensive overview of the signal transduction process. Furthermore, we explore recent advances in cytokine engineering for therapeutic development in this pathway.

Transcriptomic Analysis of Hub Genes Reveals Associated Inflammatory Pathways in Estrogen-Dependent Gynecological Diseases

Gynecological diseases are triggered by aberrant molecular pathways that alter gene expression, hormonal balance, and cellular signaling pathways, which may lead to long-term physiological consequences. This study was able to identify highly preserved modules and key hub genes that are mainly associated with gynecological diseases, represented by endometriosis (EM), ovarian cancer (OC), cervical cancer (CC), and endometrial cancer (EC), through the weighted gene co-expression network analysis (WGCNA) of microarray datasets sourced from the Gene Expression Omnibus (GEO) database. Five highly preserved modules were observed across the EM (GSE51981), OC (GSE63885), CC (GSE63514), and EC (GSE17025) datasets. The functional annotation and pathway enrichment analysis revealed that the highly preserved modules were heavily involved in several inflammatory pathways that are associated with transcription dysregulation, such as NF-kB signaling, JAK-STAT signaling, MAPK-ERK signaling, and mTOR signaling pathways. Furthermore, the results also include pathways that are relevant in gynecological disease prognosis through viral infections. Mutations in the ESR1 gene that encodes for ERα, which were shown to also affect signaling pathways involved in inflammation, further indicate its importance in gynecological disease prognosis. Potential drugs were screened through the Drug Repurposing Encyclopedia (DRE) based on the up-and downregulated hub genes, wherein a bacterial ribosomal subunit inhibitor and a benzodiazepine receptor agonist were the top candidates. Other drug candidates include a dihydrofolate reductase inhibitor, glucocorticoid receptor agonists, cholinergic receptor agonists, selective serotonin reuptake inhibitors, sterol demethylase inhibitors, a bacterial antifolate, and serotonin receptor antagonist drugs which have known anti-inflammatory effects, demonstrating that the gene network highlights specific inflammatory pathways as a therapeutic avenue in designing drug candidates for gynecological diseases.

Single-Cell RNA Sequencing Pro-angiogenic Macrophage Profiles Reveal Novel Prognostic Biomarkers and Therapeutic Targets for Osteosarcoma

Osteosarcoma (OS) is a malignant bone tumor that most commonly occurs in children and adolescents. OS patients have a poor prognosis, and 5-year survival rates have rarely improved significantly over the past few decades. OS prognosis may be related to the infiltration of tumor-associated macrophages (TAMs). However, the role of proangiogenic macrophages, a subtype of TAMs, in OS prognosis has not been reported. In this study, seven subtypes of TAMs were identified from single-cell RNA sequencing (scRNA-seq) data that we propose defining as proangiogenic TAMs (Angio-TAMs), interferon-primed TAMs (IFN-TAMs), inflammatory cytokine-enriched TAMs (Inflam-TAMs), immune regulatory TAMs (Reg-TAMs), lipid-associated TAMs (LA-TAMs), and resident-tissue macrophages like TAMs (RTM-TAMs) (containing two subcellular types). In the survival analysis of each macrophage subtype, it was found that patients with Angio-TAMs had the most significant difference in survival. Eight genes associated with Angio-TAMs were obtained by differential expression analysis, and these genes were built into a prognostic model using the LASSO algorithm. Clinical OS case samples were categorized into high-risk and low-risk subgroups using median risk scores. In comparison to the low-risk subgroup, the survival time of the high-risk subgroup was much shorter. Additional studies on immune cell infiltration and immune checkpoint molecule expression in the two risk subgroups were carried out. In immunotherapy response prediction, the Angio-TAM-associated gene risk signature was found to be negatively correlated with immune checkpoint responses. In addition, the associated enriched GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways were mainly involved in the malignant progression of tumors. As suggested by these findings, the Angio-TAM gene risk signature may be an underlying prognostic biomarker and novel therapeutic target for OS patients.Kindly check and confirm whether the ESM file is correctly identifiedWe have checked this file and confirmed that it can be correctly identified.

Anti-inflammatory and immunoregulatory effects of colistin sulphate on human PBMCs

In previous studies, CST has been identified as having an immunostimulatory effect on Caenorhabditis elegans and macrophage of rats. Here, we further investigated its immunomodulatory effects on human peripheral blood mononuclear cells (PBMCs). LPS-stimulated PBMCs inflammatory model was established. Flow cytometry was applied to measure phagocytosis of PBMCs. Cytokine mRNA and protein expression levels of LPS-stimulated PBMCs with or without CST were measured by qRT-PCR and ELISA. The transcriptomic profile of CST-treated PBMCs was investigated by RNA-sequencing. Gene Ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) were applied to find potential signalling pathways. PBMCs showed a significant increase in phagocytic activity at 6 h after being incubated with CST at the concentration of 10 μg/mL. In the presence of LPS, CST maintained and promoted the expression of TNF-α and chemokine CCL24. The content of pro-inflammatory cytokines, such as IL-1β, IL-6 and IFN-γ, which were released from LPS-stimulated PBMCs, was reduced by CST at 6 h. Anti-inflammatory cytokines, such as IL-4, IL-13 and TGF-β1, were significantly increased by CST at 24 h. A total of 277 differentially expressed immune-related genes (DEIRGs) were detected and cytokine-cytokine receptor interaction was highly enriched. CST presented obvious anti-inflammatory and immunoregulatory effects in LPS-induced PBMCs inflammatory model not only by improving the ability of PBMCs to clear pathogens but also by decreasing pro-inflammatory cytokines and increasing anti-inflammatory cytokines. And the mechanism may be related to cytokine-cytokine receptor interaction.

Matrix-Bound Hyaluronan Molecular Weight as a Regulator of Dendritic Cell Immune Potency

Hyaluronic acid (HA) is a glycosaminoglycan in the extracellular matrix with immunoregulatory properties depending on its molecular weight (MW). However, the impact of matrix-bound HA on dendritic cells (DCs) remains unclear due to varying distribution of HA MW under different physiological conditions. To investigate DCs in defined biosystems, 3D collagen matrices modified with HA of specific MW with similar microstructure and HA levels are used. It is found that HA MW influences cytokine binding to matrix, suggesting modulation of cytokine availability by the different HA MWs. These studies on DC immune potency reveal that low MW HA (8-15 kDa) enhances immature DC differentiation and antigen uptake, while medium (MMW-HA; 500-750 kDa) and high MW HA (HMW-HA; 1250-1500 kDa) increase cytokine secretion in mature DCs. The effect on DC phenotype and cytokine secretion by different MWs of HA is independent of CD44. However, blocking the CD44 receptor reveals its potential role in regulating acute inflammation through increased secretion of CCL2, CXCL8, and IL-6. Additionally, MMW- and HMW-HA matrices reduce migratory capacity of DCs, dependent on CD44. Overall, these findings provide insights into MW-dependent effects of matrix-bound HA on DCs, opening avenues for the design of DC-modulating materials to enhance DC-based therapy.

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their putative diagnostic and prognostic role

BACKGROUND

Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients.

METHODS

Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples.

RESULTS

By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints.

CONCLUSION

In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

Mucosal immunity and microbiota change in the rainbow trout (Oncorhynchus mykiss) gills after being challenged with infectious hematopoietic necrosis virus

Respiratory structures are crucial for vertebrate survival, as they serve not only to perform gas-exchange processes but also as entry points for opportunistic pathogens. Previous studies have demonstrated that fish contain gill mucosal-associated lymphoid tissue, and harbor a large number of commensal bacteria on their surface and contribute to maintaining fish health. However, by far, very limited information is known regarding the effects of viral infection on gill mucosal immunity and microbiota homeostasis. In this study, we conducted an infection model by bath with infectious hematopoietic necrosis virus (IHNV) and revealed a 27 % mortality rate among rainbow trout in the first two weeks after infection. Moreover, we found that diseased fish with the highest IHNV loads in gills exhibiting severe damage, as well as increased goblet cell counts in both primary lamellae (PL) and secondary lamellae (SL). Additionally, RT-qPCR and RNA-seq analyses revealed that IHNV infection induced a strong innate and adaptive antiviral immune responses. Interestingly, an antibacterial immune response was also observed, suggesting that a secondary bacterial infection occurred in trout gills after viral infection. Furthermore, 16S rRNA analysis of trout gills revealed a profound dysbiosis marked by a loss of beneficial taxa and expansion of pathobionts following IHNV infection. Overall, our finding demonstrates that IHNV infection induces significant changes of the microbial community in the fish respiratory surface, thus triggering local antiviral and bacterial mucosal immunity.

Characterisation of IL-23 receptor antagonists and disease relevant mutants using fluorescent probes

Association of single nucleotide polymorphisms in the IL-23 receptor with several auto-inflammatory diseases, led to the heterodimeric receptor and its cytokine-ligand IL-23, becoming important drug targets. Successful antibody-based therapies directed against the cytokine have been licenced and a class of small peptide antagonists of the receptor have entered clinical trials. These peptide antagonists may offer therapeutic advantages over existing anti-IL-23 therapies, but little is known about their molecular pharmacology. In this study, we use a fluorescent version of IL-23 to characterise antagonists of the full-length receptor expressed by living cells using a NanoBRET competition assay. We then develop a cyclic peptide fluorescent probe, specific to the IL23p19:IL23R interface and use this molecule to characterise further receptor antagonists. Finally, we use the assays to study the immunocompromising C115Y IL23R mutation, demonstrating that the mechanism of action is a disruption of the binding epitope for IL23p19.

All-in-one bioactive properties of photothermal nanofibers for accelerating diabetic wound healing

Diabetic wound healing has attracted widespread attention in biomedical engineering. However, the harsh hypoxic microenvironment (HME) comprising high glucose levels, local bleeding, and bacterial infection often leads to the formation of hyperplastic scars, increasing the clinical demand for wound dressings. Here, we report a comprehensive strategy using near-infrared NIR-assisted oxygen delivery combined with the bioactive nature of biopolymers for remodeling the HME. Black phosphorus (BP) nanosheets and hemoglobin (Hb) were self-assembled layerwise onto electrospun poly-l-lactide (PLLA) nanofibers using charged quaternized chitosan (QCS) and hyaluronic acid. BP converts NIR radiation into heat and stimulates Hb to release oxygen in situ. QCS is a hemostatic and broad-spectrum antibacterial material. Moderate BP-derived photothermal therapy can increase the sensitivity of bacteria to QCS. A series of composite wound dressings (coded as PQBH-n) with different numbers of layers were fabricated, and the in vivo diabetic wound healing potentials were tested. The molecular mechanism can be partly attributed to the cytokine-cytokine receptor interaction. Notably, this comprehensive strategy based on NIR-assisted oxygen delivery combined with the bioactive properties of biopolymers is not only applicable for fabricating multifunctional wound dressings but also has a great potential in expanding biomedical engineering fields.

Construction and validation of a bladder cancer risk model based on autophagy-related genes

Autophagy has an important association with tumorigenesis, progression, and prognosis. However, the mechanism of autophagy-regulated genes on the risk prognosis of bladder cancer (BC) patients has not been fully elucidated yet. In this study, we created a prognostic model of BC risk based on autophagy-related genes, which further illustrates the value of genes associated with autophagy in the treatment of BC. We first downloaded human autophagy-associated genes and BC datasets from Human Autophagy Database and The Cancer Genome Atlas (TCGA) database, and finally obtained differential prognosis-associated genes for autophagy by univariate regression analysis and differential analysis of cancer versus normal tissues. Subsequently, we downloaded two datasets from Gene Expression Omnibus (GEO), GSE31684 and GSE15307, to expand the total number of samples. Based on these genes, we distinguished the molecular subtypes (C1, C2) and gene classes (A, B) of BC by consistent clustering analysis. Using the genes merged from TCGA and the two GEO datasets, we conducted least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis to obtain risk genes and construct autophagy-related risk prediction models. The accuracy of this risk prediction model was assessed by receiver operating characteristic (ROC) and calibration curves, and then nomograms were constructed to predict the survival of bladder cancer patients at 1, 3, and 5 years, respectively. According to the median value of the risk score, we divided BC samples into the high- and low-risk groups. Kaplan-Meier (K-M) survival analysis was performed to compare survival differences between subgroups. Then, we used single sample gene set enrichment analysis (ssGSEA) for immune cell infiltration abundance, immune checkpoint genes, immunotherapy response, gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis, and tumor mutation burden (TMB) analysis for different subgroups. We also applied quantitative real-time polymerase chain reaction (PCR) and immunohistochemistry (IHC) techniques to verify the expression of these six genes in the model. Finally, we chose the IMvigor210 dataset for external validation. Six risk genes associated with autophagy (SPOCD1, FKBP10, NAT8B, LDLR, STMN3, and ANXA2) were finally screened by LASSO regression algorithm and multivariate Cox regression analysis. ROC and calibration curves showed that the model established was accurate and reliable. Univariate and multivariate regression analyses were used to verify that the risk model was an independent predictor. K-M survival analysis indicated that patients in the high-risk group had significantly worse overall survival than those in the low-risk group. Analysis by algorithms such as correlation analysis, gene set variation analysis (GSVA), and ssGSEA showed that differences in immune microenvironment, enrichment of multiple biologically active pathways, TMB, immune checkpoint genes, and human leukocyte antigens (HLAs) were observed in the different risk groups. Then, we constructed nomograms that predicted the 1-, 3-, and 5-year survival rates of different BC patients. In addition, we screened nine sensitive chemotherapeutic drugs using the correlation between the obtained expression status of risk genes and drug sensitivity results. Finally, the external dataset IMvigor210 verified that the model is reliable and efficient. We established an autophagy-related risk prognostic model that is accurate and reliable, which lays the foundation for future personalized treatment of bladder cancer.

C-Type Lectin Receptors-Triggered Antifungal Immunity May Synergize with and Optimize the Effects of Immunotherapy in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system worldwide, and there is a lack of effective treatment for late-stage HCC. Recent experimental studies have demonstrated that dysfunction of the intestinal flora has a significant impact on hepatocarcinogenesis. The pathophysiological link between the intestine, its microbiota, and the liver has been described as the "gut-liver axis". Dysbiosis of the intestinal flora and increased permeability of the intestinal wall are closely associated with liver pathology through the immune response. The "gut-liver axis" theory has been applied to the clinical study of the pathogenesis and treatment of HCC. The intestinal fungal community, as part of the gut microbiome, has a significant impact on human health and disease, while relatively little research has been done in HCC. In this study, we performed a comprehensive analysis of the expression and potential biological functions of the fungal recognition receptors C-type lectin receptors (CLRs) (Dectin-1, Dectin-2, Dectin-3, and Mincle) in HCC. We found that CLRs were downregulated in HCC, and their expressions were correlated with the clinical prognosis of HCC patients. Further studies suggested that the expression of CLRs were significantly correlated with immune infiltration and immunotherapy efficacy in HCC. Based on previous studies and our findings, we hypothesize that intestinal fungal communities and CLRs-triggered antifungal immunity have a key role in the pathogenesis of HCC, and these findings may provide new perspectives and targets for HCC immunotherapy.

Sequential control of myeloid cell proliferation and differentiation by cytokine receptor-based chimeric antigen receptors

As chimeric antigen receptor (CAR)-T cell therapy has been recently applied in clinics, controlling the fate of blood cells is increasingly important for curing blood disorders. In this study, we aim to construct proliferation-inducing and differentiation-inducing CARs (piCAR and diCAR) with two different antigen specificities and express them simultaneously on the cell surface. Since the two antigens are non-cross-reactive and exclusively activate piCAR or diCAR, sequential induction from cell proliferation to differentiation could be controlled by switching the antigens added in the culture medium. To demonstrate this notion, a murine myeloid progenitor cell line 32Dcl3, which proliferates in an IL-3-dependent manner and differentiates into granulocytes when cultured in the presence of G-CSF, is chosen as a model. To mimic the cell fate control of 32Dcl3 cells, IL-3R-based piCAR and G-CSFR-based diCAR are rationally designed and co-expressed in 32Dcl3 cells to evaluate the proliferation- and differentiation-inducing functions. Consequently, the sequential induction from proliferation to differentiation with switching the cytokine from IL-3 to G-CSF is successfully replaced by switching the antigen from one to another in the CARs-co-expressing cells. Thus, piCAR and diCAR may become a platform technology for sequentially controlling proliferation and differentiation of various cell types that need to be produced in cell and gene therapies.

Predicting prognosis and immune responses in hepatocellular carcinoma based on N7-methylguanosine-related long noncoding RNAs

Background: Hepatocellular carcinoma (HCC), which has high rates of recurrence and metastasis and is the main reason and the most common tumor for cancer mortality worldwide, has an unfavorable prognosis. N7-methylguanosine (m7G) modification can affect the formation and development of tumors by affecting gene expression and other biological processes. In addition, many previous studies have confirmed the unique function of long noncoding RNAs (lncRNAs) in tumor progression; however, studies exploring the functions of m7G-related lncRNAs in HCC patients has been limited.

Methods: Relevant RNA expression information was acquired from The Cancer Genome Atlas (TCGA, https://portal.gdc.cancer.gov), and m7G-related lncRNAs were identified via gene coexpression analysis. Afterward, univariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and multivariate regression analyses were implemented to construct an ideal risk model whose validity was verified using Kaplan–Meier survival, principal component, receiver operating characteristic (ROC) curve, and nomogram analyses. In addition, the potential functions of lncRNAs in the novel signature were explored through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) analyses and gene set enrichment analysis (GSEA). At last, in both risk groups and subtypes classified based on the expression of the risk-related lncRNAs, we analyzed the immune characteristics and drug sensitivity of patients.

Results: After rigorous screening processes, we built a model based on 11 m7G-related lncRNAs for predicting patient overall survival (OS). The results suggested that the survival status of patients with high-risk scores was lower than that of patients with low-risk scores, and a high-risk score was related to malignant clinical features. Cox regression analysis showed that the m7G risk score was an independent prognostic parameter. Moreover, immune cell infiltration and immunotherapy sensitivity differed between the risk groups.

Conclusion: The m7G risk score model constructed based on 11 m7G-related lncRNAs can effectively assess the OS of HCC patients and may offer support for making individualized treatment and immunotherapy decisions for HCC patients.

Mathematical Modeling of Proliferative Immune Response Initiated by Interactions Between Classical Antigen-Presenting Cells Under Joint Antagonistic IL-2 and IL-4 Signaling

During an adaptive immune response from pathogen invasion, multiple cytokines are produced by various immune cells interacting jointly at the cellular level to mediate several processes. For example, studies have shown that regulation of interleukin-4 (IL-4) correlates with interleukin-2 (IL-2) induced lymphocyte proliferation. This motivates the need to better understand and model the mechanisms driving the dynamic interplay of proliferation of lymphocytes with the complex interaction effects of cytokines during an immune response. To address this challenge, we adopt a hybrid computational approach comprising of continuous, discrete and stochastic non-linear model formulations to predict a system-level immune response as a function of multiple dependent signals and interacting agents including cytokines and targeted immune cells. We propose a hybrid ordinary differential equation-based (ODE) multicellular model system with a stochastic component of antigen microscopic states denoted as Multiscale Multicellular Quantitative Evaluator (MMQE) implemented using MATLAB. MMQE combines well-defined immune response network-based rules and ODE models to capture the complex dynamic interactions between the proliferation levels of different types of communicating lymphocyte agents mediated by joint regulation of IL-2 and IL-4 to predict the emergent global behavior of the system during an immune response. We model the activation of the immune system in terms of different activation protocols of helper T cells by the interplay of independent biological agents of classic antigen-presenting cells (APCs) and their joint activation which is confounded by the exposure time to external pathogens. MMQE quantifies the dynamics of lymphocyte proliferation during pathogen invasion as bivariate distributions of IL-2 and IL-4 concentration levels. Specifically, by varying activation agents such as dendritic cells (DC), B cells and their joint mechanism of activation, we quantify how lymphocyte activation and differentiation protocols boost the immune response against pathogen invasion mediated by a joint downregulation of IL-4 and upregulation of IL-2. We further compare our in-silico results to in-vivo and in-vitro experimental studies for validation. In general, MMQE combines intracellular and extracellular effects from multiple interacting systems into simpler dynamic behaviors for better interpretability. It can be used to aid engineering of anti-infection drugs or optimizing drug combination therapies against several diseases.

Cascade of immune mechanism and consequences of inflammatory disorders

Inflammatory responses arise as an outcome of tissues or organs exposure towards harmful stimuli like injury, toxic chemicals or pathogenic microorganism. It is a complex cascade of immune mechanism to overcome from tissue injury and to initiate the healing process by recruiting various immune cells, chemical mediators such as the vasoactive peptides and amines, pro-inflammatory cytokines, eicosanoids and acute-phase proteins to prevent tissue damage and ultimately complete restoration of the tissue function. The cytokines exhibits a central function in communication between the cells, inflammatory response initiation, amplification and their regulation. This review covers the importance of inflammatory responses; the significance of cytokines in inflammation and numerous inflammatory disorders/ailments due to the abrupt expression of cytokines and the hyper-inflammatory response or cytokine storm associated with poor prognosis in COVID-19 pandemic. Also highlighting the importance of naturally derived anti-inflammatory metabolites to overcome the side-effects of currently prevailing anti-inflammatory drugs.

Characterization of the Prognostic m6A-Related lncRNA Signature in Gastric Cancer

N6-methyladenosine (m⁶A) is a common form of mRNA modification regulated by m6A RNA methylation regulators and play an important role in the progression of gastric cancer (GC). However, the prognostic role of m⁶A-related lncRNA in gastric cancer has not been fully explored. This study aims at exploring the biological function and prognostic roles of the m⁶A-related lncRNA signature in gastric cancer. A total of 800 m6A-related lncRNAs were identified through Pearson correlation analysis between m6A regulators and all lncRNAs. Eleven m6A-related lncRNA signatures were identified through a survival analysis and the Kaplan-Meier (KM) curve analysis results suggest that patients in the low-risk group have a better overall survival (OS) and disease-free survival (DFS) outcome than the high-risk group. Also, the lncRNA signature can serve as an independent prognostic factor for OS and DFS. The gene set enrichment analysis (GSEA) result suggests that patients in the high-risk group were mainly enriched in the ECM receptor interaction, focal adhesion, and cytokine-cytokine receptor interaction pathway, while the low-risk group was characterized by the base excision repair pathway. We further constructed an individualized prognostic prediction model via the nomogram based on the independent prognostic factor for the OS and DFS, respectively. In addition, some candidate drugs aimed at GC risk group differentiation were identified using the Connective Map (CMAP) database. Lastly, four subgroups (C1, C2, C3, and C4) were identified based on the m6A-related lncRNA expression, through a consensus clustering algorithm. Among them, C1 and C2 have a greater likelihood to respond to immune checkpoint inhibitor immunotherapy, suggesting that the C1 and C2 subgroup might benefit from immunotherapy. In conclusion, the m6A-related lncRNA signature can independently predict the OS and DFS of GC and may aid in development of personalized immunotherapy strategies.

Comparative Analysis of Multiple Immunoassays for Cytokine Profiling in Drug Discovery

Cytokines and their receptors play critical roles in biological processes. Dysfunction or dysregulation of cytokines may cause a variety of pathophysiological conditions. Consequently, cytokine profiling and related technologies are essential for biological studies, disease diagnosis, and drug discovery. In this report, three cytokines, interleukin (IL)-1β, IL-6, and tumor necrosis factor alpha (TNF-α), from the same sets of samples were analyzed with several commonly used technologies (enzyme-linked immunosorbent assay [ELISA], Luminex, Meso Scale Discovery [MSD], time-resolved fluorescence resonance energy transfer [TR-FRET], cytometric bead array [CBA], AlphaLISA, and FirePlex). Through experimental data analysis, several assay features were compared, including sensitivity, dynamic range, and robustness. Our studies reveal that MSD has the best sensitivity in the low detection limit and the broadest dynamic range, while CBA and Luminex also demonstrate superior performance in the sensitivity and dynamic range. Additional aspects of these technologies, including assay principles, formats, throughputs, robustness, costs, and multiplexing capabilities, were also reviewed and compared. Combining all these features, our comparison highlights MSD as the most sensitive technology, while CBA is the most suitable one for cytokine high-throughput screening with multiplexing capability. Along with perspectives on new technology development in the field, this report aims to help readers understand these technologies and select the proper one for specific applications.

Effect of eleutheroside B1 on non‑coding RNAs and protein profiles of influenza A virus‑infected A549 cells

Influenza viruses often pose a serious threat to animals and human health. In an attempt to explore the potential of herbal medicine as a treatment for influenza virus infection, eleutheroside B1, a coumarin compound extracted from herba sarcandrae, was identified, which exhibited antiviral and anti-inflammatory activities against influenza A virus. In this study, high-throughput RNA sequencing and isobaric tags for relative and absolute quantification (iTRAQ) assays were performed to determine alterations in the non-coding RNA (ncRNA) transcriptome and proteomics. Bioinformatics and target prediction analyses were used to decipher the potential roles of altered ncRNAs in the function of eleutheroside B1. Furthermore, long ncRNA (lncRNA) and mRNA co-expressing networks were constructed to analyze the biological functions by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The analysis of RNA sequencing data revealed that 5 differentially expressed ncRNAs were upregulated and 3 ncRNAs were downregulated in the A549 cells infected with A/PR8/34/H1N1, with or without eleutheroside B1 treatment (PR8+eleu and PR8, respectively). Nuclear paraspeckle assembly transcript 1 (NEAT1) was differentially expressed between the PR8 and A549 cell groups. GO and KEGG pathway analyses indicated that eleutheroside B1 took advantage of the host cell biological processes and molecular function for its antiviral and anti-inflammatory activities, as well as for regulating cytokine-cytokine receptor interaction in the immune system, consistent with previous findings. The results of the iTRAQ assays indicated that L antigen family member 3 (LAGE3) protein, essential for tRNA processing, tRNA metabolic processes and ncRNA processing, was down-regulated in the PR8+eleu compared with the PR8 group. In the present study, these comprehensive, large-scale data analysis enhanced the understanding of multiple aspects of the transcriptome and proteomics that are involved in the antiviral and anti-inflammatory activities of eleutheroside B1. These findings demonstrate the potential of eleutheroside B1 for use in the prevention and treatment of influenza A virus-mediated infections.

A novel sponge-derived protein thrombocorticin is a new agonist for thrombopoietin receptor

We screened 868 marine extracts in search of hematopoietic molecules resulted in findings of several extracts that proliferated Ba/F3-HuMpl cells but not the cells expressed with other hematopoietic cytokine receptors, EPO and G-CSF. Separation of the most potent extract of a Micronesian sponge Corticium sp., guided by the cell proliferation assay using Ba/F3-HuMpl cells resulted in an isolation of thrombocorticin (ThC), a novel 14 kDa protein as an active principal. ThC displayed concentration-dependent proliferation of Ba/F3-HuMpl cells, and had a stronger activity than that of eltrombopag, a small molecule drug used to treat thrombocytopenia. ThC induced phosphorylation of STAT5, suggesting that it activates Jak/STAT pathway as in the case of TPO. These results together indicated that ThC is a specific agonist for c-Mpl, although the size and shape differs largely from TPO. Here we present isolation, characterization and biological activity of ThC.

Molecular engineering strategies for visualizing low-affinity protein complexes

The growing availability of complex structures in the Protein Data Bank has provided key insight into the molecular architecture of protein–protein interfaces. The remarkable diversity observed in protein binding modes is paralleled by a tremendous variation in binding affinities, with interaction half-lives ranging from days to milliseconds. Within the protein interactome, low-affinity binding events have been particularly difficult to visualize by traditional structural methods, which has spurred the development of innovative strategies for reconstituting these short-lived yet biologically essential assemblies. An important takeaway from structural studies of low-affinity systems is that there is no universal solution for stabilizing protein complexes, and approaches such as single-chain fusions, biochemical linkages, and affinity-maturation have each been successful in certain contexts. In this article, we review how advances in molecular engineering have been used to capture weakly associated complexes for structure determination, and we provide perspectives on how the continued application of these methods can shed new light on the “hidden world” of low-affinity interactions.

Impact statement

Low-affinity protein interactions, while biologically essential, have been difficult to visualize by traditional methods in structural biology. In this review, we describe a series of innovative molecular engineering strategies that have been used to stabilize weakly bound protein complexes for structure determination. By highlighting several examples from the literature along with potential advantages and disadvantages of the individual approaches, we hope to provide an introductory resource for structural biologists studying low-affinity systems.

Integrative Analysis of Dysfunctional Modules Driven by Genomic Alterations at System Level Across 11 Cancer Types

Aim and Objective:

Integrating multi-omics data to identify driver genes and key biological functions for tumorigenesis remains a major challenge.

Method:

A new computational pipeline was developed to identify the Driver Mutation-Differential Co-Expression (DM-DCE) modules based on dysfunctional networks across 11 TCGA cancers.

Results:

Functional analyses provided insight into the properties of various cancers, and found common cellular signals / pathways of cancers. Furthermore, the corresponding network analysis identified conservations or interactions across different types of cancers, thus the crosstalk between the key signaling pathways, immunity and cancers was found. Clinical analysis also identified key prognostic / survival patterns.

Conclusion:

Taken together, our study sheds light on both cancer-specific and cross-cancer characteristics systematically.

Mapping Determinants of Cytokine Signaling via Protein Engineering

Cytokines comprise a large family of secreted ligands that are critical for the regulation of immune homeostasis. Cytokines initiate signaling via dimerization or oligomerization of the cognate receptor subunits, triggering the activation of the Janus Kinases (JAKs)/ signal transducer and activator of transcription (STATs) pathway and the induction of specific gene expression programs and bioactivities. Deregulation of cytokines or their downstream signaling pathways are at the root of many human disorders including autoimmunity and cancer. Identifying and understanding the mechanistic principles that govern cytokine signaling will, therefore, be highly important in order to harness the therapeutic potential of cytokines. In this review, we will analyze how biophysical (ligand-receptor binding geometry and affinity) and cellular (receptor trafficking and intracellular abundance of signaling molecules) parameters shape the cytokine signalosome and cytokine functional pleiotropy; from the initial cytokine binding to its receptor to the degradation of the cytokine receptor complex in the proteasome and/or lysosome. We will also discuss how combining advanced protein engineering with detailed signaling and functional studies has opened promising avenues to tackle complex questions in the cytokine signaling field.

A comparative system-level analysis of the neurodegenerative diseases

Neurodegenerative diseases are disorders in the central nervous system with consequent progressive neurological symptoms including behavioral and cognitive disabilities. Alzheimer's disease, amyotrophic lateral sclerosis, Huntington's disease, Parkinson's disease, multiple sclerosis, and schizophrenia are the most important and abundant neurodegenerative diseases that affect different parts of the brain. Detailed studies unveiled the molecular mechanisms and pathways affected in each of these disorders. The role of many genes has been documented in the onset and progression of each disease. Although many system-level approaches have been used to understand the exact cause of these diseases, there is no comparative analysis in this regard. Despite all differences in the molecular basis of these diseases, overlapping symptoms might indicate the involvement of the similar pathways and processes. Here, we have applied a system biology approach to uncover many aspects of main neurodegenerative diseases using microarray data obtained from 118 cases of postmortem brain samples. Our analysis has identified key genes that might contribute to the status of diseases. We have also compared the involved biological process and pathway between different disease to find possible similar mechanisms that exist in all of them. We also predicted potentially important transcription factors in each disease and predicted the core gene regulatory networks. We have provided a list of possible new key regulators that could be further explored and also discussed the role of these hub genes. The results of this study would be useful to develop new diagnostic strategies and also to find new drug targets.

From proteomics to discovery of first-in-class ST2 inhibitors active in vivo

Soluble cytokine receptors function as decoy receptors to attenuate cytokine-mediated signaling and modulate downstream cellular responses. Dysregulated overproduction of soluble receptors can be pathological, such as soluble ST2 (sST2), a prognostic biomarker in cardiovascular diseases, ulcerative colitis, and graft-versus-host disease (GVHD). Although intervention using an ST2 antibody improves survival in murine GVHD models, sST2 is a challenging target for drug development because it binds to IL-33 via an extensive interaction interface. Here, we report the discovery of small-molecule ST2 inhibitors through a combination of high-throughput screening and computational analysis. After in vitro and in vivo toxicity assessment, 3 compounds were selected for evaluation in 2 experimental GVHD models. We show that the most effective compound, iST2-1, reduces plasma sST2 levels, alleviates disease symptoms, improves survival, and maintains graft-versus-leukemia activity. Our data suggest that iST2-1 warrants further optimization to develop treatment for inflammatory diseases mediated by sST2.

A versatile platform for activity determination of cytokines and growth factors based on the human TSLP (thymic stromal lymphopoietin) receptor

Cytokines and growth factors are signaling proteins involved in communication processes between cells. They are involved in the control of numerous essential physiological processes such as cell proliferation, gene transcription and differentiation; therefore being in the focus of basic and applied research. Many of them are also of relevance for human diseases. When observed as potential targets for pharmacological intervention and objects of structure/function studies, it is important to measure their biological activities, optionally along with potential inhibitors, in a convenient and rational manner. Such tests are frequently laborious to set up and their establishment is complicated by the necessity to employ problematic cell types and sophisticated assays. Here we present a robust and modular activity assay system which can be adapted to virtually all ligands that signal through dimerization of membrane receptors from different families. The technique rests on fusing ligand-binding domains of specific receptors to the transmembrane and intracellular components of the thymic stromal lymphopoietin (TSLP) receptor which translates signals into readily quantifiable luciferase expression in reporter cells. We show that the activation of various hematopoietic cytokine receptors, of receptor tyrosine kinases as well as of receptors bearing serine/threonine kinase domains by their respective ligands was faithfully reflected both upon transient and stable introduction of hybrid receptor and reporter gene constructs into the murine pro-B cell line Ba/F3. Moreover, we demonstrate the suitability of this platform for the functional characterization of cytokine/growth factor receptor inhibitors.

Pathways of topological rank analysis (PoTRA): a novel method to detect pathways involved in hepatocellular carcinoma

Complex diseases such as cancer are usually the result of a combination of environmental factors and one or several biological pathways consisting of sets of genes. Each biological pathway exerts its function by delivering signaling through the gene network. Theoretically, a pathway is supposed to have a robust topological structure under normal physiological conditions. However, the pathway's topological structure could be altered under some pathological condition. It is well known that a normal biological network includes a small number of well-connected hub nodes and a large number of nodes that are non-hubs. In addition, it is reported that the loss of connectivity is a common topological trait of cancer networks, which is an assumption of our method. Hence, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal or the distribution of topological ranks of genes might be altered. Based on this, we propose a new PageRank-based method called Pathways of Topological Rank Analysis (PoTRA) to detect pathways involved in cancer. We use PageRank to measure the relative topological ranks of genes in each biological pathway, then select hub genes for each pathway, and use Fisher's exact test to test if the number of hub genes in each pathway is altered from normal to cancer. Alternatively, if the distribution of topological ranks of gene in a pathway is altered between normal and cancer, this pathway might also be involved in cancer. Hence, we use the Kolmogorov-Smirnov test to detect pathways that have an altered distribution of topological ranks of genes between two phenotypes. We apply PoTRA to study hepatocellular carcinoma (HCC) and several subtypes of HCC. Very interestingly, we discover that all significant pathways in HCC are cancer-associated generally, while several significant pathways in subtypes of HCC are HCC subtype-associated specifically. In conclusion, PoTRA is a new approach to explore and discover pathways involved in cancer. PoTRA can be used as a complement to other existing methods to broaden our understanding of the biological mechanisms behind cancer at the system-level.

Ligand-induced type II interleukin-4 receptor dimers are sustained by rapid re-association within plasma membrane microcompartments

The spatiotemporal organization of cytokine receptors in the plasma membrane is still debated with models ranging from ligand-independent receptor pre-dimerization to ligand-induced receptor dimerization occurring only after receptor uptake into endosomes. Here, we explore the molecular and cellular determinants governing the assembly of the type II interleukin-4 receptor, taking advantage of various agonists binding the receptor subunits with different affinities and rate constants. Quantitative kinetic studies using artificial membranes confirm that receptor dimerization is governed by the two-dimensional ligand–receptor interactions and identify a critical role of the transmembrane domain in receptor dimerization. Single molecule localization microscopy at physiological cell surface expression levels, however, reveals efficient ligand-induced receptor dimerization by all ligands, largely independent of receptor binding affinities, in line with the similar STAT6 activation potencies observed for all IL-4 variants. Detailed spatiotemporal analyses suggest that kinetic trapping of receptor dimers in actin-dependent microcompartments sustains robust receptor dimerization and signalling.

The contribution of ligands for cytokine receptor dimerization is still not fully understood. Here, the authors show the efficient ligand-induced dimerization of type II interleukin-4 receptor at the plasma membrane and the kinetic trapping of signalling complexes by actin-dependent membrane microdomains.

IL-7 Induces an Epitope Masking of γc Protein in IL-7 Receptor Signaling Complex

IL-7 signaling via IL-7Rα and common γ-chain (γc) is necessary for the development and homeostasis of T cells. Although the delicate mechanism in which IL-7Rα downregulation allows the homeostasis of T cell with limited IL-7 has been well known, the exact mechanism behind the interaction between IL-7Rα and γc in the absence or presence of IL-7 remains unclear. Additionally, we are still uncertain as to how only IL-7Rα is separately downregulated by the binding of IL-7 from the IL-7Rα/γc complex. We demonstrate here that 4G3, TUGm2, and 3E12 epitope masking of γc protein are induced in the presence of IL-7, indicating that the epitope alteration is induced by IL-7 binding to the preassembled receptor core. Moreover, the epitope masking of γc protein is inversely correlated with the expression of IL-7Rα upon IL-7 binding, implying that the structural alteration of γc might be involved in the regulation of IL-7Rα expression. The conformational change in γc upon IL-7 binding may contribute not only to forming the functional IL-7 signaling complex but also to optimally regulating the expression of IL-7Rα.

Determination of half-maximal inhibitory concentration using biosensor-based protein interaction analysis

Half-maximal inhibitory concentration (IC50) is the most widely used and informative measure of a drug's efficacy. It indicates how much drug is needed to inhibit a biological process by half, thus providing a measure of potency of an antagonist drug in pharmacological research. Most approaches to determine IC50 of a pharmacological compound are based on assays that utilize whole cell systems. While they generally provide outstanding potency information, results can depend on the experimental cell line used and may not differentiate a compound's ability to inhibit specific interactions. Here we show using the secreted Transforming Growth Factor-β (TGF-β) family ligand BMP-4 and its receptors as example that surface plasmon resonance can be used to accurately determine IC50 values of individual ligand-receptor pairings. The molecular resolution achievable wih this approach can help distinguish inhibitors that specifically target individual complexes, or that can inhibit multiple functional interactions at the same time.

Flavonoids as Cytokine Modulators: A Possible Therapy for Inflammation-Related Diseases

High levels of cytokines, such as interleukin (IL)-1β, tumor necrosis factor (TNF)-α and IL-6, are associated with chronic diseases like rheumatoid arthritis, asthma, atherosclerosis, Alzheimer's disease and cancer; therefore cytokine inhibition might be an important target for the treatment of these diseases. Most drugs used to alleviate some inflammation-related symptoms act by inhibiting cyclooxygenases activity or by blocking cytokine receptors. Nevertheless, these drugs have secondary effects when used on a long-term basis. It has been mentioned that flavonoids, namely quercetin, apigenin and luteolin, reduce cytokine expression and secretion. In this regard, flavonoids may have therapeutical potential in the treatment of inflammation-related diseases as cytokine modulators. This review is focused on current research about the effect of flavonoids on cytokine modulation and the description of the way these compounds exert their effect.

High efficiency cell-specific targeting of cytokine activity

Systemic toxicity currently prevents exploiting the huge potential of many cytokines for medical applications. Here we present a novel strategy to engineer immunocytokines with very high targeting efficacies. The method lies in the use of mutants of toxic cytokines that markedly reduce their receptor-binding affinities, and that are thus rendered essentially inactive. Upon fusion to nanobodies specifically binding to marker proteins, activity of these cytokines is selectively restored for cell populations expressing this marker. This 'activity-by-targeting' concept was validated for type I interferons and leptin. In the case of interferon, activity can be directed to target cells in vitro and to selected cell populations in mice, with up to 1,000-fold increased specific activity. This targeting strategy holds promise to revitalize the clinical potential of many cytokines.

Receptor dimerization dynamics as a regulatory valve for plasticity of type I interferon signaling

Type I interferons (IFNs) activate differential cellular responses through a shared cell surface receptor composed of the two subunits, IFNAR1 and IFNAR2. We propose here a mechanistic model for how IFN receptor plasticity is regulated on the level of receptor dimerization. Quantitative single-molecule imaging of receptor assembly in the plasma membrane of living cells clearly identified IFN-induced dimerization of IFNAR1 and IFNAR2. The negative feedback regulator ubiquitin-specific protease 18 (USP18) potently interferes with the recruitment of IFNAR1 into the ternary complex, probably by impeding complex stabilization related to the associated Janus kinases. Thus, the responsiveness to IFNα2 is potently down-regulated after the first wave of gene induction, while IFNβ, due to its ∼100-fold higher binding affinity, is still able to efficiently recruit IFNAR1. Consistent with functional data, this novel regulatory mechanism at the level of receptor assembly explains how signaling by IFNβ is maintained over longer times compared with IFNα2 as a temporally encoded cause of functional receptor plasticity.

Functional aspects of extracellular cyclophilins

The cyclophilin family of peptidyl prolyl cis/trans isomerases includes several isoforms found to be secreted in response to different stimuli, thus existing both in the interior and the exterior of cells. The extracellular fractions of the cyclophilins CypA and CypB are involved in the control of cell-cell communication. By binding to the cell membrane receptor CD147 and cell surface heparans they elicit a variety of intracellular signaling cascades involved in inflammatory processes. Increased levels of cyclophilins in inflammatory tissues and body fluids are considered as an inflammatory response to injury. Thus, the extracellular portion of cyclophilins probably plays an important role in human diseases associated with acute or chronic inflammation like rheumatoid arthritis, sepsis, asthma and cardiovascular diseases. Specific inhibition of the cyclophilins in the extracellular space may open an effective therapeutic approach for treating inflammatory diseases.

The identification of specific methylation patterns across different cancers

Abnormal DNA methylation is known as playing an important role in the tumorgenesis. It is helpful for distinguishing the specificity of diagnosis and therapeutic targets for cancers based on characteristics of DNA methylation patterns across cancers. High throughput DNA methylation analysis provides the possibility to comprehensively filter the epigenetics diversity across various cancers. We integrated whole-genome methylation data detected in 798 samples from seven cancers. The hierarchical clustering revealed the existence of cancer-specific methylation pattern. Then we identified 331 differentially methylated genes across these cancers, most of which (266) were specifically differential methylation in unique cancer. A DNA methylation correlation network (DMCN) was built based on the methylation correlation between these genes. It was shown the hubs in the DMCN were inclined to cancer-specific genes in seven cancers. Further survival analysis using the part of genes in the DMCN revealed high-risk group and low-risk group were distinguished by seven biomarkers (PCDHB15, WBSCR17, IGF1, GYPC, CYGB, ACTG2, and PRRT1) in breast cancer and eight biomarkers (ZBTB32, OR51B4, CCL8, TMEFF2, SALL3, GPSM1, MAGEA8, and SALL1) in colon cancer, respectively. At last, a protein-protein interaction network was introduced to verify the biological function of differentially methylated genes. It was shown that MAP3K14, PTN, ACVR1 and HCK sharing different DNA methylation and gene expression across cancers were relatively high degree distribution in PPI network. The study suggested that not only the identified cancer-specific genes provided reference for individual treatment but also the relationship across cancers could be explained by differential DNA methylation.

Systems pharmacology of mifepristone (RU486) reveals its 47 hub targets and network: comprehensive analysis and pharmacological focus on FAK-Src-Paxillin complex

Mifepristone (RU486), a synthetic steroid compound used as an abortifacient drug, has received considerable attention to its anticancer activity recently. To explore the possibility of using mifepristone as a cancer metastasis chemopreventive, we performed a systems pharmacology analysis of mifepristone-related molecules in the present study. Data were collected by using Natural Language Processing (NLP) and 513 mifepristone-related genes were dug out and classified functionally using a gene ontology (GO) hierarchy, followed by KEGG pathway enrichment analysis. Potential signal pathways and targets involved in cancer were obtained by integrative network analysis. Total thirty-three proteins were involved in focal adhesion-the key signaling pathway associated with cancer metastasis. Molecular and cellular assays further demonstrated that mifepristone had the ability to prevent breast cancer cells from migration and interfere with their adhesion to endothelial cells. Moreover, mifepristone inhibited the expression of focal adhesion kinase (FAK), paxillin, and the formation of FAK/Src/Paxillin complex, which are correlated with cell adhesion and migration. This study set a good example to identify chemotherapeutic potential seamlessly from systems pharmacology to cellular pharmacology, and the revealed hub genes may be the promising targets for cancer metastasis chemoprevention.

Insights into cytokine-receptor interactions from cytokine engineering

Cytokines exert a vast array of immunoregulatory actions critical to human biology and disease. However, the desired immunotherapeutic effects of native cytokines are often mitigated by toxicity or lack of efficacy, either of which results from cytokine receptor pleiotropy and/or undesired activation of off-target cells. As our understanding of the structural principles of cytokine-receptor interactions has advanced, mechanism-based manipulation of cytokine signaling through protein engineering has become an increasingly feasible and powerful approach. Modified cytokines, both agonists and antagonists, have been engineered with narrowed target cell specificities, and they have also yielded important mechanistic insights into cytokine biology and signaling. Here we review the theory and practice of cytokine engineering and rationalize the mechanisms of several engineered cytokines in the context of structure. We discuss specific examples of how structure-based cytokine engineering has opened new opportunities for cytokines as drugs, with a focus on the immunotherapeutic cytokines interferon, interleukin-2, and interleukin-4.

Multifaceted activities of type I interferon are revealed by a receptor antagonist

Type I interferons (IFNs), including various IFN-α isoforms and IFN-β, are a family of homologous, multifunctional cytokines. IFNs activate different cellular responses by binding to a common receptor that consists of two subunits, IFNAR1 and IFNAR2. In addition to stimulating antiviral responses, they also inhibit cell proliferation and modulate other immune responses. We characterized various IFNs, including a mutant IFN-α2 (IFN-1ant) that bound tightly to IFNAR2 but had markedly reduced binding to IFNAR1. Whereas IFN-1ant stimulated antiviral activity in a range of cell lines, it failed to elicit immunomodulatory and antiproliferative activities. The antiviral activities of the various IFNs tested depended on a set of IFN-sensitive genes (the "robust" genes) that were controlled by canonical IFN response elements and responded at low concentrations of IFNs. Conversely, these elements were not found in the promoters of genes required for the antiproliferative responses of IFNs (the "tunable" genes). The extent of expression of tunable genes was cell type-specific and correlated with the magnitude of the antiproliferative effects of the various IFNs. Although IFN-1ant induced the expression of robust genes similarly in five different cell lines, its antiviral activity was virus- and cell type-specific. Our findings suggest that IFN-1ant may be a therapeutic candidate for the treatment of specific viral infections without inducing the immunomodulatory and antiproliferative functions of wild-type IFN.

Structural insights into the common γ-chain family of cytokines and receptors from the interleukin-7 pathway

Over the past 13 years, numerous crystal structures of complexes of the common γ-chain (γ(c)) cytokine receptors and their cytokines have been solved. Even with the remarkable progress in the structural biology of γ(c) receptors and their cytokines or interleukins, there are valuable lessons to be learned from the structural and biophysical studies of interleukin-7 (IL-7) and its α-receptor (IL-7Rα) and comparisons with other γ(c) family members. The structure of the IL-7/IL-7Rα complex teaches that interfaces between the γ(c) interleukins and their receptors can vary in size, polarity, and specificity, and that significant conformational changes might be necessary for complexes of interleukins and their receptors to bind the shared, activating γ(c) receptor. Binding, kinetic, and thermodynamic studies of IL-7 and IL-7Rα show that glycosylation and electrostatics can be important to interactions between interleukins and their receptor, even where the glycans and charged residues are distant from the interface. The structure of the IL-7Rα homodimer is a reminder that often-ignored non-activating complexes likely perform roles just as important to signaling as activating complexes. And last but not least, the structural and biophysical studies help explain and potentially treat the diseases caused by aberrant IL-7 signaling.

Structural reorganization of the interleukin-7 signaling complex

We report here an unliganded receptor structure in the common gamma-chain (γ(c)) family of receptors and cytokines. The crystal structure of the unliganded form of the interleukin-7 alpha receptor (IL-7Rα) extracellular domain (ECD) at 2.15 Å resolution reveals a homodimer forming an "X" geometry looking down onto the cell surface with the C termini of the two chains separated by 110 Å and the dimer interface comprising residues critical for IL-7 binding. Further biophysical studies indicate a weak association of the IL-7Rα ECDs but a stronger association between the γ(c)/IL-7Rα ECDs, similar to previous studies of the full-length receptors on CD4(+) T cells. Based on these and previous results, we propose a molecular mechanism detailing the progression from the inactive IL-7Rα homodimer and IL-7Rα-γ(c) heterodimer to the active IL-7-IL-7Rα-γ(c) ternary complex whereby the two receptors undergo at least a 90° rotation away from the cell surface, moving the C termini of IL-7Rα and γ(c) from a distance of 110 Å to less than 30 Å at the cell surface. This molecular mechanism can be used to explain recently discovered IL-7- and γ(c)-independent gain-of-function mutations in IL-7Rα from B- and T-cell acute lymphoblastic leukemia patients. The mechanism may also be applicable to other γ(c) receptors that form inactive homodimers and heterodimers independent of their cytokines.

CytReD: A database collecting human cytokinome information

The cytokines/related receptors system represents a complex regulatory network that is involved in those chronic inflammatory processes which lead to many diseases as cancers. We developed a Cytokine Receptor Database (CytReD) to collect information on cytokine receptors related to their biological activity, gene data, protein structures and diseases in which these and their ligands are implicated. This large set of information may be used by researchers as well as by physicians or clinicians to identify which cytokines, reported in the literature, are important in a given disease and, therefore, useful for purposes of diagnosis or prognostic.

AVAILABILITY

The database is available for free at http://www.cro-m.eu/CytReD/

Peptide phage display as a tool for drug discovery: targeting membrane receptors

Ligands selected from phage-displayed random peptide libraries tend to be directed to biologically relevant sites on the surface of the target protein. Consequently, peptides derived from library screenings often modulate the target protein’s activity in vitro and in vivo and can be used as lead compounds in drug design and as alternatives to antibodies for target validation in both genomics and drug discovery. This review discusses the use of phage display to identify membrane receptor modulators with agonistic or antagonistic activities. Because isolating or producing recombinant membrane proteins for use as target molecules in library screening is often impossible, innovative selection strategies such as panning against whole cells or tissues, recombinant receptor ectodomains, or neutralizing antibodies to endogenous binding partners were devised. Prominent examples from a two-decade history of peptide phage display will be presented, focusing on the design of affinity selection experiments, methods for improving the initial hits, and applications of the identified peptides.