LGI3 is secreted and binds to ADAM22 via TRIF-dependent NF-κB pathway in response to LPS in human keratinocytes

Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.

Moringa concanensis L. Alleviates DNCB-Induced Atopic Dermatitis-like Symptoms by Inhibiting NLRP3 Inflammasome-Mediated IL-1β in BALB/c Mice

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by pruritus, dry skin and redness on the face and inside elbows or knees. Most patients with AD are children and youths, but it can also develop in adults. In the therapeutic aspect, treatment with corticosteroids for AD has several side effects, such as weight loss, atrophy and acne. In the current study, we examined the anti-inflammatory effect of Moringa concanensis leaves on HaCaT keratinocytes and 2,4-dinitrochlorobenzene (DNCB)-induced atopic dermatitis-like symptoms in BALB/c mice. We observed that M. concanensis treatment exhibited significant inhibition in the production of inflammatory mediators and proinflammatory cytokines, such as IL-1β, in LPS-induced HaCaT keratinocytes by downregulating the NLRP3 inflammasome activation. Moreover, M. concanensis inhibited the activation of JNK, AP-1 and p65, which resulted in the deformation of NLRP3 in LPS-stimulated HaCaT cells. In mice with DNCB-induced AD-like skin lesions, the administration of M. concanensis ameliorated the clinical symptoms, such as the dermatitis score, thickness of lesional ear skin and TEWL. Furthermore, M. concanensis could attenuate the activation of the immune system, such as reducing the spleen index, concentration of the IgE levels and expression of the NLRP3 inflammasome in ear tissues. Therefore, our results suggest that M. concanensis exerts anti-atopic dermatitis effects by inhibiting the NLRP3 inflammasome-mediated IL-1β.

Antiaging effect of inotodiol on oxidative stress in human dermal fibroblasts

Oxidative damage is one of the major causes of human skin aging. Inotodiol is a lanostane triterpenoid that demonstrates antiviral, anticancer, and anti-inflammatory activities. Previous studies have reported that inotodiol also has antiallergic effects. However, whether inotodiol inhibits oxidative stress-induced human skin aging is not known. Stimulation of human dermal fibroblast cells with hydrogen peroxide is related to skin aging. Inotodiol inhibited the expression of mitogen-activated protein kinase (MAPK) and NADPH Oxidase 5 (NOX5). Moreover, inotodiol effectively decreased nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), as well as nitric oxide (NO), reactive oxygen species (ROS), cyclooxygenase-2 (COX-2), and cytokines such as IL-1β, IL-6, and TNF-α. Based on our results, inotodiol protects human dermal fibroblast by preventing MAPK-NOX5 and NF-κB activation and attenuates the expression of aging genes. Inotodiol may therefore be considered a potential candidate for developing natural antiaging products, because it protects the human skin from oxidative stress-induced skin aging by inhibiting the MAPK-NOX5 and NF-κB signaling pathways.

Combining explainable machine learning, demographic and multi-omic data to inform precision medicine strategies for inflammatory bowel disease

Inflammatory bowel diseases (IBDs), including ulcerative colitis and Crohn’s disease, affect several million individuals worldwide. These diseases are heterogeneous at the clinical, immunological and genetic levels and result from complex host and environmental interactions. Investigating drug efficacy for IBD can improve our understanding of why treatment response can vary between patients. We propose an explainable machine learning (ML) approach that combines bioinformatics and domain insight, to integrate multi-modal data and predict inter-patient variation in drug response. Using explanation of our models, we interpret the ML models’ predictions to infer unique combinations of important features associated with pharmacological responses obtained during preclinical testing of drug candidates in ex vivo patient-derived fresh tissues. Our inferred multi-modal features that are predictive of drug efficacy include multi-omic data (genomic and transcriptomic), demographic, medicinal and pharmacological data. Our aim is to understand variation in patient responses before a drug candidate moves forward to clinical trials. As a pharmacological measure of drug efficacy, we measured the reduction in the release of the inflammatory cytokine TNFα from the fresh IBD tissues in the presence/absence of test drugs. We initially explored the effects of a mitogen-activated protein kinase (MAPK) inhibitor; however, we later showed our approach can be applied to other targets, test drugs or mechanisms of interest. Our best model predicted TNFα levels from demographic, medicinal and genomic features with an error of only 4.98% on unseen patients. We incorporated transcriptomic data to validate insights from genomic features. Our results showed variations in drug effectiveness (measured by ex vivo assays) between patients that differed in gender, age or condition and linked new genetic polymorphisms to patient response variation to the anti-inflammatory treatment BIRB796 (Doramapimod). Our approach models IBD drug response while also identifying its most predictive features as part of a transparent ML precision medicine strategy.

Integrative proteomic network analyses support depot-specific roles for leucine rich repeat LGI family member 3 in adipose tissues

LGI family member 3 (LGI3) is a member of the LGI protein family. In our previous studies, LGI3 was determined to be expressed in adipose tissues, skin and the brain, where it served as a pleiotropic cytokine. The results indicated that LGI3 levels are increased in adipose tissues of obese individuals in comparison with control individuals and that LGI3 suppressed adipogenesis via its receptor, disintegrin and metalloproteinase domain-containing protein 23. Additionally, it was reported that LGI3 upregulates tumor necrosis factor-α and downregulated adiponectin and hypothesized that LGI3 may act as a proinflammatory adipokine involved in adipose tissue inflammation. In the present study, cytokine arrays were used to analyze cytokine levels in adipose tissues and plasma of LGI3-knockout mice and signaling protein arrays used to analyze the expression and phosphorylation of these proteins in LGI3-treated preadipocytes. The results suggested that expression levels of 129 gene products (24 cytokines and 105 signaling proteins) were altered in response to LGI3 deficiency or LGI3 treatment, respectively. Protein-protein interaction network analysis of LGI3-regulated gene products revealed that 94% of the gene products (21 cytokines and 100 signaling proteins) formed an interaction network cluster. Functional enrichment analysis for the LGI3-regulated gene products, including those from our previous studies, revealed an association with numerous biological processes, including inflammatory responses, cellular differentiation and development and metabolic regulation. Gene co-expression network analysis revealed that these LGI3-regulated gene products were involved in various biological processes in an overlapping and differential manner between subcutaneous and visceral adipose tissues. Notably, inflammatory responses were more strongly associated with the LGI3-regulated gene co-expression network in visceral adipose tissues than in subcutaneous adipose tissues. Analysis of expression quantitative trait loci identified four single nucleotide variants that affect expression of LGI3 in an adipose depot-specific manner. Taken together, the results suggested that LGI3 may serve depot-specific roles as an adipokine in adipose tissues.