Novel Immune-Related Gene-Based Signature Characterizing an Inflamed Microenvironment Predicts Prognosis and Radiotherapy Efficacy in Glioblastoma

Effective treatment of glioblastoma (GBM) remains an open challenge. Given the critical role of the immune microenvironment in the progression of cancers, we aimed to develop an immune-related gene (IRG) signature for predicting prognosis and improving the current treatment paradigm of GBM. Multi-omics data were collected, and various bioinformatics methods, as well as machine learning algorithms, were employed to construct and validate the IRG-based signature and to explore the characteristics of the immune microenvironment of GBM. A five-gene signature (ARPC1B, FCGR2B, NCF2, PLAUR, and S100A11) was identified based on the expression of IRGs, and an effective prognostic risk model was developed. The IRG-based risk model had superior time-dependent prognostic performance compared to well-studied molecular pathology markers. Besides, we found prominent inflamed features in the microenvironment of the high-risk group, including neutrophil infiltration, immune checkpoint expression, and activation of the adaptive immune response, which may be associated with increased hypoxia, epidermal growth factor receptor (EGFR) wild type, and necrosis. Notably, the IRG-based risk model had the potential to predict the effectiveness of radiotherapy. Together, our study offers insights into the immune microenvironment of GBM and provides useful information for clinical management of this desperate disease.

A Unique Immune-Related Gene Signature Represents Advanced Liver Fibrosis and Reveals Potential Therapeutic Targets

Innate and adaptive immune responses are critically associated with the progression of fibrosis in chronic liver diseases. In this study, we aim to identify a unique immune-related gene signature representing advanced liver fibrosis and to reveal potential therapeutic targets. Seventy-seven snap-frozen liver tissues with various chronic liver diseases at different fibrosis stages (1: n = 12, 2: n = 12, 3: n = 25, 4: n = 28) were subjected to expression analyses. Gene expression analysis was performed using the nCounter PanCancer Immune Profiling Panel (NanoString Technologies, Seattle, WA, USA). Biological meta-analysis was performed using the CBS Probe PINGSTM (CbsBioscience, Daejeon, Korea). Using non-tumor tissues from surgically resected specimens, we identified the immune-related, five-gene signature (CHIT1_FCER1G_OSM_VEGFA_ZAP70) that reliably differentiated patients with low- (F1 and F2) and high-grade fibrosis (F3 and F4; accuracy = 94.8%, specificity = 91.7%, sensitivity = 96.23%). The signature was independent of all pathological and clinical features and was independently associated with high-grade fibrosis using multivariate analysis. Among these genes, the expression of inflammation-associated FCER1G, OSM, VEGFA, and ZAP70 was lower in high-grade fibrosis than in low-grade fibrosis, whereas CHIT1 expression, which is associated with fibrogenic activity of macrophages, was higher in high-grade fibrosis. Meta-analysis revealed that STAT3, a potential druggable target, highly interacts with the five-gene signature. Overall, we identified an immune gene signature that reliably predicts advanced fibrosis in chronic liver disease. This signature revealed potential immune therapeutic targets to ameliorate liver fibrosis.

Moringa oleifera Leaves’ Extract Enhances Nonspecific Immune Responses, Resistance against Vibrio alginolyticus, and Growth in Whiteleg Shrimp (Penaeus vannamei)

Moringa is widely known as a plant with high medicinal properties. Therefore, moringa has a high potential for use as an immunostimulant in shrimp. This study investigated the effect of a moringa water extract on the immune response, resistance against V. alginolyticus, and growth performance of whiteleg shrimp. To perform the in vitro assay, hemocytes were incubated with different concentrations of the moringa extract. Furthermore, the moringa extract was incorporated at 0 (control), 1.25 g (ME1.25), 2.5 g (ME2.5), and 5.0 g (ME5.0) per kg of diet for the in vivo assay. During the rearing period, immune responses, namely the total hemocyte count (THC), phenoloxidase (PO) activity, phagocytosis activity, superoxide anion production, and immune-related gene expression were examined on days 0, 1, 2, 4, 7, 14, 21, and 28. Growth performance was measured 60 days after the feeding period. Furthermore, the shrimp were challenged with V. alginolyticus after being fed for different feeding durations. The results of the in vitro assay revealed that 100–250 ppm of the moringa extract enhanced the PO activity, phagocytic rate (PR), and superoxide anion production. The findings of the in vivo assay demonstrated that the THC, PO activity, PR, and immune-related gene expression, including alpha-2-macroglobulin, prophenoloxidase II, penaeidin2, penaeidin3, anti-lipopolysaccharide factor, crustin, lysozyme, superoxide dismutase, and clotting protein, were higher in the group of ME.25 and ME5.0 than in the control and ME1.25 at several time points. Growth performance was significantly increased (p < 0.05) in the ME2.5 group compared to the control group. Furthermore, the dietary ME2.5 resulted in a higher survival rate compared to that of the control group after challenging with V. alginolyticus, especially at ME2.5 administered for 4 and 7 days. This study indicated that the incorporation of the moringa extract at 2.5 g per kg of diet enhanced the immune response, the growth performance of the whiteleg shrimp, and the resistance against V. alginolyticus infection.

Prognostic Value of an Immune-Related Gene Signature in Oral Squamous Cell Carcinoma

The prognosis and immunotherapy response rates are unfavorable in patients with oral squamous cell carcinoma (OSCC). The tumor microenvironment is associated with tumor prognosis and progression, and the underlying mechanisms remain unclear. We obtained differentially expressed immune-related genes from OSCC mRNA data in The Cancer Genome Atlas (TCGA) database. Overall survival-related risk signature was constructed by univariate Cox regression analysis and LASSO Cox regression analysis. The prognostic performance was validated with receiver operating characteristic (ROC) analysis and Kaplan–Meier survival curves in the TCGA and Gene Expression Omnibus (GEO) datasets. The risk score was confirmed to be an independent prognostic factor and a nomogram was built to quantify the risk of outcome for each patient. Furthermore, a negative correlation was observed between the risk score and the infiltration rate of immune cells, as well as the expression of immunostimulatory and immunosuppressive molecules. Functional enrichment analysis between different risk score subtypes detected multiple immune-related biological processes, metabolic pathways, and cancer-related pathways. Thus, the immune-related gene signature can predict overall survival and contribute to the personalized management of OSCC patients.

Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

Objective: Sciatica pertains to neuropathic pain that has been associated with inflammatory response. We aimed to identify significant immune-related biomarkers for sciatica in peripheral blood.Methods: We utilized the GSE150408 expression profiling data from the Gene Expression Omnibus (GEO) database as the training dataset and extracted immune-related genes for further analysis. Differentially expressed immune-related genes (DEIRGs) between healthy controls and patients with sciatica were selected using the “limma” package and verified in clinical specimens by quantitative reverse transcription PCR (RT-qPCR). A diagnostic immune-related gene signature was established using the training model and random forest (RF), generalized linear model (GLM), and support vector machine (SVM) models. Sciatica patient subtypes were identified using the consensus clustering method.Results: Thirteen significant DEIRGs were acquired, of which five (CRP, EREG, FAM19A4, RLN1, and WFIKKN1) were selected to establish a diagnostic immune-related gene signature according to the most appropriate training model, namely, the RF model. A clinical application nomogram model was established based on the expression level of the five DEIRGs. The sciatica patients were divided into two subtypes (C1 and C2) according to the consensus clustering method.Conclusions: Our research established a diagnostic five immune-related gene signature to discriminate sciatica and identified two sciatica subtypes, which may be beneficial to the clinical diagnosis and treatment of sciatica.