Identification of molecular subtypes based on inflammatory response in lower-grade glioma

Characterizing the Linkage of Systemic Hypoxia and Angiogenesis in High-Grade Glioma to Define the Changes in Tumor Microenvironment for Predicting Prognosis

High-grade gliomas (HGG) comprising WHO grades 3 and 4 have a poor overall survival (OS) that has not improved in the past decade. Herein, markers representing four components of the tumor microenvironment (TME) were identified to define their linked expression in TME and predict the prognosis in HGG, namely, interleukin6 (IL6, inflammation), inducible nitric oxide synthase(iNOS), heat shock protein-70 (HSP70, hypoxia), vascular endothelial growth receptor (VEGF), and endothelin1 (ET1) (angiogenesis) and matrix metalloprotease-14 (MMP14) and intercellular adhesion molecule1 (ICAM1, extracellular matrix). To establish a non-invasive panel of biomarkers for precise prognostication in HGG. Eighty-six therapy-naive HGG patients with 45 controls were analyzed for the defined panel. Systemic expression of extracellular/secretory biomarkers was screened dot-immune assay (DIA), quantified by ELISA, and validated by immunocytochemistry (ICC). Expression of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 was found to be positively associated with grade. Quantification of circulating levels of the markers by ELISA and ICC presented a similar result. The biomarkers were observed to negatively correlate with OS (p < 0.0001). Cox-regression analysis yielded all biomarkers as good prognostic indicators and independent of confounders. On applying combination statistics, the biomarker panel achieved higher sensitivity than single markers to define survival. The intra-association of all seven biomarkers was significant, hinting of a cross-talk between the TME components and a hypoxia driven systemic inflammation upregulating the expression of other components. This is a first ever experimental study of a marker panel that can distinguish between histopathological grades and also delineate differential survival using liquid biopsy, suggesting that markers of hypoxia can be a cornerstone for personalized therapy. The panel of biomarkers of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 holds promise for prognostication in HGG.

IGFBP1 stabilizes Umod expression through m6A modification to inhibit the occurrence and development of cystitis by blocking NF-κB and ERK signaling pathways

Cystitis is a common disease closely associated with urinary tract infections, and the specific mechanisms underlying its occurrence and development remain largely unknown. In this study, we discovered that IGFBP1 suppresses the occurrence and development of cystitis by stabilizing the expression of Umod through m6A modification, inhibiting the NF-κB and ERK signaling pathways. Initially, we obtained a bladder cystitis-related transcriptome dataset from the GEO database and identified the characteristic genes Umod and IGFBP1. Further exploration revealed that IGFBP1 in primary cells of cystitis can stabilize the expression of Umod through m6A modification. Overexpression of both IGFBP1 and Umod significantly inhibited cell apoptosis and the NF-κB and ERK signaling pathways, ultimately suppressing the production of pro-inflammatory factors. Finally, using a rat model of cystitis, we demonstrated that overexpression of IGFBP1 stabilizes the expression of Umod, inhibits the NF-κB and ERK signaling pathways, reduces the production of pro-inflammatory factors, and thus prevents the occurrence and development of cystitis. Our study elucidates the crucial role of IGFBP1 and Umod in cystitis and reveals the molecular mechanisms that inhibit the occurrence and development of cystitis. This research holds promise for offering new insights into the treatment of cystitis in the future.

Irisin alleviates obesity-induced bone loss by inhibiting interleukin 6 expression via TLR4/MyD88/NF-κB axis in adipocytes

INTRODUCTION

Obesity-induced bone loss affects the life quality of patients all over the world. Irisin, one of the myokines, plays an essential role in bone and fat metabolism.

OBJECTIVE

Investigate the effects of irisin on bone metabolism via adipocytes in the bone marrow microenvironment.

METHODS

In this study, we fed fibronectin type III domain-containing protein 5 (FNDC5, the precursor protein of irisin) knockout mice (FNDC5-/-) with a high-fat diet (HFD) for 10 weeks. The quality of bone mass was assessed by micro-CT analysis, histological staining, and dynamic bone formation. In vitro, the lipogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) was assayed by Oil Red O staining, and the osteogenic differentiation was assayed by alkaline phosphatase staining. Meanwhile, the gene expression in the BMSC-differentiated adipocytes by RNA sequence and the involved pathway of irisin were determined by western blot and qRT-PCR were performed.

RESULTS

The FNDC5-/- mice fed with a HFD showed an increased body weight, fat content of the bone marrow and bone, and a decreased bone formation compared with those with a standard diet (SD). In vitro, irisin inhibited the differentiation of BMSCs into adipocytes and alleviated the inhibition of osteogenesis derived from BMSCs by the adipocyte supernatant. RNA sequence and blocking experiment showed that irisin reduced the production of interleukin 6 (IL-6) in adipocytes through downregulating the TLR4/MyD88/NF-κB pathway. Immunofluorescence staining of bone marrow further confirmed an increased IL-6 expression in the FNDC5-/- mice fed with HFD compared with those fed with SD, which suffered serious bone loss.

CONCLUSION

Irisin downregulates activation of the TLR4/MyD88/NF-κB pathway, thereby reducing IL-6 production in adipocytes to enhance the osteogenesis of BMSCs. Thus, the rescue of osteogenesis of BMSCs, initially inhibited by IL-6, is a potential therapeutic target to mitigate obesity-induced osteoporosis.

Investigation of the mechanism of silica-induced pulmonary fibrosis: The role of lung microbiota dysbiosis and the LPS/TLR4 signaling pathway

The widespread manufacture of silica and its extensive use, and potential release of silica into the environment pose a serious human health hazard. Silicosis, a severe global public health issue, is caused by exposure to silica, leading to persistent inflammation and fibrosis of the lungs. The underlying pathogenic mechanisms of silicosis remain elusive. Lung microbiota dysbiosis is associated with the development of inflammation and fibrosis. However, limited information is currently available regarding the role of lung microbiota in silicosis. The study therefore is designed to conduct a comprehensive analysis of the role of lung microbiota dysbiosis and establish a basis for future investigations into the potential mechanisms underlying silicosis. Here, the pathological and biochemical parameters were used to systematically assessed the degree of inflammation and fibrosis following silica exposure and treatment with combined antibiotics. The underlying mechanisms were studied via integrative multi-omics analyses of the transcriptome and microbiome. Analysis of 16S ribosomal DNA revealed dysbiosis of the microbial community in silicosis, characterized by a predominance of gram-negative bacteria. Exposure to silica has been shown to trigger lung inflammation and fibrosis, leading to an increased concentration of lipopolysaccharides in the bronchoalveolar lavage fluid. Furthermore, Toll-like receptor 4 was identified as a key molecule in the lung microbiota dysbiosis associated with silica-induced lung fibrosis. All of these outcomes can be partially controlled through combined antibiotic administration. The study findings demonstrate that the dysbiosis of lung microbiota enhances silica-induced fibrosis associated with the lipopolysaccharides/Toll-like receptor 4 pathway and provided a promising target for therapeutic intervention of silicosis.

Glioma: bridging the tumor microenvironment, patient immune profiles and novel personalized immunotherapy

Glioma is the most common primary brain tumor, characterized by a consistently high patient mortality rate and a dismal prognosis affecting both survival and quality of life. Substantial evidence underscores the vital role of the immune system in eradicating tumors effectively and preventing metastasis, underscoring the importance of cancer immunotherapy which could potentially address the challenges in glioma therapy. Although glioma immunotherapies have shown promise in preclinical and early-phase clinical trials, they face specific limitations and challenges that have hindered their success in further phase III trials. Resistance to therapy has been a major challenge across many experimental approaches, and as of now, no immunotherapies have been approved. In addition, there are several other limitations facing glioma immunotherapy in clinical trials, such as high intra- and inter-tumoral heterogeneity, an inherently immunosuppressive microenvironment, the unique tissue-specific interactions between the central nervous system and the peripheral immune system, the existence of the blood-brain barrier, which is a physical barrier to drug delivery, and the immunosuppressive effects of standard therapy. Therefore, in this review, we delve into several challenges that need to be addressed to achieve boosted immunotherapy against gliomas. First, we discuss the hurdles posed by the glioma microenvironment, particularly its primary cellular inhabitants, in particular tumor-associated microglia and macrophages (TAMs), and myeloid cells, which represent a significant barrier to effective immunotherapy. Here we emphasize the impact of inducing immunogenic cell death (ICD) on the migration of Th17 cells into the tumor microenvironment, converting it into an immunologically "hot" environment and enhancing the effectiveness of ongoing immunotherapy. Next, we address the challenge associated with the accurate identification and characterization of the primary immune profiles of gliomas, and their implications for patient prognosis, which can facilitate the selection of personalized treatment regimens and predict the patient's response to immunotherapy. Finally, we explore a prospective approach to developing highly personalized vaccination strategies against gliomas, based on the search for patient-specific neoantigens. All the pertinent challenges discussed in this review will serve as a compass for future developments in immunotherapeutic strategies against gliomas, paving the way for upcoming preclinical and clinical research endeavors.

Leveraging a gene signature associated with disulfidptosis identified by machine learning to forecast clinical outcomes, immunological heterogeneities, and potential therapeutic targets within lower-grade glioma

Background

Disulfidptosis, a newly defined type of programmed cell death, has emerged as a significant regulatory process in the development and advancement of malignant tumors, such as lower-grade glioma (LGG). Nevertheless, the precise biological mechanisms behind disulfidptosis in LGG are yet to be revealed, considering the limited research conducted in this field.

Methods

We obtained LGG data from the TCGA and CGGA databases and performed comprehensive weighted co-expression network analysis, single-sample gene set enrichment analysis, and transcriptome differential expression analyses. We discovered nine genes associated with disulfidptosis by employing machine learning methods like Cox regression, LASSO regression, and SVM-RFE. These were later used to build a predictive model for patients with LGG. To confirm the expression level, functional role, and impact on disulfidptosis of ABI3, the pivotal gene of the model, validation experiments were carried out in vitro.

Results

The developed prognostic model successfully categorized LGG patients into two distinct risk groups: high and low. There was a noticeable difference in the time the groups survived, which was statistically significant. The model's predictive accuracy was substantiated through two independent external validation cohorts. Additional evaluations of the immune microenvironment and the potential for immunotherapy indicated that this risk classification could function as a practical roadmap for LGG treatment using immune-based therapies. Cellular experiments demonstrated that suppressing the crucial ABI3 gene in the predictive model significantly reduced the migratory and invasive abilities of both SHG44 and U251 cell lines while also triggering cytoskeletal retraction and increased cell pseudopodia.

Conclusion

The research suggests that the prognostic pattern relying on genes linked to disulfidptosis can provide valuable insights into the clinical outcomes, tumor characteristics, and immune alterations in patients with LGG. This could pave the way for early interventions and suggests that ABI3 might be a potential therapeutic target for disulfidptosis.

Dysregulation of inflammasome activation in glioma

Gliomas are the most common brain tumors characterized by complicated heterogeneity. The genetic, molecular, and histological pathology of gliomas is characterized by high neuro-inflammation. The inflammatory microenvironment in the central nervous system (CNS) has been closely linked with inflammasomes that control the inflammatory response and coordinate innate host defenses. Dysregulation of the inflammasome causes an abnormal inflammatory response, leading to carcinogenesis in glioma. Because of the clinical importance of the various physiological properties of the inflammasome in glioma, the inflammasome has been suggested as a promising treatment target for glioma management. Here, we summarize the current knowledge on the contribution of the inflammasomes in glioma and therapeutic insights. Video Abstract.

Micro-inflammation related gene signatures are associated with clinical features and immune status of fibromyalgia

BACKGROUND

Fibromyalgia (FM) is a multifaceted disease. Along with the genetic, environmental and neuro-hormonal factors, inflammation has been assumed to have role in the pathogenesis of FM. The aim of the present study was to explore the differences in clinical features and pathophysiology of FM patients under different inflammatory status.

METHODS

The peripheral blood gene expression profile of FM patients in the Gene Expression Omnibus database was downloaded. Differentially expressed inflammatory genes were identified, and two molecular subtypes were constructed according to these genes used unsupervised clustering analysis. The clinical characteristics, immune features and pathways activities were compared further between the two subtypes. Then machine learning was used to perform the feature selection and construct a classification model.

RESULTS

The patients with FM were divided into micro-inflammation and non-inflammation subtypes according to 54 differentially expressed inflammatory genes. The micro-inflammation group was characterized by more major depression (p = 0.049), higher BMI (p = 0.021), more active dendritic cells (p = 0.010) and neutrophils. Functional enrichment analysis showed that innate immune response and antibacterial response were significantly enriched in micro-inflammation subtype (p < 0.050). Then 5 hub genes (MMP8, ENPP3, MAP2K3, HGF, YES1) were screened thought three feature selection algorithms, an accurate classifier based on the 5 hub DEIGs and 2 clinical parameters were constructed using support vector machine model. Model scoring indicators such as AUC (0.945), accuracy (0.936), F1 score (0.941), Brier score (0.079) and Hosmer-Lemeshow goodness-of-fit test (χ2 = 4.274, p = 0.832) proved that this SVM-based classifier was highly reliable.

CONCLUSION

Micro-inflammation status in FM was significantly associated with the occurrence of depression and activated innate immune response. Our study calls attention to the pathogenesis of different subtypes of FM.