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IntroductionGlioma, a prevalent and deadly brain tumor, is marked by significant cellular heterogeneity and metabolic alterations. However, the comprehensive cell-of-origin and metabolic landscape in high-grade (Glioblastoma Multiforme, WHO grade IV) and low-grade (Oligoastrocytoma, WHO grade II) gliomas remains elusive.MethodsIn this study, we undertook single-cell transcriptome sequencing of these glioma grades to elucidate their cellular and metabolic distinctions. Following the identification of cell types, we compared metabolic pathway activities and gene expressions between high-grade and low-grade gliomas.ResultsNotably, astrocytes and oligodendrocyte progenitor cells (OPCs) exhibited the most substantial differences in both metabolic pathways and gene expression, indicative of their distinct origins. The comprehensive analysis identified the most altered metabolic pathways (MCPs) and genes across all cell types, which were further validated against TCGA and CGGA datasets for clinical relevance.DiscussionCrucially, the metabolic enzyme phosphodiesterase 8B (PDE8B) was found to be exclusively expressed and progressively downregulated in astrocytes and OPCs in higher-grade gliomas. This decreased expression identifies PDE8B as a metabolism-related oncogene in IDH-mutant glioma, marking its dual role as both a protective marker for glioma grading and prognosis and as a facilitator in glioma progression.

PurposeA tertiary lymphoid structure (TLS) refers to an organized infiltration of immune cells that is linked to a positive prognosis and improved response to immunotherapy. However, methods that promote TLS formation are limited and challenging to implement in clinical settings. In this study, we aimed to promote the formation and maturation of TLSs in lung adenocarcinoma (LUAD) by combining low-dose radiotherapy (LDRT) with immunotherapy.MethodsTissue sections from 198 patients who had undergone surgery were examined. Risk factors for patient survival were assessed, and the relationship between TLSs and five-year survival was analyzed. The Kras-LSL-G12D spontaneous lung cancer mouse model was used to screen the optimal irradiation dose (0/1/2 Gy whole lung irradiation) for promoting TLS formation. LDRT combined with anti-PD-1 was used to promote the formation and maturation of TLSs.ResultsTLS+, TLSHigh, TLS+GC+ and CD8High within TLS+ were associated with a favorable prognosis. LDRT increased the formation of early TLSs in the Kras-LSL-G12D lung cancer mouse model. In addition, LDRT combined with anti-PD-1 treatment can significantly improve the maturity of TLSs in mouse LUAD, resulting in greater antitumor effects. This antitumor effect was strongly associated with the number of CD8+ T cells within the TLSs.ConclusionWe successfully applied LDRT combined with PD-1 inhibitor therapy for the first time, which increased both the quantity and maturity of TLSs in lung cancer. This approach achieved a promising antitumor effect.

BackgroundOsteosarcoma is the most frequent primary bone tumor with a poor prognosis. Immune infiltration proved to have a strong impact on prognosis. We analyzed single-cell datasets and bulk datasets to confirm the main immune cell populations and their properties in osteosarcoma.MethodsThe examples in bulk datasets GSE21257 and GSE32981 from the Gene Expression Omnibus database were divided into two immune infiltration level groups, and 34 differentially expressed genes were spotted. Then, we located these genes among nine major cell clusters and their subclusters identified from 99,668 individual cells in single-cell dataset GSE152048 including 11 osteosarcoma patients. Especially, the markers of all kinds of myeloid cells identified in single-cell dataset GSE152048 were set to gene ontology enrichment. We clustered the osteosarcoma samples in the TARGET-OS from the Therapeutically Applicable Research to Generate Effective Treatments dataset into two groups by complete component 1q positive macrophage markers and compared their survival.ResultsCompared with the low-immune infiltrated group, the high-immune infiltrated group showed a better prognosis. Almost all the 34 differentially expressed genes expressed higher or exclusively among myeloid cells. A group of complete component 1q-positive macrophages was identified from the myeloid cells. In the bulk dataset TARGET-OS, these markers and the infiltration of complete component 1q-positive macrophages related to longer survival.ConclusionsComplete component 1q-positive tumor-associated macrophages were the major immune cell population in osteosarcoma, which contributed to a better prognosis.

The most common bone cancer is osteosarcoma (OS), which mostly affects children and teenagers. Early surgical resection combined with chemotherapy significantly improves the prognosis of patients with OS. Existing chemotherapies have poor efficacy in individuals with distant metastases or inoperable resection, and these patients may respond better to novel immunotherapies. Immune escape, which is mediated by immunosuppressive cells in the tumour microenvironment (TME), is a major cause of poor OS prognosis and a primary target of immunotherapy. Myeloid-derived suppressor cells, regulatory T cells, and tumour-associated macrophages are the main immunosuppressor cells, which can regulate tumorigenesis and growth on a variety of levels through the interaction in the TME. The proliferation, migration, invasion, and epithelial–mesenchymal transition of OS cells can all be impacted by the expression of non-coding RNAs (ncRNAs), which can also influence how immunosuppressive cells work and support immune suppression in TME. Interferon, checkpoint inhibitors, cancer vaccines, and engineered chimeric antigen receptor (CAR-T) T cells for OS have all been developed using information from studies on the metabolic properties of immunosuppressive cells in TME and ncRNAs in OS cells. This review summarizes the regulatory effect of ncRNAs on OS cells as well as the metabolic heterogeneity of immunosuppressive cells in the context of OS immunotherapies.

Alzheimer’s disease (AD) is a common neurodegenerative disorder without an effective treatment, and results in an increasingly serious health problem. However, its pathogenesis is complex and poorly understood. Nonetheless, the exact role of dysfunctional glucose metabolism in AD pathogenesis remains unclear. We screened 28 core glycolysis-related genes and introduced a novel metric, the glycolysis index, to estimate the activation of glycolysis. The glycolysis index was significantly lower in the AD group in four different brain regions (frontal cortex, FC; temporal cortex, TC; hippocampus, HP; and entorhinal cortex, EC) than that in the control group. Combined with differential expression and over-representation analyses, we determined the clinical and pathological relevance of glycolysis in AD. Subsequently, we investigated the role of glycolysis in the AD brain microenvironment. We developed a glycolysis-brain cell marker connection network, which revealed a close relationship between glycolysis and seven brain cell types, most of which presented abundant variants in AD. Using immunohistochemistry, we detected greater infiltrated microglia and higher expression of glycolysis-related microglia markers in the APP/PS1 AD model than that in the control group, consistent with our bioinformatic analysis results. Furthermore, the excellent predictive value of the glycolysis index has been verified in different populations. Overall, our present findings revealed the clinical and biological significance of glycolysis and the brain microenvironment in AD.

ObjectiveThis study aimed to explore the shared mechanism and candidate drugs of multiple sclerosis (MS) and Sjögren’s syndrome (SS).MethodsMS- and SS-related susceptibility genes and differentially expressed genes (DEGs) were identified by bioinformatics analysis based on genome-wide association studies (GWAS) and transcriptome data from GWAS catalog and Gene Expression Omnibus (GEO) database. Pathway enrichment, Gene Ontology (GO) analysis, and protein–protein interaction analysis for susceptibility genes and DEGs were performed. The drugs targeting common pathways/genes were obtained through Comparative Toxicogenomics Database (CTD), DrugBank database, and Drug–Gene Interaction (DGI) Database. The target genes of approved/investigational drugs for MS and SS were obtained through DrugBank and compared with the common susceptibility genes.ResultsBased on GWAS data, we found 14 hub common susceptibility genes (HLA-DRB1, HLA-DRA, STAT3, JAK1, HLA-B, HLA-DQA1, HLA-DQA2, HLA-DQB1, HLA-DRB5, HLA-DPA1, HLA-DPB1, TYK2, IL2RA, and MAPK1), with 8 drugs targeting two or more than two genes, and 28 common susceptibility pathways, with 15 drugs targeting three or more than three pathways. Based on transcriptome data, we found 3 hub common DEGs (STAT1, GATA3, PIK3CA) with 3 drugs and 10 common risk pathways with 435 drugs. “JAK-STAT signaling pathway” was included in common susceptibility pathways and common risk pathways at the same time. There were 133 overlaps including JAK-STAT inhibitors between agents from GWAS and transcriptome data. Besides, we found that IL2RA and HLA-DRB1, identified as hub common susceptibility genes, were the targets of daclizumab and glatiramer that were used for MS, indicating that daclizumab and glatiramer may be therapeutic for SS.ConclusionWe observed the shared mechanism of MS and SS, in which JAK-STAT signaling pathway played a vital role, which may be the genetic and molecular bases of comorbidity of MS with SS. Moreover, JAK-STAT inhibitors were potential therapies for MS and SS, especially for their comorbidity.