Glioblastoma (GBM) represents a profoundly aggressive and heterogeneous brain neoplasm linked to a bleak prognosis. Hypoxia, a common feature in GBM, has been linked to tumor progression and therapy resistance. In this study, we aimed to identify hypoxia-related differentially expressed genes (DEGs) and construct a prognostic signature for GBM patients using multi-omics analysis. Patient cohorts were collected from publicly available databases, including the Gene Expression Omnibus (GEO), the Chinese Glioma Genome Atlas (CGGA), and The Cancer Genome Atlas—Glioblastoma Multiforme (TCGA-GBM), to facilitate a comprehensive analysis. Hypoxia-related genes (HRGs) were obtained from the Molecular Signatures Database (MSigDB). Differential expression analysis revealed 41 hypoxia-related DEGs in GBM patients. A consensus clustering approach, utilizing these DEGs’ expression patterns, identified four distinct clusters, with cluster 1 showing significantly better overall survival. Machine learning techniques, including univariate Cox regression and LASSO regression, delineated a prognostic signature comprising six genes (ANXA1, CALD1, CP, IGFBP2, IGFBP5, and LOX). Multivariate Cox regression analysis substantiated the prognostic significance of a set of three optimal signature genes (CP, IGFBP2, and LOX). Using the hypoxia-related prognostic signature, patients were classified into high- and low-risk categories. Survival analysis demonstrated that the high-risk group exhibited inferior overall survival rates in comparison to the low-risk group. The prognostic signature showed good predictive performance, as indicated by the area under the curve (AUC) values for one-, three-, and five-year overall survival. Furthermore, functional enrichment analysis of the DEGs identified biological processes and pathways associated with hypoxia, providing insights into the underlying mechanisms of GBM. Delving into the tumor immune microenvironment, our analysis revealed correlations relating the hypoxia-related prognostic signature to the infiltration of immune cells in GBM. Overall, our study highlights the potential of a hypoxia-related prognostic signature as a valuable resource for forecasting the survival outcome of GBM patients. The multi-omics approach integrating bulk sequencing, single-cell analysis, and immune microenvironment assessment enhances our understanding of the intricate biology characterizing GBM, thereby potentially informing the tailored design of therapeutic interventions.

Background: Migraine is a primary headache disorder that causes debilitating throbbing pain. Several functional MRI (fMRI) and voxel-based morphometry (VBM) studies have been used to investigate the structural and functional alteration in migraine. Here, we aim to study the converged brain regions of functional and structural abnormalities in gray matter volume (GMV) associated with pain processing and management in migraineurs and healthy controls (HC). Methods: A systematic search through PubMed and Sleuth was carried out for peer-reviewed functional and structural neuroimaging studies on migraine patients and HC yielded a total of 1136 studies. We performed an activation likelihood estimation (ALE) meta-analysis on VBM and pain stimulation task-based fMRI studies to investigate the converged areas of GMV and functional abnormalities between migraineurs and HC. We performed two subgroup analyses between migraine with aura (MwA) and migraine without aura (MwoA) relative to HC, and between chronic migraine (CM) and episodic migraine (EM) compared to HC. Results: The total sample included 16 fMRI and 22 VBM studies, consisting of 1295 migraine patients, compared to 995 HC. In fMRI analysis, ALE maps for pain stimulation tasks revealed hyperactivation in migraineurs in the substantia nigra compared to HC, whereas hypoactivation was seen in the cerebellum. For the VBM analysis, ALE clusters of increased GMV in migraineurs were observed in the parahippocampus and putamen nucleus. Whereas clusters of reduced GMV in migraineurs were seen in the frontal gyri. Compared to HC, MwoA patients showed a GMV reduction in the insula, and anterior cingulate, whereas MwA patients showed GMV reduction in the cerebellum, cingulate gyrus, and insula. CM patients showed decreased GMV in the precentral gyrus, whereas EM patients showed decreased GMV in the parahippocampus, and inferior frontal gyrus when compared to HC. Conclusions: Our findings represent a potential biomarker for the diagnosis and management of migraine, by showing clustered brain regions of abnormal patterns of activation and GMV changes between migraineurs and HC which might be associated with hyposensitivity to pain in migraineurs. Further studies are required to determine disease progression or therapeutic interventions’ effect on migraine.