Background: Peritumoral brain edema (PTBE) represents a characteristic phenotype of intracranial gliomas. However, there is a lack of consensus regarding the prognosis and mechanism of PTBE. In this study, clinical imaging data, along with publicly available imaging data, were utilized to assess the prognosis of PTBE in glioblastoma (GBM) patients, and the associated mechanisms were preliminarily analyzed.
Methods: We investigated relevant imaging features, including edema, in GBM patients using ITK-SNAP imaging segmentation software. Risk factors affecting progression-free survival (PFS) and overall survival (OS) were assessed using a Cox proportional hazard regression model. In addition, the impact of PTBE on PFS and OS was analyzed in clinical GBM patients using the Kaplan-Meier survival analysis method, and the results further validated by combining data from The Cancer Imaging Archive (TCIA) and The Cancer Genome Atlas (TCGA). Finally, functional enrichment analysis based on TCIA and TCGA datasets identified several pathways potentially involved in the mechanism of edema formation.
Results: This study included a total of 32 clinical GBM patients and 132 GBM patients from public databases. Univariate and multivariate analyses indicated that age and edema index (EI) are independent risk factors for PFS, but not for OS. Kaplan-Meier curves revealed consistent survival analysis results between IE groups among both clinical patients and TCIA and TCGA patients, suggesting a significant effect of PTBE on PFS but not on OS. Furthermore, functional enrichment analysis predicted the involvement of several pathways related mainly to cellular bioenergetics and vasculogenic processes in the mechanism of PTBE formation. While these novel results warrant confirmation in a larger patient cohort, they support good prognostic value for PTBE assessment in GBM.
Conclusions: Our results indicate that a low EI positively impacts disease control in GBM patients, but this does not entirely translate into an improvement in OS. Multiple genes, signaling pathways, and biological processes may contribute to the formation of peritumoral edema in GBM through cytotoxic and vascular mechanisms.
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http://dx.doi.org/10.3389/fonc.2024.1417208 | DOI Listing |
Adv Sci (Weinh)
January 2025
The First Hospital of China Medical University, Liaoning, 110001, China.
Glioblastoma multiforme (GBM) is a highly aggressive and malignant brain tumor originating from glial cells, characterized by high recurrence rates and poor patient prognosis. The heterogeneity and complex biology of GBM, coupled with the protective nature of the blood-brain barrier (BBB), significantly limit the efficacy of traditional therapies. The rapid development of nanoenzyme technology presents a promising therapeutic paradigm for the rational and targeted treatment of GBM.
View Article and Find Full Text PDFCurr Oncol
December 2024
Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, 9000 Rockville Pike, Building 10, CRC, Bethesda, MD 20892, USA.
Glioblastoma (GBM) is a primary central nervous system malignancy with a median survival of 15-20 months. The presence of both intra- and intertumoral heterogeneity limits understanding of biological mechanisms leading to tumor resistance, including immune escape. An attractive field of research to examine treatment resistance are immune signatures composed of cluster of differentiation (CD) markers and cytokines.
View Article and Find Full Text PDFCells
January 2025
Department of Neuro-Oncology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL 33612, USA.
Glioblastoma (GBM) is a highly aggressive brain tumor characterized by its ability to evade the immune system, hindering the efficacy of current immunotherapies. Recent research has highlighted the important role of immunosuppressive macrophages in the tumor microenvironment (TME) in driving this immune evasion. In this study, we are the first to identify as a key regulator of tumor-associated macrophage (TAM)-mediated immunosuppression in GBM.
View Article and Find Full Text PDFFront Cardiovasc Med
January 2025
Shengli Clinical Medical College of Fujian Medical University, Fujian Medical University, Fuzhou, Fujian, China.
Background: Depression is being increasingly acknowledged as an important risk factor contributing to coronary heart disease (CHD). Currently, there is no predictive model specifically designed to evaluate the risk of coronary heart disease among individuals with depression. We aim to develop a machine learning (ML) model that will analyze risk factors and forecast the probability of coronary heart disease in individuals suffering from depression.
View Article and Find Full Text PDFEur J Med Res
January 2025
Department of Neurosurgery, Institute of Brain Diseases, Nanfang Hospital, Southern Medical University, Guangzhou Avenue North No.1838, Guangzhou, 510515, Guangdong, People's Republic of China.
The identification of oncogenic gene fusions in diffuse gliomas may serve as potential therapeutic targets and prognostic indicators, representing a novel strategy for treating gliomas consistent with the principles of personalized medicine. This study identified detectable oncogene fusions in glioma patients through an integrated analysis of genomic and transcriptomic data, which encompassed whole exon sequencing and next-generation RNA sequencing. In addition, this study also conducted a comparison of the genetic characteristics, tumor microenvironment, mutation burden and survival between glioma patients with or without gene fusions.
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