Immunogenicity and Therapeutic Challenges of IDH-Mutant Gliomas Background Glioma is a common central nervous system tumor, and its treatment and prognosis vary significantly depending on molecular characteristics. In recent years, the diagnostic and prognostic significance of isocitrate dehydrogenase (IDH) mutations in gliomas has been increasingl...

Induction of Tertiary Lymphoid Structures in Glioma Immunotherapy and Their Anti-Tumor Immune Effects Background Introduction Glioma is a highly malignant brain tumor characterized by limited lymphocyte infiltration in the tumor microenvironment (glioma microenvironment, GME), presenting an “immune desert” state. This characteristic makes glioma in...

Molecular Classification and Prognostic Features of Gliomas Background Introduction Glioma is the most common malignant brain tumor in adults, and its classification, risk stratification, and treatment standards have undergone significant changes in recent years. With the introduction of molecular markers, the classification system for gliomas has ...

Deciphering the Topological Landscape of Glioma: A Study Based on a Network Theory Framework Glioma stem cells (GSCs) are recognized as key factors in glioma recurrence and treatment resistance, making them an important focus for new therapeutic approaches. However, the limited understanding of the role of GSCs in the hierarchy of glioma has sparke...

Association of NID2 gene single nucleotide polymorphisms with glioma risk and prognosis in Chinese Han population Academic Background Glioma is the most common primary intracranial tumor, characterized by high mortality and poor prognosis. Despite some progress in diagnostic and treatment strategies, conventional therapies have limited improvement ...

Useful Features for Overall Survival Prediction in Low-Grade Glioma Patients Academic Background Glioma is a type of neoplastic growth in the brain that usually poses a serious threat to the patients’ lives. In most cases, glioma eventually leads to the death of the patient. The analysis of glioma typically involves examining pathological slices of...

Glioma Disease Prediction Based on Optimized Integrated Machine Learning Background and Research Objectives In medical research, gliomas are the most common type of primary brain tumors, encompassing various cancer types with different clinical behaviors and treatment outcomes. Accurate prognosis prediction for glioma patients is crucial for optimi...

Study of Attention-Guided CNN Framework for 3D MRI Glioma Segmentation and Grading Gliomas are the most deadly form of brain tumors in humans. Timely diagnosis of these tumors is a crucial step for effective tumor treatment. Magnetic Resonance Imaging (MRI) typically provides a non-invasive examination of brain lesions. However, manual inspection o...

Enabling Explainable Artificial Intelligence for Glioma Prognosis: Translational Insights from Transparent Machine Learning Academic Background This study is dedicated to developing a reliable technique to detect whether patients have a specific type of brain tumor—glioma—using various machine learning methods and deep learning methods, combined wi...

Survival Analysis of Glioblastoma Patients: An Overview Empowered by Data Engineering Introduction Glioblastoma is a type of tumor that occurs in glial cells and accounts for 26.7% of all primary brain and central nervous system tumors. Survival analysis of glioblastoma patients is a key task in clinical management due to the heterogeneity of the t...