Glioblastoma (GBM) is a highly heterogeneous disease with poor clinical outcomes. To comprehensively dissect the molecular landscape of GBM and heterogeneous macrophage clusters in the progression of GBM, this study integrates single-cell and bulk transcriptome data to recognize a distinct pro-tumor macrophage cluster significantly associated with the prognosis of GBM and develop a GBM prognostic signature to facilitate prior subtypes. Leveraging glioma single-cell sequencing data, we identified a novel pro-tumor macrophage subgroup, marked by S100A9, which might interact with endothelial cells to facilitate tumor progression via angiogenesis. To further benefit clinical application, a prognostic signature was established with the genes associated with pro-tumor macrophages. Patients classified within the high-risk group characterized with enrichment in functions related to tumor progression, including epithelial-mesenchymal transition and hypoxia, displays elevated mutations in the TERT promoter region, reduced methylation in the MGMT promoter region, poorer prognoses, and diminished responses to temozolomide therapy, thus effectively discriminating between the prognostic outcomes of GBM patients. Our research sheds light on the intricate microenvironment of gliomas and identifies potential molecular targets for the development of novel therapeutic approaches.

OBJECTIVE: High-grade gliomas (HGGs) are highly malignant, aggressive, and have a high incidence and mortality rate. The aim of this study was to investigate survival outcomes and prognostic factors in patients with HGGs.
METHODS: In this retrospective study, a total of 159 patients with histologically confirmed HGGs were included. The recruitment period was from January 2011 to December 2019. We evaluated patient demographic data, tumor characteristics, treatment methods, immunocytochemistry results, overall survival (OS) time, and progression-free survival (PFS) time using Kaplan-<>Meier survival analysis with log-rank testing. Additionally, we employed Cox regression analysis to identify independent factors associated with survival outcomes.
RESULTS: Kaplan-Meier survival analysis revealed that the 1-, 2-, and 5-years OS rates were 81.8%, 50.3%, and 12.6%, respectively. Similarly, the 1-, 2-, and 5-years PFS rates were 50.9%, 22.4%, and 3.1%, respectively. The median OS duration was 35.0 months. The univariate analysis indicated that postoperative pathological classification, grade, and age were significantly associated with patient outcomes (p < 0.01). Among the patients, 147 received concurrent chemoradiotherapy, while 12 did not. The immunohistochemical markers of ki-67, MGMT, IDH1R132H, and p53 demonstrated statistically significant differences in their prognostic impact (p = 0.001, p = 0.020, p = 0.003, and p = 0.021, respectively). In conclusion, we found that grades, age, pathological classification, ki-67, MGMT, and IDH1R132H expression were statistically significantly associated with PFS (p < 0.01, p = 0.004, p = 0.003, p = 0.001, p = 0.036, and p = 0.028). Additionally, immunohistochemical expressions of TRIB3 and AURKA were significantly higher in patients with shorter survival (p = 0.015 and p = 0.023).
CONCLUSIONS: Tumor grade and the use of concurrent chemoradiotherapy after surgery were independent prognostic factors that significantly influenced patient survival. Additionally, tumor grade and MGMT expression were found to be independent factors affecting progression-free survival (PFS). Notably, the expression of TRIB3 and AURKA was higher in patients with poor survival outcomes.

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O6-methylguanine DNA methyltransferase (MGMT) is a crucial determinant of temozolomide (TMZ) sensitivity in patients with glioblastoma (GBM). The therapeutic potential of small interfering RNA (siRNA) targeting MGMT to enhance TMZ sensitivity has been hampered by serum nuclease degradation, off-target effects, poor accumulation at tumor sites, and low circulation in blood stream. In this study, we developed a framework nucleic acid-based nanoparticles (FNN), which is constructed from a six-helix DNA bundle, to encapsulate and protect siMGMT for improving TMZ sensitivity in GBM treatment. For better blood-brain barrier (BBB) penetration and GBM targeting, we conjugated Angiopep-2 (ANG) targeting modules to each end of the FNN. Nucleolin (NCL)-responsive locks were engineered along the sides of the six-helix DNA bundle, which safeguard siMGMT before tumor entry. Upon interaction with tumor-overexpressed NCL, these locks unlock, exposing siMGMT, this allows for effective suppression of MGMT, resulting in a significant improvement of TMZ therapeutic efficacy in GBM. This innovative strategy has the potential to transform the current treatment landscape for GBM.

OBJECTIVE: Analysis of long-lived patients from the group of patients with glioblastomas after using photodynamic therapy in the structure of their complex treatment in order to assess the influence of various factors on their life expectancy.
METHODS: In total, a single-center, retrospective categorical study analyzed the long-term results of treatment of 63 patients with glioblastoma in the structure of complex treatment including photodynamic therapy. Clinical factors (age, sex, number of cases, preoperative Karnofsky index, location and size of the tumor, radicality of the operation), histological (nuclear polymorphism, mitosis, vascular proliferation, necrosis), immunohistochemical (Ki-67, p53 index) molecular-genetic factors (expression of VEGF, MGMT, IDH, CD34), amount of radiation and chemotherapy were analyzed.
RESULTS: In the entire group of patients, there was a direct correlation of life expectancy with MGMT status, IDH status, the number of courses of chemotherapy, the age of the patient, and the severity of the first surgical intervention.
CONCLUSIONS: Clinical features such as age at diagnosis and extent of surgical resection and amount of chemotherapy have predictive value in assessing their effect on life expectancy. Mutations in IDH and MGMT promoter methylation were the most important molecular factors determining long-term patient survival.
UNASSIGNED: Анализ длительно живущих пациентов из группы больных глиобластомами после использования в структуре их комплексного лечения фотодинамической терапии с целью оценки влияния различных факторов на величину продолжительности жизни.
UNASSIGNED: В одноцентровом, ретроспективном категориальном исследовании анализировались отдаленные результаты лечения 63 пациентов с глиобластомой, в структуре комплексного лечения которых применена фотодинамическая терапия. Анализировались клинические факторы (возраст, пол, количество случаев, предоперационный индекс Карновского, локализация и размер опухоли, радикальность операции), гистологические (ядерный полиморфизм, митозы, сосудистая пролиферация, некрозы), иммуногистохимические (индекс Ki-67, p53), молекулярно-генетические факторы (экспрессия VEGF, MGMT, IDH, CD34), объем лучевой и химиотерапии.
UNASSIGNED: Исходя из полученных данных, прямая корреляционная связь среди всей группы пациентов была между продолжительностью жизни и статусом MGMT, IDH-статусом, количеством курсов проводимой химотерапии, возрастом пациента, радикальностью проводимого первого оперативного вмешательства.
UNASSIGNED: Клинические особенности, такие как возраст на момент постановки диагноза и степень хирургической резекции, объем химиотерапии, имели прогностическую значимость при оценке их влияния на продолжительность жизни. Мутации IDH и MGMT-метилирование промотора явились наиболее важными молекулярными факторами, определяющими долгосрочную выживаемость пациентов.

Background.Glioblastoma Multiforme (GBM) is an aggressive form of malignant brain tumor with a generally poor prognosis.O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation has been shown to be a predictive bio-marker for resistance to treatment of GBM, but it is invasive and time-consuming to determine methylation status. There has been effort to predict the MGMT methylation status through analyzing MRI scans using machine learning, which only requires pre-operative scans that are already part of standard-of-care for GBM patients.Purpose.To improve the performance of conventional transfer learning in the identification of MGMT promoter methylation status, we developed a 3D SpotTune network with adaptive fine-tuning capability. Using the pretrained weights of MedicalNet with the SpotTune network, we compared its performance with a randomly initialized network for different combinations of MR modalities.Methods.Using a ResNet50 as the base network, three categories of networks are created: (1) A 3D SpotTune network to process volumetric MR images, (2) a network with randomly initialized weights, and (3) a network pre-trained on MedicalNet. These three networks are trained and evaluated using a public GBM dataset provided by the University of Pennsylvania. The MRI scans from 240 patients are used, with 11 different modalities corresponding to a set of perfusion, diffusion, and structural scans. The performance is evaluated using 5-fold cross validation with a hold-out testing dataset.Results.The SpotTune network showed better performance than the randomly initialized network. The best performing SpotTune model achieved an area under the Receiver Operating Characteristic curve (AUC), average precision of the precision-recall curve (AP), sensitivity, and specificity values of 0.6604, 0.6179, 0.6667, and 0.6061 respectively.Conclusions.SpotTune enables transfer learning to be adaptive to individual patients, resulting in improved performance in predicting MGMT promoter methylation status in GBM using equivalent MRI modalities as compared to a randomly initialized network.

Glioblastoma (GBM) presents a daunting challenge due to its resistance to temozolomide (TMZ), a hurdle exacerbated by the proneural-to-mesenchymal transition (PMT) from a proneural (PN) to a mesenchymal (MES) phenotype. TAGLN2 is prominently expressed in GBM, particularly in the MES subtype compared to low-grade glioma (LGG) and the PN subtype. Our research reveals TAGLN2\'s involvement in PMT and TMZ resistance through a series of in vitro and in vivo experiments. TAGLN2 knockdown can restrain proliferation and invasion, trigger DNA damage and apoptosis, and heighten TMZ sensitivity in GBM cells. Conversely, elevating TAGLN2 levels amplifies resistance to TMZ in cellular and intracranial xenograft mouse models. We demonstrate the interaction relationship between TAGLN2 and ERK1/2 through co-immunoprecipitation (Co-IP) and liquid chromatography-tandem mass spectrometry (LC-MS/MS) spectrometry analysis. Knockdown of TAGLN2 results in a decrease in the expression of p-ERK1/2, whereas overexpression of TAGLN2 leads to an increase in p-ERK1/2 expression within the nucleus. Subsequently, the regulatory role of TAGLN2 in the expression and control of MGMT has been demonstrated. Finally, the regulation of TAGLN2 by NF-κB has been validated through chromatin immunoprecipitation and ChIP-PCR assays. In conclusion, our results confirm that TAGLN2 exerts its biological functions by interacting with the ERK/MGMT axis and being regulated by NF-κB, thereby facilitating the acquisition of promoting PMT and increased resistance to TMZ therapy in glioblastoma. These results provide valuable insights for the advancement of targeted therapeutic approaches to overcome TMZ resistance in clinical treatments.

Gender plays a crucial role in the occurrence and development of cancer, as well as in the metabolism of nutrients and energy. Men and women display significant differences in the incidence, prognosis, and treatment response across various types of cancer, including certain sex-specific tumors. It has been observed that male glioma patients have a higher incidence and worse prognosis than female patients, but there is currently a limited systematic evaluation of sex differences in gliomas. The purpose of this study is to provide an overview of the association between fluctuations in sex hormone levels and changes in their receptor expression with the incidence, progression, treatment, and prognosis of gliomas. Estrogen may have a protective effect on glioma patients, while exposure to androgens increases the risk of glioma. We also discussed the specific genetic and molecular differences between genders in terms of the malignant nature and prognosis of gliomas. Factors such as TP53, MGMT methylation status may play a crucial role. Therefore, it is essential to consider the gender of patients while treating glioma, particularly the differences at the hormonal and molecular levels. This approach can help in the adoption of an individualized treatment strategy.

O6-methylguanine-DNA methyltransferase (MGMT) has been demonstrated to be an important prognostic and predictive marker in glioblastoma (GBM). To establish a reliable radiomics model based on MRI data to predict the MGMT promoter methylation status of GBM. A total of 183 patients with glioblastoma were included in this retrospective study. The visually accessible Rembrandt images (VASARI) features were extracted for each patient, and a total of 14676 multi-region features were extracted from enhanced, necrotic, \"non-enhanced, and edematous\" areas on their multiparametric MRI. Twelve individual radiomics models were constructed based on the radiomics features from different subregions and different sequences. Four single-sequence models, three single-region models and the combined radiomics model combining all individual models were constructed. Finally, the predictive performance of adding clinical factors and VASARI characteristics was evaluated. The ComRad model combining all individual radiomics models exhibited the best performance in test set 1 and test set 2, with the area under the receiver operating characteristic curve (AUC) of 0.839 (0.709-0.963) and 0.739 (0.581-0.897), respectively. The results indicated that the radiomics model combining multi-region and multi-parametric MRI features has exhibited promising performance in predicting MGMT methylation status in GBM. The Modeling scheme that combining all individual radiomics models showed best performance among all constructed moels.

BACKGROUND: Extracranial metastases occur in <2% of cases of glioblastoma (GBM). When metastases do occur, bone is the most common destination. Herein, we review clinical characteristics of GBM patients with osseous metastases and evaluate both potential risk factors and prognostic significance.
METHODS: Using an institutional database, we identified and retrospectively analyzed 6 patients with both GBM and osseous metastases. We collected data on patient demographics, tumor genetics, clinical courses, and outcomes. Given the rarity of metastatic GBM, we conducted historical comparisons using previously published literature.
RESULTS: Five patients with osseous metastases (83%) were male, with a median age of 46 years at GBM diagnosis (range: 20-84). All patients had IDH-wildtype, MGMT promoter unmethylated GBM and 5 (83%) had alterations in TP53. All patients underwent surgical resection for GBM followed by radiation with concurrent and adjuvant temozolomide. Four patients (67%) received bevacizumab prior to bone metastasis diagnosis. Bone metastases were discovered at a median of 12.2 months (range: 5.3-35.2) after GBM diagnosis and 4.8 months after starting bevacizumab (range: 3.5-13.2). Three patients (50%) received immunotherapy. After osseous metastasis diagnosis, the median survival was 25 days (range: 13-225).
CONCLUSIONS: In our cohort, most patients were male and young at the time of GBM diagnosis. All patients had IDH-wildtype, MGMT promoter unmethylated GBM, and most had alterations in TP53, which may be important for osseous metastasis. Most patients received bevacizumab, which has been associated with earlier metastasis. Osseous metastases of GBM occur and portend a dismal prognosis in an already aggressive malignancy.