Temozolomide (TMZ) resistance is a major challenge in the treatment of glioblastoma (GBM). Tumour reproductive cells (TRCs) have been implicated in the development of chemotherapy resistance. By culturing DBTRG cells in three-dimensional soft fibrin gels to enrich GBM TRCs and performing RNA-seq analysis, the expression of stanniocalcin-1 (STC), a gene encoding a secreted glycoprotein, was found to be upregulated in TRCs. Meanwhile, the viability of TMZ-treated TRC cells was significantly higher than that of TMZ-treated 2D cells. Analysis of clinical data from CGGA (Chinese Glioma Genome Atlas) database showed that high expression of STC1 was closely associated with poor prognosis, glioma grade and resistance to TMZ treatment, suggesting that STC1 may be involved in TMZ drug resistance. The expression of STC1 in tissues and cells was examined, as well as the effect of STC1 on GBM cell proliferation and TMZ-induced DNA damage. The results showed that overexpression of STC1 promoted and knockdown of STC1 inhibited TMZ-induced DNA damage. These results were validated in an intracranial tumour model. These data revealed that STC1 exerts regulatory functions on MGMT expression in GBM, and provides a rationale for targeting STC1 to overcome TMZ resistance.

It is well known how the precise localization of glioblastoma multiforme (GBM) predicts the direction of tumor spread in the surrounding neuronal structures. The aim of the present review is to reveal the lateralization of GBM by evaluating the anatomical regions where it is frequently located as well as the main molecular alterations observed in different brain regions. According to the literature, the precise or most frequent lateralization of GBM has yet to be determined. However, it can be said that GBM is more frequently observed in the frontal lobe. Tractus and fascicles involved in GBM appear to be focused on the corticospinal tract, superior longitudinal I, II and III fascicles, arcuate fascicle long segment, frontal strait tract, and inferior fronto‑occipital fasciculus. Considering the anatomical features of GBM and its brain involvement, it is logical that the main brain regions involved are the frontal‑temporal‑parietal‑occipital lobes, respectively. Although tumor volumes are higher in the right hemisphere, it has been determined that the prognosis of patients diagnosed with cancer in the left hemisphere is worse, probably reflecting the anatomical distribution of some detrimental alterations such as TP53 mutations, PTEN loss, EGFR amplification, and MGMT promoter methylation. There are theories stating that the right hemisphere is less exposed to external influences in its development as it is responsible for the functions necessary for survival while tumors in the left hemisphere may be more aggressive. To shed light on specific anatomical and molecular features of GBM in different brain regions, the present review article is aimed at describing the main lateralization pathways as well as gene mutations or epigenetic modifications associated with the development of brain tumors.

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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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) is a highly aggressive brain tumor associated with poor patient survival. The current standard treatment involves invasive surgery, radiotherapy, and chemotherapy employing temozolomide (TMZ). Resistance to TMZ is, however, a major challenge. Previous work from our group has identified candidate genes linked to TMZ resistance, including genes encoding translesion synthesis (TLS) DNA polymerases iota (Polɩ) and kappa (Polκ). These specialized enzymes are known for bypassing lesions and tolerating DNA damage. Here, we investigated the roles of Polɩ and Polκ in TMZ resistance, employing MGMT-deficient U251-MG glioblastoma cells, with knockout of either POLI or POLK genes encoding Polɩ and Polκ, respectively, and assess their viability and genotoxic stress responses upon subsequent TMZ treatment. Cells lacking either of these polymerases exhibited a significant decrease in viability following TMZ treatment compared to parental counterparts. The restoration of the missing polymerase led to a recovery of cell viability. Furthermore, knockout cells displayed increased cell cycle arrest, mainly in late S-phase, and lower levels of genotoxic stress after TMZ treatment, as assessed by a reduction of γH2AX foci and flow cytometry data. This implies that TMZ treatment does not trigger a significant H2AX phosphorylation response in the absence of these proteins. Interestingly, combining TMZ with Mirin (double-strand break repair pathway inhibitor) further reduced the cell viability and increased DNA damage and γH2AX positive cells in TLS KO cells, but not in parental cells. These findings underscore the crucial roles of Polɩ and Polκ in conferring TMZ resistance and the potential backup role of homologous recombination in the absence of these TLS polymerases. Targeting these TLS enzymes, along with double-strand break DNA repair inhibition, could, therefore, provide a promising strategy to enhance TMZ\'s effectiveness in treating GBM.

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.

Decitabine and azacytidine are considered as epigenetic drugs that induce DNA methyltransferase (DNMT)-DNA crosslinks, resulting in DNA hypomethylation and damage. Although they are already applied against myeloid cancers, important aspects of their mode of action remain unknown, highly limiting their clinical potential. Using a combinatorial approach, we reveal that the efficacy profile of both compounds primarily depends on the level of induced DNA damage. Under low DNMT activity, only decitabine has a substantial impact. Conversely, when DNMT activity is high, toxicity and cellular response to both compounds are dramatically increased, but do not primarily depend on DNA hypomethylation or RNA-associated processes. By investigating proteome dynamics on chromatin, we show that decitabine induces a strictly DNMT-dependent multifaceted DNA damage response based on chromatin recruitment, but not expression-level changes of repair-associated proteins. The choice of DNA repair pathway hereby depends on the severity of decitabine-induced DNA lesions. Although under moderate DNMT activity, mismatch (MMR), base excision (BER), and Fanconi anaemia-dependent DNA repair combined with homologous recombination are activated in response to decitabine, high DNMT activity and therefore immense replication stress induce activation of MMR and BER followed by non-homologous end joining.