MGMT Promoter Research Articles

Macrophage polarization-related gene signature for risk stratification and prognosis of survival in gliomas.

Macrophage polarization plays an essential role in tumour immune cell infiltration and tumour growth. In this study, we selected a series of genes distinguishing between M1 and M2 macrophages and explored their prognostic value in gliomas. A total of 170 genes were included in our study. The CGGA database was used as the training cohort and the TCGA database as the validation cohort. The biological processes and functions were identified by GO and KEGG analysis. Kaplan-Meier analysis was used to compare survival differences between groups. Importantly, we built a risk score model using Cox regression analysis based on the CGGA and verified it in the TCGA database and our sequencing data. Patients with gliomas in the high-risk group were associated with high pathologic grade, IDH WT status, MGMT promoter unmethylation, 1p19q non-codeletion and prone to have a poor outcome. GEPIA results revealed that CD300C, CNRIP1 and MYO1F are the most related genes of immune infiltrations. The differential expression of these genes between low-grade gliomas and glioblastomas was confirmed by q-RT-PCR. Macrophage polarization-related gene signatures can predict the malignancy and outcome of patients with gliomas and might act as a promising target for glioma immunotherapy in the future.

Blood and cerebrospinal fluid biomarkers in neuro-oncology.

The purpose of this review is to discuss the value of blood and CSF biomarkers in primary CNS tumors. Several analytes can be assessed with liquid biopsy techniques, including circulating tumor cells, circulating cell-free tumor DNA, circulating cell-free RNA, circulating proteins and metabolites, extracellular vesicles and tumor-educated platelets. Among diffuse gliomas of the adult, ctDNA in blood or CSF has represented the most used analyte, with the detection of molecular alterations such as MGMT promoter, PTEN, EGFRVIII, TERT promoter mutation and IDH R132H mutation. In general, CSF is enriched for ctDNA as compared with plasma. The use of MRI-guided focused ultrasounds to disrupt the blood-brain barrier could enhance the level of biomarkers in both blood and CSF. The detection of MYD88 L265P mutation with digital droplet PCR and the detection of ctDNA with next generation sequencing represent the best tools to diagnose and monitoring CNS lymphomas under treatment. In meningiomas, the low concentration of ctDNA is a limiting factor for the detection of driver mutations, such as NF2, AKTs, SMO, KLF4, TRAF7, SMARCB1, SMARCE1, PTEN, and TERT; an alternative approach could be the isolation of ctDNA through circulating extracellular vesicles. Liquid biopsies are being used extensively for diagnosis and surveillance of diffuse midline gliomas, in particular with the detection of the driver mutation H3K27M. Last, specific methylome patterns in CSF may allow the distinction of glioblastomas from CNS lymphomas or meningiomas. This review summarizes the current knowledge and future perspectives of liquid biopsy of blood and CSF for diagnosis and monitoring of primary CNS tumors.

MGMT promoter methylation and survival following chemotherapy for WHO grade 4 IDH-mutant astrocytoma.

MGMT promoter methylation and survival following chemotherapy for WHO grade 4 IDH-mutant astrocytoma.

Epigenetic, transcriptional and splicing changes in the glioblastoma marker genes CHI3L1 and MGMT during the acquisition of temozolomide resistance

Epigenetic, transcriptional and splicing changes in the glioblastoma marker genes CHI3L1 and MGMT during the acquisition of temozolomide resistance

Integrated analyses reveal two molecularly and clinically distinct subtypes of H3 K27M-mutant diffuse midline gliomas with prognostic significance

H3 K27M-altered diffuse midline gliomas (DMGs) are highly malignant tumours that arise in the midline structures of the CNS. Most DMGs carry an H3 K27M-mutation in one of the genes encoding for histone H3. Recent studies suggested that epigenetic subgroups of DMGs can be distinguished based on alterations in the MAPK-signalling pathway, tumour localisation, mutant H3-gene, or overall survival (OS). However, as these parameters were studied individually, it is unclear how they collectively influence survival. Hence, we analysed dependencies between different parameters, to define novel epigenetic, clinically meaningful subgroups of DMGs. We collected a multifaceted cohort of 149 H3 K27M-mutant DMGs, also incorporating data of published cases. DMGs were included in the study if they could be clearly allocated to the spinal cord (n = 31; one patient with an additional sellar tumour), medulla (n = 20), pons (n = 64) or thalamus (n = 33), irrespective of further known characteristics. We then performed global genome-wide DNA methylation profiling and, for a subset, DNA sequencing and survival analyses. Unsupervised hierarchical clustering of DNA methylation data indicated two clusters of DMGs, i.e. subtypes DMG-A and DMG-B. These subtypes differed in mutational spectrum, tumour localisation, age at diagnosis and overall survival. DMG-A was enriched for DMGs with MAPK-mutations, medullary localisation and adult age. 13% of DMG-A had a methylated MGMT promoter. Contrarily, DMG-B was enriched for cases with TP53-mutations, PDGFRA-amplifications, pontine localisation and paediatric patients. In univariate analyses, the features enriched in DMG-B were associated with a poorer survival. However, all significant parameters tested were dependent on the cluster attribution, which had the largest effect on survival: DMG-A had a significantly better survival compared to DMG-B (p < 0.001). Hence, the subtype attribution based on two methylation clusters can be used to predict survival as it integrates different molecular and clinical parameters.

Molecular Profile as an Outcome Predictor in Glioblastoma along with MRI Features and Surgical Resection: A Scoping Review.

Glioblastoma (GBM) is one of the most aggressive malignant tumors of the brain. We queried PubMed for articles about molecular predictor markers in GBM. This scoping review aims to analyze the most important outcome predictors in patients with GBM and to compare these factors in terms of absolute months of survival benefit and percentages. Performing a gross total resection for patients with GBM undergoing optimal chemo- and radiotherapy provides a significant benefit in overall survival compared to those patients who received a subtotal or partial resection. However, compared to IDH-Wildtype GBMs, patients with IDH-Mutant 1/2 GBMs have an increased survival. MGMT promoter methylation status is another strong outcome predictor for patients with GBM. In the reviewed literature, patients with methylated MGMT promoter lived approximately 50% to 90% longer than those with an unmethylated MGMT gene promoter. Moreover, KPS is an important predictor of survival and quality of life, demonstrating that we should refrain from aggressive surgery in important brain areas. As new therapies (such as TTFs) emerge, we are optimistic that the overall median survival will increase, even for IDH-Wildtype GBMs. In conclusion, molecular profiles are stronger outcome predictors than the extent of neurosurgical resection for GBM.

An Insight into Emerging Phytocompounds for Glioblastoma Multiforme Therapy.

Despite intense research in the field of glioblastoma multiforme (GBM) therapeutics, the resistance against approved therapy remains an issue of concern. The resistance against the therapy is widely reported due to factors like clonal selection, involvement of multiple developmental pathways, and majorly defective mismatch repair (MMR) protein and functional O6- methylguanine DNA methyltransferase (MGMT) repair enzyme. Phytotherapy is one of the most effective alternatives to overcome resistance. It involves plant-based compounds, divided into several classes: alkaloids; phenols; terpenes; organosulfur compounds. The phytocompounds comprised in these classes are extracted or processed from certain plant sources. They can target various proteins of molecular pathways associated with the progression and survival of GBM. Phytocompounds have also shown promise as immunomodulatory agents and are being explored for immune checkpoint inhibition. Therefore, research and innovations are required to understand the mechanism of action of such phytocompounds against GBM to develop efficacious treatments for the same. This review gives insight into the potential of phytochemical-based therapeutic options for GBM treatment.

MEN1 Deficiency-Driven Activation of the β-Catenin-MGMT Axis Promotes Pancreatic Neuroendocrine Tumor Growth and Confers Temozolomide Resistance.

O6-methylguanine DNA methyltransferase (MGMT) removes alkyl adducts from the guanine O6 position (O6-MG) and repairs DNA damage. High MGMT expression results in poor response to temozolomide (TMZ). However, the biological importance of MGMT and the mechanism underlying its high expression in pancreatic neuroendocrine tumors (PanNETs) remain elusive. Here, it is found that MGMT expression is highly elevated in PanNET tissues compared with paired normal tissues and negatively associated with progression-free survival (PFS) time in patients with PanNETs. Knocking out MGMT inhibits cancer cell growth in vitro and in vivo. Ectopic MEN1 expression suppresses MGMT transcription in a manner that depends on β-Catenin nuclear export and degradation. The Leucine 267 residue of MEN1 is crucial for regulating β-Catenin-MGMT axis activation and chemosensitivity to TMZ. Interference with β-Catenin re-sensitizes tumor cells to TMZ and significantly reduces the cytotoxic effects of high-dose TMZ treatment, and MGMT overexpression counteracts the effects of β-Catenin deficiency. This study reveals the biological importance of MGMT and a new mechanism by which MEN1 deficiency regulates its expression, thus providing a potential combinational strategy for treating patients with TMZ-resistant PanNETs.

The Role of Amide Proton Transfer (APT)-Weighted Imaging in Glioma: Assessment of Tumor Grading, Molecular Profile and Survival in Different Tumor Components.

Amide Proton Transfer-weighted (APTw) imaging is a molecular MRI technique used to quantify protein concentrations in gliomas, which have heterogeneous components with varying cellularity and metabolic activity. This study aimed to assess the correlation between the component-specific APT signal of the neoplasm and WHO grade, molecular profile and survival status. Sixty-one patients with adult-type diffuse gliomas were retrospectively analyzed. APT values were semi-automatically extracted from tumor solid and, whenever present, necrotic components. APT values were compared between groups stratified by WHO grade, IDH-mutation, MGMT promoter methylation and 1- and 2-year survival status using Wilcoxon rank-sum test, adjusting for multiple comparisons. Overall survival (OS) was analyzed in the subgroup of 48 patients with grade 4 tumors using Cox proportional-hazards models. Random-effects models were used to assess inter-subject heterogeneity of the mean APT values in each tumor component. APT values of the solid component significantly differed between patients with grades 2-3 and 4 tumors (mean 1.58 ± 0.50 vs. 2.04 ± 0.56, p = 0.028) and correlated with OS after 1 year (1.81 ± 0.58 in survivors vs. 2.17 ± 0.51 in deceased patients, p = 0.030). APT values did not differ by IDH-mutation, MGMT methylation, and 2-year survival status. Within grade 4 glioma patients, higher APT kurtosis of the solid component was a negative prognostic factor (hazard ratio = 1.60, p = 0.040). Mean APT values of the necrosis showed high inter-subject variability, although most necrotic tumors were grade 4 and IDH wildtype. In conclusion, APTw imaging in the solid component provided metrics associated with glioma grade and survival status but showed weak correlation with IDH-mutation and MGMT promoter methylation status, in contrast to previous works. Further research is needed to understand APT signal variability within the necrotic component of high-grade gliomas.

Lisavanbulin (BAL101553), a novel microtubule inhibitor, plus radiation in patients with newly diagnosed, MGMT promoter unmethylated glioblastoma.

Lisavanbulin (BAL101553) is a small, lipophilic, oral microtubule destabilizer with promising antitumoral activity observed in preclinical glioblastoma (GBM) models. This multicenter phase 1 study sought to determine the MTD of oral Lisavanbulin in combination with standard RT (60 Gy/30 fractions) but without temozolomide in patients with newly diagnosed MGMT promoter unmethylated GBM (uGBM). Dose escalation followed a modified 3 + 3 design. Secondary objectives included estimation of OS and PFS and pharmacokinetic analysis. Twenty-six patients with uGBM (median age, 63 years, 42.3% male, 61.5% with gross total resection, median Karnofsky performance status 80) were enrolled; 2 tumors had an IDH1 mutation. Predefined dose levels of Lisavanbulin, administered daily concomitantly with RT, were: 4mg (5 pts), 6mg (5 pts), 8mg (7 pts), 12mg (5 pts), and 15mg (4 pts). The initial starting dose was 8mg. Due to grade 4 aseptic meningoencephalitis in the first patient, the dose was decreased to 4mg. Dose escalation resumed and continued to 15mg with dose-limiting toxicities of grade 2 confusion and memory impairment observed at 12mg. Avanbulin exposures increased in a relatively dose-proportional manner with increasing oral dose of Lisavanbulin from 4 to 15mg. Lisavanbulin in combination with RT was considered safe up to the highest predefined oral dose level of 15mg daily.

Inhibitory effects of Gracilaria edulis and Gracilaria salicornia against the MGMT and VEGFA biomarkers involved in the onset and advancement of glioblastoma using insilico and invitro approaches.

Glioblastoma (GBM), an aggressive primary brain tumor originating from glial cells, poses significant treatment challenges due to its rapid growth and invasiveness. The exact mechanisms of GBM's brain damage remain unclear. This study examines primary molecular markers commonly assessed in GBM patients, including brain-derived neurotrophic factor (BDNF), platelet-derived growth factor receptor A (PDGFRA), O6-methylguanine DNA methyltransferase (MGMT), epidermal growth factor receptor (EGFR), and vascular endothelial growth factor A (VEGFA) using computational approaches. The study revealed significant differences (p ≤ 0.05) in PDGFRA, EGFR, and VEGFA expression rates, which are particularly interesting. Additionally, MGMT and VEGFA showed higher hazard ratios. Expression levels of MGMT and VEGFA were visualized in immune and malignant cells using single-cell RNA datasets GSE103224 and GSE148842. From a total of 48 compounds in Gracilaria edulis and 86 in Gracilaria salicornia, we identified 15 compounds capable of crossing the blood-brain barrier. Notably, 2-tridecanone (binding affinity [BA] = -4.2kcal/mol; root mean square deviation [RMSD] = 1.479Å) and decanoic acid, ethyl ester (BA = -4.2kcal/mol; RMSD = 1.702Å) from G. edulis interacted with MGMT via hydrogen bonds. The compound alpha-terpineol interacted with MGMT (BA = -5.7kcal/mol; RMSD = 0.501Å) and VEGFA (BA = -4.7kcal/mol; RMSD = 2.483Å). Ethanolic and methanolic extracts from G. edulis and G. salicornia demonstrated mild anti-cell proliferation properties in the GBM LN-229 cell line, suggesting potential therapeutic benefits. This study highlights the significance of molecular markers and natural compounds in understanding and potentially treating GBM.

Tricarboxylic Acid Cycle Relationships with Non-Metabolic Processes: A Short Story with DNA Repair and Its Consequences on Cancer Therapy Resistance.

Metabolic changes involving the tricarboxylic acid (TCA) cycle have been linked to different non-metabolic cell processes. Among them, apart from cancer and immunity, emerges the DNA damage response (DDR) and specifically DNA damage repair. The oncometabolites succinate, fumarate and 2-hydroxyglutarate (2HG) increase reactive oxygen species levels and create pseudohypoxia conditions that induce DNA damage and/or inhibit DNA repair. Additionally, by influencing DDR modulation, they establish direct relationships with DNA repair on at least four different pathways. The AlkB pathway deals with the removal of N-alkylation DNA and RNA damage that is inhibited by fumarate and 2HG. The MGMT pathway acts in the removal of O-alkylation DNA damage, and it is inhibited by the silencing of the MGMT gene promoter by 2HG and succinate. The other two pathways deal with the repair of double-strand breaks (DSBs) but with opposite effects: the FH pathway, which uses fumarate to help with the repair of this damage, and the chromatin remodeling pathway, in which oncometabolites inhibit its repair by impairing the homologous recombination repair (HRR) system. Since oncometabolites inhibit DNA repair, their removal from tumor cells will not always generate a positive response in cancer therapy. In fact, their presence contributes to longer survival and/or sensitization against tumor therapy in some cancer patients.

Glioma lateralization: Focus on the anatomical localization and the distribution of molecular alterations (Review).

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.

Integrative single-cell and bulk transcriptome analyses identify a distinct pro-tumor macrophage signature that has a major prognostic impact on glioblastomas

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.

Optimizing Glioblastoma, IDH-wildtype Treatment Outcomes : A Radiomics and Support Vector Machine -Based Approach to Overall Survival Estimation.

Glioblastoma multiforme (GBM), particularly the IDH-wildtype type, represents a significant clinical challenge due to its aggressive nature and poor prognosis. Despite advancements in medical imaging and its modalities, survival rates have not improved significantly, demanding innovative treatment planning and outcome prediction approaches. This study utilizes a Support Vector Machine (SVM) classifier using radiomics features to predict the overall survival (OS) of GBM, IDH-wildtype patients to short (< 12 Months) and long (>=12 Months) survivors. A dataset comprising multi-parametric MRI (mpMRI) scans from 574 patients was analyzed. Radiomic features were extracted from T1, T2, FLAIR, and T1-Gd sequences. Low variance features were removed, and Recursive Feature Elimination (RFE) was used to select the most informative features. The SVM model was trained using a k-fold cross-validation approach. Furthermore, clinical parameters such as age, gender, and MGMT promoter methylation status were integrated to enhance prediction accuracy. The model showed reasonable results in terms of cross-validated AUC of 0.84 (95% CI: 0.80-0.90) with (p-value < 0.001) effectively categorizing patients into short and long survivors. Log-rank test (Chi-square statistics) analysis for the developed model was 0.00029 along with the 1.20 Cohen's d effect size. Most importantly, clinical data integration further refined the survival estimates, providing a more fitted prediction that considers individual patient characteristics by Kaplan-Meier curve with p-value<0.0001. The proposed method significantly enhances the predictive accuracy of OS outcomes in GBM, IDH-wildtype patients. By integrating detailed imaging features with key clinical indicators, this model offers a robust tool for personalized treatment planning, potentially improving OS.

AB003. Clinical analysis of central nervous system (CNS) World Health Organization (WHO) grade 4 gliomas with IDH-mutant versus IDH-wildtype focused on CDKN2A homozygous deletion.

We are primarily investigating the prognostic role of cell-cycle-dependent kinase inhibitor (CDKN)-2A homozygous deletion in central nervous system (CNS) World Health Organization (WHO) grade 4 gliomas. Additionally, traditional prognostic factors for grade 4 gliomas will be examined, and our results will be validated. We conducted a retrospective analysis of glioma cohorts in our institute. Medical records were reviewed for 142 glioblastoma patients for 15 years, and pathological slides were examined again for the updated diagnosis according to the 2021 WHO classification of CNS tumors. The isocitrate dehydrase (IDH) mutation and CDKN2A deletion were examined by next generation sequencing (NGS) analysis using ONCO accuPanel®. Traditional prognostic factors including age, WHO performance status, extent of resection, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation were examined. After the exclusion of 6 patients with poor status of pathologic samples, 136 glioblastoma that were diagnosed by previous WHO criteria were changed into 29 (21.3%) astrocytoma, IDH-mutant, CNS WHO grade 4 and 107 (78.7%) glioblastoma, IDH-wildtype, CNS WHO grade 4. Among them, 61 patients (56.0%) had CDKN2A deletion. Group A with IDH-wildtype and CDKN2A deletion had a mean overall survival (OS) of 15.70 months [95% confident interval (CI): 13.86-17.54], group B with IDH-mutant and CDKN2A deletion had a mean OS of 19.37 months (95% CI: 13.43-25.30), group C with IDH-wildtype and intact CDKN2A had a mean OS of 22.63 months (95% CI: 20.10-25.17), and group D with IDH-mutant and intact CDKN2A had a mean OS of 33.38 months (95% CI: 29.35-37.40). Multifactor analysis showed following factors were independently associated with OS: age [≥50 vs. <50 years; hazard ratio (HR) 4.642], extent of resection (gross total resection vs. others; HR 5.523), WHO performance (0, 1 vs. 2; HR 5.007), MGMT promoter methylation, (methylated vs. unmethylated; HR 5.075), IDH mutation (mutant vs. wildtype; HR 6.358), and CDKN2A deletion (absence vs. presence; HR 13.452). The presenting study suggests that CDKN2A deletion should play a powerful prognostic role in CNS WHO grade 4 gliomas as well as low-grade glioma. Even if CNS WHO grade 4 gliomas had mutant IDH, they can have poor clinical outcomes due to CDKN2A deletion.

Temozolomide use in elderly patients with MGMT promoter unmethylated glioblastoma: Is it finally time to dismount a dead horse?

Temozolomide use in elderly patients with MGMT promoter unmethylated glioblastoma: Is it finally time to dismount a dead horse?

MGMT protein expression is a reliable predictive biomarker for temozolomide-containing chemotherapy in osteosarcoma.

The prognosis of patients with osteosarcoma who experience recurrence or progression (R/P) is extremely poor, and more effective and less toxic therapies are needed. In the current study, the clinical data of osteosarcoma patients who experienced R/P were retrospectively analyzed to verify the reliability of O-6-methylguanine-DNA methyltransferase (MGMT) protein expression or MGMT promoter methylation for predicting the response to off-label temozolomide (TMZ)-containing chemotherapy. Of the 30 evaluable patients, 9 (30%) showed no/low MGMT protein expression, whereas all 16 evaluable patients had unmethylated MGMT promoter irrespective of MGMT protein expression levels. Twenty-three patients received TMZ-containing chemotherapy for measurable lesions (n = 14) or as adjuvant therapy following resection of recurrent lesions (n = 9). Among 14 patients with radiologically measurable lesions, the objective response rate was higher in the MGMT no/low-expression group (50.0%) than in the MGMT intermediate/high-expression group with borderline significance (0%, p = 0.066). The 6-month progression-free survival (PFS) rate in patients with radiologically measurable lesions was significantly higher in the MGMT no/low-expression group (50.0%) than in the MGMT intermediate/high-expression group (0%, p = 0.036). In the multivariate analysis of the 23 patients receiving TMZ-containing chemotherapy, MGMT expression and disease status before TMZ-containing chemotherapy were significantly associated with PFS. No severe adverse effects were observed during TMZ-containing chemotherapy. MGMT protein expression, but not MGMT promoter methylation, could predict a favorable outcome in patients receiving TMZ-containing chemotherapy.

Extended cycles of adjuvant temozolomide improves survival outcomes in glioblastoma: a retrospective analysis

Aim: Standard treatment includes post-surgical chemoradiotherapy and adjuvant temozolomide (TMZ) for glioblastoma (GBM). There is no consensus on the optimal duration for adjuvant TMZ. This study assessed whether prolonging adjuvant TMZ improved survival outcomes. Methods: We retrospectively analyzed data of GBM patients who met inclusion criteria at our institute from September 2013 to December 2022. Patients who received 6 cycles of maintenance TMZ constituted the standard group, whereas those who underwent &gt; 6 cycles were classified into the extended group. Kaplan-Meier method was used to estimate the median progression-free survival (PFS) and overall survival (OS). Independent predictors of OS and PFS were explored by Cox regression analyses. Results: 100 patients were enrolled. Extended adjuvant TMZ significantly improved OS (28.0 vs. 10.0 months, P &lt; 0.001) and PFS (22.0 vs. 8.0 months, P &lt; 0.001) in newly diagnosed GBM patients. Subgroup analysis showed that patients with MGMT promoter methylation who received &gt; 6 cycles of adjuvant TMZ experienced a significant increase in OS (34.0 vs. 9.0 months, P &lt; 0.001) and PFS (26.0 vs. 9.0 months, P = 0.008). Additionally, in the extended group, patients with MGMT promoter methylation had better survival outcomes compared to MGMT promoter unmethylated patients (OS: 34.0 vs. 17.0 months, P = 0.013; PFS: 26.0 vs. 12.0 months, P = 0.025). In patients with solitary GBM, extended adjuvant TMZ resulted in better OS (11.0 vs. 32 months, P = 0.007) and PFS (9.0 vs. 24.0 months, P &lt; 0.001). For patients with multiple GBM, undergoing six or more cycles of adjuvant TMZ did not significantly impact OS (P = 0.100) and PFS (P = 0.067). The Karnofsky Performance Status (KPS) is employed to assess the health condition of surgical patients. Patients with KPS &gt; 70 exhibited better survival outcomes in the extended group. Nausea and vomiting were the main adverse events reported in both cohorts. However, fatigue emerged as the most severe side effect, specifically within the extended group. Conclusion: This study indicated that prolonged adjuvant TMZ significantly enhanced OS and PFS in GBM, and the adverse events were acceptable. The benefits were particularly notable in those with MGMT promoter methylation, solitary GBM, and high KPS. The optimal cycles of adjuvant TMZ require large prospective studies to further validate and identify which patient groups benefit the most based on molecular subtyping and clinical characteristics.

Adaptive fine-tuning based transfer learning for the identification of MGMT promoter methylation status.

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.