Search Results (97)

Precision neurosurgery is rapidly evolving as a medical specialty by merging genomic medicine, multi-omics technologies, and artificial intelligence (AI) technology, while at the same time, society is shifting away from the traditional, anatomic model of care to consider a more precise, molecular model of care. The general purpose of this review is to contemporaneously reflect on how these advances will impact neurosurgical care by providing us with more precise diagnostic and treatment pathways. We hope to provide a relevant review of the recent advances in genomics and multi-omics in the context of clinical practice and highlight their transformational opportunities in the existing models of care, where improved molecular insights can support improvements in clinical care. More specifically, we will highlight how genomic profiling, CRISPR-Cas9, and multi-omics platforms (genomics, transcriptomics, proteomics, and metabolomics) are increasing our understanding of central nervous system (CNS) disorders. Achievements obtained with transformational technologies such as single-cell RNA sequencing and intraoperative mass spectrometry are exemplary of the molecular diagnostic possibilities in real-time molecular diagnostics to enable a more directed approach in surgical options. We will also explore how identifying specific biomarkers (e.g., IDH mutations and MGMT promoter methylation) became a tipping point in the care of glioblastoma and allowed for the establishment of a new taxonomy of tumors that became applicable for surgeons, where a change in practice enjoined a different surgical resection approach and subsequently stratified the adjuvant therapies undertaken after surgery. Furthermore, we reflect on how the novel genomic characterization of mutations like DEPDC5 and SCN1A transformed the pre-surgery selection of surgical candidates for refractory epilepsy when conventional imaging did not define an epileptogenic zone, thus reducing resective surgery occurring in clinical practice. While we are atop the crest of an exciting wave of advances, we recognize that we also must be diligent about the challenges we must navigate to implement genomic medicine in neurosurgery—including ethical and technical challenges that could arise when genomic mutation-based therapies require the concurrent application of multi-omics data collection to be realized in practice for the benefit of patients, as well as the constraints from the blood–brain barrier. The primary challenges also relate to the possible gene privacy implications around genomic medicine and equitable access to technology-based alternative practice disrupting interventions. We hope the contribution from this review will not just be situational consolidation and integration of knowledge but also a stimulus for new lines of research and clinical practice. We also hope to stimulate mindful discussions about future possibilities for conscientious and sustainable progress in our evolution toward a genomic model of precision neurosurgery. In the spirit of providing a critical perspective, we hope that we are also adding to the larger opportunity to embed molecular precision into neuroscience care, striving to promote better practice and better outcomes for patients in a global sense. Full article

Oral cancer, the most common form of head and neck cancer, is worldwide a serious public health problem. Most patients present a locally advanced disease, and face poor prognosis, even with multimodality treatment. They may also develop second primary tumors in the entirety of their upper aerodigestive tract. The most altered signaling pathways are the PI3K/AKT/mTOR, TP53, RB, and the WNT/β-catenin pathways. Genomic and molecular cytogenetic analyses have revealed frequent losses at 3p, 8p, 9p, and 18q, along with gains at 3q, 7p, 8q, and 11q, and several genes frequently affected have been identified, such as TP53, CCND1, CTTN, CDKN2A, EGFR, HRAS, PI3K, ADAM9, MGAM, SIRPB1, and FAT1, among others. Various epigenetic alterations were also found, such as the global hypomethylation and hypermethylation of CDKN2A, APC, MGMT, PTEN, CDH1, TFP12, SOX17, GATA4, ECAD, MGMT, and DAPK. Several microRNAs are upregulated in oral cancer, including miR-21, miR-24, miR-31, miR-184, miR-211, miR-221, and miR-222, while others are downregulated, such as miR-203, miR-100, miR-200, miR-133a, miR-133b, miR-138, and miR-375. The knowledge of this molecular pathogenesis has not yet been translated into clinical practice, apart from the use of cetuximab, an EGFR antibody. Oral tumors are also genetically heterogenous and affect several pathways, which means that, due to the continuous evolution of these genetic alterations, a single biopsy is not sufficient to fully evaluate the most adequate molecular targets when more drugs become available. Liquid biopsies, either resorting to circulating tumor cells, extracellular vesicles or cell-free nucleic acids, have the potential to bypass this problem, and have potential prognostic and staging value. We critically review the current knowledge on the molecular, genetic and epigenetic alterations in oral cancer, as well as the applications and challenges of liquid biopsies in its diagnosis, follow-up, and prognostic stratification. Full article

Background: Glioblastoma (GBM) remains almost uniformly fatal, owing in part to therapy-resistant cancer stem-like cells (CSCs) and to temozolomide (TMZ) resistance driven by O⁶-methylguanine-DNA methyltransferase (MGMT). Differentiation therapy with all-trans retinoic acid (ATRA) has the potential to attenuate stemness and sensitize GBM to TMZ. We therefore asked whether ATRA reduces expression of key CSC markers and MGMT in established GBM lines. Methods: Two established human GBM cell lines, U87-MG and A172, were cultured under neurosphere-promoting conditions to enrich for potential stem-like subpopulations. Cells were treated with either 1 µM ATRA or vehicle control (DMSO) for 5 days. Total RNA was extracted, and cDNA was synthesized. Quantitative Real-Time PCR (qPCR) assessed relative mRNA expression levels of key stemness transcription factors (SOX2, NES) and the DNA repair gene MGMT and corresponding protein levels were measured by an Enzyme-Linked Immunosorbent Assay (ELISA). Gene expression was normalized to the geometric mean of two validated housekeeping genes (GAPDH, ACTB). Relative quantification was calculated using the ΔΔCt method, and statistical significance was determined using Student’s t-tests. Results: ATRA markedly suppressed stemness and MGMT in both lines. In U87-MG, SOX2 mRNA fell 3.7-fold (p = 0.0008) and protein 2.99-fold (148.3 ± 6.0 → 49.7 ± 2.7 pg µg⁻¹; p = 0.0002); Nestin dropped 4.1-fold (p = 0.0005) and 3.51-fold (450.0 ± 17.3 → 128.3 ± 4.4 pg µg⁻¹; p = 0.00008). MGMT decreased 2.6-fold at transcript level (p = 0.0065) and 2.11-fold at protein level (81.7 ± 4.4 → 38.7 ± 1.8 pg µg⁻¹; p = 0.0005). In A172, SOX2 was reduced 2.9-fold (p = 0.0041) and 2.31-fold (p = 0.0007); Nestin 3.3-fold (p = 0.0028) and 2.79-fold (p = 0.00009). MGMT declined 2.2-fold (p = 0.0132) and 1.82-fold (p = 0.0015), respectively. Conclusions: Five-day exposure to ATRA diminishes SOX2, Nestin, and MGMT at both mRNA and protein levels in stem-enriched GBM cultures, supporting the premise that ATRA-induced differentiation can concurrently blunt CSC traits and TMZ-resistance mechanisms. These data provide a molecular rationale for testing ATRA in combination regimens aimed at improving GBM therapy. Full article

Background and Objectives: Glioblastoma (GBM) is among the most aggressive and lethal primary brain tumors, characterized by high heterogeneity, invasive growth, and resistance to conventional therapies. The 2021 WHO classification highlights the importance of molecular diagnostics, integrating genetic, transcriptomic, and epigenetic alterations alongside histological and immunohistochemical criteria. Materials and methods: Key molecular regulators, including ATRX, OLIG2, MGMT, and IDH2, play critical roles in chromatin remodeling, transcriptional reprogramming, DNA repair, and metabolic adaptation. However, their specific expression patterns and functional roles in GBM remain incompletely understood. This study utilizes publicly available data from The Cancer Genome Atlas (TCGA) to assess the transcriptional profiles of ATRX, OLIG2, MGMT, and IDH2 in GBM, aiming to identify potential biomarkers and therapeutic targets. Results: The expression analysis revealed that ATRX is downregulated at the gene level but overexpressed at the protein level, while OLIG2 is consistently overexpressed at both levels. MGMT showed no statistically significant changes in either gene or protein expression, whereas IDH2 was not significantly altered at the gene level but was downregulated at the protein level (p < 0.05). These discrepancies suggest potential post-transcriptional regulatory mechanisms influencing GBM molecular profiles. Notably, OLIG2 and MGMT expression correlated significantly with patient survival (p < 0.05), whereas ATRX and IDH2 did not reach statistical significance. Conclusions: Understanding these molecular relationships provides valuable insights into potential therapeutic strategies, paving the way for precision oncology approaches and combination therapies targeting multiple pathways simultaneously. Full article

The methylation status of the MGMT gene promoter is recognized as a key predictive biomarker for glioblastoma patients, influencing treatment decisions and outcomes. Emerging evidence suggests that enhancer methylation may also play a role in gene regulation and is associated with various clinical parameters, genetic variants, and demographic factors. This study aimed to assess DNA methylation levels in intergenic and intragenic MGMT enhancers to investigate their relationship with MGMT promoter methylation, MGMT protein expression, and clinical and demographic characteristics in glioblastoma. We developed 18 pyrosequencing assays to analyze 54 CpGs, including 34 in intergenic and 20 in intragenic enhancers. The assays were applied to tumor cells derived from 38 glioma patients. Intragenic enhancer CpGs showed significantly higher methylation than intergenic enhancer CpGs. Intragenic enhancer methylation showed a strong negative correlation with MGMT promoter methylation. For several CpGs in intragenic enhancers, an inverse L-shaped relationship between methylation levels and MGMT expression was observed. We identified distinct associations between enhancer methylation and clinical and demographic parameters. Intergenic enhancer methylation was primarily linked to the TERT SNP rs2853669 genotype, Ki-67 expression, age, and sex, whereas intragenic enhancer methylation was associated with MGMT promoter methylation, MGMT expression, overall survival, and progression-free survival. Further studies with larger patient cohorts are needed to validate the clinical relevance of intergenic and intragenic MGMT enhancer methylation in glioblastoma. Full article

(1) Background: Glioblastoma (GBM) is the most aggressive and common primary malignant brain tumor in adults, constituting 45.6% of tumors. We explored the impact of gene methylation of the O-6-Methylguanine-DNA Methyltransferase (MGMT) and the Transforming Growth Factor Beta (TGFB) gene complex using the TCGA dataset for GBM patients. (2) Methods: We implemented a multivariate Cox proportional hazards model to directly compare hazard ratios for TGFB1/2/3 and MGMT methylation in relation to OS, considering male versus female, age at diagnosis, and age interactions with TGFB2 gene methylation and sex variables. Reactome analysis was performed to identify enriched pathways negatively correlated with TGFB2 methylation. (3) Results: The GBM patients had high levels of TGFB2 gene methylation; this primarily benefited the young adult male patients, and multivariate analysis exhibited a significantly improved OS prognosis HR (95% CI range) = 0.04 (0.006–0.274); p = 0.001) relative to the TGFB1^highMe (HR (95% CI range) = 0.657 (0.454–0.951); p = 0.026) and MGMT^highMe (HR (95% CI range) = 0.667 (0.475–0.936); p = 0.019) groups of GBM patients. The Reactome pathways collectively represented T-cell activation, differentiation, effector functions, antigen presentation, and Toll-like receptor pathways. Gene level mRNA expression highlighted four positive prognostic genes upregulated in tumor tissues, and their expression was validated in independent single-cell RNA-seq experiments. These genes were highly expressed in macrophages (HIF1A, TRIM22, IRAK4, PARP9). In contrast, MALT1 mRNA expression was the only gene product with a negative prognostic impact on OS in GBM patients (HR (95% CI range) = 1.997 (1.1–3.625); p = 0.023). (4) Conclusions: Increased levels of TGFB2 gene methylation predict improved OS, especially in young adult male GBM patients, above that of MGMT gene methylation, and should be considered during the administration of mRNA-based TGFB2 therapies. Full article

Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, characterized by rapid growth, invasive infiltration into surrounding brain tissue, and resistance to conventional therapies. Despite advancements in surgery, radiotherapy, and chemotherapy, median survival remains approximately 15 months, underscoring the urgent need for innovative treatments. Key considerations informing treatment development include oncogenic genetic and epigenetic alterations that may dually serve as therapeutic targets and facilitate treatment resistance. Various immunotherapeutic strategies have been explored and continue to be refined for their anti-tumor potential. Technical aspects of drug delivery and blood–brain barrier (BBB) penetration have been addressed through novel vehicles and techniques including the incorporation of nanotechnology. Molecular profiling has emerged as an important tool to individualize treatment where applicable, and to identify patient populations with the most drug sensitivity. The goal of this review is to describe the spectrum of potential GBM therapeutic targets, and to provide an overview of key trial outcomes. Altogether, the progress of clinical and preclinical work must be critically evaluated in order to develop therapies for GBM with the strongest therapeutic efficacy. Full article

Circulating small extracellular vesicles (sEVs) are emerging as potential biomarkers for glioblastoma progression. This study aimed to compare the levels of matrix metalloproteinases (MMP2 and MMP9), terminal complement complex (C5b-9), and VEGF-A in circulating sEVs in glioblastoma patients (GBMPs) with and without tumor recurrence. Using differential ultracentrifugation, sEVs were isolated from blood samples of GBMPs with no tumor recurrence for over one year (n = 6) and after first relapse (n = 14). The vesicles were characterized and quantified using flow cytometry. In both groups, C5b-9 was predominantly detected on tumor-specific circulating sEVs (glial fibrillary acidic protein (GFAP)-positive sEVs) with high VEGF-A expression, while C5b-9 was significantly less frequent on sEVs with low VEGF-A expression (p < 0.05). GFAP+VEGF+dimMMP2-C5b-9+ vesicles were rarely detected in GBMPs without relapse, suggesting their potential utility as biomarkers for a favorable relapse-free prognosis. In recurrent GBMPs, a positive correlation was observed between GFAP+VEGF+bright MMP2+C5b-9+ sEVs and MGMT gene promoter methylation levels (r = 0.543, p < 0.05). Additionally, a trend toward a negative correlation was found between GFAP+VEGF+bright MMP2+C5b-9- sEVs and mutant p53 expression in primary tumor tissue (r = −0.44, p = 0.114). These findings suggest that sEV profiles may serve as valuable prognostic markers for glioblastoma recurrence and treatment responses. Full article

The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: IDH1/2, ATRX, TP53 mutations, TERT promoter mutations, CDKN2A/B homozygous deletion (CHD), EGFR amplification (EGFRamp), 7 gain/10 loss (7+/10−), 1p/19q co-deletion, and MGMT promoter methylation. GLISP consists of a pair of patch-level GLISP-P and patient-level GLISP-W models, each pair of which is for a genetic prediction task, providing flexibility in clinical utility. In this study, the Cancer Genome Atlas whole-slide images (WSIs) were used to train the model. A total of 108 WSIs from the Tokyo Women’s Medical University were used as the external dataset. In cross-validation, GLISP yielded patch-level/case-level predictions with top performances in IDH1/2 and 1p/19q co-deletion with average areas under the curve (AUCs) of receiver operating characteristics of 0.75/0.79 and 0.73/0.80, respectively. In external validation, the patch-level/case-level AUCs of IDH1/2 and 1p/19q co-deletion detection were 0.76/0.83 and 0.78/0.88, respectively. The accuracy in diagnosing IDH-mutant astrocytoma, oligodendroglioma, and IDH-wild-type glioblastoma was 0.66, surpassing the human pathologist average of 0.62 (0.54–0.67). In conclusion, GLISP is a two-stage AI framework for histology-based prediction of genetic events in adult gliomas, which is helpful in providing essential information for WHO 2021 molecular diagnoses. Full article

Background/Objectives: Glioblastoma (GBM) is the most common malignant primary central nervous system tumor with extremely poor prognosis and survival outcomes. Non-invasive methods like radiomic feature extraction, which assess sub-visual imaging features, provide a potentially powerful tool for distinguishing molecular profiles across groups of patients with GBM. Using consensus clustering of MRI-based radiomic features, this study aims to investigate differential gene expression profiles based on radiomic clusters. Methods: Patients from the TCGA and CPTAC datasets (n = 114) were included in this study. Radiomic features including T1, T1 with contrast, T2, and FLAIR MRI sequences were extracted using PyRadiomics. Selected radiomic features were then clustered using ConsensusClusterPlus (k-means base algorithm and Euclidean distance), which iteratively subsamples and clusters 80% of the data to identify stable clusters by calculating the frequency in which each patient is a member of a cluster across iterations. Gene expression data (available for n = 69 patients) was analyzed using differential gene expression (DEG) and gene set enrichment (GSEA) approaches, after batch correction using ComBat-seq. Results: Three distinct clusters were identified based on the relative consensus matrix and cumulative distribution plots (Cluster 1, n = 25; Cluster 2, n = 46; Cluster 3, n = 43). No significant differences in patient demographic characteristics, MGMT methylation status, tumor location, or overall survival were identified across clusters. Differentially expressed genes were identified in Cluster 1, which have been previously associated with GBM prognosis, recurrence, and treatment sensitivity. GSEA of Cluster 1 showed an enrichment of genes upregulated for immune-related and DNA metabolism pathways and genes downregulated in pathways associated with protein and histone deacetylation. Clusters 2 and 3 exhibited fewer DEGs which failed to reach significance after multiple testing corrections. Conclusions: Consensus clustering of radiomic features revealed unique gene expression profiles in the GBM cohort which likely represent subtle differences in tumor biology and radiosensitivity that are not visually discernible, underscoring the potential of radiomics to serve as a non-invasive alternative for identifying GBM molecular heterogeneity. Further investigation is still required to validate these findings and their clinical implications. Full article

Introduction. The treatment for patients with high-grade gliomas includes surgical resection of tumor, radiotherapy, and temozolomide chemotherapy. However, some patients do not respond to temozolomide due to a methylation reversal mechanism by the enzyme O⁶-methylguanine-DNA-methyltransferase (MGMT). In patients receiving treatment with temozolomide, this biomarker has been used as a prognostic factor. However, not all patients respond in the same way, which suggests the existence of other proteins involved in resistance to temozolomide chemotherapy. Methods. A group of thirty-one patients was recruited who were clinically and pathologically diagnosed with high-grade gliomas. The sequencing of 324 genes related to different types of cancer was performed to detect mutations. Subsequently, a statistical analysis was conducted to determine the mutated genes that were most related to resistance to treatment. Results. According to the Stupp protocol and metronomic dose of the temozolomide treatment, the mutated genes related to the second relapse of patients with high-grade glioma were PIK3C2B, KIT, ERBB3, and MLH1. Conclusions. Considering the results obtained, we suggest that mutations in the four genes and methylation of the gene promoter that codes for the MGMT protein could be related to response to treatment with temozolomide. Full article

Isocitrate dehydrogenase (IDH) and O⁶-methylguanine-DNA methyltransferase (MGMT) genes are critical molecular markers in determining treatment options and predicting the prognosis of adult-type diffuse gliomas. Objectives: this study aimed to investigate whether multimodal MRI enables the differentiation of genotypes in adult-type diffuse gliomas. Methods: a total of 116 adult-type diffuse glioma patients (61 males, 51.5 (37, 62) years old) who underwent multimodal MRI before surgery were retrospectively analysed. Multimodal MRI included conventional MRI, proton magnetic resonance spectroscopy (¹H-MRS), and diffusion tensor imaging (DTI). Conventional visual features, N-acetyl-aspartate (NAA)/Creatine (Cr), Choline (Cho)/Cr, Cho/NAA, fractional anisotropy (FA), mean diffusivity (MD), and diffusion histogram parameters were extracted on the whole tumour. Multimodal MRI parameters of IDH-mutant and IDH-wildtype gliomas were compared using the Mann–Whitney U test, Student’s t-test, or Pearson chi-square tests. Logistic regression was used to select the MRI parameters to predict IDH-mutant gliomas. Furthermore, multimodal MRI parameters were selected to establish models for predicting MGMT methylation in the IDH-wildtype gliomas. The performance of models was evaluated by the receiver operating characteristics curve. Results: a total of 56 patients with IDH-mutant gliomas and 60 patients with IDH-wildtype glioblastomas (GBM) (37 with methylated MGMT and 17 with unmethylated MGMT) were diagnosed by 2021 WHO classification criteria. The enhancement degree (OR = 4.298, p < 0.001), necrosis/cyst (OR = 5.381, p = 0.011), NAA/Cr (OR = 0.497, p = 0.037), FA-Skewness (OR = 0.497, p = 0.033), MD-Skewness (OR = 1.849, p = 0.035), FA_mean (OR = 1.924, p = 0.049) were independent factors for the multimodal combined prediction model in predicting IDH-mutant gliomas. The combined modal based on conventional MRI, ¹H-MRS, DTI parameters, and histogram performed best in predicting IDH-wildtype status (AUC = 0.890). However, only NAA/Cr (OR = 0.17, p = 0.043) and FA (OR = 0.38, p = 0.015) were associated with MGMT methylated in IDH-wildtype GBM. The combination of NAA/Cr and FA-Median is more accurate for predicting MGMT methylation levels than using these elements alone (AUC, 0.847 vs. 0.695/0.684). Conclusions: multimodal MRI based on conventional MRI, ¹H-MRS, and DTI can provide compound imaging markers for stratified individual diagnosis of IDH mutant and MGMT promoter methylation in adult-type diffuse gliomas. Full article

Background: O-6-methylguanine-DNA methyltransferase is responsible for the direct repair of O6-methylguanine lesions induced by alkylating agents, including temozolomide. O-6-methylguanine-DNA methyltransferase promoter hypermethylation is a well-established biomarker for temozolomide response in glioblastoma patients, also correlated with therapeutic response in colorectal cancer. Objectives: The ARETHUSA clinical trial aims to stratify colorectal cancer patients based on their mismatch repair status. Mismatch repair-deficient patients are eligible for treatment with immune checkpoint inhibitors (anti-PDL-1), whereas mismatch repair-proficient samples are screened for O-6-methylguanine-DNA methyltransferase promoter methylation to identify those suitable for temozolomide treatment. Methods: In this context, a subset of ARETHUSA metastatic colorectal cancer samples was used to compare two different techniques for assessing O-6-methylguanine-DNA methyltransferase hypermethylation: Methyl-BEAMing, a highly sensitive digital PCR approach that combines emulsion PCR and flow cytometry, and droplet digital PCR, a more automated procedure that enables the rapid, operator-independent analysis of a large number of samples. Results: Our study clearly demonstrates that the results obtained using Methyl-BEAMing and droplet digital PCR are comparable, with both techniques showing similar accuracy, sensitivity, and reproducibility. Conclusions: Digital droplet PCR proved to be an efficient method for detecting gene promoter methylation. However, the Methyl-BEAMing method has proved more sensitive for detecting low quantities of DNA. Full article

Laryngeal cancer poses a substantial challenge in head and neck oncology, and there is a growing focus on customized medicine techniques. The present state of gene expression indicators in laryngeal cancer and their potential to inform tailored therapy choices are thoroughly examined in this review. We examine significant molecular changes, such as TP53, CDKN2A, PIK3CA, and NOTCH1 mutations, which have been identified as important participants in the development of laryngeal cancer. The study investigates the predictive and prognostic significance of these genetic markers in addition to the function of epigenetic changes such as the methylation of the MGMT promoter. We also go over the importance of cancer stem cell-related gene expression patterns, specifically CD44 and ALDH1A1 expression, in therapy resistance and disease progression. The review focuses on indicators, including PD-L1, CTLA-4, and tumor mutational burden (TMB) in predicting immunotherapy responses, highlighting recent developments in our understanding of the intricate interactions between tumor genetics and the immune milieu. We also investigate the potential for improving prognosis accuracy and treatment selection by the integration of multi-gene expression panels with clinicopathological variables. The necessity for uniform testing and interpretation techniques is one of the difficulties, in implementing these molecular insights into clinical practice, that are discussed. This review seeks to provide a comprehensive framework for promoting personalized cancer therapy by combining the most recent data on gene expression profiling in laryngeal cancer. Molecularly guided treatment options may enhance patient outcomes. Full article

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. Full article