The prognostic value of MGMT promoter methylation in Glioblastoma multiforme: a meta-analysis

Prognostic Factors for Recurrent Glioma: A Population-Based Analysis

Background

The overall survival (OS) for patients with recurrent glioma is meager. Also, the effect of radionecrosis and prognostic factors for recurrent glioma remains controversial. In this regard, developing effective predictive models and guiding clinical care is crucial for these patients.

Methods

We screened patients with recurrent glioma after radiotherapy and those who received surgery between August 1, 2013, and December 31, 2020. Univariate and multivariate Cox regression analyses determined the independent prognostic factors affecting the prognosis of recurrent glioma. Moreover, nomograms were constructed to predict recurrent glioma risk and prognosis. Statistical methods were used to determine the prediction accuracy and discriminability of the nomogram prediction model based on the area under the curve (AUC), the C-index, the decision curve analysis (DCA), and the calibration curve. In order to distinguish high-risk and low-risk groups for OS, the X-Tile and Kaplan-Meier (K-M) survival curves were employed, and the nomogram prediction model was further validated by the X-Tile and K-M survival curves.

Results

According to a Cox regression analysis, independent prognostic factors of recurrent glioma after radiotherapy with radionecrosis were World Health Organization (WHO) grade and gliosis percentage. We utilized a nomogram prediction model to analyze results visually. The C-index was 0.682 (95% CI: 0.616-0.748). According to receiver operating characteristic (ROC) analysis, calibration plots, and DCA, the nomogram prediction model was found to have a high-performance ability, and all patients were divided into low-risk and high-risk groups based on OS (P < .001).

Conclusion

WHO grade and gliosis percentage are prognostic factors for recurrent glioma with radionecrosis, and a nomogram prediction model was established based on these two variables. Patients could be divided into high- and low-risk groups with different OS by this model, and it will provide individualized clinical decisions for future treatment.

Prognosis of MGMT -Positive Gene in Patients with Brain Tumors of Grade III and Grade IV

Sumit GoyalObjective  To evaluate MGMT gene positivity is associated with better survival in patients diagnosed with brain tumor World Health Organization (WHO) grades III and IV Material and Methods  Single-institute restrospective study. A total of 80 patients were enrolled, all underwent surgery either total or subtotal excision of the tumor and MGMT gene testing on tumor tissue by RT-PCR. All received adjuvant radiation (60 Gy/30 fractions, 5 fractions/week) with concurrent temozolomide (75 mg/m 2 ), followed by 12 cycles of adjuvant temozolomide (150 mg/m 2 1st cycle followed by 200 mg/m 2 ) with regular follow-up. Results  A total of 80 patients, 75 underwent subtotal excision, 27 were WHO grade III vs. 48 WHO grade IV. Five underwent total excision 1 was WHO grade III vs. 4 WHO grade IV. The median PFS and OS in five patients in total excision in grade III patient was 9.0 and 20 compared with Grade IV, where the median PFS and OS was 8.8 and 17.8 months. Out of 75 patients in the subtotal group median PFS and OS, respectively, in Grade III group was 9.1 and 19.3 and, WHO grade IV with median PFS of 8.8 and OS of 18.8. Conclusion   MGMT gene positivity is a prognostic factor in grade III and IV brain tumor.

Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme

Glioblastoma multiforme (GM) is a malignant tumor of the central nervous system considered to be highly aggressive and often carrying a terrible survival prognosis. An accurate prognosis is therefore pivotal for deciding a good treatment plan for patients. In this context, computational intelligence applied to data of electronic health records (EHRs) of patients diagnosed with this disease can be useful to predict the patients' survival time. In this study, we evaluated different machine learning models to predict survival time in patients suffering from glioblastoma and further investigated which features were the most predictive for survival time. We applied our computational methods to three different independent open datasets of EHRs of patients with glioblastoma: the Shieh dataset of 84 patients, the Berendsen dataset of 647 patients, and the Lammer dataset of 60 patients. Our survival time prediction techniques obtained concordance index (C-index) = 0.583 in the Shieh dataset, C-index = 0.776 in the Berendsen dataset, and C-index = 0.64 in the Lammer dataset, as best results in each dataset. Since the original studies regarding the three datasets analyzed here did not provide insights about the most predictive clinical features for survival time, we investigated the feature importance among these datasets. To this end, we then utilized Random Survival Forests, which is a decision tree-based algorithm able to model non-linear interaction between different features and might be able to better capture the highly complex clinical and genetic status of these patients. Our discoveries can impact clinical practice, aiding clinicians and patients alike to decide which therapy plan is best suited for their unique clinical status.

Prognostic evaluation of patients with glioblastoma using a new score prediction model

Despite the wide reportage of prognostic factors for glioblastoma (GBM), it is difficult to determine how these factors interact to affect patients' survival. To determine the combination of prognostic factors, we retrospectively analyzed the clinic data of 248 IDH wild-type GBM patients and built a novel prediction model. The survival variables of patients were identified via univariate and multivariate analyses. In addition, the score prediction models were constructed by combining classification and regression tree (CART) analysis with Cox regression analysis. Finally, the prediction model was internally validated using the bootstrap method. Patients were followed for a median of 34.4 (interquartile range, 26.1-46.0) months. Multivariate analysis identified gross total resection (GTR) (HR 0.50, 95% CI: 0.38-0.67), unopened ventricles (HR 0.75 [0.57-0.99]), and MGMT methylation (HR 0.56 [0.41-0.76]) as favorable independent prognostic factors for PFS. GTR (HR 0.67 [0.49-0.92]), unopened ventricles (HR 0.60 [0.44-0.82]), and MGMT methylation (HR 0.54 [0.38-0.76]) were favorable independent prognostic factors for OS. In the process of building the model, we incorporated GTR, ventricular opening, MGMT methylation status, and age. The model had six and five terminal nodules in PFS and OS respectively. We grouped terminal nodes with similar hazard ratios together to form three sub-groups with different PFS and OS (P < 0.001). After the internal verification of bootstrap method, the model had a good fitting and calibration. GTR, unopened ventricles, and MGMT methylation were independently associated with more satisfactory survival. The novel score prediction model which we construct can provide a prognostic reference for GBM.

A Holistic Approach to Hard-to-Treat Cancers: The Future of Immunotherapy for Glioblastoma, Triple Negative Breast Cancer, and Advanced Prostate Cancer

Immunotherapy represents an attractive avenue for cancer therapy due to its tumour specificity and relatively low frequency of adverse effects compared to other treatment modalities. Despite many advances being made in the field of cancer immunotherapy, very few immunotherapeutic treatments have been approved for difficult-to-treat solid tumours such as triple negative breast cancer (TNBC), glioblastoma multiforme (GBM), and advanced prostate cancer (PCa). The anatomical location of some of these cancers may also make them more difficult to treat. Many trials focus solely on immunotherapy and have failed to consider or manipulate, prior to the immunotherapeutic intervention, important factors such as the microbiota, which itself is directly linked to lifestyle factors, diet, stress, social support, exercise, sleep, and oral hygiene. This review summarises the most recent treatments for hard-to-treat cancers whilst factoring in the less conventional interventions which could tilt the balance of treatment in favour of success for these malignancies.

Identification of Prominent Genes between 3D Glioblastoma Models and Clinical Samples via GEO/TCGA/CGGA Data Analysis

A paradigm shift in preclinical evaluations of new anticancer GBM drugs should occur in favour of 3D cultures. This study leveraged the vast genomic data banks to investigate the suitability of 3D cultures as cell-based models for GBM. We hypothesised that correlating genes that are highly upregulated in 3D GBM models will have an impact in GBM patients, which will support 3D cultures as more reliable preclinical models for GBM. Using clinical samples of brain tissue from healthy individuals and GBM patients from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA), and Genotype-Tissue Expression (GTEx) databases, several genes related to pathways such as epithelial-to-mesenchymal transition (EMT)-related genes (CD44, TWIST1, SNAI1, CDH2, FN1, VIM), angiogenesis/migration-related genes (MMP1, MMP2, MMP9, VEGFA), hypoxia-related genes (HIF1A, PLAT), stemness-related genes (SOX2, PROM1, NES, FOS), and genes involved in the Wnt signalling pathway (DKK1, FZD7) were found to be upregulated in brain samples from GBM patients, and the expression of these genes were also enhanced in 3D GBM cells. Additionally, EMT-related genes were upregulated in GBM archetypes (wild-type IDH1^R132 ) that historically have poorer treatment responses, with said genes being significant predictors of poorer survival in the TCGA cohort. These findings reinforced the hypothesis that 3D GBM cultures can be used as reliable models to study increased epithelial-to-mesenchymal transitions in clinical GBM samples.

Influence of MMR, MGMT Promotor Methylation and Protein Expression on Overall and Progression-Free Survival in Primary Glioblastoma Patients Treated with Temozolomide

Glioblastoma is the most common malignant brain tumor in adults. Standard treatment includes tumor resection, radio-chemotherapy and adjuvant chemotherapy with temozolomide (TMZ). TMZ methylates DNA, whereas O6-methylguanine DNA methyltransferase (MGMT) counteracts TMZ effects by removing the intended proteasomal degradation signal. Non-functional MGMT mediates the mismatch repair (MMR) system, leading to apoptosis after futile repair attempts. This study investigated the associations between MGMT promoter methylation, MGMT and MMR protein expression, and their effect on overall survival (OS) and progression-free survival (PFS) in patients with glioblastoma. MGMT promoter methylation was assessed in 42 treatment-naïve patients with glioblastoma WHO grade IV by pyrosequencing. MGMT and MMR protein expression was analyzed using immunohistochemistry. MGMT promoter methylation was present in 52%, whereas patients <70 years of age revealed a significantly longer OS using a log-rank test and a significance threshold of p ≤ 0.05. MGMT protein expression and methylation status showed no correlation. MMR protein expression was present in all patients independent of MGMT status and did not influence OS and PFS. Overall, MGMT promoter methylation implicates an improved OS in patients with glioblastoma aged <70 years. In the elderly, the extent of surgery has an impact on OS rather than the MGMT promoter methylation or protein expression.

MGMT Promoter Methylation as a Prognostic Factor in Primary Glioblastoma: A Single-Institution Observational Study

Glioblastoma is the most malignant central nervous system tumor, which represents 50% of all glial tumors. The understanding of glioma genesis, prognostic evaluation, and treatment planning has been significantly enhanced by the discovery of molecular genetic biomarkers. This study aimed to evaluate survival in patients with primary glioblastoma concerning O6-methylguanine–DNA methyltransferase (MGMT) promoter methylation and other clinical factors. The study included 41 newly diagnosed glioblastoma patients treated from 2011 to 2014 in the 10th Military Research Hospital and Polyclinic, Poland. All patients underwent surgical resection followed by radiation and chemotherapy with alkylating agents. The MGMT promoter methylation was evaluated in all patients, and 43% were found to be methylated. In 26 and 15 cases, gross total resection and subtotal resection were conducted, respectively. Patients with a methylated MGMT promoter had a median survival of 504 days, while those without methylation had a median survival of 329 days. The group that was examined had a median age of 53. In a patient group younger than 53 years, those with methylation had significantly longer overall survival (639 days), compared to 433.5 days for patients without methylation. The most prolonged survival (551 days) was in patients with MGMT promoter methylation after gross total resection. The value of MGMT promoter methylation as a predictive biomarker is widely acknowledged. However, its prognostic significance remains unclear. Our findings proved that MGMT promoter methylation is also an essential positive prognostic biomarker.

Molecular Biomarkers in Glioblastoma: A Systematic Review and Meta-Analysis

Background: Glioblastoma (GBM) is a highly aggressive cancer with poor prognosis that needs better treatment modalities. Moreover, there is a lack of reliable biomarkers to predict the response and outcome of current or newly designed therapies. While several molecular markers have been proposed as potential biomarkers for GBM, their uptake into clinical settings is slow and impeded by marker heterogeneity. Detailed assessment of prognostic and predictive value for biomarkers in well-defined clinical trial settings, if available, is scattered throughout the literature. Here we conducted a systematic review and meta-analysis to evaluate the prognostic and predictive significance of clinically relevant molecular biomarkers in GBM patients. Material and methods: A comprehensive literature search was conducted to retrieve publications from 3 databases (Pubmed, Cochrane and Embase) from January 2010 to December 2021, using specific terms. The combined hazard ratios (HR) and confidence intervals (95% CI) were used to evaluate the association of biomarkers with overall survival (OS) in GBM patients. Results: Twenty-six out of 1831 screened articles were included in this review. Nineteen articles were included in the meta-analyses, and 7 articles were quantitatively summarised. Fourteen studies with 1231 GBM patients showed a significant association of MGMT methylation with better OS with the pooled HR of 1.66 (95% CI 1.32−2.09, p < 0.0001, random effect). Five studies including 541 GBM patients analysed for the prognostic significance of IDH1 mutation showed significantly better OS in patients with IDH1 mutation with a pooled HR of 2.37 (95% CI 1.81−3.12; p < 0.00001]. Meta-analysis performed on 5 studies including 575 GBM patients presenting with either amplification or high expression of EGFR gene did not reveal any prognostic significance with a pooled HR of 1.31 (95% CI 0.96−1.79; p = 0.08). Conclusions: MGMT promoter methylation and IDH1 mutation are significantly associated with better OS in GBM patients. No significant associations were found between EGFR amplification or overexpression with OS.

Survival Outcomes and Prognostic Factors in Glioblastoma

Background: IDH-wildtype glioblastoma is the most common malignant primary brain tumour in adults. As there is limited information on prognostic factors outside of clinical trials; thus, we conducted a retrospective study to characterise the glioblastoma population at our centre. Methods: Demographic, tumour molecular profiles, treatment, and survival data were collated for patients diagnosed with glioblastoma at our centre between July 2011 and December 2015. We used multivariate proportional hazard model associations with survival. Results: 490 patients were included; 60% had debulking surgery and 40% biopsy only. Subsequently, 56% had standard chemoradiotherapy, 25% had non-standard chemo/radio-therapy, and 19% had no further treatment. Overall survival was 9.2 months. In the multivariate analysis, longer survival was associated with debulking surgery vs. biopsy alone (14.9 vs. 8 months) (HR 0.54 [95% CI 0.41−0.70]), subsequent treatment after diagnosis (HR 0.12 [0.08−0.16]) (standard chemoradiotherapy [16.9 months] vs. non-standard regimens [9.2 months] vs. none [2.0 months]), tumour MGMT promotor methylation (HR 0.71 [0.58−0.87]), and younger age (hazard ratio vs. age < 50: 1.70 [1.26−2.30] for ages 50−59; 3.53 [2.65−4.70] for ages 60−69; 4.82 [3.54−6.56] for ages 70+). Conclusions: The median survival for patients with glioblastoma is less than a year. Younger age, debulking surgery, treatment with chemoradiotherapy, and MGMT promotor methylation are independently associated with longer survival.

ERβ overexpression may not be a direct prognostic factor in patients with NSCLC: A meta-analysis

BACKGROUND

Overall survival of non-small cell lung cancer (NSCLC) patients remains disappointingly low. The estrogen receptor (ER) was considered a promising therapeutic target for NSCLC. Numerous studies have linked expression of ERβ to lung cancer outcome. However, results are conflicting regarding the association of ERβ with surviving lung cancer.

METHOD

The aim of this meta-analysis was to evaluate the prognostic aspect of ERβ expression on survival among NSCLC patients. We performed a final analysis of prognostic value of overexpression ERβ on 3500 patients from 18 evaluable studies (from January 1, 2000 to May 1, 2021). The reference category is specified as low ERβ expression levels. Summarized hazard ratios were calculated.

RESULTS

Our study showed that the pooled hazard ratios of ERβ overexpression for overall survival in NSCLC was 0.81 (95% confidence interval (CI): 0.64-1.02, P = 0.07) by univariate analysis and 1.06 (95% CI: 0.83-1.36, P = 0.63) by multivariate analysis. Pooled hazard ratio by univariate analysis in Asian studies was 0.73 (95%CI: 0.59-0.89, P = 0.002). Pooled hazard ratio by univariate analysis was 0.75 (95% CI: 0.61-0.93, P = 0.009) from seven studies reported for nuclear ERβ. No significant results were found in subgroups by multivariate analysis. No significant results were found in studies outside Asia or in studies reported for cytoplasmic ERβ.

CONCLUSION

Our results suggested that expression of ERβ might not be a direct prognostic factor for NSCLC patients. More detailed prospective studies are needed to identify direct prognostic factors in these patients.

IDH-wild-type glioblastoma cell density and infiltration distribution influence on supramarginal resection and its impact on overall survival: a mathematical model

OBJECTIVE

Recent studies have proposed resection of the T2 FLAIR hyperintensity beyond the T1 contrast enhancement (supramarginal resection [SMR]) for IDH-wild-type glioblastoma (GBM) to further improve patients' overall survival (OS). GBMs have significant variability in tumor cell density, distribution, and infiltration. Advanced mathematical models based on patient-specific radiographic features have provided new insights into GBM growth kinetics on two important parameters of tumor aggressiveness: proliferation rate (ρ) and diffusion rate (D). The aim of this study was to investigate OS of patients with IDH-wild-type GBM who underwent SMR based on a mathematical model of cell distribution and infiltration profile (tumor invasiveness profile).

METHODS

Volumetric measurements were obtained from the selected regions of interest from pre- and postoperative MRI studies of included patients. The tumor invasiveness profile (proliferation/diffusion [ρ/D] ratio) was calculated using the following formula: ρ/D ratio = (4π/3)2/3 × (6.106/[VT21/1 - VT11/1])2, where VT2 and VT1 are the preoperative FLAIR and contrast-enhancing volumes, respectively. Patients were split into subgroups based on their tumor invasiveness profiles. In this analysis, tumors were classified as nodular, moderately diffuse, or highly diffuse.

RESULTS

A total of 101 patients were included. Tumors were classified as nodular (n = 34), moderately diffuse (n = 34), and highly diffuse (n = 33). On multivariate analysis, increasing SMR had a significant positive correlation with OS for moderately and highly diffuse tumors (HR 0.99, 95% CI 0.98-0.99; p = 0.02; and HR 0.98, 95% CI 0.96-0.99; p = 0.04, respectively). On threshold analysis, OS benefit was seen with SMR from 10% to 29%, 10% to 59%, and 30% to 90%, for nodular, moderately diffuse, and highly diffuse, respectively.

CONCLUSIONS

The impact of SMR on OS for patients with IDH-wild-type GBM is influenced by the degree of tumor invasiveness. The authors' results show that increasing SMR is associated with increased OS in patients with moderate and highly diffuse IDH-wild-type GBMs. When grouping SMR into 10% intervals, this benefit was seen for all tumor subgroups, although for nodular tumors, the maximum beneficial SMR percentage was considerably lower than in moderate and highly diffuse tumors.

Differences in stem cell marker and osteopontin expression in primary and recurrent glioblastoma

Background

Despite of a multimodal approach, recurrences can hardly be prevented in glioblastoma. This may be in part due to so called glioma stem cells. However, there is no established marker to identify these stem cells.

Methods

Paired samples from glioma patients were analyzed by immunohistochemistry for expression of the following stem cell markers: CD133, Musashi, Nanog, Nestin, octamer-binding transcription factor 4 (Oct4), and sex determining region Y-box 2 (Sox2). In addition, the expression of osteopontin (OPN) was investigated. The relative number of positively stained cells was determined. By means of Kaplan–Meier analysis, a possible association with overall survival by marker expression was investigated.

Results

Sixty tissue samples from 30 patients (17 male, 13 female) were available for analysis. For Nestin, Musashi and OPN a significant increase was seen. There was also an increase (not significant) for CD133 and Oct4. Patients with mutated Isocitrate Dehydrogenase-1/2 (IDH-1/2) status had a reduced expression for CD133 and Nestin in their recurrent tumors. Significant correlations were seen for CD133 and Nanog between OPN in the primary and recurrent tumor and between CD133 and Nestin in recurrent tumors. By confocal imaging we could demonstrate a co-expression of CD133 and Nestin within recurrent glioma cells. Patients with high CD133 expression had a worse prognosis (22.6 vs 41.1 months, p = 0.013). A similar trend was seen for elevated Nestin levels (24.9 vs 41.1 months, p = 0.08).

Conclusions

Most of the evaluated markers showed an increased expression in their recurrent tumor. CD133 and Nestin were associated with survival and are candidate markers for further clinical investigation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-022-02510-4.

European Mistletoe (Viscum album) Extract Is Cytotoxic to Canine High-Grade Astrocytoma Cells In Vitro and Has Additive Effects with Mebendazole

Malignant gliomas are associated with extremely poor clinical outcomes in both humans and dogs, and novel therapies are needed. Glioma-bearing canine patients may serve as promising preclinical models for human therapies, including complementary medicine. The objective of this study was to evaluate the effects of mistletoe extract (Viscum album) alone and in combination with mebendazole in an in vitro model of canine high-grade astrocytoma using the cell line SDT-3G. SDT-3G cells were exposed to a range of concentrations of mistletoe extract alone to obtain an IC50. In separate experiments, cells were exposed to mebendazole at a previously determined IC50 (0.03 µM) alone or in conjunction with varying concentrations of mistletoe extract to determine the additive effects. The IC50 for mistletoe alone was 5.644 ± 0.09 SD μg/mL. The addition of mistletoe at 5 μg/mL to mebendazole at 0.03 µM led to increased cell death compared to what would be expected for each drug separately. The cytotoxicity of mistletoe in vitro and its additive effect with mebendazole support future expanded in vitro and in vivo studies in dogs and supply early evidence that this may be a useful adjunct therapeutic agent for use in glioma-bearing dogs. To the authors’ knowledge, this is the first published report of Viscum album extract in canine glioma.

The Impact of Tumor Treating Fields on Glioblastoma Progression Patterns

BACKGROUND

Tumor-treating fields (TTFields) is an antimitotic treatment modality that interferes with glioblastoma cell division and organelle assembly by delivering low-intensity alternating electric fields to the tumor. A previous analysis from the pivotal EF-14 trial demonstrated a clear correlation between TTFields dose-density at the tumor bed and survival in patients treated with TTFields. This study tests the hypothesis that the antimitotic effects of TTFields result in measurable changes in the location and patterns of progression of newly diagnosed glioblastoma (nGBM) patients.

METHODS

MRI images of 428 nGBM patients that participated in the pivotal EF-14 trial were reviewed and the rates at which distant progression occurred in the TTFields treatment and control arm were compared. Realistic head models of 252 TTFields treated patients were created and TTFields intensity distributions were calculated using a Finite Elements Method. TTFields dose was calculated within regions of the tumor bed and normal brain and its relationship with progression determined.

RESULTS

Distant progression was frequently observed in the TTFields-treated arm, and distant lesions in the TTFields-treated arm appeared at larger distances from the primary lesion than in the control arm. Distant progression correlated with improved clinical outcome in the TTFields patients, with no such correlation observed in the controls. Areas of normal brain that remained normal were exposed to higher TTFields doses compared to normal brain that subsequently exhibited neoplastic progression. Additionally, the average dose to areas of enhancing tumor that returned to normal was significantly higher than in the areas of normal brain that progressed to enhancing tumor.

CONCLUSIONS

There was a direct correlation between TTFields dose distribution and tumor response, confirming the therapeutic activity of TTFields and the rationale for optimizing array placement to maximize TTFields dose in areas at highest risk of progression, as well as array layout adaptation after progression.

Approaching Sites of Action of Temozolomide for Pharmacological and Clinical Studies in Glioblastoma

Temozolomide (TMZ), together with bulk resection and focal radiotherapy, is currently a standard of care for glioblastoma. Absorption, distribution, metabolism, and excretion (ADME) parameters, together with the mode of action of TMZ, make its biochemical and biological action difficult to understand. Accurate understanding of the mode of action of TMZ and the monitoring of TMZ at its anatomical, cellular, and molecular sites of action (SOAs) would greatly benefit precision medicine and the development of novel therapeutic approaches in combination with TMZ. In the present perspective article, we summarize the known ADME parameters and modes of action of TMZ, and we review the possible methodological options to monitor TMZ at its SOAs. We focus our descriptions of methodologies on mass spectrometry-based approaches, and all related considerations are taken into account regarding the avoidance of artifacts in mass spectrometric analysis during sampling, sample preparation, and the evaluation of results. Finally, we provide an overview of potential applications for precision medicine and drug development.

DNA damage repair in glioblastoma: current perspectives on its role in tumour progression, treatment resistance and PIKKing potential therapeutic targets

BACKGROUND

The aggressive, invasive and treatment resistant nature of glioblastoma makes it one of the most lethal cancers in humans. Total surgical resection is difficult, and a combination of radiation and chemotherapy is used to treat the remaining invasive cells beyond the tumour border by inducing DNA damage and activating cell death pathways in glioblastoma cells. Unfortunately, recurrence is common and a major hurdle in treatment, often met with a more aggressive and treatment resistant tumour. A mechanism of resistance is the response of DNA repair pathways upon treatment-induced DNA damage, which enact cell-cycle arrest and repair of DNA damage that would otherwise cause cell death in tumour cells.

CONCLUSIONS

In this review, we discuss the significance of DNA repair mechanisms in tumour formation, aggression and treatment resistance. We identify an underlying trend in the literature, wherein alterations in DNA repair pathways facilitate glioma progression, while established high-grade gliomas benefit from constitutively active DNA repair pathways in the repair of treatment-induced DNA damage. We also consider the clinical feasibility of inhibiting DNA repair in glioblastoma and current strategies of using DNA repair inhibitors as agents in combination with chemotherapy, radiation or immunotherapy. Finally, the importance of blood-brain barrier penetrance when designing novel small-molecule inhibitors is discussed.

Prognostic and Predictive Biomarkers in Gliomas

Gliomas are the most common central nervous system tumors. New technologies, including genetic research and advanced statistical methods, revolutionize the therapeutic approach to the patient and reveal new points of treatment options. Moreover, the 2021 World Health Organization Classification of Tumors of the Central Nervous System has fundamentally changed the classification of gliomas and incorporated many molecular biomarkers. Given the rapid progress in neuro-oncology, here we compile the latest research on prognostic and predictive biomarkers in gliomas. In adult patients, IDH mutations are positive prognostic markers and have the greatest prognostic significance. However, CDKN2A deletion, in IDH-mutant astrocytomas, is a marker of the highest malignancy grade. Moreover, the presence of TERT promoter mutations, EGFR alterations, or a combination of chromosome 7 gain and 10 loss upgrade IDH-wildtype astrocytoma to glioblastoma. In pediatric patients, H3F3A alterations are the most important markers which predict the worse outcome. MGMT promoter methylation has the greatest clinical significance in predicting responses to temozolomide (TMZ). Conversely, mismatch repair defects cause hypermutation phenotype predicting poor response to TMZ. Finally, we discussed liquid biopsies, which are promising diagnostic, prognostic, and predictive techniques, but further work is needed to implement these novel technologies in clinical practice.

MGMT promoter methylation testing to predict overall survival in people with glioblastoma treated with temozolomide: a comprehensive meta-analysis based on a Cochrane Systematic Review

BACKGROUND

The DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT) causes resistance of tumor cells to alkylating agents. It is a predictive biomarker in high-grade gliomas treated with temozolomide, however, there is no consensus on which test method, methylation sites, and cutoff values to use.

METHODS

We performed a Cochrane Review to examine studies using different techniques to measure MGMT and predict survival in glioblastoma patients treated with temozolomide. Eligible longitudinal studies included (i) adults with glioblastoma treated with temozolomide with or without radiotherapy, or surgery; (ii) where MGMT status was determined in tumor tissue, and assessed by 1 or more technique; and (iii) where overall survival was an outcome parameter, with sufficient information to estimate hazard ratios (HRs). Two or more methods were compared in 32 independent cohorts with 3474 patients.

RESULTS

Methylation-specific PCR (MSP) and pyrosequencing (PSQ) techniques were more prognostic than immunohistochemistry for MGMT protein, and PSQ is a slightly better predictor than MSP.

CONCLUSIONS

We cannot draw strong conclusions about use of frozen tissue vs formalin-fixed paraffin-embedded in MSP and PSQ. Also, our meta-analysis does not provide strong evidence about the best CpG sites or threshold. MSP has been studied mainly for CpG sites 76-80 and 84-87 and PSQ at CpG sites ranging from 72 to 95. A cutoff threshold of 9% for CpG sites 74-78 performed better than higher thresholds of 28% or 29% in 2 of the 3 good-quality studies. About 190 studies were identified presenting HRs from survival analysis in patients in which MGMT methylation was measured by 1 technique only.

Algorithmically Deduced FREM2 Molecular Pathway Is a Potent Grade and Survival Biomarker of Human Gliomas

Gliomas are the most common malignant brain tumors with high mortality rates. Recently we showed that the FREM2 gene has a role in glioblastoma progression. Here we reconstructed the FREM2 molecular pathway using the human interactome model. We assessed the biomarker capacity of FREM2 expression and its pathway as the overall survival (OS) and progression-free survival (PFS) biomarkers. To this end, we used three literature and one experimental RNA sequencing datasets collectively covering 566 glioblastomas (GBM) and 1097 low-grade gliomas (LGG). The activation level of deduced FREM2 pathway showed strong biomarker characteristics and significantly outperformed the FREM2 expression level itself. For all relevant datasets, it could robustly discriminate GBM and LGG (p < 1.63 × 10-13, AUC > 0.74). High FREM2 pathway activation level was associated with poor OS in LGG (p < 0.001), and low PFS in LGG (p < 0.001) and GBM (p < 0.05). FREM2 pathway activation level was poor prognosis biomarker for OS (p < 0.05) and PFS (p < 0.05) in LGG with IDH mutation, for PFS in LGG with wild type IDH (p < 0.001) and mutant IDH with 1p/19q codeletion(p < 0.05), in GBM with unmethylated MGMT (p < 0.05), and in GBM with wild type IDH (p < 0.05). Thus, we conclude that the activation level of the FREM2 pathway is a potent new-generation diagnostic and prognostic biomarker for multiple molecular subtypes of GBM and LGG.

Influence of supramarginal resection on survival outcomes after gross-total resection of IDH-wild-type glioblastoma

OBJECTIVE

The authors' goal was to use a multicenter, observational cohort study to determine whether supramarginal resection (SMR) of FLAIR-hyperintense tumor beyond the contrast-enhanced (CE) area influences the overall survival (OS) of patients with isocitrate dehydrogenase-wild-type (IDH-wt) glioblastoma after gross-total resection (GTR).

METHODS

The medical records of 888 patients aged ≥ 18 years who underwent resection of GBM between January 2011 and December 2017 were reviewed. Volumetric measurements of the CE tumor and surrounding FLAIR-hyperintense tumor were performed, clinical variables were obtained, and associations with OS were analyzed.

RESULTS

In total, 101 patients with newly diagnosed IDH-wt GBM who underwent GTR of the CE tumor met the inclusion criteria. In multivariate analysis, age ≥ 65 years (HR 1.97; 95% CI 1.01-2.56; p < 0.001) and contact with the lateral ventricles (HR 1.59; 95% CI 1.13-1.78; p = 0.025) were associated with shorter OS, but preoperative Karnofsky Performance Status ≥ 70 (HR 0.47; 95% CI 0.27-0.89; p = 0.006), MGMT promotor methylation (HR 0.63; 95% CI 0.52-0.99; p = 0.044), and increased percentage of SMR (HR 0.99; 95% CI 0.98-0.99; p = 0.02) were associated with longer OS. Finally, 20% SMR was the minimum percentage associated with beneficial OS (HR 0.56; 95% CI 0.35-0.89; p = 0.01), but > 60% SMR had no significant influence (HR 0.74; 95% CI 0.45-1.21; p = 0.234).

CONCLUSIONS

SMR is associated with improved OS in patients with IDH-wt GBM who undergo GTR of CE tumor. At least 20% SMR of the CE tumor was associated with beneficial OS, but greater than 60% SMR had no significant influence on OS.

Prognostic value of test(s) for O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation for predicting overall survival in people with glioblastoma treated with temozolomide

BACKGROUND

Glioblastoma is an aggressive form of brain cancer. Approximately five in 100 people with glioblastoma survive for five years past diagnosis. Glioblastomas that have a particular modification to their DNA (called methylation) in a particular region (the O6-methylguanine-DNA methyltransferase (MGMT) promoter) respond better to treatment with chemotherapy using a drug called temozolomide.

OBJECTIVES

To determine which method for assessing MGMT methylation status best predicts overall survival in people diagnosed with glioblastoma who are treated with temozolomide.

SEARCH METHODS

We searched MEDLINE, Embase, BIOSIS, Web of Science Conference Proceedings Citation Index to December 2018, and examined reference lists. For economic evaluation studies, we additionally searched NHS Economic Evaluation Database (EED) up to December 2014.

SELECTION CRITERIA

Eligible studies were longitudinal (cohort) studies of adults with diagnosed glioblastoma treated with temozolomide with/without radiotherapy/surgery. Studies had to have related MGMT status in tumour tissue (assessed by one or more method) with overall survival and presented results as hazard ratios or with sufficient information (e.g. Kaplan-Meier curves) for us to estimate hazard ratios. We focused mainly on studies comparing two or more methods, and listed brief details of articles that examined a single method of measuring MGMT promoter methylation. We also sought economic evaluations conducted alongside trials, modelling studies and cost analysis.

DATA COLLECTION AND ANALYSIS

Two review authors independently undertook all steps of the identification and data extraction process for multiple-method studies. We assessed risk of bias and applicability using our own modified and extended version of the QUality In Prognosis Studies (QUIPS) tool. We compared different techniques, exact promoter regions (5'-cytosine-phosphate-guanine-3' (CpG) sites) and thresholds for interpretation within studies by examining hazard ratios. We performed meta-analyses for comparisons of the three most commonly examined methods (immunohistochemistry (IHC), methylation-specific polymerase chain reaction (MSP) and pyrosequencing (PSQ)), with ratios of hazard ratios (RHR), using an imputed value of the correlation between results based on the same individuals.

MAIN RESULTS

We included 32 independent cohorts involving 3474 people that compared two or more methods. We found evidence that MSP (CpG sites 76 to 80 and 84 to 87) is more prognostic than IHC for MGMT protein at varying thresholds (RHR 1.31, 95% confidence interval (CI) 1.01 to 1.71). We also found evidence that PSQ is more prognostic than IHC for MGMT protein at various thresholds (RHR 1.36, 95% CI 1.01 to 1.84). The data suggest that PSQ (mainly at CpG sites 74 to 78, using various thresholds) is slightly more prognostic than MSP at sites 76 to 80 and 84 to 87 (RHR 1.14, 95% CI 0.87 to 1.48). Many variants of PSQ have been compared, although we did not see any strong and consistent messages from the results. Targeting multiple CpG sites is likely to be more prognostic than targeting just one. In addition, we identified and summarised 190 articles describing a single method for measuring MGMT promoter methylation status.

AUTHORS' CONCLUSIONS

PSQ and MSP appear more prognostic for overall survival than IHC. Strong evidence is not available to draw conclusions with confidence about the best CpG sites or thresholds for quantitative methods. MSP has been studied mainly for CpG sites 76 to 80 and 84 to 87 and PSQ at CpG sites ranging from 72 to 95. A threshold of 9% for CpG sites 74 to 78 performed better than higher thresholds of 28% or 29% in two of three good-quality studies making such comparisons.

The Potential Use of Radiomics with Pre-Radiation Therapy MR Imaging in Predicting Risk of Pseudoprogression in Glioblastoma Patients

Glioblastoma (GBM) is the most common adult glioma. Differentiating post-treatment effects such as pseudoprogression from true progression is paramount for treatment. Radiomics has been shown to predict overall survival and MGMT (methylguanine-DNA methyltransferase) promoter status in those with GBM. A potential application of radiomics is predicting pseudoprogression on pre-radiotherapy (RT) scans for patients with GBM. A retrospective review was performed with radiomic data analyzed using pre-RT MRI scans. Pseudoprogression was defined as post-treatment findings on imaging that resolved with steroids or spontaneously on subsequent imaging. Of the 72 patients identified for the study, 35 were able to be assessed for pseudoprogression, and 8 (22.9%) had pseudoprogression. A total of 841 radiomic features were examined along with clinical features. Receiver operating characteristic (ROC) analyses were performed to determine the AUC (area under ROC curve) of models of clinical features, radiomic features, and combining clinical and radiomic features. Two radiomic features were identified to be the optimal model combination. The ROC analysis found that the predictive ability of this combination was higher than using clinical features alone (mean AUC: 0.82 vs. 0.62). Additionally, combining the radiomic features with clinical factors did not improve predictive ability. Our results indicate that radiomics is potentially capable of predicting future development of pseudoprogression in patients with GBM using pre-RT MRIs.

Outcomes and Patterns of Care in Elderly Patients with Glioblastoma Multiforme

BACKGROUND

Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults, with an increased incidence among the elderly. However, the optimal treatment strategy in elderly patients remains unclear. This study seeks to investigate the effect of patient selection and treatment strategies on survival trends in these patients.

METHODS

Patients with diagnosis codes specific for GBM were queried from the National Cancer Database during 2004-2016. Univariate and multivariate Cox regression analysis was performed to investigate outcomes. Survival curves and 5-year survival were also generated based on patient-specific factors.

RESULTS

Among 104,456 patients with GBM identified, elderly patients were less likely to receive radiotherapy (61.3% vs. 77.8%; P < 0.001) or chemotherapy (47.2% vs. 62.9%; P < 0.001) or to undergo surgical resection (68.3% vs. 81.8; P < 0.001). Mean overall survival was 9.1 months (standard deviation, 10.0) and 5-year survival was 5.3%. Multivariate analysis showed age 75-84 years (hazard ratio [HR], 1.39; 95% confidence interval [CI], 1.12-1.73; P = 0.003) and lower Karnofsky Performance Status (50-70: HR, 1.68, 95% CI, 1.35-2.08, P < 0.001; ≤40: HR, 1.79, 95% CI 1.18-2.72, P = 0.006) were associated with decreased overall survival, whereas surgical resection (subtotal resection: HR, 0.52, 95% CI, 0.38-0.71, P < 0.001; gross total resection: HR, 0.29, 95% CI, 0.21-0.41, P < 0.001), radiotherapy (HR, 0.65; 95% CI, 0.47-0.91; P = 0.012), and chemotherapy (HR, 0.65; 95% CI, 0.48-0.88; P = 0.006) were associated with increased overall survival in elderly patients.

CONCLUSIONS

In an analysis of 104,456 patients with GBM, all treatment modalities were found to be used less frequently in elderly patients. Increasing age and poor performance status were associated with worsened survival. Gross total resection was associated with the greatest survival benefit, and chemotherapy and radiotherapy also improved survival outcomes. These treatment options improved outcomes regardless of performance status. Although maximal treatment strategies may improve survival in elderly patients with GBM, these treatment strategies must be balanced against patient-specific factors and quality-of-life concerns.

Point-of-care cancer diagnostic devices: From academic research to clinical translation

Early and timely diagnosis of cancer plays a decisive role in appropriate treatment and improves clinical outcomes, improving public health. Significant advances in biosensor technologies are leading to the development of point-of-care (POC) diagnostics, making the testing process faster, easier, cost-effective, and suitable for on-site measurements. Moreover, the incorporation of various nanomaterials into the sensing platforms has yielded POC testing (POCT) platforms with enhanced sensitivity, cost-effectiveness and simplified detection schemes. POC cancer diagnostic devices provide promising platforms for cancer biomarker detection as compared to conventional in vitro diagnostics, which are time-consuming and require sophisticated instrumentation, centralized laboratories, and experienced operators. Current innovative approaches in POC technologies, including biosensors, smartphone interfaces, and lab-on-a-chip (LOC) devices are expected to quickly transform the healthcare landscape. However, only a few cancer POC devices (e.g. lateral flow platforms) have been translated from research laboratories to clinical care, likely due to challenges include sampling procedures, low levels of sensitivity and specificity in clinical samples, system integration and signal readout requirements. In this review, we emphasize recent advances in POC diagnostic devices for cancer biomarker detection and discuss the critical challenges which must be surmounted to facilitate their translation into clinical settings.

Use of DNA methylation profiling in translational oncology

DNA methylation is a highly regulated process that has a critical role in human development and homeostatic control of the cell. The number of genes affected by anomalous DNA methylation in cancer-associated pathways is swiftly accelerating and with the advancement of molecular technologies, new layers of complexity are opening up and refining our strategies to combat cancer. DNA methylation profiling is an essential facet to understanding malignant transformation and is becoming an increasingly important tool for cancer diagnosis, prognosis and therapy monitoring. In this review, the role of DNA methylation in normal cellular function is discussed, as well as how epigenetic aberrations override normal cellular cues that lead to tumor initiation and propagation. The review also focuses on the latest advancements in DNA methylation profiling as a biomarker for early cancer detection, predicting patient clinical outcomes and responses to treatment and provides new insights into epigenetic-based therapy in clinical oncology.

Prediction of Molecular Mutations in Diffuse Low-Grade Gliomas using MR Imaging Features

Diffuse low-grade gliomas (LGG) have been reclassified based on molecular mutations, which require invasive tumor tissue sampling. Tissue sampling by biopsy may be limited by sampling error, whereas non-invasive imaging can evaluate the entirety of a tumor. This study presents a non-invasive analysis of low-grade gliomas using imaging features based on the updated classification. We introduce molecular (MGMT methylation, IDH mutation, 1p/19q co-deletion, ATRX mutation, and TERT mutations) prediction methods of low-grade gliomas with imaging. Imaging features are extracted from magnetic resonance imaging data and include texture features, fractal and multi-resolution fractal texture features, and volumetric features. Training models include nested leave-one-out cross-validation to select features, train the model, and estimate model performance. The prediction models of MGMT methylation, IDH mutations, 1p/19q co-deletion, ATRX mutation, and TERT mutations achieve a test performance AUC of 0.83 ± 0.04, 0.84 ± 0.03, 0.80 ± 0.04, 0.70 ± 0.09, and 0.82 ± 0.04, respectively. Furthermore, our analysis shows that the fractal features have a significant effect on the predictive performance of MGMT methylation IDH mutations, 1p/19q co-deletion, and ATRX mutations. The performance of our prediction methods indicates the potential of correlating computed imaging features with LGG molecular mutations types and identifies candidates that may be considered potential predictive biomarkers of LGG molecular classification.

One-carbon metabolism for cancer diagnostic and therapeutic approaches

Altered metabolism is critical for the rapid and unregulated proliferation of cancer cells; hence the requirement for an abundant source of nucleotides. One characteristic of this metabolic reprogramming is in one-carbon (1C) metabolism, which is particularly noteworthy for its role in DNA synthesis. Various forms of methylation are also noteworthy as they relate to cancer cell survival and proliferation. In recent years, 1C metabolism has received substantial attention for its role in cancer malignancy via these functions. Therefore, therapeutic inhibitors targeting 1C metabolism have been utilized as anticancer drugs. This review outlines the importance of 1C metabolism and its clinical application in cancer. Understanding 1C metabolism could aid the development of novel cancer diagnostic and therapeutic methods.

Clinical and Molecular Recursive Partitioning Analysis of High-grade Glioma Treated With IMRT

INTRODUCTION

Despite multimodal treatment for high-grade gliomas, prognosis remains grim. Prior Radiation Therapy Oncology Group-Recursive Partitioning Analysis (RTOG-RPA) reports indicate based on pretreatment and treatment-related factors, a subset of patients experience a significantly improved survival. Since the development of the RTOG-RPA, high-grade gliomas have seen the widespread introduction of temozolomide and tumor oncogenetics. Here we aimed to determine whether the RTOG-RPA retained prognostic significance in the context of modern treatment, as well as generate an updated RPA incorporating both clinical and genetic variables.

METHODS

Patients with histologically proven glioblastoma, gliosarcoma, anaplastic astrocytoma, and anaplastic oligodendroglioma treated with intensity-modulated radiation therapy (IMRT) between 2004 and 2017 were reviewed. The primary endpoint was overall survival from date of diagnosis. Primary analysis compared actual survival rates to that expected of corresponding RTOG-RPA class. Secondary analysis utilized the rpart function to recursively partition overall survival by numerous clinical and genetic pretreatment and treatment-related variables. A tertiary analysis recursively partitioned a subset of patients in which the status of all genetic markers were known.

RESULTS

We identified 878 patients with histologically proven high-grade glioma treated with IMRT and 291 patients in our genetic subset. Median overall survival for the entire cohort was 14.2 months (95% confidence interval, 13.1-15.3). Applying the RTOG-RPA to our cohort validated the relative prognostic ordering of the survival classes except class II. Generating our new RPA created 7 significantly different survival classes (P<0.001, χ=584) with median survival ranging from 96.4 to 2.9 months based on age, histology, O6-methylguanine-DNA methyltransferase methylation status, radiation fractions, tumor location, radiation dose, temozolomide status, and resection status. Our second RPA of our genetic subset generated 5 significantly different survival classes (P<0.001, χ=166) with survival ranging from 65.3 to 5.6 months based on age, isocitrate dehydrogenase 1 mutation status, O6-methylguanine-DNA methyltransferase methylation status, neurological functional classification, hospitalization during IMRT, temozolomide status, and Karnofsky performance status.

CONCLUSIONS

The RTOG-RPA retains partial prognostic significance, however, should be updated to reflect recent advancements. This series represents a large RPA analyzing both clinical and genetic factors and generated 7 distinct survival classes. Further assessment of patients with fully available genetic markers generated 5 distinct survival classes. These survival classifications need to be validated by a prospective data set and compared against the RTOG-RPA to determine whether they provide improved prognostic power.

Temozolomide and Other Alkylating Agents in Glioblastoma Therapy

The alkylating agent temozolomide (TMZ) together with maximal safe bulk resection and focal radiotherapy comprises the standard treatment for glioblastoma (GB), a particularly aggressive and lethal primary brain tumor. GB affects 3.2 in 100,000 people who have an average survival time of around 14 months after presentation. Several key aspects make GB a difficult to treat disease, primarily including the high resistance of tumor cells to cell death-inducing substances or radiation and the combination of the highly invasive nature of the malignancy, i.e., treatment must affect the whole brain, and the protection from drugs of the tumor bulk—or at least of the invading cells—by the blood brain barrier (BBB). TMZ crosses the BBB, but—unlike classic chemotherapeutics—does not induce DNA damage or misalignment of segregating chromosomes directly. It has been described as a DNA alkylating agent, which leads to base mismatches that initiate futile DNA repair cycles; eventually, DNA strand breaks, which in turn induces cell death. However, while much is assumed about the function of TMZ and its mode of action, primary data are actually scarce and often contradictory. To improve GB treatment further, we need to fully understand what TMZ does to the tumor cells and their microenvironment. This is of particular importance, as novel therapeutic approaches are almost always clinically assessed in the presence of standard treatment, i.e., in the presence of TMZ. Therefore, potential pharmacological interactions between TMZ and novel drugs might occur with unforeseeable consequences.

To be Wild or Mutant: Role of Isocitrate Dehydrogenase 1 (IDH1) and 2-Hydroxy Glutarate (2-HG) in Gliomagenesis and Treatment Outcome in Glioma

Molecular and clinical research based on isocitrate dehydrogenase (IDH) mutations is much sought after in glioma research since a decade of its discovery in 2008. IDH enzyme normally catalyzes isocitrate to α-keto-glutarate (α-KG), but once the gene is mutated it produces an 'oncometabolite', 2-hydroxyglutarate (2-HG). 2-HG is proposed to inhibit α-KG-dependent dioxygenases and also blocks cellular differentiation. Here, we discuss the role of the IDH1 mutation in gliomagenesis. The review also focuses on the effect of 2-HG on glioma epigenetics, the cellular signaling involved in IDH1 mutant glioma cells and the therapeutic response seen in mutant IDH1(mIDH1) harboring glioma patients in comparison to the patients with wild-type IDH1. The review encompasses the debatable impacts of the mutation on immune microenvironment a propos of various mIDH1 inhibitors in practice or in trials. Recent studies revealing the relation of IDH mutation with the immune microenvironment and inflammatory status in untreated versus treated glioblastoma patients are highlighted with respect to prospective therapeutic targets. Also at the molecular level, the association of mIDH1/2-HG with the intracellular components such as mitochondria and other neighboring cells is discussed.

Molecular profile of long-term survivors of glioblastoma: A scoping review of the literature

Molecular aberrations of malignancy are becoming widely recognized as important predictive and prognostic markers for treatment response and survival in oncology and have been linked to the discovery of novel treatment targets. This area of research in glioblastoma continues to evolve. The aim of this scoping review was to document the hallmark molecular characteristics of long-term survivors of glioblastoma. MEDLINE, Scopus and EMBASE were searched with core concepts: (1) glioblastoma, (2) long-term survivor and (3) molecular OR mutation. A thematic analysis was undertaken of the 18 included studies. Four main classes of characteristics were obtained: IDH mutation, MGMT methylation, other known characteristics and novel discoveries. While MGMT methylation or the combination with IDH mutation are suggested to be hallmark characteristics, there remains enough uncertainty to suggest further factors may be involved, such as CD34 expression. Further research is required to accurately describe hallmark molecular characteristics of long-term survivors to assist in defining these patients at diagnosis, preventing treatment complications and discovering novel treatments.

Molecular Neuropathology in Practice: Clinical Profiling and Integrative Analysis of Molecular Alterations in Glioblastoma

Molecular profiling of glioblastoma has revealed complex cytogenetic, epigenetic, and molecular abnormalities that are necessary for diagnosis, prognosis, and treatment. Our neuro-oncology group has developed a data-driven, institutional consensus guideline for efficient and optimal workup of glioblastomas based on our routine performance of molecular testing. We describe our institution’s testing algorithm, assay development, and genetic findings in glioblastoma, to illustrate current practices and challenges in neuropathology related to molecular and genetic testing. We have found that coordination of test requisition, tissue handling, and incorporation of results into the final pathologic diagnosis by the neuropathologist improve patient care. Here, we present analysis of O⁶-methylguanine-DNA-methyltransferase promoter methylation and next-generation sequencing results of 189 patients, obtained utilizing our internal processes led by the neuropathology team. Our institutional pathway for neuropathologist-driven molecular testing has streamlined the management of glioblastoma samples for efficient return of results for incorporation of genomic data into the pathological diagnosis and optimal patient care.

Transcriptional and epigenetic mechanisms underlying astrocyte identity

Astrocytes play a significant role in coordinating neural development and provide critical support for the function of the CNS. They possess important adaptation capacities that range from their transition towards reactive astrocytes to their ability to undergo reprogramming, thereby revealing their potential to retain latent features of neural progenitor cells. We propose that the mechanisms underlying reactive astrogliosis or astrocyte reprogramming provide an opportunity for initiating neuronal regeneration, a process that is notably reduced in the mammalian nervous system throughout evolution. Conversely, this plasticity may also affect normal astrocytic functions resulting in pathologies ranging from neurodevelopmental disorders to neurodegenerative diseases and brain tumors. We postulate that epigenetic mechanisms linking extrinsic cues and intrinsic transcriptional programs are key factors to maintain astrocyte identity and function, and critically, to control the balance of regenerative and degenerative activity. Here, we will review the main evidences supporting this concept. We propose that unravelling the epigenetic and transcriptional mechanisms underlying the acquisition of astrocyte identity and plasticity, as well as understanding how these processes are modulated by the local microenvironment under specific threatening or pathological conditions, may pave the way to new therapeutic avenues for several neurological disorders including neurodegenerative diseases and brain tumors of astrocytic lineage.

Intratumoral heterogeneity of endogenous tumor cell invasive behavior in human glioblastoma

Intratumoral genetic heterogeneity is a widely accepted characteristic of human cancer, including the most common primary malignant brain tumor, glioblastoma. However, the variability in biological behaviors amongst cells within individual tumors is not well described. Invasion into unaffected brain parenchyma is one such behavior, and a leading mechanism of tumor recurrence unaddressed by the current therapeutic armamentarium. Further, providing insight into variability of tumor cell migration within individual tumors may inform discovery of novel anti-invasive therapeutics. In this study, ex vivo organotypic slice cultures from EGFR-wild type and EGFR-amplified patient tumors were treated with the EGFR inhibitor gefitinib to evaluate potential sub-population restricted intratumoral drug-specific responses. High-resolution time-lapse microscopy and quantitative path tracking demonstrated migration of individual cells are punctuated by intermittent bursts of movement. Elevation of population aggregate mean speeds were driven by subpopulations of cells exhibiting frequent high-amplitude bursts, enriched within EGFR-amplified tumors. Treatment with gefitinib specifically targeted high-burst cell subpopulations only in EGFR-amplified tumors, decreasing bursting frequency and amplitude. We provide evidence of intratumoral subpopulations of cells with enhanced migratory behavior in human glioblastoma, selectively targeted via EGFR inhibition. These data justify use of direct human tumor slice cultures to investigate patient-specific therapies designed to limit tumor invasion.

Immunogenetics of glioblastoma: the future of personalized patient management

The prognosis of glioblastoma has changed little over the past two decades, with only minor improvements in length of overall survival through the addition of temozolomide (temodal) to standard of care and the recommended use of alternating electric field therapy (optune) to newly diagnosed patients. In an effort to define novel therapeutic targets across molecularly heterogeneous disease subgroups, researchers have begun to uncover the complex interplay between epigenetics, cell signaling, metabolism, and the immunosuppressive tumor microenvironment. Indeed, IDH mutations are now recognized as a defining differential factor not only influencing global hypermethylation and patient prognosis but also degree of immune infiltration within individual tumors. Likewise, next-generation sequencing has defined subgroup-specific transcriptional profiles that correlate with different mechanisms of immune evasion, including increased PD-L1 and CTLA-4 among mesenchymal tumors. Interestingly, sequencing of the T cell repertoire from numerous patient samples suggests that the correlation between mutational burden and enrichment of tumor-specific peptides may be less convincing than originally suspected. While this raises questions over the efficacy of dendritic cell or tumor-lysate vaccines and CAR-T therapies, these avenues continue to be explored. In addition to these active immunotherapies, inhibitors of molecular hubs with wide reaching effects, including STAT3, IDO, and TGF-β, are now in early-phase clinical trials. With the potential to block intrinsic biological properties of tumor growth and invasion while bolstering the immunogenic profile of the tumor microenvironment, these new targets represent a new direction for GBM therapies. In this review, we show the advances in molecular profiling and immunophenotyping of GBM, which may lead to the development of new personalized therapeutic strategies.

Pyrosequencing Analysis of MGMT Promoter Methylation in Meningioma

BACKGROUND

Methylation of the O⁶-methylguanine-DNA methyltransferase (MGMT) gene promoter is a well-established predictor of response to the DNA-alkylating agent temozolomide in patients with glioblastoma.

MATERIALS AND METHODS

Pyrosequencing analysis was used to determine the MGMT promoter methylation status in 61 meningiomas, to clarify whether it might have a predictive role.

RESULTS

Only two tumors (3%) had a mean methylation frequency higher than the cut-off value of 10% for the four CpG sites examined.

CONCLUSION

The methylation of the MGMT promoter is uncommon, or occurs at a low frequency in meningiomas. There is no convincing rationale to test such tumors for their MGMT methylation status in a clinical setting.

Towards DNA methylation detection using biosensors

DNA methylation, a stable and heritable covalent modification which mostly occurs in the context of a CpG dinucleotide, has great potential as a biomarker to detect disease, provide prognoses and predict therapeutic responses. It can be detected in a quantitative manner by many different approaches both genome-wide and at specific gene loci, in various biological fluids such as urine, plasma, and serum, which can be obtained without invasive procedures. The current, classical methods are effective in studying DNA methylation patterns, however, for the most part; they have major drawbacks such as expensive instruments, complicated and time consuming protocols as well as relatively low sensitivity, and high false positive rates. To overcome these obstacles, great efforts have been made toward the development of reliable sensor devices to solve these limitations, providing sensitive, fast and cost-effective measurements. The use of biosensors for DNA methylation biomarkers has increased in recent years, because they are portable, simple, rapid, and inexpensive which offers a straightforward way to detect methylated biomarkers. In this review, we give an overview of the conventional techniques for the detection of DNA methylation and then will focus on recent advances in biosensor based methylation detection that eliminate bisulfite conversion and PCR amplification.

Real-time methylation-specific PCR for the evaluation of methylation status of MGMT gene in glioblastoma

The methylation status of the O6-methylguanine-DNA methyltransferase (MGMT) gene is a strong predictor for the efficacy of temozolomide chemotherapy and survival periods. However, the correlation between the extent of methylation and the difference in survival times has not been fully clarified. Simple and quantitative evaluations of the methylation status in the promotor region of the MGMT gene are expected to be worldwide standardized diagnostics. We applied real-time semi-quantitative methylation-specific polymerase chain reaction (SQ-MSP) of the MGMT gene promoter region to 84 glioblastoma patients. The SQ-MSP result showed that the ΔCt value, which represents the difference between uCt and mCt (uCt value – mCt value), is inversely correlated with overall survival. With adequate cutoff setting, this assay showed that those patients suffering from a tumor with low ΔCt (methylated) survived significantly longer than those having tumors with high ΔCt (un-methylated). The most significant difference was observed when the cutoff was set at a ΔCt of 2. Using this cutoff point, the result of MGMT immunohistochemical analysis was also significantly correlated with the methylation status examined with real-time SQ-MSP. These results collectively show that MGMT promoter methylation status actually affects patients’ survival and protein expression depending on its methylation level, and the extent of methylated CpGs would be better assessed with real-time SQ-MSP than with the standard gel-based MSP. This method is cost- and labor-saving compared with pyrosequencing, and significantly contributes to the accurate and objective prediction of patient survival.

Epigenetics and Precision Oncology

Epigenetic alterations such as DNA methylation defects and aberrant covalent histone modifications occur within all cancers and are selected for throughout the natural history of tumor formation, with changes being detectable in early onset, progression, and ultimately recurrence and metastasis. The ascertainment and use of these marks to identify at-risk patient populations, refine diagnostic criteria, and provide prognostic and predictive factors to guide treatment decisions are of growing clinical relevance. Furthermore, the targetable nature of epigenetic modifications provides a unique opportunity to alter treatment paradigms and provide new therapeutic options for patients whose malignancies possess these aberrant epigenetic modifications, paving the way for new and personalized medicine. DNA methylation has proven to be of significant clinical utility for its stability and relative ease of testing. The intent of this review is to elaborate upon well-supported examples of epigenetic precision medicine and how the field is moving forward, primarily in the context of aberrant DNA methylation.

The Roles of DNA Methylation in the Stages of Cancer

Next year will mark 60 years since Dr. Leslie Foulds outlined his hypothesis that cancer is "a dynamic process advancing through stages that are qualitatively different," leading the way to our view of cancer progression as we know it today. Our understanding of the mechanisms of these stages has been continuously evolving this past half-century, and there has always been an active discussion of the roles of both genetic and epigenetic changes in directing this progression. In this review, we focus on the roles one particular epigenetic mark-DNA methylation-plays in these various "discontinuous" stages of cancer. Understanding these steps not only gives us a better picture of how this fascinating biological process operates, but also opens the doors to new prognostic biomarkers and therapies against these malignancies.

Alterations in Cell Motility, Proliferation, and Metabolism in Novel Models of Acquired Temozolomide Resistant Glioblastoma

Glioblastoma (GBM) is an aggressive and incurable tumor of the brain with limited treatment options. Current first-line standard of care is the DNA alkylating agent temozolomide (TMZ), but this treatment strategy adds only ~4 months to median survival due to the rapid development of resistance. While some mechanisms of TMZ resistance have been identified, they are not fully understood. There are few effective strategies to manage therapy resistant GBM, and we lack diverse preclinical models of acquired TMZ resistance in which to test therapeutic strategies on TMZ resistant GBM. In this study, we create and characterize two new GBM cell lines resistant to TMZ in vitro, based on the 8MGBA and 42MGBA cell lines. Analysis of the TMZ resistant (TMZres) variants in conjunction with their parental, sensitive cell lines shows that acquisition of TMZ resistance is accompanied by broad phenotypic changes, including increased proliferation, migration, chromosomal aberrations, and secretion of cytosolic lipids. Importantly, each TMZ resistant model captures a different facet of the “go” (8MGBA-TMZres) or “grow” (42MGBA-TMZres) hypothesis of GBM behavior. These in vitro model systems will be important additions to the available tools for investigators seeking to define molecular mechanisms of acquired TMZ resistance.

Radiogenomics correlation between MR imaging features and major genetic profiles in glioblastoma

OBJECTIVES

To assess the association between MR imaging features and major genomic profiles in glioblastoma.

METHODS

Qualitative and quantitative imaging features such as volumetrics and histogram analysis from normalised CBV (nCBV) and ADC (nADC) were evaluated based on both T2WI and CET1WI. The imaging parameters of different genetic profile groups were compared and regression analyses were used for identifying imaging-molecular associations. Progression-free survival (PFS) was analysed by a Kaplan-Meier test and Cox proportional hazards model.

RESULTS

An IDH mutation was observed in 18/176 patients, and ATRX loss was positive in 17/158 of the IDH-wt cases. The IDH-mut group showed a larger volume on T2WI and a higher volume ratio between T2WI and CET1WI than the IDH-wt group (p < 0.05). In the IDH-mut group, higher mean nADC values were observed compared with the IDH-wt tumours (p < 0.05). Among the IDH-wt tumours, IDH-wt, ATRX-loss tumours revealed higher 5th percentile nADC values than the IDH-wt, ATRX-noloss tumours (p = 0.03). PFS was the longest in the IDH-mut group, followed by the IDH-wt, ATRX-loss groups and the IDH-wt, ATRX-noloss groups, consecutively (p < 0.05). We found significant associations of PFS with the genetic profiles and imaging parameters.

CONCLUSION

Major genetic profiles of glioblastoma showed a significant association with MR imaging features, along with some genetic profiles, which are independent prognostic parameters for GBM.

KEY POINTS

• Significant correlation exists between radiological parameters such as volumetric and ADC values and major genomic profiles such as IDH mutation and ATRX loss status • Radiological parameters such as the ADC value were feasible predictors of glioblastoma patients' prognosis • Imaging features can predict major genomic profiles of the tumours and the prognosis of glioblastoma patients.

Novel Radiomic Features Based on Joint Intensity Matrices for Predicting Glioblastoma Patient Survival Time

This paper presents a novel set of image texture features generalizing standard grey-level co-occurrence matrices (GLCM) to multimodal image data through joint intensity matrices (JIMs). These are used to predict the survival of glioblastoma multiforme (GBM) patients from multimodal MRI data. The scans of 73 GBM patients from the Cancer Imaging Archive are used in our study. Necrosis, active tumor, and edema/invasion subregions of GBM phenotypes are segmented using the coregistration of contrast-enhanced T1-weighted (CE-T1) images and its corresponding fluid-attenuated inversion recovery (FLAIR) images. Texture features are then computed from the JIM of these GBM subregions and a random forest model is employed to classify patients into short or long survival groups. Our survival analysis identified JIM features in necrotic (e.g., entropy and inverse-variance) and edema (e.g., entropy and contrast) subregions that are moderately correlated with survival time (i.e., Spearman rank correlation of 0.35). Moreover, nine features were found to be associated with GBM survival with a Hazard-ratio range of 0.38-2.1 and a significance level of p < 0.05 following Holm-Bonferroni correction. These features also led to the highest accuracy in a univariate analysis for predicting the survival group of patients, with AUC values in the range of 68-70%. Considering multiple features for this task, JIM features led to significantly higher AUC values than those based on standard GLCMs and gene expression. Furthermore, an AUC of 77.56% with p = 0.003 was achieved when combining JIM, GLCM, and gene expression features into a single radiogenomic signature. In summary, our study demonstrated the usefulness of modeling the joint intensity characteristics of CE-T1 and FLAIR images for predicting the prognosis of patients with GBM.

Molecular Targeting of Acid Ceramidase in Glioblastoma: A Review of Its Role, Potential Treatment, and Challenges

Glioblastoma is the most common, malignant primary tumor of the central nervous system. The average prognosis for life expectancy after diagnosis, with the triad of surgery, chemotherapy, and radiation therapy, is less than 1.5 years. Chemotherapy treatment is mostly limited to temozolomide. In this paper, the authors review an emerging, novel drug called acid ceramidase, which targets glioblastoma. Its role in cancer treatment in general, and more specifically, in the treatment of glioblastoma, are discussed. In addition, the authors provide insights on acid ceramidase as a potential druggable target for glioblastoma.