Prognostic relevance of radiological findings on early postoperative MRI for 187 consecutive glioblastoma patients receiving standard therapy.

Several prognostic factors are known to influence survival for patients treated with IDH-wildtype glioblastoma, but unknown factors may remain. We aimed to investigate the prognostic implications of early postoperative MRI findings. A total of 187 glioblastoma patients treated with standard therapy were consecutively included. Patients either underwent a biopsy or surgery followed by an early postoperative MRI. Progression-free survival (PFS) and overall survival (OS) were analysed for known prognostic factors and MRI-derived candidate factors: resection status as defined by the response assessment in neuro-oncology (RANO)-working group (no contrast-enhancing residual tumour, non-measurable contrast-enhancing residual tumour, or measurable contrast-enhancing residual tumour) with biopsy as reference, contrast enhancement patterns (no enhancement, thin linear, thick linear, diffuse, nodular), and the presence of distant tumours. In the multivariate analysis, patients with no contrast-enhancing residual tumour or non-measurable contrast-enhancing residual tumour on the early postoperative MRI displayed a significantly improved progression-free survival compared with patients receiving only a biopsy. Only patients with non-measurable contrast-enhancing residual tumour showed improved overall survival in the multivariate analysis. Contrast enhancement patterns were not associated with survival. The presence of distant tumours was significantly associated with both poor progression-free survival and overall survival and should be considered incorporated into prognostic models.

A systematic review of targeted therapy for vestibular schwannoma in patients with NF2-related schwannomatosis.

Background: One of the hallmarks of NF2-related Schwannomatosis (NF2-related SWN) is bilateral vestibular schwannomas (VS) that can cause progressive hearing impairment in patients. This systematic review was performed to investigate the efficacy and toxicity of tested targeted agents. Methods: The systematic search was conducted on PubMed and EMBASE Ovid databases from inception to October 2022, according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The incidence of outcomes in studies involving bevacizumab and other targeted therapies was extracted. The bevacizumab results were pooled, and 95% confidence intervals (95% CI) were calculated. Results: Sixteen studies (8 prospective and 8 retrospective) testing 6 drugs were selected out of 721 search results. There were 10 studies concerning bevacizumab, with a total of 200 patients. The pooled radiographic response rate (RR) was 38% (95% CI: 31 - 45%) and the pooled hearing response rate (HR) was 45% (95% CI: 36 - 54%). The most frequent bevacizumab-related toxicities were hypertension and menorrhagia. Of other targeted therapies showing activity, lapatinib had a RR of 6% and a HR of 31%. A VEGFR vaccine showed RR in 29% and HR in 40% of patients. Both agents had a manageable safety profile. Conclusions: Bevacizumab, in comparison to other targeted agents, showed the highest efficacy. Lower dosage of bevacizumab shows comparable efficacy and may reduce toxicity. Other targeted agents, administered alone or as combination therapy, have the potential to improve outcomes for VS in patients with NF2-related SWN, but future clinical studies are needed.

Evaluation of the HD-GLIO Deep Learning Algorithm for Brain Tumour Segmentation on Postoperative MRI.

In the context of brain tumour response assessment, deep learning-based three-dimensional (3D) tumour segmentation has shown potential to enter the routine radiological workflow. The purpose of the present study was to perform an external evaluation of a state-of-the-art deep learning 3D brain tumour segmentation algorithm (HD-GLIO) on an independent cohort of consecutive, post-operative patients. For 66 consecutive magnetic resonance imaging examinations, we compared delineations of contrast-enhancing (CE) tumour lesions and non-enhancing T2/FLAIR hyperintense abnormality (NE) lesions by the HD-GLIO algorithm and radiologists using Dice similarity coefficients (Dice). Volume agreement was assessed using concordance correlation coefficients (CCCs) and Bland-Altman plots. The algorithm performed very well regarding the segmentation of NE volumes (median Dice = 0.79) and CE tumour volumes larger than 1.0 cm3 (median Dice = 0.86). If considering all cases with CE tumour lesions, the performance dropped significantly (median Dice = 0.40). Volume agreement was excellent with CCCs of 0.997 (CE tumour volumes) and 0.922 (NE volumes). The findings have implications for the application of the HD-GLIO algorithm in the routine radiological workflow where small contrast-enhancing tumours will constitute a considerable share of the follow-up cases. Our study underlines that independent validations on clinical datasets are key to asserting the robustness of deep learning algorithms.

Implementing targeted therapies in the treatment of glioblastoma: Previous shortcomings, future promises, and a multimodal strategy recommendation.

The introduction of targeted therapies to the field of oncology has prolonged the survival of several tumor types. Despite extensive research and numerous trials, similar outcomes have unfortunately not been realized for glioblastoma. For more than 15 years, the standard treatment of glioblastoma has been unchanged. This review walks through the elements that have challenged the success of previous trials and highlight some future promises. Concurrently, this review describes how institutions, through a multimodal and comprehensive strategy with 4 essential components, may increase the probability of finding a meaningful role for targeted therapies in the treatment of glioblastoma. These components are (1) prudent trial designs, (2) considered drug and target selection, (3) harnessed real-world clinical and molecular evidence, and (4) incorporation of translational research.

Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images.

Survival prediction models can potentially be used to guide treatment of glioblastoma patients. However, currently available MR imaging biomarkers holding prognostic information are often challenging to interpret, have difficulties generalizing across data acquisitions, or are only applicable to pre-operative MR data. In this paper we aim to address these issues by introducing novel imaging features that can be automatically computed from MR images and fed into machine learning models to predict patient survival. The features we propose have a direct anatomical-functional interpretation: They measure the deformation caused by the tumor on the surrounding brain structures, comparing the shape of various structures in the patient's brain to their expected shape in healthy individuals. To obtain the required segmentations, we use an automatic method that is contrast-adaptive and robust to missing modalities, making the features generalizable across scanners and imaging protocols. Since the features we propose do not depend on characteristics of the tumor region itself, they are also applicable to post-operative images, which have been much less studied in the context of survival prediction. Using experiments involving both pre- and post-operative data, we show that the proposed features carry prognostic value in terms of overall- and progression-free survival, over and above that of conventional non-imaging features.

Health-related quality of life and caregiver perspectives in glioblastoma survivors: a mixed-methods study.

BACKGROUND: The purpose of antineoplastic treatment of high-grade glioma (HGG) is to achieve progression-free survival with delayed neurological and cognitive deterioration. Health-related quality of life (HRQOL) has become increasingly important next to more traditional outcome measures such as progression-free survival. However, the clinical outcome of long-term, HGG survivors and their caregivers' quality of life is poorly understood. OBJECTIVE: This study aims to address HRQOL and perspectives on the daily life experiences of long-term survivors (LTS) with HGG and their caregivers. METHODS: This mixed-methods study applies a convergent design using identical sampling. Separate telephone interviews with patients diagnosed for more than 3 years and their caregivers were conducted. Patients filled out self-reported questionnaires; the Hospital Anxiety and Depression Scale, the Functional Assessment of Cancer Therapy (FACT), General and Brain (FACT-Br), and the Leisure Time Physical Activity Questionnaire. RESULTS: Three themes shared by patients and their caregivers were identified: searching for meaningful activities, selecting information that enhances self-management strategies and protection for safety reasons. Ten per cent showed moderate depressive symptoms, which is lower compared with the newly diagnosed. The HRQOL scores seem to be rated higher than the normative sample. The FACT-Br total score indicated that a previously identified significant increase in the emotional well-being of 1-year survivors was the same or improved. A central finding is that the LTS expressed frustration and sadness due to their reduced ability to manage work and daily life activities. Caregivers are challenged throughout the entire trajectory, and patient safety issues are a key concern for them. CONCLUSIONS: The LTS desire participation in satisfying, meaningful activities that consider their cognitive and physical capacities. Advance care planning must be a key component in future research, as discussing life strategies can enhance positive beliefs, which are apparently imperative to their well-being. TRIAL REGISTRATION NUMBER: Clinical Trial.gov: NCT02965144.

Plasma IL-8 and ICOSLG as prognostic biomarkers in glioblastoma.

BACKGROUND: CNS immune privilege has been challenged in recent years. Glioblastoma (GBM) immune dysfunction includes complex interactions with the immune system outside the CNS. The aim of this study was to determine diagnostic and prognostic potential of immune-related proteins in plasma in GBM and interrogate biomarker presence in the brain tumor microenvironment (TME). METHODS: One hundred and fifty-eight patients with glioma WHO grade II-IV were included. Plasma collected at surgery was screened for 92 proteins using proximity extension assay technology and related to clinical outcome. Secretion and expression of candidate prognostic biomarkers were subsequently analyzed in 8 GBM cell lines and public RNAseq data. RESULTS: Plasma levels of 20 out of 92 screened proteins were significantly different in patients with GBM compared to patients with astrocytoma WHO grade II-III. High plasma interleukin-8 (IL-8) (hazard ratio [HR] = 1.52; P = .0077) and low CD244 (HR = 0.36; P = .0004) were associated with short progression-free survival and high plasma IL-8 (HR = 1.40; P = .044) and low ICOS ligand (ICOSLG) (HR = 0.17; P = .0003) were associated with short overall survival (OS) in newly diagnosed patients with GBM. A similar trend was found for ICOSLG (HR = 0.34; P = .053) in recurrent GBM. IL-8 was mostly secreted and expressed by mesenchymal GBM cell lines and expressed by vascular cells and immune cells in the TME. This was also the case for ICOSLG, although less consistent, and with additional expression in tumor-associated oligodendrocytes. CONCLUSIONS: High plasma IL-8 and low ICOSLG at surgery are associated with short OS in newly diagnosed GBM. Source of plasma ICOSLG may be found outside the TME.

Perspective: targeting VEGF-A and YKL-40 in glioblastoma - matter matters.

Glioblastomas (GBM) are heterogeneous highly vascular brain tumors exploiting the unique microenvironment in the brain to resist treatment and anti-tumor responses. Anti-angiogenic agents, immunotherapy, and targeted therapy have been studied extensively in GBM patients over a number of decades with minimal success. Despite maximal efforts, prognosis remains dismal with an overall survival of approximately 15 months.Bevacizumab, a humanized anti-vascular endothelial growth factor (VEGF) antibody, underwent accelerated approval by the U.S. Food and Drug Administration in 2009 for the treatment of recurrent GBM based on promising preclinical and early clinical studies. Unfortunately, subsequent clinical trials did not find overall survival benefit. Pursuing pleiotropic targets and leaning toward multitarget strategies may be a key to more effective therapeutic intervention in GBM, but preclinical evaluation requires careful consideration of model choices. In this study, we discuss bevacizumab resistance, dual targeting of pro-angiogenic modulators VEGF and YKL-40 in the context of brain tumor microenvironment, and how model choice impacts study conclusions and its translational significance.

A Prognostic Model for Glioblastoma Patients Treated With Standard Therapy Based on a Prospective Cohort of Consecutive Non-Selected Patients From a Single Institution.

BACKGROUND: Glioblastoma patients administered standard therapies, comprising maximal surgical resection, radiation therapy with concomitant and adjuvant temozolomide, have a variable prognosis with a median overall survival of 15-16 months and a 2-year overall survival of 30%. The aim of this study was to develop a prognostic nomogram for overall survival for glioblastoma patients treated with standard therapy outside clinical trials. METHODS: The study included 680 consecutive, non-selected glioblastoma patients administered standard therapy as primary treatment between the years 2005 and 2016 at Rigshospitalet, Copenhagen, Denmark. The prognostic model was generated employing multivariate Cox regression analysis modeling overall survival. RESULTS: The following poor prognostic factors were included in the final prognostic model for overall survival: Age (10-year increase: HR = 1.18, 95% CI: 1.08-1.28, p < 0.001), ECOG performance status (PS) 1 vs. 0 (HR = 1.30, 95% CI: 1.07-1.57, p = 0.007), PS 2 vs. 0 (HR = 2.99, 95% CI: 1.99-4.50, p < 0.001), corticosteroid use (HR = 1.42, 95% CI: 1.18-1.70, p < 0.001), multifocal disease (HR = 1.63, 95% CI: 1.25-2.13, p < 0.001), biopsy vs. resection (HR = 1.35, 95% CI: 1.04-1.72, p = 0.02), un-methylated promoter of the MGMT (O6-methylguanine-DNA methyltransferase) gene (HR = 1.71, 95% CI: 1.42-2.04, p < 0.001). The model was validated internally and had a concordance index of 0.65. CONCLUSION: A nomogram for overall survival was established. This model can be used for risk stratification and treatment planning, as well as improve enrollment criteria for clinical trials.

Systemic Immune Modulation in Gliomas: Prognostic Value of Plasma IL-6, YKL-40, and Genetic Variation in YKL-40.

Background: Complex local and systemic immune dysfunction in glioblastoma (GBM) may affect survival. Interleukin (IL)-6 and YKL-40 are pleiotropic biomarkers present in the tumor microenvironment and involved in immune regulation. We therefore analyzed plasma IL-6, YKL-40, and genetic variation in YKL-40 and explored their ability to distinguish between glioma subtypes and predict survival in GBM. Methods: One hundred fifty-eight patients with glioma WHO grade II-IV were included in the study. Plasma collected at surgery was analyzed for IL-6 and YKL-40 (CHI3L1) by ELISA. CHI3L1 rs4950928 genotyping was analyzed on whole-blood DNA. Results: Neither plasma IL-6 nor YKL-40 corrected for age or rs4950928 genotype could differentiate GBM from lower grade gliomas. GC and GG rs4950928 genotype were associated with lower plasma YKL-40 levels (CC vs. GC, p = 0.0019; CC vs. GG, p = 0.01). Only 10 and 14 out of 94 patients with newly diagnosed GBM had elevated IL-6 or YKL-40, respectively. Most patients received corticosteroid treatment at time of blood-sampling. Higher pretreatment plasma IL-6 was associated with short overall survival (OS) [HR = 1.19 (per 2-fold change), p = 0.042] in univariate analysis. The effect disappeared in multivariate analysis. rs4950928 genotype did not associate with OS [HR = 1.30, p = 0.30]. In recurrent GBM, higher YKL-40 [HR = 2.12 (per 2-fold change), p = 0.0005] but not IL-6 [HR = 0.99 (per 2-fold change), p = 0.92] were associated with short OS in univariate analysis. Conclusion: In recurrent GBM high plasma YKL-40 may hold promise as a prognostic marker. In newly diagnosed GBM perioperative plasma IL-6, YKL-40, and genetic variation in YKL-40 did not associate with survival. Corticosteroid use may complicate interpretation of results.

Angiotensinogen promoter methylation predicts bevacizumab treatment response of patients with recurrent glioblastoma.

Patients with recurrent glioblastoma achieving response to bevacizumab combined with chemotherapy have clinical improvement and prolonged survival. High gene expression of angiotensinogen (AGT) is associated with a poor bevacizumab response. Because AGT expression is epigenetically regulated, we aimed to investigate whether AGT promoter methylation in tumor tissue predicts response to bevacizumab combination therapy in patients with recurrent glioblastoma. The study included 159 patients with recurrent glioblastoma, treated with bevacizumab combination treatment (training cohort, n = 77; validation cohort, n = 82). All patients could be evaluated for treatment response and biomarkers. DNA methylation of 4 CpG sites in the AGT promoter was measured using pyrosequencing. A model for nonresponse was established using logistic regression analysis. In the training cohort, lower methylation of each of the four CpG sites in the AGT promoter was significantly associated with nonresponse (all P < 0.05). Moreover, the mean methylation level of all four CpG sites was associated with an increased likelihood of not achieving response to bevacizumab combination therapy (twofold decrease: odds ratio = 3.01; 95% confidence interval: 1.41-6.44; P = 0.004). We developed a model for nonresponse in the training cohort, where a threshold of mean AGT promoter methylation levels was set to below 12%. The model could predict bevacizumab nonresponse with 96% specificity. Importantly, this predictor was also significantly associated with nonresponse in the validation cohort (P = 0.037). Taken together, our findings suggest that low AGT promoter methylation in tumor tissue predicts nonresponse to bevacizumab combination treatment in patients with recurrent glioblastoma. We have, thus, established and successfully validated a predictor for nonresponse that can be used to identify patients who will not benefit from bevacizumab combination therapy.

ABCB1 single-nucleotide variants and survival in patients with glioblastoma treated with radiotherapy concomitant with temozolomide.

Standard treatment for glioblastoma (GBM) patients is surgery and radiochemotherapy (RCT) with temozolomide (TMZ). TMZ is a substrate for ABCB1, a transmembrane drug transporter. It has been suggested that survival for GBM patients receiving TMZ is influenced by different single-nucleotide variants (SNV) of ABCB1. We therefore examined SNV:s of ABCB1, namely 1199G>A, 1236C>T, 2677G>T/A, and 3435C>T and correlated to survival for GBM patients receiving RCT. In a pilot cohort (97 patients) a significant correlation to survival was found for SNV 1199G>A, with median OS for variant G/G patients being 18.2 months versus 11.5 months for A/G (p = 0.012). We found no correlation to survival for the other SNV:s. We then expanded the cohort to 179 patients (expanded cohort) and also included a confirmatory cohort (49 patients) focusing on SNV 1199G>A. Median OS for G/G versus A/G plus A/A was 15.7 and 11.5 months, respectively (p = 0.085) for the expanded cohort and 13.8 versus 16.8 months (p = 0.19) for the confirmatory. In conclusion, in patients with GBM receiving RCT with TMZ, no correlation with survival was found for the SNV:s 1236C>T, 2677G>T/A, and 3435C>T of ABCB1. Although the SNV 1199G>A might have some impact, a clinically significant role could not be confirmed.

Cell-free DNA in newly diagnosed patients with glioblastoma - a clinical prospective feasibility study.

Background: Glioblastoma (GB) is an incurable brain cancer with limited treatment options. The aim was to test the feasibility of using cell-free DNA (cfDNA) to support evaluation of treatment response, pseudo-progression and whether progression could be found before clinical and/or radiologic progression. Results: CfDNA fluctuated during treatment with the highest levels before diagnostic surgery and at progression. An increase was seen in 3 out of 4 patients at the time of progression while no increase was seen in 3 out of 4 patients without progression. CfDNA levels could aid in 3 out of 3 questionable cases of pseudo-progression. Methods: Eight newly diagnosed GB patients were included. Blood samples were collected prior to diagnosis, before start and during oncologic treatment until progression. Seven patients received concurrent radiotherapy/Temozolomide with adjuvant Temozolomide with one of the patients included in a clinical trial with either immunotherapy or placebo as add-on. One patient received radiation alone. CfDNA concentration was determined for each blood sample. Conclusions: It was feasible to measure cfDNA concentration. Despite the limited cohort size, there was a good tendency between cfDNA and treatment course and -response, respectively with the highest levels at progression.

Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma.

Glioblastoma multiforme (GBM) is the most aggressive brain tumor with poor prognosis to most patients. Immunotherapy of GBM is a potentially beneficial treatment option, whose optimal implementation may depend on familiarity with tumor specific antigens, presented as HLA peptides by the GBM cells. Further, early detection of GBM, such as by a routine blood test, may improve survival, even with the current treatment modalities. This study includes large-scale analyses of the HLA peptidome (immunopeptidome) of the plasma-soluble HLA molecules (sHLA) of 142 plasma samples, and the membranal HLA of GBM tumors of 10 of these patients' tumor samples. Tumor samples were fresh-frozen immediately after surgery and the plasma samples were collected before, and at multiple visits after surgery. In total, this HLA peptidome analysis involved 52 different HLA allotypes and resulted in the identification of more than 35,000 different HLA peptides. Strong correlations were observed in the signal intensities and in the repertoires of identified peptides between the tumors and plasma-soluble HLA peptidomes of the individual patients, whereas low correlations were observed between these HLA peptidomes and the tumors' proteomes. HLA peptides derived from Cancer/Testis Antigens (CTAs) were selected based on their presence among the HLA peptidomes of the patients and absence of expression of their source genes from any healthy and essential human tissues, except from immune-privileged sites. Additionally, peptides were selected as potential biomarkers if their levels in the plasma-sHLA peptidome were significantly reduced after the removal of tumor mass. The CTAs identified among the analyzed HLA peptidomes provide new opportunities for personalized immunotherapy and for early diagnosis of GBM.

Clinical Characteristics of Gliosarcoma and Outcomes From Standardized Treatment Relative to Conventional Glioblastoma.

Background: Gliosarcoma (GS) is a rare histopathologic variant of glioblastoma (GBM) characterized by a biphasic growth pattern consisting of both glial and sarcomatous components. Reports regarding its relative prognosis compared to conventional GBM are conflicting and although GS is treated as conventional GBM, supporting evidence is lacking. The aim of this study was to characterize demographic trends, clinical outcomes and prognostic variables of GS patients receiving standardized therapy and compare these to conventional GBM. Methods: Six hundred and eighty GBM patients, treated with maximal safe resection followed by radiotherapy with concomitant and adjuvant temozolomide at a single institution, were retrospectively reevaluated by reviewing histopathological records and tumor tissue for identification of GS patients. Clinico-pathological- and tumor growth characteristics were obtained via assessment of medical records and imaging analysis. Kaplan-Meier survival estimates were compared with log-rank testing, while Cox-regression modeling was tested for prognostic factors in GS patients. Results: The cohort included 26 primary gliosarcoma (PGS) patients (3.8%) and 7 secondary gliosarcoma (SGS) patients (1.0%). Compared to conventional GBM tumors, PGS tumors were significantly more often MGMT-unmethylated (73.9%) and located in the temporal lobe (57.7%). GS tumors often presented dural contact, while extracranial metastasis was only found in 1 patient. No significant differences were found between PGS and conventional GBM in progression-free-survival (6.8 and 7.6 months, respectively, p = 0.105) and in overall survival (13.4 and 15.7 months, respectively, p = 0.201). Survival following recurrence was not significantly different between PGS, SGS, and GBM. Temporal tumor location and MGMT status were found associated with PGS survival (p = 0.036 and p = 0.022, respectively). Conclusion: Despite histopathological and location difference between GS and GBM tumors, the patients present similar survival outcome from standardized treatment. These findings support continued practice of radiation and temozolomide for GS patients.

Identification of Tumor Antigens Among the HLA Peptidomes of Glioblastoma Tumors and Plasma.

Glioblastoma multiforme (GBM) is the most aggressive brain tumor with poor prognosis to most patients. Immunotherapy of GBM is a potentially beneficial treatment option, whose optimal implementation may depend on familiarity with tumor specific antigens, presented as HLA peptides by the GBM cells. Furthermore, early detection of GBM, such as by a routine blood test, may improve survival, even with the current treatment modalities. This study includes large-scale analyses of the HLA peptidome (immunopeptidome) of the plasma-soluble HLA molecules (sHLA) of 142 plasma samples, and the membranal HLA of GBM tumors of 10 of these patients' tumor samples. Tumor samples were fresh-frozen immediately after surgery and the plasma samples were collected before, and at multiple visits after surgery. In total, this HLA peptidome analysis involved 52 different HLA allotypes and resulted in the identification of more than 35,000 different HLA peptides. Strong correlations were observed in the signal intensities and in the repertoires of identified peptides between the tumors and plasma-soluble HLA peptidomes of the individual patients, whereas low correlations were observed between these HLA peptidomes and the tumors' proteomes. HLA peptides derived from Cancer/Testis Antigens (CTAs) were selected based on their presence among the HLA peptidomes of the patients and absence of expression of their source genes from any healthy and essential human tissues, except from immune-privileged sites. Additionally, peptides were selected as potential biomarkers if their levels in the plasma-sHLA peptidome were significantly reduced after the removal of tumor mass. The CTAs identified among the analyzed HLA peptidomes provide new opportunities for personalized immunotherapy and for early diagnosis of GBM.

DNA Methylation Levels of the ELMO Gene Promoter CpG Islands in Human Glioblastomas.

Complete surgical resection of glioblastoma is difficult due to the invasive nature of this primary brain tumor, for which the molecular mechanisms behind remain poorly understood. The three human ELMO genes play key roles in cellular motility, and have been linked to metastasis and poor prognosis in other cancer types. The aim of this study was to investigate methylation levels of the ELMO genes and their correlation to clinical characteristics and outcome in patients diagnosed with glioblastoma. To measure DNA methylation levels we designed pyrosequencing assays targeting the promoter CpG island of each the ELMO genes. These were applied to diagnostic tumor specimens from a well-characterized cohort of 121 patients who received standard treatment consisting of surgery, radiation therapy, plus concomitant and adjuvant chemotherapy. The promoter methylation levels of ELMO1 and ELMO2 were generally low, whereas ELMO3 methylation levels were high, in the tumor biopsies. Thirteen, six, and 18 biopsies were defined as aberrantly methylated for ELMO1, ELMO2, and ELMO3, respectively. There were no significant associations between the methylation status of any of the ELMO gene promoter CpG islands and overall survival, progression-free survival, and clinical characteristics of the patients including intracranial tumor location. Therefore, the methylation status of the ELMO gene promoter CpG islands is unlikely to have prognostic value in glioblastoma.

Biomarkers in Recurrent Grade III Glioma Patients Treated with Bevacizumab and Irinotecan.

Predictive biomarkers and prognostic models are required to identify recurrent grade III glioma patients who benefit from existing treatment. In this study of 62 recurrent grade III glioma patients, a range of clinical and paraclinical factors are tested for association with progression-free survival, overall survival, and response to bevacizumab and irinotecan therapy. Significant factors from univariate screening are included in multivariate analysis. Biomarkers previously advanced as predictive or prognostic in the first-line setting did not affect outcome in this patient cohort. Based on the optimized model for overall survival, comprising performance status and p53 expression, a prognostic index is established.

Targeting glioma stem-like cell survival and chemoresistance through inhibition of lysine-specific histone demethylase KDM2B.

Glioblastoma (GBM) ranks among the most lethal cancers, with current therapies offering only palliation. Inter- and intrapatient heterogeneity is a hallmark of GBM, with epigenetically distinct cancer stem-like cells (CSCs) at the apex. Targeting GSCs remains a challenging task because of their unique biology, resemblance to normal neural stem/progenitor cells, and resistance to standard cytotoxic therapy. Here, we find that the chromatin regulator, JmjC domain histone H3K36me2/me1 demethylase KDM2B, is highly expressed in glioblastoma surgical specimens compared to normal brain. Targeting KDM2B function genetically or pharmacologically impaired the survival of patient-derived primary glioblastoma cells through the induction of DNA damage and apoptosis, sensitizing them to chemotherapy. KDM2B loss decreased the GSC pool, which was potentiated by coadministration of chemotherapy. Collectively, our results demonstrate KDM2B is crucial for glioblastoma maintenance, with inhibition causing loss of GSC survival, genomic stability, and chemoresistance.