A new landscape for systemic pharmacotherapy of recurrent glioblastoma?

Glioblastoma is the most common and aggressive primary malignant brain tumor in adult patients [...

Thrombocytopenia limits the feasibility of salvage lomustine chemotherapy in recurrent glioblastoma: a secondary analysis of EORTC 26101

BACKGROUND Thrombocytopenia represents the main cause of stopping alkylating chemotherapy for toxicity. Here, we explored the incidence, and the consequences for treatment exposure and survival, of thrombocytopenia induced by lomustine in recurrent glioblastoma. METHODS We performed a retrospective analysis of the associations of thrombocytopenia with treatment delivery and outcome in EORTC 26101, a randomised trial designed to define the role of lomustine versus bevacizumab versus their combination in recurrent glioblastoma. RESULTS A total of 225 patients were treated with lomustine alone (median 1 cycle) (group 1) and 283 patients were treated with lomustine plus bevacizumab (median 3 lomustine cycles) (group 2). Among cycle delays and dose reductions of lomustine for toxicity, thrombocytopenia was the leading cause. Among 129 patients (57%) of group 1 and 187 patients (66%) of group 2 experiencing at least one episode of thrombocytopenia, 36 patients (16%) in group 1 and 93 (33%) in group 2 had their treatment modified because of thrombocytopenia. Lomustine was discontinued for thrombocytopenia in 16 patients (7.1%) in group 1 and in 38 patients (13.4%) in group 2. On adjusted analysis accounting for major prognostic factors, dose modification induced by thrombocytopenia was associated with inferior progression-free survival in patients with MGMT promoter-methylated tumours in groups 1 and 2. This effect was noted for overall survival, too, but only for group 2 patients. CONCLUSION Drug-induced thrombocytopenia is a major limitation to adequate exposure to lomustine chemotherapy in recurrent glioblastoma. Mitigating thrombocytopenia to enhance lomustine exposure might improve outcome in patients with MGMT promoter-methylated tumours

Recurrent glioblastoma: From molecular landscape to new treatment perspectives

Glioblastoma is the most frequent and aggressive form among malignant central nervous system primary tumors in adults. Standard treatment for newly diagnosed glioblastoma consists in maximal safe resection, if feasible, followed by radiochemotherapy and adjuvant chemotherapy with temozolomide; despite this multimodal treatment, virtually all glioblastomas relapse. Once tumors progress after first-line therapy, treatment options are limited and management of recurrent glioblastoma remains challenging. Loco-regional therapy with re-surgery or re-irradiation may be evaluated in selected cases, while traditional systemic therapy with nitrosoureas and temozolomide rechallenge showed limited efficacy. In recent years, new clinical trials using, for example, regorafenib or a combination of tyrosine kinase inhibitors and immunotherapy were performed with promising results. In particular, molecular targeted therapy could show efficacy in selected patients with specific gene mutations. Nonetheless, some molecular characteristics and genetic alterations could change during tumor progression, thus affecting the efficacy of precision medicine. We therefore reviewed the molecular and genomic landscape of recurrent glioblastoma, the strategy for clinical management and the major phase I-III clinical trials analyzing recent drugs and combination regimens in these patients

Genomic aberrations associated with outcome in anaplastic oligodendroglial tumors treated within the EORTC phase III trial 26951

Despite similar morphological aspects, anaplastic oligodendroglial tumors (AOTs) form a heterogeneous clinical subgroup of gliomas. The chromosome arms 1p/19q codeletion has been shown to be a relevant biomarker in AOTs and to be perfectly exclusive from EGFR amplification in gliomas. To identify new genomic regions associated with prognosis, 60 AOTs from the EORTC trial 26951 were analyzed retrospectively using BAC-array-based comparative genomic hybridization. The data were processed using a binary tree method. Thirty-three BACs with prognostic value were identified distinguishing four genomic subgroups of AOTs with different prognosis (p < 0.0001). Type I tumors (25%) were characterized by: (1) an EGFR amplification, (2) a poor prognosis, (3) a higher rate of necrosis, and (4) an older age of patients. Type II tumors (21.7%) had: (1) loss of prognostic BACs located on 1p tightly associated with 19q deletion, (2) a longer survival, (3) an oligodendroglioma phenotype, and (4) a frontal location in brain. Type III AOTs (11.7%) exhibited: (1) a deletion of prognostic BACs located on 21q, and (2) a short survival. Finally, type IV tumors (41.7%) had different genomic patterns and prognosis than type I, II and III AOTs. Multivariate analysis showed that genomic type provides additional prognostic data to clinical, imaging and pathological features. Similar results were obtained in the cohort of 45 centrally reviewed–validated cases of AOTs. Whole genome analysis appears useful to screen the numerous genomic abnormalities observed in AOTs and to propose new biomarkers particularly in the non-1p/19q codeleted AOTs

Drug sensitivity of single cancer cells is predicted by changes in mass accumulation rate

Assays that can determine the response of tumor cells to cancer therapeutics could greatly aid the selection of drug regimens for individual patients. However, the utility of current functional assays is limited, and predictive genetic biomarkers are available for only a small fraction of cancer therapies. We found that the single-cell mass accumulation rate (MAR), profiled over many hours with a suspended microchannel resonator, accurately defined the drug sensitivity or resistance of glioblastoma and B-cell acute lymphocytic leukemia cells. MAR revealed heterogeneity in drug sensitivity not only between different tumors, but also within individual tumors and tumor-derived cell lines. MAR measurement predicted drug response using samples as small as 25 μl of peripheral blood while maintaining cell viability and compatibility with downstream characterization. MAR measurement is a promising approach for directly assaying single-cell therapeutic responses and for identifying cellular subpopulations with phenotypic resistance in heterogeneous tumors.United States. National Institutes of Health (R01 CA170592)United States. National Institutes of Health (R33 CA191143)National Cancer Institute (U.S.) (U54 CA143874)United States. National Institutes of Health (NIH/NIGMS T32 GM008334

Prognostic Markers of DNA Methylation and Next-Generation Sequencing in Progressive Glioblastoma from the EORTC-26101 Trial

PURPOSE: The EORTC-26101 study was a randomized phase II and III clinical trial of bevacizumab in combination with lomustine versus lomustine alone in progressive glioblastoma. Other than for progression-free survival (PFS), there was no benefit from addition of bevacizumab for overall survival (OS). However, molecular data allow for the rare opportunity to assess prognostic biomarkers from primary surgery for their impact in progressive glioblastoma. EXPERIMENTAL DESIGN: We analyzed DNA methylation array data and panel sequencing from 170 genes of 380 tumor samples of the EORTC-26101 study. These patients were comparable with the overall study cohort in regard to baseline characteristics, study treatment, and survival.RESULTS: Of patients' samples, 295/380 (78%) were classified into one of the main glioblastoma groups, receptor tyrosine kinase (RTK)1, RTK2 and mesenchymal. There were 10 patients (2.6%) with isocitrate dehydrogenase mutant tumors in the biomarker cohort. Patients with RTK1 and RTK2 classified tumors had lower median OS compared with mesenchymal (7.6 vs. 9.2 vs. 10.5 months). O6-methylguanine DNA-methyltransferase (MGMT) promoter methylation was prognostic for PFS and OS. Neurofibromin (NF)1 mutations were predictive of response to bevacizumab treatment.CONCLUSIONS: Thorough molecular classification is important for brain tumor clinical trial inclusion and evaluation. MGMT promoter methylation and RTK1 classifier assignment were prognostic in progressive glioblastoma. NF1 mutation may be a predictive biomarker for bevacizumab treatment.</p

Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology:a multicentre, retrospective cohort study

International audienceBackground Gadolinium-based contrast agents (GBCAs) are widely used to enhance tissue contrast during MRI scans and play a crucial role in the management of patients with cancer. However, studies have shown gadolinium deposition in the brain after repeated GBCA administration with yet unknown clinical significance. We aimed to assess the feasibility and diagnostic value of synthetic post-contrast T1-weighted MRI generated from pre-contrast MRI sequences through deep convolutional neural networks (dCNN) for tumour response assessment in neuro-oncology. Methods In this multicentre, retrospective cohort study, we used MRI examinations to train and validate a dCNN for synthesising post-contrast T1-weighted sequences from pre-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery sequences. We used MRI scans with availability of these sequences from 775 patients with glioblastoma treated at Heidelberg University Hospital, Heidelberg, Germany (775 MRI examinations); 260 patients who participated in the phase 2 CORE trial (1083 MRI examinations, 59 institutions); and 505 patients who participated in the phase 3 CENTRIC trial (3147 MRI examinations, 149 institutions). Separate training runs to rank the importance of individual sequences and (for a subset) diffusion-weighted imaging were conducted. Independent testing was performed on MRI data from the phase 2 and phase 3 EORTC-26101 trial (521 patients, 1924 MRI examinations, 32 institutions). The similarity between synthetic and true contrast enhancement on post-contrast T1-weighted MRI was quantified using the structural similarity index measure (SSIM). Automated tumour segmentation and volumetric tumour response assessment based on synthetic versus true post-contrast T1-weighted sequences was performed in the EORTC-26101 trial and agreement was assessed with Kaplan-Meier plots. Interpretation Generating synthetic post-contrast T1-weighted MRI from pre-contrast MRI using dCNN is feasible and quantification of the contrast-enhancing tumour burden from synthetic post-contrast T1-weighted MRI allows assessment of the patient's response to treatment with no significant difference by comparison with true post-contrast T1-weighted sequences with administration of GBCAs. This finding could guide the application of dCNN in radiology to potentially reduce the necessity of GBCA administration

DNA Fragmentation Simulation Method (FSM) and Fragment Size Matching Improve aCGH Performance of FFPE Tissues

Whole-genome copy number analysis platforms, such as array comparative genomic hybridization (aCGH) and single nucleotide polymorphism (SNP) arrays, are transformative research discovery tools. In cancer, the identification of genomic aberrations with these approaches has generated important diagnostic and prognostic markers, and critical therapeutic targets. While robust for basic research studies, reliable whole-genome copy number analysis has been unsuccessful in routine clinical practice due to a number of technical limitations. Most important, aCGH results have been suboptimal because of the poor integrity of DNA derived from formalin-fixed paraffin-embedded (FFPE) tissues. Using self-hybridizations of a single DNA sample we observed that aCGH performance is significantly improved by accurate DNA size determination and the matching of test and reference DNA samples so that both possess similar fragment sizes. Based on this observation, we developed a novel DNA fragmentation simulation method (FSM) that allows customized tailoring of the fragment sizes of test and reference samples, thereby lowering array failure rates. To validate our methods, we combined FSM with Universal Linkage System (ULS) labeling to study a cohort of 200 tumor samples using Agilent 1 M feature arrays. Results from FFPE samples were equivalent to results from fresh samples and those available through the glioblastoma Cancer Genome Atlas (TCGA). This study demonstrates that rigorous control of DNA fragment size improves aCGH performance. This methodological advance will permit the routine analysis of FFPE tumor samples for clinical trials and in daily clinical practice

Influence of Treatment With Tumor-Treating Fields on Health-Related Quality of Life of Patients With Newly Diagnosed Glioblastoma: A Secondary Analysis of a Randomized Clinical Trial

Importance Tumor-treating fields (TTFields) therapy improves both progression-free and overall survival in patients with glioblastoma. There is a need to assess the influence of TTFields on patients' health-related quality of life (HRQoL). Objective To examine the association of TTFields therapy with progression-free survival and HRQoL among patients with glioblastoma. Design, Setting, and Participants This secondary analysis of EF-14, a phase 3 randomized clinical trial, compares TTFields and temozolomide or temozolomide alone in 695 patients with glioblastoma after completion of radiochemotherapy. Patients with glioblastoma were randomized 2:1 to combined treatment with TTFields and temozolomide or temozolomide alone. The study was conducted from July 2009 until November 2014, and patients were followed up through December 2016. Interventions Temozolomide, 150 to 200 mg/m2/d, was given for 5 days during each 28-day cycle. TTFields were delivered continuously via 4 transducer arrays placed on the shaved scalp of patients and were connected to a portable medical device. Main Outcomes and Measures Primary study end point was progression-free survival; HRQoL was a predefined secondary end point, measured with questionnaires at baseline and every 3 months thereafter. Mean changes from baseline scores were evaluated, as well as scores over time. Deterioration-free survival and time to deterioration were assessed for each of 9 preselected scales and items. Results Of the 695 patients in the study, 639 (91.9%) completed the baseline HRQoL questionnaire. Of these patients, 437 (68.4%) were men; mean (SD) age, 54.8 (11.5) years. Health-related quality of life did not differ significantly between treatment arms except for itchy skin. Deterioration-free survival was significantly longer with TTFields for global health (4.8 vs 3.3 months; P < .01); physical (5.1 vs 3.7 months; P < .01) and emotional functioning (5.3 vs 3.9 months; P < .01); pain (5.6 vs 3.6 months; P < .01); and leg weakness (5.6 vs 3.9 months; P < .01), likely related to improved progression-free survival. Time to deterioration, reflecting the influence of treatment, did not differ significantly except for itchy skin (TTFields worse; 8.2 vs 14.4 months; P < .001) and pain (TTFields improved; 13.4 vs 12.1 months; P < .01). Role, social, and physical functioning were not affected by TTFields. Conclusions and Relevance The addition of TTFields to standard treatment with temozolomide for patients with glioblastoma results in improved survival without a negative influence on HRQoL except for more itchy skin, an expected consequence from the transducer arrays. Trial Registration clinicaltrials.gov Identifier: NCT00916409