Dataset Information

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab.

ABSTRACT: PURPOSE:We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients. PATIENTS AND METHODS:TCGA microRNA expression data from tumors resected at first diagnosis of glioblastoma in patients treated with bevacizumab at any time during the course of their disease were randomly separated into training (n = 50) and test (n = 37) groups for model generation. MicroRNA-seq data for 51 patients whose treatment included bevacizumab in the BELOB trial were used as an independent validation cohort. RESULTS:Using penalized regression we identified 8 microRNAs as potential predictors of overall survival in the training set. We dichotomized the response score based on the most prognostic minimum of a density plot of the response scores (log-rank HR = 0.16, p = 1.2e(-5)) and validated the profile in the test cohort (one-sided log-rank HR = 0.34, p = 0.026). Analysis of the profile using all samples in the TCGA glioblastoma dataset, regardless of treatment received, (n = 473) showed that the prediction of patient benefit was not significant (HR = 0.84, p = 0.083) suggesting the profile is specific to bevacizumab. Further independent validation of our microRNA profile in RNA-seq data from patients treated with bevacizumab (alone or in combination with CCNU) at glioblastoma recurrence in the BELOB trial confirmed that our microRNA profile predicted patient benefit from bevacizumab (HR = 0.59, p = 0.043). CONCLUSION:We have identified and validated an 8-microRNA profile that predicts overall survival in patients with glioblastoma treated with bevacizumab. This may be useful for identifying patients who are likely to benefit from this agent.

SUBMITTER: Hayes J

PROVIDER: S-EPMC5423205 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab.

Hayes Josie J Thygesen Helene H Gregory Walter W Westhead David R DR French Pim J PJ Van Den Bent Martin J MJ Lawler Sean E SE Short Susan C SC

Molecular oncology 20160701 8

<h4>Purpose</h4>We investigated whether microRNA expression data from glioblastoma could be used to produce a profile that defines a bevacizumab responsive group of patients.<h4>Patients and methods</h4>TCGA microRNA expression data from tumors resected at first diagnosis of glioblastoma in patients treated with bevacizumab at any time during the course of their disease were randomly separated into training (n = 50) and test (n = 37) groups for model generation. MicroRNA-seq data for 51 patients ...[more]

PMID: 27396951

Similar Datasets

Project description:BackgroundIn the context of patients with hepatocellular carcinoma (HCC) treated with systemic therapy, the correlation between the appearance of adverse events (AEs) and reported efficacy outcomes is well-known and widely investigated. From other pathological settings, we are aware of the prognostic and predictive value of the occurrence of immune-related AEs in patients treated with immune-checkpoint inhibitors.ObjectiveThis retrospective multicenter real-world study aims to investigate the potential prognostic value of AEs in patients with HCC treated with atezolizumab plus bevacizumab in the first-line setting.Patients and methodsThe study population consisted of 823 patients from five countries (Italy, Germany, Portugal, Japan, and the Republic of Korea).ResultsOf the patients, 73.3% presented at least one AE during the study period. The most common AEs were proteinuria (29.6%), arterial hypertension (27.2%), and fatigue (26.0%). In all, 17.3% of the AEs were grade (G) 3. One death due to bleeding was reported. The multivariate analysis confirmed the appearance of decreased appetite G < 2 [versus G ≥ 2; hazard ratio (HR) 0.60; 95% confidence interval (CI) 0.13-0.90; p < 0.01] and immunotoxicity G < 2 (versus G ≥ 2; HR: 0.70; 95% CI 0.24-0.99; p = 0.04) as independent prognostic factors for overall survival, and the appearance of decreased appetite G < 2 (versus G ≥ 2; HR: 0.73; 95% CI 0.43-0.95; p = 0.01), diarrhea (yes versus no; HR: 0.57, 95% CI 0.38-0.85; p = 0.01), fatigue (yes versus no; HR: 0.82, 95% CI 0.65-0.95; p < 0.01), arterial hypertension G < 2 (versus G ≥ 2; HR: 0.68, 95% CI 0.52-0.87; p < 0.01), and proteinuria (yes versus no; HR: 0.79, 95% CI 0.64-0.98; p = 0.03) as independent prognostic factors for progression-free survival.ConclusionsAs demonstrated for other therapies, there is also a correlation between the occurrence of AEs and outcomes for patients with HCC for the combination of atezolizumab plus bevacizumab.

Project description:BackgroundAnti-angiogenic therapy with bevacizumab is the most widely used treatment option for recurrent glioblastoma, but therapeutic response varies substantially and effective biomarkers for patient selection are not available. To this end, we determine whether novel quantitative radiomic strategies on the basis of MRI have the potential to noninvasively stratify survival and progression in this patient population.MethodsIn an initial cohort of 126 patients, we identified a distinct set of features representative of the radiographic phenotype on baseline (pretreatment) MRI. These selected features were evaluated on a second cohort of 165 patients from the multicenter BRAIN trial with prospectively acquired clinical and imaging data. Features were evaluated in terms of prognostic value for overall survival (OS), progression-free survival (PFS), and progression within 3, 6, and 9 months using baseline imaging and first follow-up imaging at 6 weeks posttreatment initiation.ResultsMultivariable analysis of features derived at baseline imaging resulted in significant stratification of OS (hazard ratio [HR] = 2.5; log-rank P = 0.001) and PFS (HR = 4.5; log-rank P = 2.1 × 10-5) in validation data. These stratifications were stronger compared with clinical or volumetric covariates (permutation test false discovery rate [FDR] <0.05). Univariable analysis of a prognostic textural heterogeneity feature (information correlation) derived from postcontrast T1-weighted imaging revealed significantly higher scores for patients who progressed within 3 months (Wilcoxon test P = 8.8 × 10-8). Generally, features derived from postcontrast T1-weighted imaging yielded higher prognostic power compared with precontrast enhancing T2-weighted imaging.ConclusionRadiomics provides prognostic value for survival and progression in patients with recurrent glioblastoma receiving bevacizumab treatment. These results could lead to the development of quantitative pretreatment biomarkers to predict benefit from bevacizumab using standard of care imaging.

Project description:Background and aimsThis retrospective review of patients with recurrent glioblastoma treated at the Preston Robert Tisch Brain Tumor Center investigated treatment patterns, survival, and safety with bevacizumab in a real-world setting.MethodsAdult patients with glioblastoma who initiated bevacizumab at disease progression between January 1, 2009, and May 14, 2012, were included. A Kaplan-Meier estimator was used to describe overall survival (OS), progression-free survival (PFS), and time to greater than or equal to 20% reduction in Karnofsky Performance Status (KPS). The effect of baseline demographic and clinical factors on survival was examined using a Cox proportional hazards model. Adverse event (AE) data were collected.ResultsSeventy-four patients, with a median age of 59 years, were included in this cohort. Between bevacizumab initiation and first failure, defined as the first disease progression after bevacizumab initiation, biweekly bevacizumab and bevacizumab/irinotecan were the most frequently prescribed regimens. Median duration of bevacizumab treatment until failure was 6.4 months (range, 0.5-58.7). Median OS and PFS from bevacizumab initiation were 11.1 months (95% confidence interval [CI], 7.3-13.4) and 6.4 months (95% CI, 3.9-8.5), respectively. Median time to greater than or equal to 20% reduction in KPS was 29.3 months (95% CI, 13.8-∞). Lack of corticosteroid usage at the start of bevacizumab therapy was associated with both longer OS and PFS, with a median OS of 13.2 months (95% CI, 8.6-16.6) in patients who did not initially require corticosteroids versus 7.2 months (95% CI, 4.8-12.5) in those who did (P = 0.0382, log-rank), while median PFS values were 8.6 months (95% CI, 4.6-9.7) and 3.7 months (95% CI, 2.7-6.6), respectively (P = 0.0243, log-rank). Treatment failure occurred in 70 patients; 47 of whom received salvage therapy, and most frequently bevacizumab/carboplatin (7/47; 14.9%). Thirteen patients (18%) experienced a grade 3 AE of special interest for bevacizumab.ConclusionsTreatment patterns and outcomes for patients with recurrent glioblastoma receiving bevacizumab in a real-world setting were comparable with those reported in prospective clinical trials.

Dataset Information

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab.

Publications

A validated microRNA profile with predictive potential in glioblastoma patients treated with bevacizumab.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets