Association between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3T.

BACKGROUND AND PURPOSE: Acidification of the tumor microenvironment from abnormal metabolism along with angiogenesis to meet metabolic demands are both hallmarks of malignant brain tumors; however, the interdependency of tumor acidity and vascularity has not been explored. Therefore, our aim was to investigate the association between pH-sensitive amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) and relative cerebral blood volume (CBV) measurements obtained from dynamic susceptibility contrast (DSC) perfusion MRI in patients with gliomas. MATERIALS AND METHODS: In this retrospective study, 90 patients with histologically confirmed gliomas were scanned between 2015 and 2018 (median age, 50.3 years; male/female ratio = 59:31). pH-weighting was obtained using chemical exchange saturation transfer echo-planar imaging estimation of the magnetization transfer ratio asymmetry at 3 ppm, and CBV was estimated using DSC-MR imaging. The voxelwise correlation and patient-wise median value correlation between the magnetization transfer ratio asymmetry at 3 ppm and CBV within T2-hyperintense lesions and contrast-enhancing lesions were evaluated using the Pearson correlation analysis. RESULTS: General colocalization of elevated perfusion and high acidity was observed in tumors, with local intratumor heterogeneity. For patient-wise analysis, median CBV and magnetization transfer ratio asymmetry at 3 ppm within T2-hyperintense lesions were significantly correlated (R = 0.3180, P = .002), but not in areas of contrast enhancement (P = .52). The positive correlation in T2-hyperintense lesions remained within high-grade gliomas (R = 0.4128, P = .001) and in isocitrate dehydrogenase wild-type gliomas (R = 0.4300, P = .002), but not in World Health Organization II or in isocitrate dehydrogenase mutant tumors. Both magnetization transfer ratio asymmetry at 3 ppm and the voxelwise correlation between magnetization transfer ratio asymmetry and CBV were higher in high-grade gliomas compared with low-grade gliomas in T2-hyperintense tumors (magnetization transfer ratio asymmetry, P = .02; Pearson correlation, P = .01). The same trend held when comparing isocitrate dehydrogenase wild-type gliomas and isocitrate dehydrogenase mutant gliomas (magnetization transfer ratio asymmetry, P = .04; Pearson correlation, P = .01). CONCLUSIONS: A positive linear correlation between CBV and acidity in areas of T2-hyperintense, nonenhancing tumor, but not enhancing tumor, was observed across patients. Local heterogeneity was observed within individual tumors.

Improved Spatiotemporal Resolution of Dynamic Susceptibility Contrast Perfusion MRI in Brain Tumors Using Simultaneous Multi-Slice Echo-Planar Imaging.

DSC perfusion MR imaging in brain tumors requires a trade-off between spatial and temporal resolution, resulting in less spatial coverage to meet the temporal resolution requirements for accurate relative CBV estimation. DSC-MR imaging could potentially benefit from the advantages associated with simultaneous multi-slice imaging, including increased spatiotemporal resolution. In the current article, we demonstrate how simultaneous multi-slice EPI can be used to improve DSC-MR imaging spatiotemporal resolution in patients with glioblastoma.

Improved Leakage Correction for Single-Echo Dynamic Susceptibility Contrast Perfusion MRI Estimates of Relative Cerebral Blood Volume in High-Grade Gliomas by Accounting for Bidirectional Contrast Agent Exchange.

BACKGROUND AND PURPOSE: Contrast agent extravasation through a disrupted blood-brain barrier potentiates inaccurate DSC MR imaging estimation of relative CBV. We explored whether incorporation of an interstitial washout rate in a leakage-correction model for single-echo, gradient-echo DSC MR imaging improves relative CBV estimates in high-grade gliomas. MATERIALS AND METHODS: We modified the traditional model-based postprocessing leakage-correction algorithm, assuming unidirectional contrast agent extravasation (Boxerman-Weisskoff model) to account for bidirectional contrast agent exchange between intra- and extravascular spaces (bidirectional model). For both models, we compared the goodness of fit with the parent leakage-contaminated relaxation rate curves by using the Akaike Information Criterion and the difference between modeled interstitial relaxation rate curves and dynamic contrast-enhanced MR imaging by using Euclidean distance in 21 patients with glioblastoma multiforme. RESULTS: The bidirectional model had improved Akaike Information Criterion versus the bidirectional model in >50% of enhancing tumor voxels in all 21 glioblastoma multiformes (77% ± 9%; P < .0001) and had reduced the Euclidean distance in >50% of enhancing tumor voxels for 17/21 glioblastoma multiformes (62% ± 17%; P = .0041). The bidirectional model and dynamic contrast-enhanced-derived kep demonstrated a strong correlation (r = 0.74 ± 0.13). On average, enhancing tumor relative CBV for the Boxerman-Weisskoff model exceeded that for the bidirectional model by 16.6% ± 14.0%. CONCLUSIONS: Inclusion of the bidirectional exchange in leakage-correction models for single-echo DSC MR imaging improves the model fit to leakage-contaminated DSC MR imaging data and significantly improves the estimation of relative CBV in high-grade gliomas.

Arterial spin-labeling perfusion MRI stratifies progression-free survival and correlates with epidermal growth factor receptor status in glioblastoma.

BACKGROUND AND PURPOSE: Glioblastoma is a common primary brain tumor with a poor but variable prognosis. Our aim was to investigate the feasibility of MR perfusion imaging by using arterial spin-labeling for determining the prognosis of patients with glioblastoma. MATERIALS AND METHODS: Pseudocontinuous arterial spin-labeling with 3D background-suppressed gradient and spin-echo was acquired before surgery on 53 patients subsequently diagnosed with glioblastoma. The calculated CBF color maps were visually evaluated by 3 independent readers blinded to patient history. Pathologic and survival data were correlated with CBF map findings. Arterial spin-labeling values in tumor tissue were also quantified by using manual fixed-size ROIs. RESULTS: Two perfusion patterns were characterized by visual evaluation of CBF maps on the basis of either the presence (pattern 1) or absence (pattern 2) of substantial hyperperfused tumor tissue. Evaluation of the perfusion patterns was highly concordant among the 3 readers (κ = 0.898, P < .001). Pattern 1 (versus pattern 2) was associated with significantly shorter progression-free survival by Kaplan-Meier analysis (median progression-free survival of 182 days versus 485 days, P < .01) and trended with shorter overall survival (P = .079). There was a significant association between pattern 1 and epidermal growth factor receptor variant III expression (P < .01). CONCLUSIONS: Qualitative evaluation of arterial spin-labeling CBF maps can be used to stratify survival and predict epidermal growth factor receptor variant III expression in patients with glioblastoma.

Pretreatment ADC histogram analysis is a predictive imaging biomarker for bevacizumab treatment but not chemotherapy in recurrent glioblastoma.

BACKGROUND AND PURPOSE: Pre-treatment ADC characteristics have been shown to predict response to bevacizumab in recurrent glioblastoma multiforme. However, no studies have examined whether ADC characteristics are specific to this particular treatment. The purpose of the current study was to determine whether ADC histogram analysis is a bevacizumab-specific or treatment-independent biomarker of treatment response in recurrent glioblastoma multiforme. MATERIALS AND METHODS: Eighty-nine bevacizumab-treated and 43 chemotherapy-treated recurrent glioblastoma multiformes never exposed to bevacizumab were included in this study. In all patients, ADC values in contrast-enhancing ROIs from MR imaging examinations performed at the time of recurrence, immediately before commencement of treatment for recurrence, were extracted and the resulting histogram was fitted to a mixed model with a double Gaussian distribution. Mean ADC in the lower Gaussian curve was used as the primary biomarker of interest. The Cox proportional hazards model and log-rank tests were used for survival analysis. RESULTS: Cox multivariate regression analysis accounting for the interaction between bevacizumab- and non-bevacizumab-treated patients suggested that the ability of the lower Gaussian curve to predict survival is dependent on treatment (progression-free survival, P = .045; overall survival, P = .003). Patients with bevacizumab-treated recurrent glioblastoma multiforme with a pretreatment lower Gaussian curve > 1.2 µm(2)/ms had a significantly longer progression-free survival and overall survival compared with bevacizumab-treated patients with a lower Gaussian curve < 1.2 µm(2)/ms. No differences in progression-free survival or overall survival were observed in the chemotherapy-treated cohort. Bevacizumab-treated patients with a mean lower Gaussian curve > 1.2 µm(2)/ms had a significantly longer progression-free survival and overall survival compared with chemotherapy-treated patients. CONCLUSIONS: The mean lower Gaussian curve from ADC histogram analysis is a predictive imaging biomarker for bevacizumab-treated, not chemotherapy-treated, recurrent glioblastoma multiforme. Patients with recurrent glioblastoma multiforme with a mean lower Gaussian curve > 1.2 µm(2)/ms have a survival advantage when treated with bevacizumab.

Probabilistic radiographic atlas of glioblastoma phenotypes.

BACKGROUND AND PURPOSE: Tumor location is a significant prognostic factor in glioblastoma, which may reflect the genetic profile of tumor precursor cells. The purpose of the current study was to construct and analyze probabilistic radiographic atlases reflecting preoperative tumor locations and corresponding demographic, "-omic," and interventional phenotypes to provide insight into potential niche locations of glioblastoma cells of origin. MATERIALS AND METHODS: Preoperative anatomic MR images in 507 patients with de novo glioblastoma were analyzed. Images were registered to stereotactic space, tumors were segmented, and the stereospecific frequency of tumor occurrence was analyzed statistically by age, extent of resection, MGMT methylation, IDH1 mutation, gene expression subclassification, PTEN loss, PTEN deficiency, EGFR amplification, EGFR variant 3 expression, progression-free survival from the start of radiochemotherapy, and overall survival from initial diagnosis. RESULTS: Most glioblastomas grow into the periventricular white matter regions adjacent to the subventricular zone. MGMT promoter methylated tumors occur more frequently in the left temporal lobe, in young patients with glioblastoma, in IDH1 mutant tumors, in tumors having the proneural gene expression subtype, and in tumors lacking loss of PTEN occurring most frequently in the frontal lobe. MGMT methylated tumors with the IDH1 mutation tended to occur in the left frontal lobe. EGFR amplified and EGFR variant 3-expressing tumors occurred most frequently in the left temporal lobe. A similar region in the left temporal lobe was associated with favorable response to radiochemotherapy and increased survival. CONCLUSIONS: Radiographic atlases for specific phenotypes provide insight into overlap between prognostic variables and may help to identify niche locations for cancer cells of origin.

Persistent diffusion-restricted lesions in bevacizumab-treated malignant gliomas are associated with improved survival compared with matched controls.

BACKGROUND AND PURPOSE: A subset of patients with malignant glioma develops conspicuous lesions characterized by persistent restricted diffusion during treatment with bevacizumab. The purpose of the current study was to characterize the evolution of these lesions and to determine their relationship to patient outcome. MATERIALS AND METHODS: Twenty patients with malignant glioma with persistent restricted-diffusion lesions undergoing treatment with bevacizumab were included in the current study. Mean ADC and the volume of restricted diffusion were computed for each patient during serial follow-up. Differences in TTP, TTS, and OS were compared between patients with restricted diffusion and matched controls by using Kaplan-Meier analysis with the logrank test and Cox hazard models. RESULTS: Mean ADC values were generally stable with time (mean, 5.2 ± 12.6% change from baseline). The volume of restricted diffusion increased a median of 23% from baseline by 6 months. Patients with restricted-diffusion lesions had significantly greater TTP (logrank, P = .013), TTS (logrank, P = .008), and OS (logrank, P = .010) than matched controls. When available, advanced physiologic imaging of restricted-diffusion lesions showed hypovascularity on perfusion MR imaging and decreased amino acid uptake on (18)F-FDOPA PET scans. Atypical gelatinous necrotic tissue was confirmed in the area of restricted diffusion in 1 patient. CONCLUSIONS: Restricted-diffusion lesions in malignant gliomas treated with bevacizumab are generally stable with time and are associated with improved outcomes. These results combined with physiologic imaging and histopathologic data suggest that these lesions are not consistent with aggressive tumor.

Relationship between tumor enhancement, edema, IDH1 mutational status, MGMT promoter methylation, and survival in glioblastoma.

BACKGROUND AND PURPOSE: Both IDH1 mutation and MGMT promoter methylation are associated with longer survival. We investigated the ability of imaging correlates to serve as noninvasive biomarkers for these molecularly defined GBM subtypes. MATERIALS AND METHODS: MR imaging from 202 patients with GBM was retrospectively assessed for nonenhancing tumor and edema among other imaging features. IDH1 mutational and MGMT promoter methylation status were determined by DNA sequencing and methylation-specific PCR, respectively. Overall survival was determined by using a multivariate Cox model and the Kaplan-Meier method with a log rank test. A logistic regression model followed by ROC analysis was used to classify the IDH1 mutation and methylation status by using imaging features. RESULTS: MGMT promoter methylation and IDH1 mutation were associated with longer median survival. Edema levels stratified survival for methylated but not unmethylated tumors. Median survival for methylated tumors with little/no edema was 2476 days (95% CI, 795), compared with 586 days (95% CI, 507-654) for unmethylated tumors or tumors with edema. All IDH1 mutant tumors were nCET positive, and most (11/14, 79%) were located in the frontal lobe. Imaging features including larger tumor size and nCET could be used to determine IDH1 mutational status with 97.5% accuracy, but poorly predicted MGMT promoter methylation. CONCLUSIONS: Imaging features are potentially predictive of IDH1 mutational status but were poorly correlated with MGMT promoter methylation. Edema stratifies survival in MGMT promoter methylated but not in unmethylated tumors; patients with methylated tumors with little or no edema have particularly long survival.

Differential gene expression in glioblastoma defined by ADC histogram analysis: relationship to extracellular matrix molecules and survival.

BACKGROUND AND PURPOSE: ADC histogram analysis can stratify outcomes in patients with GBM treated with bevacizumab. Therefore, we compared gene expression between high-versus-low ADC tumors to identify gene expression modules that could underlie this difference and impact patient prognosis. MATERIALS AND METHODS: Up-front bevacizumab-treated patients (N = 38) with newly diagnosed glioblastoma were analyzed by using an ADC histogram approach based on enhancing tumor. Using microarrays, we compared gene expression in high-versus-low ADC tumors in patients subsequently treated with bevacizumab. Tissue sections from a subset of tumors were stained for collagen and collagen-binding proteins. Progression-free and overall survival was determined by using Cox proportional hazard ratios and the Kaplan-Meier method with the log rank test. RESULTS: A total of 13 genes were expressed at 2-fold or greater levels in high- compared with low-ADC tumors at the P < .05 level. Of these, 6 encode for collagen or collagen-binding proteins. High gene expression for the collagen-binding protein decorin was associated with shorter survival (HR, 2.5; P = .03). The pattern and degree of collagen staining were highly variable in both high- and low-ADC tumors. CONCLUSIONS: High-ADC GBMs show greater levels of ECM protein gene expression compared with low-ADC GBMs. It is unclear whether this translates to the accumulation of higher levels of the encoded proteins. However, because ECM molecules could contribute to a proinvasive phenotype, this relationship merits further investigation.

Review: molecular pathology in adult high-grade gliomas: from molecular diagnostics to target therapies.

The classification of malignant gliomas is moving from a morphology-based guide to a system built on molecular criteria. The development of a genomic landscape for gliomas and a better understanding of its functional consequences have led to the development of internally consistent molecular classifiers. However, development of a biologically insightful classification to guide therapy is still a work in progress. Response to targeted treatments is based not only on the presence of drugable targets, but rather on the molecular circuitry of the cells. Further, tumours are heterogeneous and change and adapt in response to drugs. Therefore, the challenge of developing molecular classifiers that provide meaningful ways to stratify patients for therapy remains a major challenge for the field. In this review, we examine the potential role of MGMT methylation, IDH1/2 mutations, 1p/19q deletions, aberrant epidermal growth factor receptor and PI3K pathways, abnormal p53/Rb pathways, cancer stem-cell markers and microRNAs as prognostic and predictive molecular markers in the setting of adult high-grade gliomas and we outline the clinically relevant subtypes of glioblastoma with genomic, transcriptomic and proteomic integrated analyses. Furthermore, we describe how these advances, especially in epidermal growth factor receptor/PI3K/mTOR signalling pathway, affect our approaches towards targeted therapy, raising new challenges and identifying new leads.

AVAglio: Phase 3 trial of bevacizumab plus temozolomide and radiotherapy in newly diagnosed glioblastoma multiforme.

Despite treatment with the current standard-of-care therapies, patients with newly diagnosed glioblastoma multiforme (GBM) exhibit dismal prognoses. Bevacizumab has demonstrated activity in patients with recurrent GBM and phase 2 trials indicate that the combination of bevacizumab with standard-of-care therapy is feasible and active for patients with newly diagnosed GBM. Bevacizumab has been granted US approval for use as single-agent therapy for patients with progressive GBM following prior therapy, although it has not received approval for use in patients with GBM in Europe. Phase 3 studies have been initiated in patients with newly diagnosed GBM and are currently recruiting patients. We describe the protocol for the AVAglio phase 3 registration trial, which is designed to evaluate the efficacy and safety of combining bevacizumab with standard-of-care therapy in patients with newly diagnosed GBM.

Apparent diffusion coefficient histogram analysis stratifies progression-free survival in newly diagnosed bevacizumab-treated glioblastoma.

BACKGROUND AND PURPOSE: Currently it is difficult to predict tumor response to anti-angiogenic therapy in individual patients. Our aim was to determine if ADC histogram analysis can stratify progression-free and overall survival in patients with newly diagnosed GBM treated "up-front" (ie, before tumor recurrence) with bevacizumab. MATERIALS AND METHODS: Up-front bevacizumab-treated and control patients (n = 59 and 62, respectively) with newly diagnosed GBM were analyzed by using an ADC histogram approach based on enhancing tumor. Progression-free and overall survival was determined by using Cox proportional HRs and the Kaplan-Meier method with logrank and Wilcoxon tests. RESULTS: For up-front bevacizumab-treated patients, lower ADC(L) was associated with significantly longer progression-free survival (median, 459 days for ADC(L) < 1200 versus 315 days for ADC(L) ≥ 1200 10(-6)mm(2)/s; P = .008, logrank test) and trended with longer overall survival (581 versus 429 days, P = .055). ADC values did not stratify progression-free or overall survival for patients in the control group (P = .92 and P = .22, respectively). Tumors with MGMT promoter methylation had lower ADC(L) values than unmethylated tumors (mean, 1071 versus 1183 10(-6)mm(2)/s; P = .01, 2-group t test). CONCLUSIONS: Pretreatment ADC histogram analysis can stratify progression-free survival in bevacizumab-treated patients with newly diagnosed GBM. Lower ADC is associated with tumor MGMT promoter methylation, which may, in part, account for the favorable outcome associated with low ADC(L) tumors.

Patterns of progression in patients with recurrent glioblastoma treated with bevacizumab.

OBJECTIVE: We evaluated patterns of tumor progression in patients with recurrent glioblastoma who were treated with bevacizumab (BEV) alone or in combination with irinotecan (CPT-11) while participating in the BRAIN study. METHODS: An independent neuroradiologist reviewed MRI scans at baseline and progression in patients who received BEV (n = 85) or BEV+CPT-11 (n = 82) while on BRAIN. Tumor patterns were scored as local, distant, diffuse, or multifocal. Median progression-free survival (PFS) and overall survival (OS) were estimated using Kaplan-Meier methods. Hazard ratios for PFS and OS were estimated using a Cox regression model. RESULTS: Twenty-eight percent of patients who participated in BRAIN had nonlocal disease at baseline (72% local disease). Sixty-seven (79%) patients treated with single-agent BEV and 57 (70%) patients treated with BEV+CPT-11 experienced disease progression while on BRAIN. Most patients in each treatment group did not have a change in the radiographic pattern of their tumor (i.e., "no shift") at the time of progression. The proportion of BEV patients with no shift (82%) was greater than that of BEV+CPT-11 patients (53%, χ(2) p = 0.0004), and a greater proportion of BEV+CPT-11 patients (39%) compared with BEV patients (16%) experienced local-to-diffuse tumor pattern at progression (χ(2) p = 0.002). Patients treated with BEV or BEV+CPT-11 who had local-to-local or local-to-diffuse progression patterns had similar efficacy outcomes, including objective response, PFS, and OS. CONCLUSIONS: Most patients treated with BEV or BEV+CPT-11 on BRAIN did not experience a change from baseline in radiographic characteristics of disease at the time of progression.

Predicting the efficacy of radiotherapy in individual glioblastoma patients in vivo: a mathematical modeling approach.

Glioblastoma multiforme (GBM) is the most malignant form of primary brain tumors known as gliomas. They proliferate and invade extensively and yield short life expectancies despite aggressive treatment. Response to treatment is usually measured in terms of the survival of groups of patients treated similarly, but this statistical approach misses the subgroups that may have responded to or may have been injured by treatment. Such statistics offer scant reassurance to individual patients who have suffered through these treatments. Furthermore, current imaging-based treatment response metrics in individual patients ignore patient-specific differences in tumor growth kinetics, which have been shown to vary widely across patients even within the same histological diagnosis and, unfortunately, these metrics have shown only minimal success in predicting patient outcome. We consider nine newly diagnosed GBM patients receiving diagnostic biopsy followed by standard-of-care external beam radiation therapy (XRT). We present and apply a patient-specific, biologically based mathematical model for glioma growth that quantifies response to XRT in individual patients in vivo. The mathematical model uses net rates of proliferation and migration of malignant tumor cells to characterize the tumor's growth and invasion along with the linear-quadratic model for the response to radiation therapy. Using only routinely available pre-treatment MRIs to inform the patient-specific bio-mathematical model simulations, we find that radiation response in these patients, quantified by both clinical and model-generated measures, could have been predicted prior to treatment with high accuracy. Specifically, we find that the net proliferation rate is correlated with the radiation response parameter (r = 0.89, p = 0.0007), resulting in a predictive relationship that is tested with a leave-one-out cross-validation technique. This relationship predicts the tumor size post-therapy to within inter-observer tumor volume uncertainty. The results of this study suggest that a mathematical model can create a virtual in silico tumor with the same growth kinetics as a particular patient and can not only predict treatment response in individual patients in vivo but also provide a basis for evaluation of response in each patient to any given therapy.

Bevacizumab for recurrent ependymoma.

BACKGROUND: Ependymoma is a rare type of glioma, representing 5% of all CNS malignancies. Radiotherapy (RT) is commonly administered, but there is no standard chemotherapy. At recurrence, ependymoma is notoriously refractory to therapy and the prognosis is poor. In recurrent glioblastoma, encouraging responses with bevacizumab have been observed. METHODS: In this Institutional Review Board-approved study, we retrospectively analyzed the records of 8 adult patients treated for recurrent ependymoma and anaplastic ependymoma with bevacizumab containing chemotherapy regimens. We determined radiographic response (Macdonald criteria), median time to progression (TTP), and median overall survival (OS; Kaplan-Meier method). RESULTS: There were 4 men and 4 women with a median age of 40 years (range, 20-65). Prior treatment included surgery (n = 8), RT (8), temozolomide (5), and carboplatin (4). Bevacizumab (5-15 mg/kg every 2-3 weeks) was administered alone (2) or concurrently with cytotoxic chemotherapy including irinotecan (3), carboplatin (2), or temozolomide (1). Six patients achieved a partial response (75%) and 1 remained stable for over 8 months. Median TTP was 6.4 months (95% confidence interval 1.4-7.4) and median OS was 9.4 months (95% confidence interval 7.0-not reached), with a median follow-up of 5.2 months among 5 surviving patients (63%). CONCLUSIONS: The radiographic response rate to bevacizumab-containing regimens is high. A prospective study is warranted.

Bevacizumab and chemotherapy for recurrent glioblastoma: a single-institution experience.

OBJECTIVE: Bevacizumab has been shown to be effective in the treatment of recurrent glioblastoma in combination with chemotherapy compared with historic controls but not in randomized trials. METHODS: We conducted a retrospective analysis of patients treated for recurrent glioblastoma with bevacizumab vs a control group of patients, comparing progression-free survival (PFS) and overall survival (OS) between the two groups, and performed subgroup analysis based on age and performance status. Expression of vascular endothelial growth factor (VEGF) based on age was examined using DNA microarray analysis. We also evaluated the impact of bevacizumab on quality of life. RESULTS: We identified 44 patients who received bevacizumab and 79 patients who had not been treated with bevacizumab. There was a significant improvement in PFS and OS in the bevacizumab-treated group. Patients of older age (> or =55 years) and poor performance status (Karnofsky Performance Status < or =80) had significantly better PFS when treated with bevacizumab, and bevacizumab-treated older patients had significantly increased OS. VEGF expression was significantly higher in older glioblastoma patients (aged > or =55 years). Patients treated with bevacizumab also required less dexamethasone use and maintained their functional status longer than the control group. CONCLUSIONS: Bevacizumab in combination with chemotherapy may be a more effective treatment for recurrent glioblastoma and warrants further randomized prospective studies to determine its effect on survival. Bevacizumab also has more effect in those with older age and might reflect biologic differences in glioblastoma in different age groups as seen with the expression of vascular endothelial growth factor.

Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target.

Glioblastoma is the most common primary malignant brain tumor of adults and one of the most lethal of all cancers. Patients with this disease have a median survival of 15 months from the time of diagnosis despite surgery, radiation, and chemotherapy. New treatment approaches are needed. Recent works suggest that glioblastoma patients may benefit from molecularly targeted therapies. Here, we address the compelling need for identification of new molecular targets. Leveraging global gene expression data from two independent sets of clinical tumor samples (n = 55 and n = 65), we identify a gene coexpression module in glioblastoma that is also present in breast cancer and significantly overlaps with the "metasignature" for undifferentiated cancer. Studies in an isogenic model system demonstrate that this module is downstream of the mutant epidermal growth factor receptor, EGFRvIII, and that it can be inhibited by the epidermal growth factor receptor tyrosine kinase inhibitor Erlotinib. We identify ASPM (abnormal spindle-like microcephaly associated) as a key gene within this module and demonstrate its overexpression in glioblastoma relative to normal brain (or body tissues). Finally, we show that ASPM inhibition by siRNA-mediated knockdown inhibits tumor cell proliferation and neural stem cell proliferation, supporting ASPM as a potential molecular target in glioblastoma. Our weighted gene coexpression network analysis provides a blueprint for leveraging genomic data to identify key control networks and molecular targets for glioblastoma, and the principle eluted from our work can be applied to other cancers.

MRI in patients with high-grade gliomas treated with bevacizumab and chemotherapy.

Patients with recurrent gliomas (n = 14) were treated with bevacizumab and carboplatin, cpt-11, or etoposide. Follow-up MRI scans were obtained 2 to 6 weeks after initiation of treatment. Contrast-enhancing tumor shrank in 7 patients, with reductions evident in as little as 2 weeks after initiation of therapy. Treatment seemed more effective for heterogeneously enhancing tumor compared with solidly enhancing tumor.

Mapping therapeutic response in a patient with malignant glioma.

Short-interval scanning of patients offers a detailed understanding of the natural progression of tumor tissue, as revealed through imaging markers such as contrast enhancement and edema, prior to therapy. Following treatment, short-interval scanning can also provide evidence of attenuation of growth rates. We present a longitudinal imaging study of a patient with glioblastoma multiforme (GBM) scanned 15 times in 104 days on a 3 T MR scanner. Images were analyzed independently by two automated algorithms capable of creating detailed maps of tumor changes as well as volumetric analysis. The algorithms, a nearest-neighbor-based tissue segmentation and a surface-modeling algorithm, tracked the patient's response to temozolomide, showing an attenuation of growth. The need for surrogate imaging end-points, of which growth rates are an example, is discussed. Further, the strengths of these algorithms, the insight gained by short-interval scanning, and the need for a better understanding of imaging markers are also described.