Molecular Profiling Reveals Biologically Discrete Subsets and Pathways of Progression in Diffuse Glioma.

Therapy development for adult diffuse glioma is hindered by incomplete knowledge of somatic glioma driving alterations and suboptimal disease classification. We defined the complete set of genes associated with 1,122 diffuse grade II-III-IV gliomas from The Cancer Genome Atlas and used molecular profiles to improve disease classification, identify molecular correlations, and provide insights into the progression from low- to high-grade disease. Whole-genome sequencing data analysis determined that ATRX but not TERT promoter mutations are associated with increased telomere length. Recent advances in glioma classification based on IDH mutation and 1p/19q co-deletion status were recapitulated through analysis of DNA methylation profiles, which identified clinically relevant molecular subsets. A subtype of IDH mutant glioma was associated with DNA demethylation and poor outcome; a group of IDH-wild-type diffuse glioma showed molecular similarity to pilocytic astrocytoma and relatively favorable survival. Understanding of cohesive disease groups may aid improved clinical outcomes.

The somatic genomic landscape of glioblastoma.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

A multi-site phase I trial of Veliparib with standard radiation and temozolomide in patients with newly diagnosed glioblastoma multiforme (GBM).

PURPOSE: A multi-site Phase I trial was conducted to determine the safety, maximum tolerated dose, and pharmacokinetics (PK) of Veliparib, a Poly (ADP-ribose) polymerase [PARP] enzyme inhibitor, when administered with temozolomide (TMZ) alone and then with temozolomide and radiation (RT) in patients with newly diagnosed glioblastoma. METHODS: Given the potential for myelosuppression when a PARP inhibitor is combined with chemotherapy, the first 6 patients accrued were given Veliparib 10 mg bid and TMZ 75 mg/m2/d daily for six weeks. If this was well tolerated, the same doses of Veliparib and TMZ would be tested along with standard radiation with plans to dose escalate the Veliparib in subsequent patient cohorts. Once a maximal tolerated dose was determined, a 78 patient phase II study was planned. Peripheral blood pharmacokinetics were assessed. RESULTS: Twenty-four patients were enrolled. In the first 6 patients who received 6 weeks of TMZ with Veliparib only one dose limiting toxicity (DLT) occurred. The next 12 patients received 6 weeks of RT + TMZ + veliparib and 4/12 (33%) had dose limiting hematologic toxicities. As a result, Veliparib was reduced by 50% to 10 mg BID every other week, but again 3/3 patients had dose limiting hematologic toxicities. The trial was then terminated. The mean clearance (± SD) CL/F of Veliparib for the initial dose (27.0 ± 9.0 L/h, n = 16) and at steady-state for 10 mg BID (23.5 ± 10.4 L/h, n = 18) were similar. Accumulation for BID dosing was 56% (± 33%). CONCLUSIONS: Although Veliparib 10 mg BID administered with TMZ 75 mg/m2 for six weeks was well tolerated, when this regimen was combined with standard partial brain irradiation it was severely myelosuppressive even when the dose was reduced by 50%. This study again highlights the potential of localized cranial radiotherapy to significantly increase hematologic toxicity of marginally myelosuppressive systemic therapies.

Radiomics for precision medicine in glioblastoma.

INTRODUCTION: Being the most common primary brain tumor, glioblastoma presents as an extremely challenging malignancy to treat with dismal outcomes despite treatment. Varying molecular epidemiology of glioblastoma between patients and intra-tumoral heterogeneity explains the failure of current one-size-fits-all treatment modalities. Radiomics uses machine learning to identify salient features of the tumor on brain imaging and promises patient-specific management in glioblastoma patients. METHODS: We performed a comprehensive review of the available literature on studies investigating the role of radiomics and radiogenomics models for the diagnosis, stratification, prognostication as well as treatment planning and monitoring of glioblastoma. RESULTS: Classifiers based on a combination of various MRI sequences, genetic information and clinical data can predict non-invasive tumor diagnosis, overall survival and treatment response with reasonable accuracy. However, the use of radiomics for glioblastoma treatment remains in infancy as larger sample sizes, standardized image acquisition and data extraction techniques are needed to develop machine learning models that can be translated effectively into clinical practice. CONCLUSION: Radiomics has the potential to transform the scope of glioblastoma management through personalized medicine.

Randomized prospective trial of fractionated stereotactic radiosurgery with chemotherapy versus chemotherapy alone for bevacizumab-resistant high-grade glioma.

PURPOSE: Outcomes for patients with recurrent high-grade glioma (HGG) progressing on bevacizumab (BEV) are dismal. Fractionated stereotactic radiosurgery (FSRS) has been shown to be feasible and safe when delivered in this setting, but prospective evidence is lacking. This single-institution randomized trial compared FSRS plus BEV-based chemotherapy versus BEV-based chemotherapy alone for BEV-resistant recurrent malignant glioma. MATERIALS AND METHODS: HGG patients on BEV with tumor progression after 2 previous treatments were randomized to 1) FSRS plus BEV-based chemotherapy or 2) BEV-based chemotherapy with irinotecan, etoposide, temozolomide, or carboplatin. FSRS was delivered as 32 Gy (8 Gy × 4 fractions within 2 weeks) to the gross target volume and 24 Gy (6 Gy × 4 fractions) to the clinical target volume (fluid-attenuated inversion recovery abnormality). The primary endpoints were local control (LC) at 2 months and progression-free survival (PFS). RESULTS: Of the 35 patients enrolled, 29 had glioblastoma (WHO IV) and 6 had anaplastic glioma (WHO III). The median number of prior recurrences was 3. Patients treated with FSRS had significantly improved PFS (5.1 vs 1.8 months, P < .001) and improved LC at 2 months (82% [14/17] vs 27% [4/15], P = .002). The overall median survival was 6.6 months (7.2 months with FSRS vs 4.8 months with chemotherapy alone, P = .11). CONCLUSIONS: FSRS combined with BEV-based chemotherapy in recurrent HGG patients progressing on BEV is feasible and improves LC and PFS when compared to treatment with BEV-based chemotherapy alone.

Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.

BACKGROUND: Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS: We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS: Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS: The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).

Whole-genome and multisector exome sequencing of primary and post-treatment glioblastoma reveals patterns of tumor evolution.

Glioblastoma (GBM) is a prototypical heterogeneous brain tumor refractory to conventional therapy. A small residual population of cells escapes surgery and chemoradiation, resulting in a typically fatal tumor recurrence ∼ 7 mo after diagnosis. Understanding the molecular architecture of this residual population is critical for the development of successful therapies. We used whole-genome sequencing and whole-exome sequencing of multiple sectors from primary and paired recurrent GBM tumors to reconstruct the genomic profile of residual, therapy resistant tumor initiating cells. We found that genetic alteration of the p53 pathway is a primary molecular event predictive of a high number of subclonal mutations in glioblastoma. The genomic road leading to recurrence is highly idiosyncratic but can be broadly classified into linear recurrences that share extensive genetic similarity with the primary tumor and can be directly traced to one of its specific sectors, and divergent recurrences that share few genetic alterations with the primary tumor and originate from cells that branched off early during tumorigenesis. Our study provides mechanistic insights into how genetic alterations in primary tumors impact the ensuing evolution of tumor cells and the emergence of subclonal heterogeneity.

Correction to: First results on survival from a large Phase 3 clinical trial of an autologous dendritic cell vaccine in newly diagnosed glioblastoma.

Following publication of the original article [1], the authors reported an error in the spelling of one of the author names. In this Correction the incorrect and correct author names are indicated and the author name has been updated in the original publication. The authors also reported an error in the Methods section of the original article. In this Correction the incorrect and correct versions of the affected sentence are indicated. The original article has not been updated with regards to the error in the Methods section.

First results on survival from a large Phase 3 clinical trial of an autologous dendritic cell vaccine in newly diagnosed glioblastoma.

BACKGROUND: Standard therapy for glioblastoma includes surgery, radiotherapy, and temozolomide. This Phase 3 trial evaluates the addition of an autologous tumor lysate-pulsed dendritic cell vaccine (DCVax®-L) to standard therapy for newly diagnosed glioblastoma. METHODS: After surgery and chemoradiotherapy, patients were randomized (2:1) to receive temozolomide plus DCVax-L (n = 232) or temozolomide and placebo (n = 99). Following recurrence, all patients were allowed to receive DCVax-L, without unblinding. The primary endpoint was progression free survival (PFS); the secondary endpoint was overall survival (OS). RESULTS: For the intent-to-treat (ITT) population (n = 331), median OS (mOS) was 23.1 months from surgery. Because of the cross-over trial design, nearly 90% of the ITT population received DCVax-L. For patients with methylated MGMT (n = 131), mOS was 34.7 months from surgery, with a 3-year survival of 46.4%. As of this analysis, 223 patients are ≥ 30 months past their surgery date; 67 of these (30.0%) have lived ≥ 30 months and have a Kaplan-Meier (KM)-derived mOS of 46.5 months. 182 patients are ≥ 36 months past surgery; 44 of these (24.2%) have lived ≥ 36 months and have a KM-derived mOS of 88.2 months. A population of extended survivors (n = 100) with mOS of 40.5 months, not explained by known prognostic factors, will be analyzed further. Only 2.1% of ITT patients (n = 7) had a grade 3 or 4 adverse event that was deemed at least possibly related to the vaccine. Overall adverse events with DCVax were comparable to standard therapy alone. CONCLUSIONS: Addition of DCVax-L to standard therapy is feasible and safe in glioblastoma patients, and may extend survival. Trial registration Funded by Northwest Biotherapeutics; Clinicaltrials.gov number: NCT00045968; https://clinicaltrials.gov/ct2/show/NCT00045968?term=NCT00045968&rank=1 ; initially registered 19 September 2002.

DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique.

This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimated by the model selection (MS) technique in dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data analysis, and patient age. DCE-MRI investigations of 33 treatment-naïve patients with GBM were studied. Using the modified Tofts model and MS technique, the following physiologically nested models were constructed: Model 1, no vascular leakage (normal tissue); Model 2, leakage without efflux; Model 3, leakage with bidirectional exchange (influx and efflux). For each patient, the PK parameters of the three models were estimated as follows: blood plasma volume (vp ) for Model 1; vp and volume transfer constant (Ktrans ) for Model 2; vp , Ktrans and rate constant (kep ) for Model 3. Using Cox regression analysis, the best combination of the estimated PK parameters, together with patient age, was identified for the design and training of ANFIS. A K-fold cross-validation (K = 33) technique was employed for training, testing and optimization of ANFIS. Given the survival time distribution, three classes of survival were determined and a confusion matrix for the correct classification fraction (CCF) of the trained ANFIS was estimated as an accuracy index of ANFIS's performance. Patient age, kep and ve (Ktrans /kep ) of Model 3, and Ktrans of Model 2, were found to be the most effective parameters for training ANFIS. The CCF of the trained ANFIS was 84.8%. High diagonal elements of the confusion matrix (81.8%, 90.1% and 81.8% for Class 1, Class 2 and Class 3, respectively), with low off-diagonal elements, strongly confirmed the robustness and high performance of the trained ANFIS for predicting the three survival classes. This study confirms that DCE-MRI PK analysis, combined with the MS technique and ANFIS, allows the construction of a DCE-MRI-based fuzzy integrated predictor for the prediction of the survival of patients with GBM.

An extended vascular model for less biased estimation of permeability parameters in DCE-T1 images.

One of the key elements in dynamic contrast enhanced (DCE) image analysis is the arterial input function (AIF). Traditionally, in DCE studies a global AIF sampled from a major artery or vein is used to estimate the vascular permeability parameters; however, not addressing dispersion and delay of the AIF at the tissue level can lead to biased estimates of these parameters. To find less biased estimates of vascular permeability parameters, a vascular model of the cerebral vascular system is proposed that considers effects of dispersion of the AIF in the vessel branches, as well as extravasation of the contrast agent (CA) to the extravascular-extracellular space. Profiles of the CA concentration were simulated for different branching levels of the vascular structure, combined with the effects of vascular leakage. To estimate the permeability parameters, the extended model was applied to these simulated signals and also to DCE-T1 (dynamic contrast enhanced T1 ) images of patients with glioblastoma multiforme tumors. The simulation study showed that, compared with the case of solving the pharmacokinetic equation with a global AIF, using the local AIF that is corrected by the vascular model can give less biased estimates of the permeability parameters (Ktrans , vp and Kb ). Applying the extended model to signals sampled from different areas of the DCE-T1 image showed that it is able to explain the CA concentration profile in both the normal areas and the tumor area, where effects of vascular leakage exist. Differences in the values of the permeability parameters estimated in these images using the local and global AIFs followed the same trend as the simulation study. These results demonstrate that the vascular model can be a useful tool for obtaining more accurate estimation of parameters in DCE studies.

A parametric model of the brain vascular system for estimation of the arterial input function (AIF) at the tissue level.

In this paper, we introduce a novel model of the brain vascular system, which is developed based on laws of fluid dynamics and vascular morphology. This model is used to address dispersion and delay of the arterial input function (AIF) at different levels of the vascular structure and to estimate the local AIF in DCE images. We developed a method based on the simplex algorithm and Akaike information criterion to estimate the likelihood of the contrast agent concentration signal sampled in DCE images belonging to different layers of the vascular tree or being a combination of different signal levels from different nodes of this structure. To evaluate this method, we tested the method on simulated local AIF signals at different levels of this structure. Even down to a signal to noise ratio of 5.5 our method was able to accurately detect the branching level of the simulated signals. When two signals with the same power level were combined, our method was able to separate the base signals of the composite AIF at the 50% threshold. We applied this method to dynamic contrast enhanced computed tomography (DCE-CT) data, and using the parameters estimated by our method we created an arrival time map of the brain. Our model corrected AIF can be used for solving the pharmacokinetic equations for more accurate estimation of vascular permeability parameters in DCE imaging studies.

NRG oncology RTOG 0625: a randomized phase II trial of bevacizumab with either irinotecan or dose-dense temozolomide in recurrent glioblastoma.

Angiogenesis, a hallmark of glioblastoma, can potentially be targeted by inhibiting the VEGF pathway using bevacizumab, a humanized monoclonal antibody against VEGF-A. This study was designed to determine the efficacy and safety of these regimens in the cooperative group setting. Eligibility included age ≥18, recurrent or progressive GBM after standard chemoradiation. Treatment was intravenous bevacizumab 10 mg/kg and either irinotecan (CPT) 125 mg/m2 every 2 weeks or temozolomide (TMZ) 75-100 mg/m2 day 1-21 of 28 day cycle. Accrual goal was 57 eligible patients per arm. Primary endpoint was 6 month progression-free survival (6-m PFS); a predetermined rate of ≥35 % to declare efficacy. 60 eligible patients were enrolled on TMZ arm and 57 patients on CPT arm. Median age was 56, median KPS was 80. For TMZ arm, the 6-m-PFS rate was 39 % (23/59); for the CPT arm, the 6-m-PFS rate was 38.6 % (22/57). Objective responses: TMZ arm had 2 (3 %) CR, 9 (16 %) PR; CPT arm had 2 (4 %) CR, 13 (24 %) PR. Overall there was moderate toxicity: TMZ arm with 33 (55 %) grade 3, 11 (18 %) grade 4, and 1 (2 %) grade 5 (fatal) toxicities; CPT arm had 22 (39 %) grade 3, 7 (12 %) grade 4, and 3 (5 %) grade 5 toxicities. The 6-m-PFS surpassed the predetermined efficacy threshold for both arms, corroborating the efficacy of bevacizumab and CPT and confirming activity for bevacizumab and protracted TMZ for recurrent/progressive GBM, even after prior temozolomide exposure. Toxicities were within anticipated frequencies with a moderately high rate of venous thrombosis, moderate hypertension and one intracranial hemorrhage.

Phase 2 study of CT-322, a targeted biologic inhibitor of VEGFR-2 based on a domain of human fibronectin, in recurrent glioblastoma.

VEGF signaling through VEGFR-2 is the major factor in glioblastoma angiogenesis. CT-322, a pegylated protein engineered from the 10th type III human fibronectin domain, binds the VEGFR-2 extracellular domain with high specificity and affinity to block VEGF-induced VEGFR-2 signaling. This study evaluated CT-322 in an open-label run-in/phase 2 setting to assess its efficacy and safety in recurrent glioblastoma. Eligible patients had 1st, 2nd or 3rd recurrence of glioblastoma with measurable tumor on MRI and no prior anti-angiogenic therapy. The initial CT-322 dose was 1 mg/kg IV weekly, with plans to escalate subsequent patients to 2 mg/kg weekly if tolerated; within each CT-322 dose cohort, patients were randomized to ±irinotecan IV semiweekly. The primary endpoint was 6-month progression-free survival (PFS-6). Sixty-three patients with a median age of 56 were treated, the majority at first recurrence. One-third experienced serious adverse events, of which four were at least possibly related to study treatment (two intracranial hemorrhages and two infusion reactions). Twenty-nine percent of subjects developed treatment-emergent hypertension. The PFS-6 rate in the CT-322 monotherapy groups was 18.6 and 0.0 % in the 1 and 2 mg/kg treatment groups, respectively; results from the 2 mg/kg group indicated that the null hypothesis that PFS-6 ≤12 % could not be rejected. The study was terminated prior to reaching the planned enrollment for all treatment groups because data from the completed CT-322 2 mg/kg monotherapy treatment arm revealed insufficient efficacy. Despite biological activity and a tolerable side effect profile, CT-322 failed to meet the prespecified threshold for efficacy in recurrent glioblastoma.

Peritumoral tissue compression is predictive of exudate flux in a rat model of cerebral tumor: an MRI study in an embedded tumor.

MRI estimates of extracellular volume and tumor exudate flux in peritumoral tissue are demonstrated in an experimental model of cerebral tumor. Peritumoral extracellular volume predicted the tumor exudate flux. Eighteen RNU athymic rats were inoculated intracerebrally with U251MG tumor cells and studied with dynamic contrast enhanced MRI (DCE-MRI) approximately 18 days post implantation. Using a model selection paradigm and a novel application of Patlak and Logan plots to DCE-MRI data, the distribution volume (i.e. tissue porosity) in the leaky rim of the tumor and that in the tissue external to the rim (the outer rim) were estimated, as was the tumor exudate flow from the inner rim of the tumor through the outer rim. Distribution volume in the outer rim was approximately half that of the inner adjacent region (p < 1 × 10(-4)). The distribution volume of the outer ring was significantly correlated (R(2) = 0.9) with tumor exudate flow from the inner rim. Thus, peritumoral extracellular volume predicted the rate of tumor exudate flux. One explanation for these data is that perfusion, i.e. the delivery of blood to the tumor, was regulated by the compression of the mostly normal tissue of the tumor rim, and that the tumor exudate flow was limited by tumor perfusion.

Identification of regions of normal grey matter and white matter from pathologic glioblastoma and necrosis in frozen sections using Raman imaging.

In neurosurgical applications, a tool capable of distinguishing grey matter, white matter, and areas of tumor and/or necrosis in near-real time could greatly aid in tumor resection decision making. Raman spectroscopy is a non-destructive spectroscopic technique which provides molecular information about the tissue under examination based on the vibrational properties of the constituent molecules. With careful measurement and data processing, a spatial step and repeat acquisition of Raman spectra can be used to create Raman images. Forty frozen brain tissue sections were imaged in their entirety using a 300-µm-square measurement grid, and two or more regions of interest within each tissue were also imaged using a 25 µm-square step size. Molecular correlates for histologic features of interest were identified within the Raman spectra, and novel imaging algorithms were developed to compare molecular features across multiple tissues. In previous work, the relative concentration of individual biomolecules was imaged. Here, the relative concentrations of 1004, 1300:1344, and 1660 cm(-1), which correspond primarily to protein and lipid content, were simultaneously imaged across all tissues. This provided simple interpretation of boundaries between grey matter, white matter, and diseased tissue, and corresponded with findings from adjacent hematoxylin and eosin-stained sections. This novel, yet simple, multi-channel imaging technique allows clinically-relevant resolution with straightforward molecular interpretation of Raman images not possible by imaging any single peak. This method can be applied to either surgical or laboratory tools for rapid, non-destructive imaging of grey and white matter.

Phase I study of iniparib concurrent with monthly or continuous temozolomide dosing schedules in patients with newly diagnosed malignant gliomas.

Iniparib is a prodrug that converts to highly reactive cytotoxic metabolites intracellularly with activity in preclinical glioma models. We investigated the maximum tolerated dose (MTD) of iniparib with monthly (m) and continuous (c) temozolomide (TMZ) dosing schedules in patients with malignant gliomas (MG). Adults with newly diagnosed MG who had successfully completed ≥80% of radiation (RT) and TMZ without toxicity received mTMZ dosing (150-200 mg/m(2) days 1-5/28 days) or cTMZ dosing (75 mg/m(2)/days × 6 weeks) in conjunction with iniparib (i.v. 2 days/week) in the adjuvant setting. Iniparib was dose escalated using a modified continual reassessment method (mCRM). 43 patients (32 male; 34 GBM, 8 AA, 1 gliosarcoma; median age 54 years; median KPS 90) were enrolled across 4 dose levels. In the mTMZ group, 2/4 patients had dose limiting toxicities (DLT) at 19 mg/kg/week (rash/hypersensitivity). At 17.2 mg/kg/week, 1/9 patients had a DLT (grade 3 fatigue). Additional grade 3 toxicities were neutropenia, lymphopenia, and nausea. In the cTMZ group, one DLT (thromboembolic event) occurred at 10.2 mg/kg/week. Dose escalation stopped at 16 mg/kg/week based on mCRM. The mean maximum plasma concentration of iniparib increased with dose. Concentration of the two major circulating metabolites, 4-iodo-3-aminobenzamide and 4-iodo-3-aminobenzoic acid, was ≤5% of the corresponding iniparib concentration. Iniparib is well tolerated, at doses higher than previously investigated, in combination with TMZ after completion of RT + TMZ in patients with MG. Recommended phase 2 dosing of iniparib based on mCRM is 17.2 mg/kg/week with mTMZ and 16 mg/kg/week with cTMZ. An efficacy study of TMZ/RT + iniparib followed by TMZ + iniparib in newly diagnosed GBM using these doses has completed enrollment. Survival assessment is ongoing.

Phase II trial of sunitinib as adjuvant therapy after stereotactic radiosurgery in patients with 1-3 newly diagnosed brain metastases.

Patients with 1-3 brain metastases (BM) often receive sterotactic radiosurgery (SRS) without whole brain radiotherapy (WBRT). SRS without WBRT carries a high rate of relapse in the central nervous system (CNS). This trial used sunitinib as an alternative to WBRT for post-SRS adjuvant therapy. Eligible patients with 1-3 newly diagnosed BM, RTOG RPA class 1-2, received sunitinib after SRS. Patients with controlled systemic disease were allowed to continue chemotherapy for their primary disease according to a list of published regimens (therapy + sunitinib) included in the protocol. Patients received sunitinib 37.5 or 50 mg/days 1-28 every 42 days until CNS progression. Neuropsychological testing and MRIs were obtained every two cycles. The primary endpoint was the rate of CNS progression at 6 months (PFS6) after SRS. Fourteen patients with a median age of 59 years were enrolled. Primary cancers included lung 43 %, breast 21 %, melanoma 14 %. Toxicity included grade 3 or higher fatigue in five patients and neutropenia in two patients. The CNS PFS6 and PFS12 were 43 ± 14 and 34 ± 14 %, respectively. Of the ten patients who completed >1 neurocognitive assessment, none showed cognitive decline. Sunitinib after SRS for 1-3 BM was well tolerated with a PFS6 of 43 %. The prevention of progressive brain metastasis after SRS requires the incorporation of chemotherapy regimens to control the patient's primary disease. Future trials should continue to explore the paradigm of secondary chemoprevention of BM after definitive local therapy.

Intratumoral heterogeneity of receptor tyrosine kinases EGFR and PDGFRA amplification in glioblastoma defines subpopulations with distinct growth factor response.

Glioblastoma (GBM) is distinguished by a high degree of intratumoral heterogeneity, which extends to the pattern of expression and amplification of receptor tyrosine kinases (RTKs). Although most GBMs harbor RTK amplifications, clinical trials of small-molecule inhibitors targeting individual RTKs have been disappointing to date. Activation of multiple RTKs within individual GBMs provides a theoretical mechanism of resistance; however, the spectrum of functional RTK dependence among tumor cell subpopulations in actual tumors is unknown. We investigated the pattern of heterogeneity of RTK amplification and functional RTK dependence in GBM tumor cell subpopulations. Analysis of The Cancer Genome Atlas GBM dataset identified 34 of 463 cases showing independent focal amplification of two or more RTKs, most commonly platelet-derived growth factor receptor α (PDGFRA) and epidermal growth factor receptor (EGFR). Dual-color fluorescence in situ hybridization was performed on eight samples with EGFR and PDGFRA amplification, revealing distinct tumor cell subpopulations amplified for only one RTK; in all cases these predominated over cells amplified for both. Cell lines derived from coamplified tumors exhibited genotype selection under RTK-targeted ligand stimulation or pharmacologic inhibition in vitro. Simultaneous inhibition of both EGFR and PDGFR was necessary for abrogation of PI3 kinase pathway activity in the mixed population. DNA sequencing of isolated subpopulations establishes a common clonal origin consistent with late or ongoing divergence of RTK genotype. This phenomenon is especially common among tumors with PDGFRA amplification: overall, 43% of PDGFRA-amplified GBM were found to have amplification of EGFR or the hepatocyte growth factor receptor gene (MET) as well.

Addition of MR imaging features and genetic biomarkers strengthens glioblastoma survival prediction in TCGA patients.

PURPOSE: The purpose of our study was to assess whether a model combining clinical factors, MR imaging features, and genomics would better predict overall survival of patients with glioblastoma (GBM) than either individual data type. METHODS: The study was conducted leveraging The Cancer Genome Atlas (TCGA) effort supported by the National Institutes of Health. Six neuroradiologists reviewed MRI images from The Cancer Imaging Archive (http://cancerimagingarchive.net) of 102 GBM patients using the VASARI scoring system. The patients' clinical and genetic data were obtained from the TCGA website (http://www.cancergenome.nih.gov/). Patient outcome was measured in terms of overall survival time. The association between different categories of biomarkers and survival was evaluated using Cox analysis. RESULTS: The features that were significantly associated with survival were: (1) clinical factors: chemotherapy; (2) imaging: proportion of tumor contrast enhancement on MRI; and (3) genomics: HRAS copy number variation. The combination of these three biomarkers resulted in an incremental increase in the strength of prediction of survival, with the model that included clinical, imaging, and genetic variables having the highest predictive accuracy (area under the curve 0.679±0.068, Akaike's information criterion 566.7, P<0.001). CONCLUSION: A combination of clinical factors, imaging features, and HRAS copy number variation best predicts survival of patients with GBM.