Towards Consistency in Pediatric Brain Tumor Measurements: Challenges, Solutions, and the Role of AI-Based Segmentation.

MR imaging is central to the assessment of tumor burden and changes over time in neuro-oncology. Several response assessment guidelines have been set forth by the Response Assessment in Pediatric Neuro-Oncology (RAPNO) working groups in different tumor histologies; however, the visual delineation of tumor components using MRIs is not always straightforward, and complexities not currently addressed by these criteria can introduce inter- and intra-observer variability in manual assessments. Differentiation of non-enhancing tumor from peritumoral edema, mild enhancement from absence of enhancement, and various cystic components can be challenging; particularly given a lack of sufficient and uniform imaging protocols in clinical practice. Automated tumor segmentation with artificial intelligence (AI) may be able to provide more objective delineations, but rely on accurate and consistent training data created manually (ground truth). Herein, this paper reviews existing challenges and potential solutions to identifying and defining subregions of pediatric brain tumors (PBTs) that are not explicitly addressed by current guidelines. The goal is to assert the importance of defining and adopting criteria for addressing these challenges, as it will be critical to achieving standardized tumor measurements and reproducible response assessment in PBTs, ultimately leading to more precise outcome metrics and accurate comparisons among clinical studies.

Comparison of Volumetric and 2D Measurements and Longitudinal Trajectories in the Response Assessment of BRAF V600E-Mutant Pediatric Gliomas in the Pacific Pediatric Neuro-Oncology Consortium Clinical Trial.

BACKGROUND AND PURPOSE: Response on imaging is widely used to evaluate treatment efficacy in clinical trials of pediatric gliomas. While conventional criteria rely on 2D measurements, volumetric analysis may provide a more comprehensive response assessment. There is sparse research on the role of volumetrics in pediatric gliomas. Our purpose was to compare 2D and volumetric analysis with the assessment of neuroradiologists using the Brain Tumor Reporting and Data System (BT-RADS) in BRAF V600E-mutant pediatric gliomas. MATERIALS AND METHODS: Manual volumetric segmentations of whole and solid tumors were compared with 2D measurements in 31 participants (292 follow-up studies) in the Pacific Pediatric Neuro-Oncology Consortium 002 trial (NCT01748149). Two neuroradiologists evaluated responses using BT-RADS. Receiver operating characteristic analysis compared classification performance of 2D and volumetrics for partial response. Agreement between volumetric and 2D mathematically modeled longitudinal trajectories for 25 participants was determined using the model-estimated time to best response. RESULTS: Of 31 participants, 20 had partial responses according to BT-RADS criteria. Receiver operating characteristic curves for the classification of partial responders at the time of first detection (median = 2 months) yielded an area under the curve of 0.84 (95% CI, 0.69-0.99) for 2D area, 0.91 (95% CI, 0.80-1.00) for whole-volume, and 0.92 (95% CI, 0.82-1.00) for solid volume change. There was no significant difference in the area under the curve between 2D and solid (P = .34) or whole volume (P = .39). There was no significant correlation in model-estimated time to best response (ρ = 0.39, P >.05) between 2D and whole-volume trajectories. Eight of the 25 participants had a difference of ≥90 days in transition from partial response to stable disease between their 2D and whole-volume modeled trajectories. CONCLUSIONS: Although there was no overall difference between volumetrics and 2D in classifying partial response assessment using BT-RADS, further prospective studies will be critical to elucidate how the observed differences in tumor 2D and volumetric trajectories affect clinical decision-making and outcomes in some individuals.

Use of External Control Cohorts in Pediatric Brain Tumor Clinical Trials.

Why, when, and how to consider external control cohorts in pediatric brain tumor clinical trials.

Everolimus for Children With Recurrent or Progressive Low-Grade Glioma: Results From the Phase II PNOC001 Trial.

PURPOSE: The PNOC001 phase II single-arm trial sought to estimate progression-free survival (PFS) associated with everolimus therapy for progressive/recurrent pediatric low-grade glioma (pLGG) on the basis of phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway activation as measured by phosphorylated-ribosomal protein S6 and to identify prognostic and predictive biomarkers. PATIENTS AND METHODS: Patients, age 3-21 years, with progressive/recurrent pLGG received everolimus orally, 5 mg/m2 once daily. Frequency of driver gene alterations was compared among independent pLGG cohorts of newly diagnosed and progressive/recurrent patients. PFS at 6 months (primary end point) and median PFS (secondary end point) were estimated for association with everolimus therapy. RESULTS: Between 2012 and 2019, 65 subjects with progressive/recurrent pLGG (median age, 9.6 years; range, 3.0-19.9; 46% female) were enrolled, with a median follow-up of 57.5 months. The 6-month PFS was 67.4% (95% CI, 60.0 to 80.0) and median PFS was 11.1 months (95% CI, 7.6 to 19.8). Hypertriglyceridemia was the most common grade ≥3 adverse event. PI3K/AKT/mTOR pathway activation did not correlate with clinical outcomes (6-month PFS, active 68.4% v nonactive 63.3%; median PFS, active 11.2 months v nonactive 11.1 months; P = .80). Rare/novel KIAA1549::BRAF fusion breakpoints were most frequent in supratentorial midline pilocytic astrocytomas, in patients with progressive/recurrent disease, and correlated with poor clinical outcomes (median PFS, rare/novel KIAA1549::BRAF fusion breakpoints 6.1 months v common KIAA1549::BRAF fusion breakpoints 16.7 months; P < .05). Multivariate analysis confirmed their independent risk factor status for disease progression in PNOC001 and other, independent cohorts. Additionally, rare pathogenic germline variants in homologous recombination genes were identified in 6.8% of PNOC001 patients. CONCLUSION: Everolimus is a well-tolerated therapy for progressive/recurrent pLGGs. Rare/novel KIAA1549::BRAF fusion breakpoints may define biomarkers for progressive disease and should be assessed in future clinical trials.

Rational combination platform trial design for children and young adults with diffuse midline glioma: A report from PNOC.

Background Diffuse midline glioma (DMG) is a devastating pediatric brain tumor unresponsive to hundreds of clinical trials. Approximately 80% of DMGs harbor H3K27M oncohistones, which reprogram the epigenome to increase the metabolic profile of the tumor cells. Methods We have previously shown preclinical efficacy of targeting both oxidative phosphorylation and glycolysis through treatment with ONC201, which activates the mitochondrial protease ClpP, and paxalisib, which inhibits PI3K/mTOR, respectively. Results ONC201 and paxalisib combination treatment aimed at inducing metabolic distress led to the design of the first DMG-specific platform trial PNOC022 (NCT05009992). Conclusions Here, we expand on the PNOC022 rationale and discuss various considerations, including liquid biome, microbiome, and genomic biomarkers, quality-of-life endpoints, and novel imaging modalities, such that we offer direction on future clinical trials in DMG.

Bevacizumab Alone and in Combination With Irinotecan in Recurrent Glioblastoma.

PURPOSE: We evaluated the efficacy of bevacizumab, alone and in combination with irinotecan, in patients with recurrent glioblastoma in a phase II, multicenter, open-label, noncomparative trial. PATIENTS AND METHODS: One hundred sixty-seven patients were randomly assigned to receive bevacizumab 10 mg/kg alone or in combination with irinotecan 340 mg/m2 or 125 mg/m2 (with or without concomitant enzyme-inducing antiepileptic drugs, respectively) once every 2 weeks. Primary end points were 6-month progression-free survival and objective response rate, as determined by independent radiology review. Secondary end points included safety and overall survival. RESULTS: In the bevacizumab-alone and the bevacizumab-plus-irinotecan groups, estimated 6-month progression-free survival rates were 42.6% and 50.3%, respectively; objective response rates were 28.2% and 37.8%, respectively; and median overall survival times were 9.2 months and 8.7 months, respectively. There was a trend for patients who were taking corticosteroids at baseline to take stable or decreasing doses over time. Of the patients treated with bevacizumab alone or bevacizumab plus irinotecan, 46.4% and 65.8%, respectively, experienced grade ≥ 3 adverse events, the most common of which were hypertension (8.3%) and convulsion (6.0%) in the bevacizumab-alone group and convulsion (13.9%), neutropenia (8.9%), and fatigue (8.9%) in the bevacizumab-plus-irinotecan group. Intracranial hemorrhage was noted in two patients (2.4%) in the bevacizumab-alone group (grade 1) and in three patients (3.8%) patients in the bevacizumab-plus-irinotecan group (grades 1, 2, and 4, respectively). CONCLUSION: Bevacizumab, alone or in combination with irinotecan, was well tolerated and active in recurrent glioblastoma.

Current Strategies for Management of Medulloblastoma.

Medulloblastoma (MB) is the most common malignant central nervous system tumor of childhood, which includes multiple molecular subgroups (4) and subtypes (8 to 12), each with different outcomes and potential therapy options. Long-term survival remains poor for many of the subtypes, with high late mortality risks and poor health-related quality of life. Initial treatment strategies integrate molecular subgroup information with more standard clinical and phenotypic factors to risk stratify newly diagnosed patients. Clinical trials treating relapsed disease, often incurable, now include multiple new approaches in an attempt to improve progression-free and overall survival.

OpenPBTA: The Open Pediatric Brain Tumor Atlas.

Pediatric brain and spinal cancers are collectively the leading disease-related cause of death in children; thus, we urgently need curative therapeutic strategies for these tumors. To accelerate such discoveries, the Children's Brain Tumor Network (CBTN) and Pacific Pediatric Neuro-Oncology Consortium (PNOC) created a systematic process for tumor biobanking, model generation, and sequencing with immediate access to harmonized data. We leverage these data to establish OpenPBTA, an open collaborative project with over 40 scalable analysis modules that genomically characterize 1,074 pediatric brain tumors. Transcriptomic classification reveals universal TP53 dysregulation in mismatch repair-deficient hypermutant high-grade gliomas and TP53 loss as a significant marker for poor overall survival in ependymomas and H3 K28-mutant diffuse midline gliomas. Already being actively applied to other pediatric cancers and PNOC molecular tumor board decision-making, OpenPBTA is an invaluable resource to the pediatric oncology community.

PNOC015: Repeated convection-enhanced delivery of MTX110 (aqueous panobinostat) in children with newly diagnosed diffuse intrinsic pontine glioma.

BACKGROUND: The objective of this study was to determine the safety, tolerability, and distribution of MTX110 (aqueous panobinostat) delivered by convection-enhanced delivery (CED) in patients with newly diagnosed diffuse intrinsic pontine glioma (DIPG) who completed focal radiation therapy (RT). METHODS: Patients with DIPG (2-21 years) were enrolled after RT. CED of MTX110 combined with gadoteridol was completed across 7 dose levels (DL) (30-90 µM; volumes ranging from 3 mL to 2 consecutive doses of 6 mL). An accelerated dose escalation design was used. Distribution of infusate was monitored with real-time MR imaging. Repeat CED was performed every 4-8 weeks. Quality-of-life (QoL) assessments were obtained at baseline, every 3 months on therapy, and end of therapy. RESULTS: Between May 2018 and March 2020, 7 patients who received a total of 48 CED infusions, were enrolled (median age 8 years, range 5-21). Three patients experienced dose-limited toxicities. Four grade 3 treatment-related adverse events were observed. Most toxicities were transient new or worsening neurologic function. Median overall survival (OS) was 26.1 months (95% confidence interval: 14.8-not reached). Progression-free survival was 4-14 months (median, 7). Cumulative percentage of tumor coverage for combined CED infusions per patient ranged from 35.6% to 81.0%. Increased CED infusions were negatively associated with self-reported QoL assessments. CONCLUSION: Repeat CED of MTX110 with real-time imaging with gadoteridol is tolerable for patients with DIPG. Median OS of 26.1 months compares favorably with historical data for children with DIPG. The results support further investigation of this strategy in a larger cohort.

Evaluating preclinical evidence for clinical translation in childhood brain tumours: Guidelines from the CONNECT, PNOC, and ITCC brain networks.

Clinical outcomes for many childhood brain tumours remain poor, despite our increasing understanding of the underlying disease biology. Advances in molecular diagnostics have refined our ability to classify tumour types and subtypes, and efforts are underway across multiple international paediatric neuro-oncology consortia to take novel biological insights in the worst prognosis entities into innovative clinical trials. Whilst for the first time we are designing such studies on the basis of disease-specific biological data, the levels of preclincial evidence in appropriate model systems on which these trials are initiated is still widely variable. We have considered these issues between CONNECT, PNOC and ITCC-Brain, and developed a framework in which we can assess novel concepts being brought forward for possible clinical translation. Whilst not intended to be proscriptive for every possible circumstance, these criteria provide a basis for self-assessment of evidence by laboratory scientists, and a platform for discussion and rational decision-making prior to moving forward clinically.

Automated tumor segmentation and brain tissue extraction from multiparametric MRI of pediatric brain tumors: A multi-institutional study.

Background: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability. We present a multi-institutional deep learning-based method for automated brain extraction and segmentation of pediatric brain tumors based on multi-parametric MRI scans. Methods: Multi-parametric scans (T1w, T1w-CE, T2, and T2-FLAIR) of 244 pediatric patients ( n = 215 internal and n = 29 external cohorts) with de novo brain tumors, including a variety of tumor subtypes, were preprocessed and manually segmented to identify the brain tissue and tumor subregions into four tumor subregions, i.e., enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED). The internal cohort was split into training ( n = 151), validation ( n = 43), and withheld internal test ( n = 21) subsets. DeepMedic, a three-dimensional convolutional neural network, was trained and the model parameters were tuned. Finally, the network was evaluated on the withheld internal and external test cohorts. Results: Dice similarity score (median ± SD) was 0.91 ± 0.10/0.88 ± 0.16 for the whole tumor, 0.73 ± 0.27/0.84 ± 0.29 for ET, 0.79 ± 19/0.74 ± 0.27 for union of all non-enhancing components (i.e., NET, CC, ED), and 0.98 ± 0.02 for brain tissue in both internal/external test sets. Conclusions: Our proposed automated brain extraction and tumor subregion segmentation models demonstrated accurate performance on segmentation of the brain tissue and whole tumor regions in pediatric brain tumors and can facilitate detection of abnormal regions for further clinical measurements.

mRNA aggregates harness danger response for potent cancer immunotherapy.

Messenger RNA (mRNA) has emerged as a remarkable tool for COVID-19 prevention but its use for induction of therapeutic cancer immunotherapy remains limited by poor antigenicity and a regulatory tumor microenvironment (TME). Herein, we develop a facile approach for substantially enhancing immunogenicity of tumor-derived mRNA in lipid-particle (LP) delivery systems. By using mRNA as a molecular bridge with ultrapure liposomes and foregoing helper lipids, we promote the formation of 'onion-like' multi-lamellar RNA-LP aggregates (LPA). Intravenous administration of RNA-LPAs mimics infectious emboli and elicits massive DC/T cell mobilization into lymphoid tissues provoking cancer immunogenicity and mediating rejection of both early and late-stage murine tumor models. Unlike current mRNA vaccine designs that rely on payload packaging into nanoparticle cores for toll-like receptor engagement, RNA-LPAs stimulate intracellular pathogen recognition receptors (RIG-I) and reprogram the TME thus enabling therapeutic T cell activity. RNA-LPAs were safe in acute/chronic murine GLP toxicology studies and immunologically active in client-owned canines with terminal gliomas. In an early phase first-in-human trial for patients with glioblastoma, we show that RNA-LPAs encoding for tumor-associated antigens elicit rapid induction of pro-inflammatory cytokines, mobilization/activation of monocytes and lymphocytes, and expansion of antigen-specific T cell immunity. These data support the use of RNA-LPAs as novel tools to elicit and sustain immune responses against poorly immunogenic tumors.

Automated Tumor Segmentation and Brain Tissue Extraction from Multiparametric MRI of Pediatric Brain Tumors: A Multi-Institutional Study.

Background: Brain tumors are the most common solid tumors and the leading cause of cancer-related death among all childhood cancers. Tumor segmentation is essential in surgical and treatment planning, and response assessment and monitoring. However, manual segmentation is time-consuming and has high interoperator variability. We present a multi-institutional deep learning-based method for automated brain extraction and segmentation of pediatric brain tumors based on multi-parametric MRI scans. Methods: Multi-parametric scans (T1w, T1w-CE, T2, and T2-FLAIR) of 244 pediatric patients (n=215 internal and n=29 external cohorts) with de novo brain tumors, including a variety of tumor subtypes, were preprocessed and manually segmented to identify the brain tissue and tumor subregions into four tumor subregions, i.e., enhancing tumor (ET), non-enhancing tumor (NET), cystic components (CC), and peritumoral edema (ED). The internal cohort was split into training (n=151), validation (n=43), and withheld internal test (n=21) subsets. DeepMedic, a three-dimensional convolutional neural network, was trained and the model parameters were tuned. Finally, the network was evaluated on the withheld internal and external test cohorts. Results: Dice similarity score (median±SD) was 0.91±0.10/0.88±0.16 for the whole tumor, 0.73±0.27/0.84±0.29 for ET, 0.79±19/0.74±0.27 for union of all non-enhancing components (i.e., NET, CC, ED), and 0.98±0.02 for brain tissue in both internal/external test sets. Conclusions: Our proposed automated brain extraction and tumor subregion segmentation models demonstrated accurate performance on segmentation of the brain tissue and whole tumor regions in pediatric brain tumors and can facilitate detection of abnormal regions for further clinical measurements. Key Points: We proposed automated tumor segmentation and brain extraction on pediatric MRI.The volumetric measurements using our models agree with ground truth segmentations. Importance of the Study: The current response assessment in pediatric brain tumors (PBTs) is currently based on bidirectional or 2D measurements, which underestimate the size of non-spherical and complex PBTs in children compared to volumetric or 3D methods. There is a need for development of automated methods to reduce manual burden and intra- and inter-rater variability to segment tumor subregions and assess volumetric changes. Most currently available automated segmentation tools are developed on adult brain tumors, and therefore, do not generalize well to PBTs that have different radiological appearances. To address this, we propose a deep learning (DL) auto-segmentation method that shows promising results in PBTs, collected from a publicly available large-scale imaging dataset (Children's Brain Tumor Network; CBTN) that comprises multi-parametric MRI scans of multiple PBT types acquired across multiple institutions on different scanners and protocols. As a complementary to tumor segmentation, we propose an automated DL model for brain tissue extraction.

Genome-wide analysis of aberrant position and sequence of plasma DNA fragment ends in patients with cancer.

Genome-wide fragmentation patterns in cell-free DNA (cfDNA) in plasma are strongly influenced by cellular origin due to variation in chromatin accessibility across cell types. Such differences between healthy and cancer cells provide the opportunity for development of novel cancer diagnostics. Here, we investigated whether analysis of cfDNA fragment end positions and their surrounding DNA sequences reveals the presence of tumor-derived DNA in blood. We performed genome-wide analysis of cfDNA from 521 samples and analyzed sequencing data from an additional 2147 samples, including healthy individuals and patients with 11 different cancer types. We developed a metric based on genome-wide differences in fragment positioning, weighted by fragment length and GC content [information-weighted fraction of aberrant fragments (iwFAF)]. We observed that iwFAF strongly correlated with tumor fraction, was higher for DNA fragments carrying somatic mutations, and was higher within genomic regions affected by copy number amplifications. We also calculated sample-level means of nucleotide frequencies observed at genomic positions spanning fragment ends. Using a combination of iwFAF and nine nucleotide frequencies from three positions surrounding fragment ends, we developed a machine learning model to differentiate healthy individuals from patients with cancer. We observed an area under the receiver operative characteristic curve (AUC) of 0.91 for detection of cancer at any stage and an AUC of 0.87 for detection of stage I cancer. Our findings remained robust with as few as 1 million fragments analyzed per sample, demonstrating that analysis of fragment ends can become a cost-effective and accessible approach for cancer detection and monitoring.

ABTC-0904: targeting glioma stem cells in GBM: a phase 0/II study of hedgehog pathway inhibitor GDC-0449.

PURPOSE: Gliomagenesis and resistance of glioblastoma (GBM) are believed to be mediated by glioma stem cells (GSC). Evidence suggests that SHH signaling promotes GSC proliferation and self-renewal. METHODS: ABTC-0904 was a two-arm, multicenter phase 0/II study of GDC-0449, an oral inhibitor of Smoothened (SMO) in patients undergoing resection for recurrent GBM. All patients (Arms I and II) had surgery and received drug post-operatively. Only patients in Arm I received drug prior to surgery. The primary objective was to determine 6-month progression free survival (PFS-6). Secondary endpoints include median PFS (mPFS) and overall survival (mOS), response rate, and toxicity. Correlative studies included bioanalysis of GDC-0449, and inhibition of SHH signaling, GSC proliferation and self-renewal. RESULTS: Forty-one patients were enrolled. Pharmacokinetics of GDC-0449 in plasma demonstrated levels within expected therapeutic range in 75% of patients. The proportion of tumorcells producing CD133+ neurospheres, neurosphere proliferation, self-renewal, and expression of the SHh downstream signaling was significantly decreased in Arm I following GDC-0449 treatment (p < 0.005; p < 0.001 respectively) compared to Arm II (no drug pre-op). Treatment was well tolerated. There were no objective responders in either arm. Overall PFS-6 was 2.4% (95% CI 0.9-11.1%). Median PFS was 2.3 months (95% CI 1.9-2.6) and mOS was 7.8 months (95% CI 5.4-10.1). CONCLUSIONS: GDC-0449 was well tolerated, reached tumor, and inhibited CD133+ neurosphere formation, but had little clinical efficacy as a single agent in rGBM. This suggests growth and maintenance of rGBM is not solely dependent on the SHH pathway thus targeting SMO may require combined approaches.

Upfront Biology-Guided Therapy in Diffuse Intrinsic Pontine Glioma: Therapeutic, Molecular, and Biomarker Outcomes from PNOC003.

PURPOSE: PNOC003 is a multicenter precision medicine trial for children and young adults with newly diagnosed diffuse intrinsic pontine glioma (DIPG). PATIENTS AND METHODS: Patients (3-25 years) were enrolled on the basis of imaging consistent with DIPG. Biopsy tissue was collected for whole-exome and mRNA sequencing. After radiotherapy (RT), patients were assigned up to four FDA-approved drugs based on molecular tumor board recommendations. H3K27M-mutant circulating tumor DNA (ctDNA) was longitudinally measured. Tumor tissue and matched primary cell lines were characterized using whole-genome sequencing and DNA methylation profiling. When applicable, results were verified in an independent cohort from the Children's Brain Tumor Network (CBTN). RESULTS: Of 38 patients enrolled, 28 patients (median 6 years, 10 females) were reviewed by the molecular tumor board. Of those, 19 followed treatment recommendations. Median overall survival (OS) was 13.1 months [95% confidence interval (CI), 11.2-18.4] with no difference between patients who followed recommendations and those who did not. H3K27M-mutant ctDNA was detected at baseline in 60% of cases tested and associated with response to RT and survival. Eleven cell lines were established, showing 100% fidelity of key somatic driver gene alterations in the primary tumor. In H3K27-altered DIPGs, TP53 mutations were associated with worse OS (TP53mut 11.1 mo; 95% CI, 8.7-14; TP53wt 13.3 mo; 95% CI, 11.8-NA; P = 3.4e-2), genome instability (P = 3.1e-3), and RT resistance (P = 6.4e-4). The CBTN cohort confirmed an association between TP53 mutation status, genome instability, and clinical outcome. CONCLUSIONS: Upfront treatment-naïve biopsy provides insight into clinically relevant molecular alterations and prognostic biomarkers for H3K27-altered DIPGs.

A single institution retrospective analysis on survival based on treatment paradigms for patients with anaplastic oligodendroglioma.

INTRODUCTION: Anaplastic oligodendrogliomas are high-grade gliomas defined molecularly by 1p19q co-deletion. There is no curative therapy, and standard of care includes surgical resection followed by radiation and chemotherapy. However, the benefit of up-front radiation with chemotherapy compared to chemotherapy alone has not been demonstrated in a randomized control trial. Given the potential long-term consequences of radiation therapy, such as cognitive impairment, arteriopathy, endocrinopathy, and hearing/visual impairment, there is an effort to balance longevity with radiation toxicity. METHODS: We performed a retrospective single institution analysis of survival of patients with anaplastic oligodendroglioma over 20 years. RESULTS: 159 patients were identified as diagnosed with an anaplastic oligodendroglioma between 1996 and 2016. Of those, 40 patients were found to have AO at original diagnosis and had documented 1p19q co-deletion with a median of 7.1 years of follow-up (range: 0.6-16.7 years). After surgery, 45 % of patients were treated with radiation and chemotherapy at diagnosis, and 50 % were treated with adjuvant chemotherapy alone. The group treated with chemotherapy alone had a trend of receiving more cycles of chemotherapy than patients treated with radiation and chemotherapy upfront (p = 0.051). Median overall survival has not yet been reached. The related risk of progression in the upfront, adjuvant chemotherapy only group was almost 5-fold higher than the patients who received radiation and chemotherapy (hazard ratio = 4.85 (1.74-13.49), p = 0.002). However, there was no significant difference in overall survival in patients treated with upfront chemotherapy compared to patients treated upfront with chemotherapy and radiation (p = 0.8). Univariate analysis of age, KPS, extent of resection, or upfront versus delayed radiation was not associated with improved survival. CONCLUSIONS: Initial treatment with adjuvant chemotherapy alone, rather than radiation and chemotherapy, may be an option for some patients with anaplastic oligodendroglioma, as it is associated with similar overall survival despite shorter progression free survival.

BRCA1 Protein Expression Predicts Survival in Glioblastoma Patients from an NRG Oncology RTOG Cohort.

PURPOSE: Glioblastoma, the most common malignant brain tumor, was associated with a median survival of <1 year in the pre-temozolomide (TMZ) era. Despite advances in molecular and genetic profiling studies identifying several predictive biomarkers, none has been translated into routine clinical use. Our aim was to investigate the prognostic significance of a panel of diverse cellular molecular markers of tumor formation and growth in an annotated glioblastoma tissue microarray (TMA). METHODS AND MATERIALS: A TMA composed of archived glioblastoma tumors from patients treated with surgery, radiation, and non-TMZ chemother-apy, was provided by RTOG. RAD51, BRCA-1, phosphatase and tensin homolog tumor suppressor gene (PTEN), and miRNA-210 expression levels were assessed using quantitative in situ hybridization and automated quantitative protein analysis. The objectives of this analysis were to determine the association of each biomarker with overall survival (OS), using the Cox proportional hazard model. Event-time distributions were estimated using the Kaplan-Meier method and compared by the log-rank test. RESULTS: A cohort of 66 patients was included in this study. Among the 4 biomarkers assessed, only BRCA1 expression had a statistically significant correlation with survival. From univariate analysis, patients with low BRCA1 protein expression showed a favorable outcome for OS (p = 0.04; hazard ratio = 0.56) in comparison with high expressors, with a median survival time of 18.9 versus 4.8 months. CONCLUSIONS: BRCA1 protein expression was an important survival predictor in our cohort of glioblastoma patients. This result may imply that low BRCA1 in the tumor and the consequent low level of DNA repair cause vulnerability of the cancer cells to treatment.