Colman, Howard

Abstract Purpose: Glioblastoma is an aggressive and molecularly heterogeneous cancer with few effective treatment options. We hypothesized that next-generation sequencing can be used to guide treatment recommendations within a clinically acceptable time frame following surgery for patients with recurrent glioblastoma. Experimental Design: We conducted a prospective genomics-informed feasibility trial in adults with recurrent and progressive glioblastoma. Following surgical resection, genome-wide tumor/normal exome sequencing and tumor RNA sequencing were performed to identify molecular targets for potential matched therapy. A multidisciplinary molecular tumor board issued treatment recommendations based on the genomic results, blood–brain barrier penetration of the indicated therapies, drug–drug interactions, and drug safety profiles. Feasibility of generating genomics-informed treatment recommendations within 35 days of surgery was assessed. Results: Of the 20 patients enrolled in the study, 16 patients had sufficient tumor tissue for analysis. Exome sequencing was completed for all patients, and RNA sequencing was completed for 14 patients. Treatment recommendations were provided within the study's feasibility time frame for 15 of 16 (94%) patients. Seven patients received treatment based on the tumor board recommendations. Two patients reached 12-month progression-free survival, both adhering to treatments based on the molecular profiling results. One patient remained on treatment and progression free 21 months after surgery, 3 times longer than the patient's previous time to progression. Analysis of matched nonenhancing tissue from 12 patients revealed overlapping as well as novel putatively actionable genomic alterations. Conclusions: Use of genome-wide molecular profiling is feasible and can be informative for guiding real-time, central nervous system–penetrant, genomics-informed treatment recommendations for patients with recurrent glioblastoma. Clin Cancer Res; 24(2); 295–305. ©2017 AACR. See related commentary by Wick and Kessler, p. 256

LBA2010 Background: RTOG 0825 evaluated the addition of BEV to standard CRT in the treatment of GBM and included molecular stratification that assessed the degree of mesenchymal (MES) gene enrichment. We investigated the ability of the MES signature to predict response to BEV. Methods: Sufficient FFPE tissue for molecular analysis was available for 650 registered, eligible patients. TaqMan PCR was performed prospectively using the molecular stratifier on all patients and an expanded 43 member MES set on 234 cases. A subset of specimens was subjected to whole genome expression profiling (GEP). Predictive models were evaluated for their ability to predict survival (overall, OS, and progression-free, PFS) in the training cohort of the BEV arm after adjusting for prognostic factors and treatment arm. Unsupervised clustering of GEP data was used to identify molecular subsets and gene set enrichment analysis (GSEA) performed to evaluate for MES enrichment. Results: We observed a significant association between increasing MES signature and worse PFS and OS in the BEV arm (p=0.036 and p=0.032, respectively). Based on the association between high MES expression and poor outcome in the BEV arm, we sought to optimize a predictor using an expanded set of MES genes. Unbiased gene selection from a total of 43 genes followed by radial basis machine modeling identified a 10-gene predictor of outcome in the BEV arm (p<0.001/HR 4.04 for OS and p<0.001/HR 2.21 for PFS). To further support the association of MES enrichment and poor outcome in the BEV arm, we performed GEP. Unsupervised clustering identified a subtype of tumors with MES enrichment associated with the 10-gene predictor survival probability (p=0.0124, t-test). Ongoing studies will determine the extent to which this represents a predictive marker for BEV. Conclusions: We developed a 10-gene predictor specific to BEV treatment and suitable for FFPE that may serve to identify subsets of patients with newly diagnosed GBM who benefit from BEV. Supported by RTOG grant U10 CA21661, CCOP grant U10 CA37422, and Brain SPORE P50 CA127001 from the NCI and Genentech. Clinical trial information: NCT00884741.

1 Background: Chemoradiation (CRT) with temozolomide (TMZ/RT→TMZ) is the standard of care for newly diagnosed GBM. This trial determined if the addition of Bev to standard CRT improves survival (OS) or progression-free survival (PFS) in newly diagnosed GBM. Methods: This phase III trial was conducted by the RTOG, NCCTG, and ECOG. Neurologically stable pts > 18 yrs with KPS ≥ 60, and > 1cm3 tumor tissue block, were randomized to Arm 1: standard CRT + placebo or Arm 2: standard CRT plus Bev (10 mg/kg iv q 2wks). Experimental treatment began at wk 4 of radiation then thru 6-12 cycles of maintenance chemotherapy. Protocol specified co-primary endpoints were OS and PFS, with significance levels of .023 and .002, respectively. At progression, treatment was unblinded and pts allowed to crossover or continue Bev. Symptom, QOL and neurocognitive (NCF) testing was performed in the majority of pts. Secondary analyses evaluated impact of MGMT methylation (meth) and prognostic 9 gene signature status. Results: From 978 registered pts, 637 were randomized. Inadequate tissue (n=105) and blood on imaging (n=40) were key reasons for non-randomization. No difference was found between arms for OS (median 16.1 vs. 15.7 mo, p = 0.11). PFS was extended for Arm 2 (7.3 vs. 10.7 mo, p = 0.004). Pts with MGMT meth had superior OS (23.2 vs. 14.3 mo, p < 0.001) and PFS (14.1 vs. 8.2 mo, p < 0.001). Neither the 9 gene signature nor MGMT predicted selective benefit for Bev treatment, but best prognosis pts (MGMT meth, favorable 9-gene), had a worse survival trend with Bev (15.7 vs 25 mo p = 0.08). To date, 128 pts were unblinded on Arm 1 (salvage Bev in 86) and 87 pts on Arm 2 (continued Bev in 39). Increased grade ≥ 3 toxicity was seen with Bev, mostly neutropenia, hypertension, and DVT/PE. Conclusions: The addition of Bev for newly diagnosed GBM did not improve OS, did improve PFS but did not reach the significance criterion. MGMT and 9 gene profile did not identify selective benefit, but risk subset results suggested strongly against the upfront use of Bev in the best prognosis pts. Full interpretation of the PFS results incorporating symptom burden, QOL, and NCF is ongoing. Support: NCI U10 CA 21661, U10 CA37422, and Genentech. Clinical trial information: NCT00884741.

LBA2000 Background: Formalin-fixed, paraffin embedded GBM tumor tissue, adequate for conventional MGMT methylation analyses, was required for entry onto the RTOG 0525 clinical trial. Methods: Four prognostic biomarkers were evaluated on a training set of 220 retrospectively obtained GBM samples, consisting of IDH1 mutation, the glioma-CpG island methylator phenotype (G-CIMP), a microarray-based mRNA panel and a novel MGMT promoter methylation assay. For each biomarker, 2 (IDH1 and mRNA) or 3 subgroups (G-CIMP and MGMT) were defined based on associations with overall survival. All combinations (36 possible) of each of the 4 biomarker-derived subgroups were then defined and compared with survival data and then consolidated into 4 risk groups. Once created in the training set, this model was applied to the RTOG 0525 samples (n=763) for external validation. Results: Application of the molecular risk classification to RTOG 0525 samples (left table) showed a highly significant survival association (p<0.001). When compared to the recursive partitioning analysis (RPA, table on right), this composite molecular classifier better identified patients with long term survival and appears to improve resolution by revealing an additional distinct risk group. The molecular classifier was prognostic in each of the treatment arms individually. Conclusions: Four distinct biomarkers or biomarker panels were tested in GBM. These biomarkers were compared with clinical outcome in a training set to optimize a method to combine them into a classifier. This classifier was then validated on a large sample set from a large phase III clinical trial. This composite panel may represent an improvement over the existing RPA with respect to risk stratification of patients for GBM. Additionally, it has the potential to impact future clinical trial designs and provide enhanced opportunities for personalization of therapy for GBM. Support: NCI U10 CA2121661, U10 CA37422, P50 CA127001. [Table: see text]

Purpose The clinical significance of epidermal growth factor receptor variant III (EGFRvIII) expression in glioblastoma multiforme (GBM) and its relationship with other key molecular markers are not clear. We sought to evaluate the clinical significance of GBM subtypes as defined by EGFRvIII status. Patients and Methods The expression of EGFRvIII was assessed by immunohistochemistry in 649 patients with newly diagnosed GBM. These data were then examined in conjunction with the expression of phospho-intermediates (in a subset of these patients) of downstream AKT and Ras pathways and YKL-40 as well as with known clinical risk factors, including the Radiation Therapy Oncology Group's recursive partitioning analysis (RTOG-RPA) class. Results The RTOG-RPA class was highly predictive of survival in EGFRvIII-negative patients but much less predictive in EGFRvIII-positive patients. These findings were seen in both an initial test set (n = 268) and a larger validation set (n = 381). Similarly, activation of the AKT/MAPK pathways and YKL-40 positivity were predictive of poor outcome in EGFRvIII-negative patients but not in EGFRvIII-positive patients. Pair-wise combinations of markers identified EGFRvIII and YKL-40 as prognostically important. In particular, outcome in patients with EGFRvIII-negative/YKL-40–negative tumors was significantly better than the outcome in patients with the other three combinations of these two markers. Conclusion Established prognostic factors in GBM were not predictive of outcome in the EGFRvIII-positive subset, although this requires confirmation in independent data sets. GBMs negative for both EGFRvIII and YKL-40 show less aggressive behavior.

Abstract Purpose: YKL-40 is a secreted protein that has been reported to be overexpressed in epithelial cancers and gliomas, although its function is unknown. Previous data in a smaller sample set suggested that YKL-40 was a marker associated with a poorer clinical outcome and a genetically defined subgroup of glioblastoma. Here we test these findings in a larger series of patients with glioblastoma, and in particular, determine if tumor YKL-40 expression is associated with radiation response. Experimental Design: Patients (n = 147) with subtotal resections were studied for imaging-assessed changes in tumor size in serial studies following radiation therapy. An additional set (n = 140) of glioblastoma patients who underwent a gross-total resection was tested to validate the survival association and extend them to patients with minimal residual disease. Results: In the subtotal resection group, higher YKL-40 expression was significantly associated with poorer radiation response, shorter time to progression and shorter overall survival. The association of higher YKL-40 expression with poorer survival was validated in the gross-total resection group. In multivariate analysis with both groups combined (n = 287), YKL-40 was an independent predictor of survival after adjusting for patient age, performance status, and extent of resection. YKL-40 expression was also compared with genetically defined subsets of glioblastoma by assessing epidermal growth factor receptor amplification and loss at chromosome 10q, two of the common recurring aberrations in these tumors, using fluorescent in situ hybridization. YKL-40 was significantly associated with 10q loss. Conclusions: The findings implicate YKL-40 as an important marker of therapeutic response and genetic subtype in glioblastomas and suggest that it may play an oncogenic role in these tumors.