Nabors, Burt

Glioma incidence is highest in non‐Hispanic Whites, and to date, glioma genome‐wide association studies (GWAS) to date have only included European ancestry (EA) populations. African Americans and Hispanics in the US have varying proportions of EA, African (AA) and Native American ancestries (NAA). It is unknown if identified GWAS loci or increased EA is associated with increased glioma risk. We assessed whether EA was associated with glioma in African Americans and Hispanics. Data were obtained for 832 cases and 675 controls from the Glioma International Case–Control Study and GliomaSE Case–Control Study previously estimated to have <80% EA, or self‐identify as non‐White. We estimated global and local ancestry using fastStructure and RFMix, respectively, using 1,000 genomes project reference populations. Within groups with ≥40% AA (AFR ≥0.4 ), and ≥15% NAA (AMR ≥0.15 ), genome‐wide association between local EA and glioma was evaluated using logistic regression conditioned on global EA for all gliomas. We identified two regions (7q21.11, p = 6.36 × 10 −4 ; 11p11.12, p = 7.0 × 10 −4 ) associated with increased EA, and one associated with decreased EA (20p12.13, p = 0.0026) in AFR ≥0.4 . In addition, we identified a peak at rs1620291 ( p = 4.36 × 10 −6 ) in 7q21.3. Among AMR ≥0.15 , we found an association between increased EA in one region (12q24.21, p = 8.38 × 10 −4 ), and decreased EA in two regions (8q24.21, p = 0. 0010; 20q13.33, p = 6.36 × 10 −4 ). No other significant associations were identified. This analysis identified an association between glioma and two regions previously identified in EA populations (8q24.21, 20q13.33) and four novel regions (7q21.11, 11p11.12, 12q24.21 and 20p12.13). The identifications of novel association with EA suggest regions to target for future genetic association studies.

PURPOSE Adequately prioritizing the numerous therapies and biomarkers available in late-stage testing for patients with glioblastoma (GBM) requires an efficient clinical testing platform. We developed and implemented INSIGhT (Individualized Screening Trial of Innovative Glioblastoma Therapy) as a novel adaptive platform trial (APT) to develop precision medicine approaches in GBM. METHODS INSIGhT compares experimental arms with a common control of standard concurrent temozolomide and radiation therapy followed by adjuvant temozolomide. The primary end point is overall survival. Patients with newly diagnosed unmethylated GBM who are IDH R132H mutation negative and with genomic data available for biomarker grouping are eligible. At the initiation of INSIGhT, three experimental arms (neratinib, abemaciclib, and CC-115), each with a proposed genomic biomarker, are tested simultaneously. Initial randomization is equal across arms. As the trial progresses, randomization probabilities adapt on the basis of accumulating results using Bayesian estimation of the biomarker-specific probability of treatment impact on progression-free survival. Treatment arms may drop because of low probability of treatment impact on overall survival, and new arms may be added. Detailed information on the statistical model and randomization algorithm is provided to stimulate discussion on trial design choices more generally and provide an example for other investigators developing APTs. CONCLUSION INSIGhT (NCT02977780) is an ongoing novel biomarker-based, Bayesian APT for patients with newly diagnosed unmethylated GBM. Our goal is to dramatically shorten trial execution timelines while increasing scientific power of results and biomarker discovery using adaptive randomization. We anticipate that trial execution efficiency will also be improved by using the APT format, which allows for the collaborative addition of new experimental arms while retaining the overall trial structure.

TPS2079 Background: Patient with glioblastoma (GBM) with unmethylated MGMT promoters derive limited benefit from temozolomide (TMZ) and have dismal outcome. Prioritizing the numerous available therapies and biomarkers for late stage testing requires an efficient clinical testing platform. INSIGhT (NCT02977780) is a biomarker-based, Bayesian adaptively randomized, multi-arm phase II platform screening trial for patients with newly diagnosed GBM and unmethylated MGMT promoters. Methods: INSIGhT compares experimental arms to a common control of standard concurrent TMZ and radiation therapy (RT) followed by adjuvant TMZ. The primary endpoint is overall survival (OS). Patients with newly diagnosed, unmethylated GBM that are IDH R132H mutation negative, and with genomic data available or who consent to whole exome sequencing through the ALLELE companion study for biomarker grouping are eligible. Two experimental arms consist of concurrent RT/TMZ followed by adjuvant neratinib (EGFR, HER2, and HER4 inhibitor) or abemaciclib CDK 4/6 inhibitor), respectively, in place of TMZ. The other experimental arm is CC-115 (TORC1/2 and DNA PK inhibitor), which replaces TMZ in both the concurrent and adjuvant phases. Biomarker groups include: EGFR + patients with EGFR amplification/mutation; PI3K + patients with PIK3CA mutation/amplification, PIK3R1 mutation, AKT3amplification, PIK3C2B > 1 copy gain, or PTEN dual loss; CDK: + patients with wild-type RB1 and CDK4 amplification, CDK6 amplification, or CDKN2A > 1 copy loss. Given the lack of pretrial biomarker data and the anticipated overlap of the groups, randomization will initially be equal. As the trial progresses, randomization probabilities will be adapted based on the Bayesian estimation of the probability of treatment impact on progression-free survival (PFS). These randomization probabilities can vary among the biomarker groups so predictive biomarkers will be identified and utilized if present. Treatment arms may drop due to low probability of treatment impact on OS, and new arms may be added. Experimental arms are compared only with control and should be thought of as discrete experimental questions, with INSIGhT being open to new investigators with proposed therapeutic hypotheses. Clinical trial information: NCT02977780.

Abstract Glioma incidence is highest in non-Hispanic Whites, where it occurs ~2x as frequently compared with other race/ethnicity groups. Glioma GWAS to date have included European ancestry populations only, and it is unknown whether variants identified by these analyses are associated with glioma in non- European ancestry populations. African Americans and Hispanics are admixed populations with varying proportions of European ancestry. While global ancestry may be similar within admixed groups, the proportion of European ancestry at each allele can vary across the genome. As glioma is more common in European ancestry populations, the presence of increased local European ancestry in these admixed populations could be used to identify glioma risk loci. Here we assessed whether excess European ancestry at established risk loci (Melin et al, Nature Genetics, 2017) was associated with glioma risk in non-European ancestry populations. Global ancestry was estimated using fastStructure, and local ancestry was estimated using RFMix. Both methods used 1,000 genomes project reference populations (African: YRI; European: CEU; East Asian: CHB/JPT; and Native American: CLM/PEL/MXL). We evaluated differences in local European ancestry between cases and controls using logistic regression conditioned on global European ancestry within 500kb of 25 previously identified risk variants among individuals with ≥50% African ancestry, and ≥30% Native American ancestry for all gliomas, and for grade IV glioblastoma (GBM) and grade II-III non-GBM. There were 347 individuals (184 cases and 163 controls) with ≥50% global African ancestry, and 277 individuals (153 cases and 124 controls) with ≥30% global American ancestry. There was no significant difference in proportion of global European ancestry between cases and controls with ≥50% global African ancestry (cases: 18.2%, controls: 17.7%, p=0.6834), and no significant difference in proportion of global European ancestry between cases and controls with ≥30% global American ancestry (cases: 51.1%, controls: 49.0%, p=0.2123). Among individuals with &gt;50% African ancestry, we observed a nominally significant association between all glioma and increased local European ancestry at 7p11.2 (EGFR, pmin=0.0070) and between GBM and increased local European ancestry at 22q13.1 (CSNK1E, pmin=0.0098), both near SNPs previously associated with glioblastoma in majority European-ancestry populations. The dataset used for this analysis represents the largest collection of genotyped non-European glioma cases. These results suggest that glioma risk in African Americans may be associated with an increased local European ancestry variants at glioma risk loci previously identified in majority European ancestry populations (7p11.2 and 22q13.1). Citation Format: Quinn T. Ostrom, Kathleen M. Egan, L. Burt Nabors, Travis Gerke, Reid C. Thompson, Jeffrey J. Olson, Renato LaRocca, Sajeel Chowdhary, Jeanette E. Eckel-Passow, Georgina Armstrong, John K. Wiencke, Christopher I. Amos, Jonine L. Bernstein, Elizabeth B. Claus, Dora Il'yasova, Christoffer Johansen, Daniel H. Lachance, Rose Lai, Ryan T. Merrell, Sara H. Olson, Siegal Sadetzki, Joellen Schildkraut, Sanjay Shete, Richard S. Houlston, Robert B. Jenkins, Beatrice Melin, Melissa L. Bondy, Jill S. Barnholtz-Sloan. Evaluating glioma risk associated with extent of European admixture in African-Americans and Latinos [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 233.

Abstract Purpose: Glioblastoma is a devastating, incurable disease with few known prognostic factors. Here, we present the first genome-wide survival and validation study for glioblastoma. Experimental Design: Cox regressions for survival with 314,635 inherited autosomal single-nucleotide polymorphisms (SNP) among 315 San Francisco Adult Glioma Study patients for discovery and three independent validation data sets [87 Mayo Clinic, 232 glioma patients recruited from several medical centers in Southeastern United States (GliomaSE), and 115 The Cancer Genome Atlas patients] were used to identify SNPs associated with overall survival for Caucasian glioblastoma patients treated with the current standard of care, resection, radiation, and temozolomide (total n = 749). Tumor expression of the gene that contained the identified prognostic SNP was examined in three separate data sets (total n = 619). Genotype imputation was used to estimate hazard ratios (HR) for SNPs that had not been directly genotyped. Results: From the discovery and validation analyses, we identified a variant in single-stranded DNA-binding protein 2 (SSBP2) on 5q14.1 associated with overall survival in combined analyses (HR, 1.64; P = 1.3 × 10−6). Expression of SSBP2 in tumors from three independent data sets also was significantly related to patient survival (P = 5.3 × 10−4). Using genotype imputation, the SSBP2 SNP rs17296479 had the strongest statistically significant genome-wide association with poorer overall patient survival (HR, 1.79; 95% CI, 1.45-2.22; P = 1.0 × 10−7). Conclusion: The minor allele of SSBP2 SNP rs17296479 and the increased tumor expression of SSBP2 were statistically significantly associated with poorer overall survival among glioblastoma patients. With further confirmation, previously unrecognized inherited variations influencing survival may warrant inclusion in clinical trials to improve randomization. Unaccounted for genetic influence on survival could produce unwanted bias in such studies. Clin Cancer Res; 18(11); 3154–62. ©2012 AACR.